ALBERT

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): James H. Gawron, Gregory A. Keoleian, Robert D. De Kleine, Timothy J. Wallington, Hyung Chul Kim〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Although recent studies of autonomous taxis (ATs) have begun to explore potential environmental implications of fleet deployment, little is known about their impacts over the long term. We present a life-cycle assessment framework that incorporates both direct and indirect effects of ATs at the subsystem, vehicle, and mobility-system levels. Eco-driving and intersection connectivity are the direct effects analyzed along with indirect effects that include empty kilometers, parking, charging infrastructure, powertrain rightsizing, electric vehicle adoption, ride-sharing, and fleet-turnover rates. A case study of an AT fleet in Austin, Texas from 2020 to 2050 with constant travel demand indicates the strategic deployment of an electrified AT fleet can reduce cumulative energy and greenhouse gas (GHG) emissions by 60% in the base case, with a majority of this benefit resulting from electrified powertrains. Further reductions up to 87% can be achieved with accelerated electrical grid decarbonization, dynamic ride-share, longer vehicle lifetime, more energy efficient computer systems, and faster fuel efficiency improvements for new vehicles. We highlight the major opportunities for maximizing the environmental performance of AT fleets over the long term.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): Ran Tu, Lama Alfaseeh, Shadi Djavadian, Bilal Farooq, Marianne Hatzopoulou〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Communication between vehicles and road infrastructure can enable more efficient use of the road network and hence reduce congestion in urban areas. This improvement can be enhanced by distributed control due to its lighter computational load and higher reliability. Despite favourable impacts on traffic, little is known about the effects of such systems on near-road air quality. In this study, an End-To-End (E2E) dynamic distributed routing algorithm in Connected and Automated Vehicles (CAVs) was applied in downtown Toronto, to identify whether benefits to network throughput were associated with lower near-road NO〈sub〉2〈/sub〉 concentrations. We observe significant reductions in the emissions of Greenhouse Gases (GHGs) with increased penetration of CAVs. Nonetheless, at times, the emissions of nitrogen oxides (NO〈sub〉x〈/sub〉) increased with higher CAVs. Besides, a higher frequency and severity of NO〈sub〉2〈/sub〉 hot-spots were observed under a 100% CAV scenario. Impacts of the proposed system on electric energy consumption in a full electric vehicle network were also investigated, indicating that the addition of CAVs that are electric did not contribute to high energy savings. We propose that such new transformative technologies in transportation should be designed with air pollution and public health goals.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 29 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment〈/p〉 〈p〉Author(s): Zhao Zhang, Brian Wolshon, Pamela Murray-Tuite〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Evacuations, a critical and widely used emergency response action, vary widely in terms of their scale, scope, urgency and level of organization. While they differ from event to event, history shows that there are a small set of variables, inherent to all evacuations, that largely govern their effectiveness. In this paper, these fundamental variables are described from a theoretical perspective to illustrate how factors of evacuation demand and supply affect clearance time and how they can also be used to relate evacuation planning to concepts of risk, resiliency, and resource allocation. This work provides a basis for a general theory of evacuation processes that can be used it to conceptualize relationships like cost-benefit tradeoffs in evacuation management to improve long-range evacuation planning through a better understanding of the investment and allocation of resources.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 75〈/p〉 〈p〉Author(s): Kate Hosford, Meghan Winters, Daniel Fuller〈/p〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 75〈/p〉 〈p〉Author(s): Michał A. Niedzielski, Rafał Kucharski〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Urban spatial structure, transport mode and space-time constraints are known to affect accessibility to activities for a city’s residents. However, most studies measure accessibility from home only and report accessibility in terms of the travel time or number of activities. Such studies neglect the mobility and time budget constraints on people’s accessibility. Furthermore, modal accessibility disparity studies have not considered inequality between modes during the afternoon commute. We examine accessibility to non-work activities by automobile and public transport using spatiotemporal measures that determine the number of minutes people have available to participate in activities, given time budget and activity duration constraints, rather than simply the number of activities. We examine modal accessibility disparity in Warsaw, Poland. Our two major findings are the reverse of findings in previous studies: that disparity shifts toward public transport as the activity duration increases and the travel time decreases; and that it shifts toward public transport with increasing distance away from the city center.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 75〈/p〉 〈p〉Author(s): Michael Held, Maximilian Schücking〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The utilization has a significant effect on the life-cycle assessment (LCA) of battery electric vehicles (BEVs). This article evaluates this effect in detail by presenting a case-driven LCA for BEVs deployed in two commercial mobility applications. The empirical data was recorded over 2.5 years and 450,000 km. The findings of this article indicate that regular and predictable mobility demand patterns in combination with a high vehicle utilization are favorable conditions for an environmentally beneficial deployment of BEVs. These characteristics allow tailoring the battery capacity to the requirements and avoiding an unnecessary offset from production. When charging the vehicles with electricity from renewable energy sources (RESs), the high operating grade utilizes the comparatively lower environmental impacts per kilometer. A high lifetime mileage allows breaking-even to comparable internal combustion engine vehicles (ICEVs) in most investigated impact categories. Since regular and predictable mobility patterns, as well as a high operating grade, are commonly found in commercial applications these are especially suitable for replacing ICEVs with BEVs from an environmental perspective.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Yewen Gu, Stein W. Wallace, Xin Wang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Global warming is a major challenge for this planet, and its solution requires efforts throughout society. Maritime transportation, which carries more than 90% of the global trade, plays a critical role in the contribution of greenhouse gas (GHG) emissions. However, the GHGs emitted by the global fleet still fall outside the emission reduction scheme established by the Kyoto Protocol. Alternative solutions are therefore sought. Several market-based measures have been proposed and submitted to IMO for discussion and evaluation. In this paper, we focus on one of these measures, namely the Maritime Emissions Trading Scheme (METS). An optimization model that integrates (global or regional) METS into the classical fleet composition and deployment problem is proposed. This model is used as a tool to study the impact of METS on fleet operations and their CO〈sub〉2〈/sub〉 emissions. The results of the computational study suggest that, in the short term, the implementation of METS does not lead to emission reduction in most scenarios. However, in the case of low bunker prices, high allowance costs or global METS coverage, a more significant CO〈sub〉2〈/sub〉 decrease in the short term can be expected.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 20 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment〈/p〉 〈p〉Author(s): Elham Hajhashemi, Pamela M. Murray-Tuite, Susan L. Hotle, Kris Wernstedt〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Hurricane Sandy greatly disrupted the New York City (NYC) region’s transportation systems, electric power systems, work locations, and schools in 2012. This study uses survey responses from NYC Metropolitan Area residents to develop an agent-based model that depicts commuter travel behavior and adaptation after the disruption. Six scenarios were tested to quantify which systems were more critical to recover for an earlier return to productivity - defined as the ability to work for one’s employer. The recommended system restoration order depends on the pattern of normal commuting behavior. In the NYC Metropolitan Area, a larger share of commuters use transit to commute than in any other US metropolitan area. This resulted in the model indicating the subway/rail system recovery as the most important factor for returning the most people to productivity. The second most important factor is widespread power restoration itself, which allows residents to telework while waiting for the transportation system to recover. The next most important factor is the reopening of schools and daycares (with associated infrastructure systems), freeing parents to commute. The remaining expedited system recovery scenarios tested using the agent-based model resulted in a faster return to productivity than the baseline, but to a lesser degree than the subway/rail, power, and childcare systems scenarios. Additional analysis of recovery shows that households with higher annual income benefit more from power recovery compared to those with lower incomes. Moreover, the effectiveness of recovery scenarios can differ based on residential location and the extent of disruption in that location.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Chaoying Yin, Chunfu Shao, Chunjiao Dong, Xiaoquan Wang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Although the relationship between commuting time and residents’ happiness has been widely investigated, few studies have examined how the connection varies with urbanization levels. Using 7,774 individual samples across China, this study employs a multilevel ordered logit model to examine how commuting time is correlated with residents’ happiness. The effects of both the neighborhood and city-level built environment are revealed. Our findings show that commuting time is an essential factor correlated with residents’ happiness and the correlation varies across urbanization levels. People from cities with high urbanization rates (〉70%) have a strong mental endurance of commuting time, whereas commuting time is more influential on residents’ happiness in cities with low urbanization rates (〈50%). For the effects of the built environment, residents’ happiness is significantly associated with both levels of built environment in cities with urbanization rates higher than 50%. Conversely, residents’ happiness is only significantly correlated with the neighborhood built environment in cities with urbanization rates lower than 50%. Hence, to enhance residents’ happiness, urban planners and policy makers should consider multi-scale built environment characteristics and improve the public transport services according to local urbanization levels.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Min Zhou, Nan Kong, Lindu Zhao, Fuhua Huang, Song Wang, Kathryn S. Campy〈/p〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Hua Wang, De Zhao, Yutong Cai, Qiang Meng, Ghim Ping Ong〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉As a cost-effective and environmental-friendly transport means, electric vehicle (EV) has received widespread attention in the recent decade. The increasing market share and wider adoption of EV in transportation systems also bring about the energy use issues. In this paper, we propose a method to estimate network-wide EV energy consumption by taking into account battery degradation. We first derive unit energy consumption functions with respect to the battery degradation rate by quadratic regression method using EV operational data in the US. We then put forward an easy-to-implement and tangible method to estimate EV network energy consumption based on EV trajectories and the derived unit energy consumption function. In detail, EVs’ battery degradation rates are assumed to follow a given and known probability distribution and daily travel mileage of each EV is derived from EV trajectories. Based on these, we can get the expected total energy consumption in the network. We also propose a prorated assignment approach to determine the expected energy consumed by EVs through each EV charging point based on the estimated temporal-spatial charging demand distribution from EVs’ trajectories. A case study in Singapore is demonstrated in the end and the importance of incorporating battery degradation is highlighted. The results reveal that overlooking battery degradation would lead to more than 10% of estimation error in energy consumption estimation.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): 〈/p〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Shahin Zargarnezhad, Reza Dashti, Rouhollah Ahmadi〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Energy distribution companies use various vehicles such as Outage Elimination Maintenance Vehicles (OEMVs), Maintenance Vehicles (MVs) and Supervision Vehicles (SVs) in order to resolve network faults, to conduct inspection, service and maintenance activities and to monitor the integrity of operations. These vehicles have different levels of fuel consumption which concerns companies with regards to the cost and environmental hazards. Hence, it is important to know that a distribution company how many and what types of vehicles do need to predict the fuel consumption of these vehicles. Extra fuel consumption may be required owing to carry unnecessary equipment or used vehicles with large engine volume. Therefore, in this paper, the fuel consumption levels of outage elimination maintenance, maintenance, and supervision vehicles are considered. Then, given the fact that fuel consumption increases with the increase of vehicle weight and Engine Displacement (ED), the extra fuel consumption has been predicted using Artificial Neural Networks (ANNs). In a case study, the total annual fuel cost in the network under consideration is estimated to be $66750. In the case of a 40% increase in vehicle weight, the fuel consumption cost will rise by $24500, and when the engine displacement increases for a 500 CC, the cost rises up $17400 per year.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): William Brazil, Steffen Kallbekken, Håkon Sælen, James Carroll〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Transitioning to more sustainable transport behaviours is key to achieving national and international climate change objectives. Households can contribute to the new low carbon economy by switching to more energy efficient vehicles. In addition to societal and environmental benefits, such a change should lead to private benefits for households through lower energy expenses, while avoiding the perceived costs that could accompany a modal change in personal transportation (switching away from cars). This paper uses a discrete choice experiment (stated preference) to explore the effects of using alternative fuel cost labels on the demand for more efficient cars. Results show that reframing from fuel consumption (litres) to monthly fuel costs increases the willingness to pay for higher levels of fuel efficiency. More generally, these results highlight that informational interventions can be improved by framing information in a metric that is more salient and familiar to consumers.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Gabriela Codrina Tiţă, Marina Viorela Marcu, Gheorghe Ignea, Stelian Alexandru Borz〈/p〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 76〈/p〉 〈p〉Author(s): Xiaolei Ma, Xian Zhang, Xin Li, Xingju Wang, Xu Zhao〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The development of bike sharing system (BSS) has changed travelers’ commuting and lifestyle in recent years. Whether BSSs are complementary or competitive to public transit remains controversial. This study uses a propensity score matching-based difference-in-difference (DID) method to evaluate the impact of free-floating BSS on bus ridership in Chengdu, China. The transaction data of bus service and BSS and the neighboring points of interest are investigated. Results indicate that, (a) on the bus route level, each shared bike results in a 4.23 increment and a 0.56 reduction in daily bus ridership on weekdays and weekends, respectively; (b) on the bus stop level, the increment in shared bikes significantly negatively impacts bus ridership on weekends; (c) on the route level, regarding the time of day, each unit increment of shared bike significantly increases bus ridership on weekdays by 0.54, 0.34, and 0.15 during a.m. peak, p.m. peak, and off peak, respectively; and (d) on the bus stop level, the relationship between shared bikes and bus ridership is insignificant on weekdays. This study reveals that the demand pattern of commuters strongly impacts the relationship between shared bike and public transportation.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 76〈/p〉 〈p〉Author(s): Long Cheng, Freke Caset, Jonas De Vos, Ben Derudder, Frank Witlox〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Taking into account the rapidly aging demographic landscape in China, securing elderly’s right to participate in society has become an urgent challenge. Geographical access to urban amenities is known to influence social participation and integration. However, the application of accessibility analysis to elderly population in China has received little attention to date. This study examines the walking accessibility to recreational amenities for older adults in the Chinese context with an explicit focus on equity. Building on empirically-based estimates of a cumulative opportunity approach, we calculate the levels of accessibility at the traffic analysis zone level, evaluate how accessibility varies across age cohorts, and present the distribution of accessibility across zones. To this end, we draw on the 2015 Nanjing Travel Survey and the city’s GIS database. Instead of assuming a fixed threshold, this paper applies a spatial expansion model to allow for person- and location-specific walking distances to measure accessibility. The spatial disparities in access to recreational amenities are evaluated using the notion of vertical equity for identifying areas that are better-off or worse-off. Our results show pronounced distributional effects of current land-use and transportation policies for different age cohorts. In particular, elderly people experience lower accessibility to chess/card rooms and urban parks than their younger counterparts. The empirical evidence in this research can inform planning and policy interventions and feed current scientific debates on the role of accessibility in addressing social inclusion for an age-friendly society.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Johannes Kester, Gerardo Zarazua de Rubens, Benjamin K. Sovacool, Lance Noel〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Public awareness and acceptance of electric vehicles (EVs) are essential components to catalyse a faster uptake of more sustainable passenger transport as well as vehicle-to-grid (V2G) mobility. As such, public perceptions are central to decarbonize transportation and help capture the co-benefits of reduced local pollution, noise emissions, and oil dependency. However, we observe that the general public is often treated statically and seen as either problematic or peripheral to questions within the transport and energy studies communities. This paper asks two questions. First, given increasing adoption in the Nordic region, how do ordinary members of the public perceive EVs? And second, how do they perceive V2G? With these questions, the paper offers an international and in-depth assessment of public perceptions of EVs and V2G systems across five Nordic countries using original data drawn from eight focus groups. We find eight themes of relevance for future research and policy. These include often discussed insights like an EV’s environmental sustainability, range, charging or price, but also insights around themes like social status, sound, and acceleration. Additionally, we asked the participants whether V2G strengthens (or weakens) the desirability of EVs. The paper ends with a reflection on the knowledge discrepancies between national focus groups and individuals with and without EV presence and the different informational requirements that are needed to address them.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Yuche Chen, Marc Melaina〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The future of fuel cell electric vehicle (FCEV) depends on its cost and performance competitiveness in the automobile market. In this study, we develop a techno-economic analysis framework to compare the cost and performance of major vehicle technologies (internal combustion, hybrid, plug-in hybrid, battery and fuel cell electric) under various progress scenarios for the years 2035 and 2050. We utilize a vehicle powertrain model to compare vehicle technologies with similar engineering performance and evaluate their cost competitiveness. We define the cost as (2018) U.S. dollars per mile driven ($/mile) during a certain ownership period and include the vehicle purchase price and fuel cost. Our results show that, in the 2035 scenarios, the costs per mile for FCEVs are 36% or 22% higher than those of conventional gasoline cars, based on a 5-year or 15-year ownership period, respectively. In the 2050 scenarios, the 15-year ownership costs of FCEVs are comparable to those of gasoline cars with comparable engineering performance. In all the 2035 and 2050 scenarios, fuel cell vehicles have a lower driving cost compared with electric vehicles with 200-mile driving range. Our sensitivity analysis suggests that hydrogen price and fuel cell system cost are the major uncertainties that determine cost competitiveness of FCEVs.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Bernd Herrenkind, Ilja Nastjuk, Alfred Benedikt Brendel, Simon Trang, Lutz M. Kolbe〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉The self-driving public bus (SDPB) holds the potential to replace human-operated driving with more eco-friendly means and is therefore a valuable mobility solution for our future. The SDPB is based on the innovative technology of autonomous driving, which can only be guaranteed future market success with broad enough user acceptance. This acceptance is thus an essential factor for the growth of SDPB services. In this context, the travel behavior of young people is particularly interesting, as its development will continually demonstrate future mobility behavior trends. However, little research has been conducted regarding the best methods for motivating young people to accept SDPBs as a viable mode of travel.〈/p〉 〈p〉To address this topic, we first conducted a literature review, identifying factors that potentially influence SDPB acceptance. Subsequently, we developed a comprehensive research model based on the life-oriented approach and the technology acceptance model. This conceptualization was validated by a survey of 268 SDPB riders in real-world traffic. The results reveal several novel factors influencing the acceptance of SDPBs, in particular regarding differences in age. Our research contributes to existing research on both the life-oriented and travel behavior approaches by highlighting age differences and their importance in the field. For instance, our findings demonstrate a vital need to account for age differences when deriving policy implications for future mobility solutions.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): S.M. Patella, F. Scrucca, F. Asdrubali, S. Carrese〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉This paper presents the results of a Carbon Footprint (CF) study of Autonomous Vehicles (AVs) and their environmental impact on the transportation network. By assuming that fully AVs are battery electric vehicles (BEVs) with connectivity, light detection and ranging sensors, this study measures the environmental impact at the urban mobility level. The AV complete life cycle impact was firstly evaluated. Next, by comparing the current situation with a future hypothetical scenario (100% AVs penetration), the positive environmental effect of the adoption of AVs on a real road network (city of Rome) is shown. For this scope, a traffic simulation-based approach was used to investigate the effects of AVs on the network congestion.〈/p〉 〈p〉The results show that the full AVs penetration scenario leads to an improvement in the network performances in terms of travel time and average speed. The Total Time Spent (TTS) decreases (−35% for intra-urban roads and −21% for highways), and the average network speed increases (48% for intra-urban road and 37% for highways). Moreover, the final amount of Vehicle Kilometer Traveled (VKT) shows an 8% increase on longer extra-urban routes, due to the higher capacity impact of AVs on highways, with a consequent load reduction for intra-urban shortcutting routes. In terms of life cycle impacts, AVs are characterized by the highest Greenhouse Gases (GHG) emissions related to construction, maintenance and end-of-life processes (on average 35% compared to internal combustion engine vehicles, 22% compared to hybrid electric vehicles and 5% compared to battery electric vehicles). Nevertheless, a 100% AVs penetration scenario generates a reduction of the environmental impact at the mobility system level of about 60%.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Jingjing Yu, Stefan Voß, Guolei Tang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Shore side electricity (SSE) is the use of electricity from the shore to power a ship’s system when it is berthing at ports. It is a solution to reduce the emissions of auxiliary engines at berth and to improve the local and regional air quality. This paper develops a multi-objective model that integrates spatial and temporal dimensions for strategic planning regarding whether and when to retrofit ships to use SSE. The strategic planning problem is to maximize the environmental benefit and to minimize the payback period of the investment over the entire planning horizon. By adopting an improved multi-objective genetic algorithm (NSGA-II), a series of retrofit strategies for container ships calling at Dalian Port in China are obtained under a projected annual visiting frequency of ships with different ship sizes and shipping lines. Depending on a selected retrofit strategy, the sum of the payback periods of ships that are determined to be retrofitted is 46 years (on average less than four years) and the environmental benefit of using SSE can be up to 128 million USD for Dalian Port in the planning horizon from 2020 to 2035. The results show that using SSE is an efficient method to decline emissions within the maritime sector and validate that the proposed methodology can be useful to ship owners to decide upon investing in SSE applications and to promote the development of green shipping and green ports.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Sina Rastani, Tuğçe Yüksel, Bülent Çatay〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Electric freight vehicles have strong potential to reduce emissions stemming from logistics operations; however, their limited range still causes critical limitations. Range anxiety is directly related to the total amount of energy consumed during trips. There are several operational factors that affect the energy consumption of electric vehicles and should be considered for accurate route planning. Among them, ambient temperature arises as a key factor because cabin heating or cooling may significantly increase the energy discharged from the battery during the trip and reduce the driving range. Additionally, cold temperatures decrease the battery efficiency and cause performance losses. In this study, we investigate the effect of ambient temperature on the fleet composition, energy consumption, and routing decisions in last-mile delivery operations. First, we present the mathematical programming formulation of the problem. Next, we perform an extensive computational study based on benchmark data from the literature. For solving the small-size instances we use a commercial solver. For solving the large-size instances we employ an adaptive large neighborhood search algorithm. Our results show that the route plans made without considering the ambient temperature effect may lead to inefficient operations and disruptions. Specifically, the fleet size and energy consumption can increase by 46% and 81%, respectively, in small-size problems on average due to ambient temperature whereas the average increase can reach 15% and 68%, respectively, in large-size problems. Finally, we present a case study from a logistics company operating in Southern Turkey to provide managerial insights to both researchers and practitioners.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Alexandros T. Zachiotis, Evangelos G. Giakoumis〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The effect of various non-regulatory parameters on a vehicle’s performance and emissions is investigated in this study, i.e. road grade, presence of crosswinds, surface wetness, tire pressure and use of the vehicle’s auxiliary systems. The vehicle under study is a diesel-powered turbocharged light commercial vehicle, running on the WLTC 3–2 cycle; comparison with the NEDC is also provided. The results derive from a computational code based on an engine-mapping approach applying experimentally derived correction coefficients accounting for transient operation. The engine code is coupled to a vehicle model that calculates the main longitudinal dynamic parameters (tire rolling resistance, aerodynamic performance, gearbox efficiency) on a fundamental basis. Soot and nitrogen monoxide are the examined pollutants, with fuel and energy consumption and CO〈sub〉2〈/sub〉 emissions computed and discussed too. From the parameters examined, road grade was found to have the greatest impact on emissions (CO〈sub〉2〈/sub〉: +116.8%, NO: +107.2%, Soot: +100.7%, for the maximum road grade examined of 8%), followed by wind speed (CO〈sub〉2〈/sub〉: +38.9%, NO: +33.6%, Soot: +12%, for the maximum wind speed examined of 80 km/h). Auxiliary power demand can have a considerable effect, mostly on fuel consumption/CO〈sub〉2〈/sub〉 emissions (+13.7% for maximum auxiliary power demand of 5000 W); the impact of tire inflation pressure and surface wetness is comparably smaller. Among the two driving cycles, the WLTC proved to be more ‘sensitive’ to road load changes, due to the broader speed range encompassed and its highly transient nature, compared to the softer NEDC.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 65〈/p〉 〈p〉Author(s): Michel André, Anaïs Pasquier, Marion Carteret〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Low emission zones are frequently envisaged as a means of decreasing air pollution in city centres. In the present study, we used video monitoring to characterize the in-use local vehicle fleet at several points in the Île-de-France region (which includes the city of Paris), enabling accurate description of the type of engine and vehicle age and emission standard, which together determine their pollutant emission levels. Local vehicle fleets differed from French national estimates, as further confirmed by a Regional Mobility Survey. Both approaches (video monitoring and mobility survey) demonstrated geographical differences in the proportions of diesel and of recent vehicles. Economically advantaged areas, with lower rates of polluting and diesel-fuelled vehicles, are thus further advantaged as regards air quality and less affected by driving restrictions. Simulation of pollutant emissions demonstrated the sensitivity of the estimates to local fleet composition. They also raised the important contributions of traffic outside the city centre, of heavy vehicles and cold starts. Knowledge of the local vehicle fleet is thus important for designing low emission zones that will be effective in terms of air pollution and equitable in terms of geographical areas.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 65〈/p〉 〈p〉Author(s): Laura Minet, Jonathan Stokes, James Scott, Junshi Xu, Scott Weichenthal, Marianne Hatzopoulou〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study was motivated by an interest in capturing the factors affecting the exposure of cyclists to ambient Ultrafine Particles (UFP), Black Carbon (BC), and noise (LA〈sub〉eq〈/sub〉) across the entire bicycle network of the City of Toronto. Measurements were conducted along 270 km of unique roads, and we developed land use regression models and exposure surfaces. Median UFP, BC and noise levels recorded were 19,848 part/cm〈sup〉3〈/sup〉, 1224 ng/m〈sup〉3〈/sup〉, and 72.9 dB respectively. The average UFP and BC exposures along the biking routes (18,900 part/cm〈sup〉3〈/sup〉 and 1130 ng/m〈sup〉3〈/sup〉) were higher than the average levels measured at a fixed station located in downtown Toronto (13,300 part/cm〈sup〉3〈/sup〉 and 809 ng/m〈sup〉3〈/sup〉). The highest UFP and BC levels were experienced on dedicated bicycle tracks (30,000 part/cm〈sup〉3〈/sup〉 and 1600 ng/m〈sup〉3〈/sup〉 as median concentrations), while the highest noise levels occurred on major roads (median of 74 dB). In contrast, median levels on trails were 13,200 part/cm〈sup〉3〈/sup〉, 535 ng/m〈sup〉3〈/sup〉 and 70.2 dB, for UFP, BC, and noise. The exposure surfaces developed for the air pollutants and noise were intersected with the planned extensions to the bicycle network in the City of Toronto to evaluate the distributions of exposures expected across the future cycling network. We observe that the mean and median UFP, BC, and noise levels across planned facilities are equal to or significantly higher than the levels across the current network.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S1361920918301925-ga1.jpg" width="269" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 70〈/p〉 〈p〉Author(s): Tom Wenzel, Clement Rames, Eleftheria Kontou, Alejandro Henao〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper identifies major aspects of ridesourcing services provided by Transportation Network Companies (TNCs) which influence vehicles miles traveled (VMT) and energy use. Using detailed data on approximately 1.5 million individual rides provided by RideAustin in Austin Texas, we quantify the additional miles TNC drivers travel: before beginning and after ending their shifts, to reach a passenger once a ride has been requested, and between consecutive rides (all of which is referred to as deadheading); and the relative fuel efficiency of the vehicles that RideAustin drivers use compared to the average vehicle registered in Austin. We conservatively estimate that TNC drivers commute to and from their service areas accounts for 19% of the total ridesourcing VMT. In addition, we estimate that TNC drivers drove 55% more miles between ride requests within 60 min of each other, accounting for 26% of total ridesourcing VMT. Vehicles used for ridesourcing are on average two miles per gallon more fuel efficient than comparable light-duty vehicles registered in Austin, with twice as many are hybrid-electric vehicles. New generation battery electric vehicles with 200 miles of range would be able to fulfill 90% of full-time drivers’ shifts on a single charge. We estimate that the net effect of ridesourcing on energy use is a 41–90% increase compared to baseline, pre-TNC, personal travel.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S1361920918309878-ga1.jpg" width="298" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 70〈/p〉 〈p〉Author(s): Stefanie Peer〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper investigates the determinants of cycling in a rather unique setting: the relocation of one of the largest Austrian universities from the North to the East of Vienna (a distance of approximately 5 km). We analyze the students’ cycling behavior before and after the university relocation based on a large-scale (retrospective) online survey. Unlike earlier studies on cycling determinants, which often suffer from endogeneity, we can exploit the fact that the university relocation causes commute-related variables to change exogenously, whereas socio-economic and attitudinal characteristics as well as the trip purpose remain constant. We find a large positive correlation in the propensity to cycle to the old and the new university location at the person level as well as substantial heterogeneity in cycling inclination across students, which can only partially be explained by socio-economic and attitudinal variables. Moreover, we find evidence that past cycling times form a reference point for future mode choice decisions.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 70〈/p〉 〈p〉Author(s): Emir Çabukoglu, Gil Georges, Lukas Küng, Giacomo Pareschi, Konstantinos Boulouchos〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.gif" overflow="scroll"〉〈mrow〉〈msub〉〈mrow〉〈mi mathvariant="italic"〉CO〈/mi〉〈/mrow〉〈mrow〉〈mn〉2〈/mn〉〈/mrow〉〈/msub〉〈/mrow〉〈/math〉 emissions of road freight transport may seem secondary to passenger cars, but electrification could eliminate direct emissions of cars. For heavy-duty trucks, it is unclear if substituting Diesel is even an option. We developed a data-driven approach to explore this issue: it estimates feasibility considering the daily operation patterns of every vehicle in the fleet. This paper presents results for fuel cell propulsion systems. If every Swiss truck drove on hydrogen produced exclusively by electrolysis, full decarbonisation would draw over 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si31.gif" overflow="scroll"〉〈mrow〉〈mn〉8〈/mn〉〈mspace width="0.25em"〉〈/mspace〉〈mtext〉TWh〈/mtext〉〈/mrow〉〈/math〉 of renewable electricity (〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si32.gif" overflow="scroll"〉〈mrow〉〈mn〉13〈/mn〉〈mo〉%〈/mo〉〈/mrow〉〈/math〉 of the national consumption). That corresponds to roughly 60 km〈sup〉2〈/sup〉 of photovoltaic panels with 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si33.gif" overflow="scroll"〉〈mrow〉〈mn〉1.5〈/mn〉〈mspace width="0.25em"〉〈/mspace〉〈mtext〉GW〈/mtext〉〈/mrow〉〈/math〉 peak power. We found that current fuel-cell technology almost completely realized that potential, provided vehicles could refuel during the day. The autonomy range was generally better than with battery electric systems without significant weight increase (relative to the original vehicle). Refuelling could take over half an hour, requiring a dense energy infrastructure, able to refuel hundreds of vehicles in parallel to avoid congestion (i.e. vehicles waiting). The reduction of direct emissions was easily overcompensated by indirect emissions of generation: the Swiss consumer mix lead to virtually no overall reduction, while natural gas powerplants lead to a significant 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.gif" overflow="scroll"〉〈mrow〉〈msub〉〈mrow〉〈mi mathvariant="italic"〉CO〈/mi〉〈/mrow〉〈mrow〉〈mn〉2〈/mn〉〈/mrow〉〈/msub〉〈/mrow〉〈/math〉 increase. We concluded that hydrogen is technically a very attractive decarbonisation agent for heavy-duty vehicles, but significant investments may be required to ensure that (a) hydrogen production is truly renewable and (b) vehicles have adequate access to additional energy during the day.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 14 December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment〈/p〉 〈p〉Author(s): N. Coulombel, V. Boutueil, L. Liu, V. Viguié, B. Yin〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper investigates how and to what extent changes in user behavior may mitigate the environmental benefits of urban ridesharing, a phenomenon commonly referred to as “rebound effect”. Ridesharing reduces both the individual cost of car travel (through cost splitting) and road travel times (by decreasing congestion). This may trigger a number of behavioral changes among transportation users, including: making less detours to avoid congestion (〈em〉route choice〈/em〉 effect), switching from public transit and active modes to the car (〈em〉modal shift〈/em〉 effect), travelling longer distances (〈em〉distance〈/em〉 effect), and relocating further from the urban center (〈em〉relocation〈/em〉 effect). Taking Paris region as a case study, this research applies an integrated transportation/land-use model to evaluate several ridesharing scenarios and quantify the four rebound effects. The overall rebound effect is found to be substantial, cancelling out from 68 to 77% of CO〈sub〉2〈/sub〉 emission reductions and from 52 to 73% of aggregated social benefits (including congestion, air quality, CO〈sub〉2〈/sub〉 emissions, noise) expected from ridesharing. This is primarily the result of the modal shift effect, supplemented as ridesharing develops by the distance effect. Although the simplified representation of ridesharing in the baseline model calls for caution regarding these estimates, a sensitivity analysis corroborates the main findings and the prevalence of substantial rebound effects. The paper also investigates to what extent three complementary policies - improving public transit, reducing road capacity or increasing the cost of car travel – might limit the overall rebound effect and thereby maximize the benefits of urban ridesharing.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 11 December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment〈/p〉 〈p〉Author(s): Scott Hardman, Rosaria Berliner, Gil Tal〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Most major automakers are developing vehicles with some level of automated driving capability. These vehicles range from those with adaptive cruise control to full driverless vehicles. These vehicles are collectively referred to as automated vehicles. The adoption of automated vehicles by consumers is not well understood. It is likely that the first buyers will be typical early adopters i.e. consumers who have different lifestyles, attitudes, and socio-demographic profiles compared to the general population. Using a questionnaire survey of 2715 consumers in 36 states in the USA, we investigate the attitudes of early adopters of one automotive technology: plug-in electric vehicles (PEVs). This sample was selected so that the perceptions and purchase intentions of early adopters could be investigated. This is opposed to assessing the attitudes of the public who are unlikely to be knowledgeable about automated vehicles and unable to accurately assess the vehicles and estimate their own purchase intentions. This study finds that PEV early adopters have positive perceptions of automated vehicles. However, being a PEV adopter does not necessarily lead to interest in purchasing an automated vehicle. PEV adopters are clustered into 5 different groups with differing levels of interest in automated vehicles (from “Pioneers” to “Laggards”). The results suggest that automated vehicles are likely to be purchased by a small group of pioneering consumers. These “Pioneers” are likely to be high income consumers, with good knowledge and positive perceptions of the automated vehicles (on safety, comfort, and purchase price), and positive attitudes towards technology in general.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): Anders Nordelöf, Emma Grunditz, Sonja Lundmark, Anne-Marie Tillman, Mikael Alatalo, Torbjörn Thiringer〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Ongoing development of electrified road vehicles entails a risk of conflict between resource issues and the reduction of greenhouse gas emissions. In this study, the environmental impact of the core design and magnet material for three electric vehicle traction motors was explored with life cycle assessment (LCA): two permanent magnet synchronous machines with neodymium-dysprosium-iron-boron or samarium-cobalt magnets, and a permanent magnet-assisted synchronous reluctance machine (PM-assisted SynRM) with strontium-ferrite magnets. These combinations of motor types and magnets, although highly relevant for vehicles, are new subjects for LCA. The study included substantial data compilation, machine design and drive-cycle calculations. All motors handle equal take-off, top speed, and driving conditions. The production (except of magnets) and use phases are modeled for two countries – Sweden and the USA – to exemplify the effects of different electricity supply. Impacts on climate change and human toxicity were found to be most important. Complete manufacturing range within 1.7–2.0 g CO〈sub〉2〈/sub〉-eq./km for all options. The PM-assisted SynRM has the highest efficiency and lowest emissions of CO〈sub〉2〈/sub〉. Copper production is significant for toxicity impacts and effects on human health, with problematic emissions from mining. Resource depletion results are divergent depending on evaluation method, but a sensitivity analysis proved other results to be robust. Key motor design targets are identified: high energy efficiency, slender housings, compact end-windings, segmented laminates to reduce production scrap, and easy disassembly.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S1361920918302530-ga1.jpg" width="252" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): Aliasghar Mehdizadeh Dastjerdi, Sigal Kaplan, Joao de Abreu e Silva, Otto Anker Nielsen, Francisco Camara Pereira〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The increasing complexity and demand of transport services strains transportation systems especially in urban areas with limited possibilities for building new infrastructure. The solution to this challenge requires changes of travel behavior. One of the proposed means to induce such change is multimodal travel apps. However, understanding the motivators underlying individuals’ travel intentions is essential to design and evaluate their effectiveness. This paper pinpoints and analyses the drivers and barriers that influence individual travel decisions when using such apps. The analytical framework relies on Alderfer's ERG model of human needs that relate the individual’s intentions to three domains, namely (1) Existence, (2) Relatedness and (3) Growth needs. Furthermore, environmental attitude, information privacy concerns and perceived difficulties when using the system are incorporated as to better explain user-sided heterogeneity. The case-study focuses on a new travel information system in Copenhagen (Denmark), which is not yet operational, through a technology-use preference survey among 828 travelers. Structural equation models revealed that the motivation for choices are specific to individual users and depend on wide-ranging factors that go beyond traditional economic and socio-demographic methods. The study revealed (1) different intentions among individuals according to the perceived value of the new information system, (2) a relation between different environmental attitude constructs and users’ needs, (3) a stronger appeal to use the system for individuals with higher needs of developing social self-concept and eco-travel self-efficacy as well as with lower perceived privacy risk and perceived difficulties, (4) that both functional and psychological factors affect adoption intention.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S1361920918304735-ga1.jpg" width="366" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): Rafael F.F. Lemme, Edilson F. Arruda, Laura Bahiense〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Electromobility can be one of many solutions to the environmental challenge facing society nowadays, and the dissemination of policies towards the adoption of electric vehicles (EVs) urges the development of studies to assess their actual benefits in contrast to both conventional and other alternative technologies. This work proposes an optimization model to evaluate the influence of the selected parameters in the economic and environmental dimensions of different vehicle technologies and the optimal fleet composition for small-scale car sharing. The model is applied to car sharing system VAMO, located in Fortaleza (Brazil), and the decision variables comprise pure electric (BEV), plug-in hybrid (PHEV) and internal combustion engine (ICEV) vehicles. Baseline results are strongly influenced by the economic dimension, showing that existing infrastructure and well-established technology are great advantages for ICEVs and major barriers for EVs. In that sense, ethanol arises as a balanced alternative between costs and emissions. However, EVs represent a strong environmental appeal considering global emissions and local pollutants and even with economic losses in the short-term, investments in electromobility could come out as a positioning strategy in a future business with strong perspectives of growth, be it technological or in market share. The results suggest that all vehicle technologies will play an important role during this transition period to a desired sustainable mobility.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): J. Semeijn, C.J. Gelderman, J.M.C. Schijns, R. van Tiel〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Although it is often assumed that physically disabled people have different environmental attitudes and behavior, there has been very little empirical evidence supporting this claim. This study is the first to shed light upon the determinants of physically disabled consumers’ pro environmental purchase intentions. We gathered survey data from (net) 118 physically disabled consumers about their purchase intentions for environmentally friendly cars. Structural equation modeling is used for the analysis. The results show that attitude and social norms are important predictors of environmentally friendly purchase intentions. Both hedonic and functional motivation have an indirect effect, while attitude has a direct effect on physically disabled people’s purchase intentions for environmentally friendly cars. Apparently, physically disabled people value the opinions of others in their living and working environment. Notably, we did not observe an expected impact of behavioral control or lack thereof on the purchase intention of environmentally friendly cars. The study offers insights that can be helpful to marketing managers and policymakers in tailoring their strategies to the purchase intentions of physically disabled consumers.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): Federico Perrotta, Tony Parry, Luis C. Neves, Thomas Buckland, Emma Benbow, Mohammad Mesgarpour〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉This paper presents an assessment of the accuracy of the HDM-4 fuel consumption model calibrated for the United Kingdom and evaluates the need for further calibration of the model. The study focuses on HGVs and compares estimates made by HDM-4 to measurements from a large fleet of vehicles driving on motorways in England. The data was obtained from the telematic database of truck fleet managers (SAE J1939) and includes three types of HGVs: light, medium and heavy trucks. Some 19,991 records from 1645 trucks are available in total. These represent records of trucks driving at constant speed along part of the M1 and the M18, two motorways in England.〈/p〉 〈p〉These conditions have been simulated in HDM-4 by computing fuel consumption for each truck type driving at a constant speed of 85 km/h on a flat and straight road segment in good condition.〈/p〉 〈p〉Estimates are compared to real measurements under two separate sets of assumptions. First, the HDM-4 model calibrated for the UK has been used. Then, the model was updated to take into account vehicle weight and frontal area specific to the considered vehicles.〈/p〉 〈p〉The paper shows that the current calibration of HDM-4 for the United Kingdom already requires recalibration. The quality of the model estimates can be improved significantly by updating vehicle weight and frontal area in HDM-4. The use of HGV fleet and network condition data as described in this paper provides an opportunity to verify HDM-4 continuously.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): Dafeng Xu〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉More than 50 bikeshare programs have been launched in the U.S. since 2010. In this paper, I estimate the effects of bikeshare programs on the prevalence of obesity at the county level. To do so, I merge bikeshare system data with obesity data released by Centers for Disease Control and Prevention, and construct a county-level panel covering the period of 2007–2013. I employ a difference-in-differences empirical framework, in which I compare the obesity rate before and after the introduction of the bikeshare programs in counties that have ever launched bikeshare programs, and use counties that have never introduced bikeshare programs as the control group. Difference-in-differences estimates suggest the significant public health effect of bikeshare programs: the introduction of the bikeshare programs leads to moderate declines in obesity rates; a possible mechanism is its impacts on leisure-time physical activities. I also conduct various additional tests to check the robustness of the above findings. These tests show that the conclusion of this paper is robust to changes to samples and empirical models.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): Na Chen, Greg Lindsey, Chih-Hao Wang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Transportation, parks, and health organizations are collaborating to develop multiuse trail networks that meet the needs of metropolitan residents for utilitarian travel, recreation, and fitness. This paper describes how trails are used and explores correlates of trail use in the Greater Cincinnati region. Drawing on a systematic survey of users, we use ordinary probit and spatial models to explore the effects of socio-demographics, trip characteristics, attitudes, and the built environment, on recreational and utilitarian use. Most (89%) respondents report using trails for recreation; just 8.8% say they use trails for utilitarian purposes. Ordinary probit models show that users reporting recreational use are significantly more likely to be female, have incomes greater than $120,000, and travel longer distances on trails, but less likely to bike or walk to access trails. Transit connectivity is negatively correlated with recreational use. Trail users reporting utilitarian purposes are disproportionately male, significantly less likely to have incomes greater than $120,000, and more likely to take short trips on trails and to access trails by cycling or walking. They say they would commute more by cycling if connectivity were improved. Spatial probit model indicates negative spatial relationships among recreational users, implying the absence of a spatially-based common culture of trail use. Trail planners in this region can use these findings to strengthen the planning and design of trail networks and to meet the needs of different users. Given the finding most trail use is for recreational purposes, additional studies of the needs of utilitarian users are warranted.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): Alexandros Sdoukopoulos, Magda Pitsiava-Latinopoulou, Socrates Basbas, Panagiotis Papaioannou〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Transport is widely considered as a sector with significant positive and negative externalities affecting society, environment and economy. The fact of incorporating the main principles of sustainable development into transport planning is of prime importance. However, moving towards transport sustainability is a challenging task; it requires a paradigm shift as well as the constant monitoring and intensive evaluation of the current conditions through broadly accepted methodological tools such as indicators. In this context, the scope of the current research is to provide a complete picture of the approaches which aim at measuring progress towards transport sustainability as well as facilitating the development of new initiatives by highlighting the major trends. Consequently, a considerable number (78) of sustainable transport indicator initiatives were selected through an extensive literature review. Accordingly, descriptive statistics was used regarding the main features of the examined initiatives, while an analysis focused on the 2644 included indicators was subsequently implemented. The current research illustrates the linkages among the sustainability pillars and the selected objectives/themes. It also points out the great variability regarding the hierarchical structure, categorizes the considerable number of themes found in the literature into smaller groups, presents the most commonly used themes and indicators, and finally proposes an alternative categorization of weighting schemes concerning indexes. An attempt has been made so that this study can become a meaningful operational tool for researchers aiming at promoting the relevant research by contributing to the selection of the most suitable yet compatible and scientifically valid methods for each case.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): João Paulo C. Araújo, Carlos A.O. Palha, Francisco F. Martins, Hugo M.R.D. Silva, Joel R.M. Oliveira〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The energy or fuel consumption of the millions of vehicles that daily operate in road pavements has a significant economic and environmental impact on the use phase of road infrastructures regarding their life cycle analysis. Therefore, new solutions should be studied to reduce the vehicles energy consumption, namely due to the tire-pavement interaction, and contribute towards the sustainable development. This study aims at estimating the energy consumption due to the rolling resistance of tires moving over pavements with distinct surface characteristics. Thus, different types of asphalt mixtures were used in the surface course to determine the main parameters influencing the energy consumption. A laboratory scale prototype was developed explicitly for this evaluation. Data mining techniques were used to analyze the experimental results due to the complex correlation between the data collected during the tests, providing meaningful results. In particular, the artificial neural network allowed to obtain models with excellent capacity to estimate energy consumption. A sensitive analysis was carried out with a five input parameter model, which showed that the main parameters controlling the energy consumption are the vehicle speed and the mean texture depth.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): Luis María Abadie, Nestor Goicoechea〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Over the last decade, marine engine engineering has evolved considerably, to the point where engine technology can be considered mature and reliable using LNG as fuel without affecting safety at sea. This paper analyses the choice between diesel or dual engines jointly and considers the alternatives of installing or not installing a sulphur scrubber when building a new vessel. The dual engine is more flexible because it can consume liquefied natural gas (LNG) as other marine fuels but the initial investment is more expensive. On the other hand, the use of scrubbers enables the use of marine fuels with high sulphur content in Emission Control Areas (ECAs), these marine fuels are usually cheaper also we consider Selective Catalytic Reduction technology (SCR) in all cases to minimize NOx. The paper calibrates a stochastic model for LNG and determines four marine fuel correlated prices. The work also considers a possible regulatory change from a non ECA to an ECA in the future. When we aggregate the installation costs to the present value of the expected combustible cost under uncertainty we can select the cheapest alternative. We obtain a minimum of expected present value of investment and fuels cost of 25.62 million US$ with a Dual engine with scrubber configuration. Our work shows that, in the cases considered, the use of a dual engine is the best alternative minimizing the total of investment and fuel costs. Finally, we analyse the distribution of fuel cost and its associated risks.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S1361920918310733-ga1.jpg" width="283" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): J. van Manen, V. Grewe〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Aviation contributes significantly to anthropogenic climate change, and one promising possibility for mitigation is eco-efficient flight planning by avoiding climate sensitive regions with only small changes in the aircraft trajectories. Climate sensitive regions result from strong spatial variation of the global climate impact of local non-CO〈sub〉2〈/sub〉 emissions, which are expressed by so-called climate change functions. Previous research established high-fidelity climate change functions (CCFs) for aviation water vapour and NO〈sub〉x〈/sub〉 emissions, and contrail formation with a climate model as inputs for air traffic optimisation. The mitigation potential in this case study is promising but the climate change function simulations are too computationally intensive for real-time calculation and thus cannot be applied operationally. In this study we show for the first time that this problem can be overcome by formulating algorithmic approximations of the global climate impact. Here we approximate water vapour concentration changes from local aviation water vapour emissions, ozone changes from local NO〈sub〉x〈/sub〉 emissions and methane changes from local NO〈sub〉x〈/sub〉 emissions (i.e. algorithmic climate change functions; aCCFs) from instantaneous model weather data using regression analysis. Four candidate algorithms are formulated per chemical species and traded off. The final adjusted regression coefficients, indicating how well the aCCFs represent the CCFs, are 0.59, 0.42, and 0.17 for water vapour, ozone and methane. The results show that the meteorology at the time of emission largely controls the fate of the emitted species, where the quality of the aCCF degrades with increasing lifetime of the respective species.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 24 December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment〈/p〉 〈p〉Author(s): Rainer Lempert, Jiaying Zhao, Hadi Dowlatabadi〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Carshare membership in North America has grown approximately 25% per year over the past decade. Some have attributed this to pro-environmental values and low-impact lifestyles of millennials, the primary users of carsharing. Many municipal governments have adopted this belief and support carsharing through various accommodations and subsidies. Results from a survey in Vancouver, Canada (which has the highest level of carsharing in North America) showed that one-way and two-way carsharing members have different motivations for carsharing and travel patterns. One-way members, primarily millennials, self-report that they carshare for convenience, using shared vehicles twice as frequently and private vehicles three times as frequently as two-way members. Two-way members choose carsharing for financial savings and a more efficient lifestyle. They tend to walk and bike more often than one-way members and the overall Vancouver population. These trip mode and frequency differences are consistent across age, gender, income, and geography. Perhaps as a consequence of the above, we also found that while one-way members are on average younger and wealthier, two-way members self-report as having more affordable lifestyles. These findings point to two-way carsharing members adhering to more efficient, sustainable lifestyles. Municipalities may consider these differences in motivations and trip patterns between one-way and two-way members of relevance in their carsharing policies.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 23 December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment〈/p〉 〈p〉Author(s): Juelin Yin, Lixian Qian, Junjie Shen〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Sharing-economy platforms have gained momentum in urban areas worldwide by offering the potential for efficient resource utilisation and novel value creation. A recent addition to the mobility sector of the sharing economy is the dockless bike-sharing system (DBSS), which emerged in late 2015 with the aim of complementing urban mobility and contributing to urban sustainability. However, recently, debate and controversy have emerged about the potential negative consequences of DBSS. Building on the value-creation literature, and drawing on practice theory and the resource-integration perspective, we investigate how users participate in value co-creation and co-destruction activities related to DBSS. Through a thematic analysis of 8813 social media (i.e. Sina Weibo) tweets from April 2016 to December 2017, we find that riding experience is the most important practice in the core using process for both value co-creation and co-destruction, and that post-riding practices can result in significant value co-destruction. In the value-formation process of DBSS, the critical firm resources are product–service resources and relational resources, and the critical customer resources are emotional resources, relational resources and energy resources. We also argue the enabling role of peripheral practices in the transition between value co-creation and co-destruction. We contribute to the literature by proposing a value co-creation and co-destruction framework for DBSS derived from key social practices and resources.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 28 December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment〈/p〉 〈p〉Author(s): Liridona Sopjani, Jenny Janhager Stier, Sofia Ritzén, Mia Hesselgren, Peter Georén〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Low-carbon mobility alternatives, such as shared services integrating light electric vehicles, support transitions to sustainable transport systems. However, new products and services are not enough, as changes must also incorporate the practices of travelling, infrastructure, and mobility cultures in which users of mobility solutions are core stakeholders. This paper argues that user involvement is necessary in sustainable innovation processes but that the expected diversity of user roles and their involvement can also lead to contrasting outcomes for sustainable innovation transitions. Guided by theory in user involvement, this study investigated users and nonusers of light electric vehicles in a sharing mobility service system set up as living lab in two large workplaces in Sweden. Fifty-one interviews with employees at the workplaces were conducted during the implementation process and analysed combined with a questionnaire and data from system tracking through sensor technology. The paper finds that both users and non-users are co-creators in building momentum for sustainable mobility alternatives and provides a spectrum of user roles with defined characteristics. Four roles are distinguished within this spectrum: 〈em〉vigilant users〈/em〉, 〈em〉passive collaborators〈/em〉, 〈em〉active decision makers〈/em〉 and 〈em〉ambassadors〈/em〉. We suggest that a 〈em〉convergent activation strategy〈/em〉 is deployed for involving a full spectrum of users in order to capture their insights in ways that positively affect transition. Such a strategy addresses users and non-users as part of decision-making concerning alternatives and cultivates a culture of user collaboration, while also enabling a plurality of contributions in order to challenge existing regimes and established practices among individuals.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): ChengHe Guan, Sumeeta Srinivasan, Chris P. Nielsen〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Developing less auto-dependent urban forms and promoting low-carbon transportation (LCT) are challenges facing our cities. Previous literature has supported the association between neighborhood form and low-carbon travel behaviour. Several studies have attempted to measure neighborhood forms focusing on physical built-environment factors such as population and employment density and socio-economic conditions such as income and race. We find that these characteristics may not be sufficiently fine-grained to differentiate between neighborhoods in Chinese cities. This research assesses characteristics of neighborhood spatial configuration that may influence the choice of LCT modes in the context of dense Chinese cities. Urban-form data from 40 neighborhoods in Chengdu, China, along with a travel behaviour survey of households conducted in 2016, were used to generate several measures of land use diversity and accessibility for each neighborhood. We use principle component analysis (PCA) to group these variables into dimensions that could be used to classify the neighborhoods. We then estimate regression models of low-carbon mode choices such as walking, bicycling, and transit to better understand the significance of these built-environment differences at the neighbourhood level. We find that, first, members of households do choose to walk or bike or take transit to work provided there is relatively high population density and sufficient access to public transit and jobs. Second, land-use diversity alone was not found to be significant in affecting LCT mode choice. Third, the proliferation of gated communities was found to reduce overall spatial connectivity within neighborhoods and had a negative effect on choice of LCT.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 14 December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment〈/p〉 〈p〉Author(s): Christine Kormos, Jonn Axsen, Zoe Long, Suzanne Goldberg〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This is Part 2 of a two-part study that explores latent demand for three types of zero-emissions vehicles (ZEVs): plug-in hybrid electric vehicles (PHEVs), battery electric vehicles (BEVs), and hydrogen fuel cell vehicles (HFCVs). Using an in-depth, Reflexive Participant approach to data collection, our survey instrument includes two measures of latent demand implemented with a representative sample of 2123 new vehicle-buying households in Canada in 2017. While Part 1 (Long et al., this issue) reports on a design space exercise, here we summarize results from a stated choice experiment, using a latent class choice model to quantify respondent preferences and motivations, and the heterogeneity therein. We identify five unique respondent classes (or segments) that largely differ by their preferred drivetrain, only three of which demonstrate significant interest in ZEVs: PEV-enthusiast (representing 13% of the sample), PHEV-oriented (22%), and ZEV-neutral (21%). Respondents in all three classes tend to have higher levels of environmental concern or engagement in an environment-oriented lifestyle. All classes significantly value purchase price and incentives, but vary widely in valuation of fuel savings, charging access, and refueling access – with little overall valuation of driving range and public charging access. We calculate conditional choice probabilities as estimates of ZEV latent demand, which is equivalent to 29% of new market share under base conditions, and significantly increases to a high of 49% with purchase incentives and widespread charger deployment. Our discussion compares insights provided by the two stated response approaches to latent demand (in Parts 1 and 2), making a case for overall complementarity.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): Raphael E. Stern, Yuche Chen, Miles Churchill, Fangyu Wu, Maria Laura Delle Monache, Benedetto Piccoli, Benjamin Seibold, Jonathan Sprinkle, Daniel B. Work〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉It is anticipated that in the near future, the penetration rate of vehicles with some autonomous capabilities (e.g., adaptive cruise control, lane following, full automation, etc.) will increase on roadways. This work investigates the potential reduction of vehicular emissions caused by the whole traffic stream, when a small number of autonomous vehicles (e.g., 5% of the vehicle fleet) are designed to stabilize the traffic flow and dampen stop-and-go waves. To demonstrate this, vehicle velocity and acceleration data are collected from a series of field experiments that use a single autonomous-capable vehicle to dampen traffic waves on a circular ring road with 20–21 human-piloted vehicles. From the experimental data, vehicle emissions (hydrocarbons, carbon monoxide, carbon dioxide, and nitrogen oxides) are estimated using the MOVES emissions model. This work finds that vehicle emissions of the entire fleet may be reduced by between 15% (for carbon dioxide) and 73% (for nitrogen oxides) when stop-and-go waves are reduced or eliminated by the dampening action of the autonomous vehicle in the flow of human drivers. This is possible if a small fraction (〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.gif" overflow="scroll"〉〈mrow〉〈mo〉∼〈/mo〉〈/mrow〉〈/math〉5%) of vehicles are autonomous and designed to actively dampen traffic waves. However, these reductions in emissions apply to driving conditions under which stop-and-go waves are present. Less significant reductions in emissions may be realized from a deployment of AVs in a broader range of traffic conditions.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): Ivan Muñiz, Miquel-Àngel Garcia-López〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this research we examine the relationship between the ecological footprint of commuting and several variables of urban form and spatial structure for the case of the Barcelona Metropolitan Region, paying special attention to the role of population density and polycentrism. Stopping the low density urban dispersion and encourage polycentrism are two of the main policies advocated by the supporters of the Compact City Approach to achieve more sustainable cities. The literature on the impact of population density offers inconclusive results and studies that address the role of spatial structure are very scarce. The results obtained in this research indicate that polycentrism has advantages in terms of low footprint. The effect of population density is more controversial. These results indicate that polycentric spatial planning can be a good strategy to reduce the ecological footprint of cities.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): Chiara Fiori, Vincenzo Arcidiacono, Georgios Fontaras, Michail Makridis, Konstantinos Mattas, Vittorio Marzano, Christian Thiel, Biagio Ciuffo〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Decreasing road transport's harmful effects on environment and health and reducing road accidents are major policy priorities. A variety of technologies could drastically improve air quality, reduce energy consumption and CO〈sub〉2〈/sub〉 emissions of road vehicles: in this respect, a prominent trend leverages Electric Vehicles (EVs), supported by improved performance and energy efficiency through connectivity and automation. A noteworthy research question in the transition from Internal Combustion Engine Vehicles (ICEVs) to the alternative technologies, is to understand how Intelligent Transport Systems and other traffic-related measures can contribute to the reduction of fuel consumption and greenhouse gas emissions. In fact, a widely acknowledged tenet assumes that congestion removal or mitigation in presence of ICEVs implies also a reduction of transport-related externalities. This paper explores whether this effect still holds for EVs, by performing an analysis of energy consumption over different vehicle trajectories, under both congested and free-flow conditions. Calculations are carried out using two vehicle simulators: the VT-CPEM (Virginia Tech Comprehensive Power-based Energy consumption model) model for EVs and the CO〈sub〉2〈/sub〉MPAS (CO〈sub〉2〈/sub〉 model for Passenger and commercial vehicle Simulation) vehicle simulator for the ICEVs, for both electric and conventional cases passengers and freight/commercial powertrains have been analysed. Results are presented on real and simulated data related to four powertrain-vehicle combinations, in terms of general trends of energy/fuel consumption versus speed. Interestingly, results show that, differently from ICEVs, the relationship between congestion and energy consumption underlying EVs can change with higher energy consumption connected to an increased average traffic speed.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): Mohammed Hamad Almannaa, Hao Chen, Hesham A. Rakha, Amara Loulizi, Ihab El-Shawarby〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper field implements and conducts a unique controlled field experiment designed to evaluate an Eco-Cooperative Adaptive Cruise Control (Eco-CACC) system that computes fuel-efficient trajectories that are either recommended to drivers or implemented within a traditional ACC system. The controlled field experiment included three different scenarios: normal driving, driving with a speed advisory (manual Eco-CACC system), and automated Eco-CACC. The controlled field experiment was conducted for four red indication offset values (with two repetitions for each offset) randomly delivered to drivers traveling along an uphill and downhill approach on the Smart Road test facility. In total, 1536 trips were conducted by 32 different participants between the ages of 18 and 30 with an equal number of males and females. The collected data were compared with regard to fuel economy and travel time over a fixed distance starting upstream and ending downstream of the intersection (from 820 feet [250 m] upstream of the intersection to 590 feet [180 m] downstream for a total length of 1410 feet [430 m]). The results demonstrate that the proposed Eco-CACC system reduces fuel consumption levels significantly, especially when driving downhill. Specifically, the results indicate that the automated scenario could achieve fuel and travel time savings of 31% and 9% on average, respectively. These results also demonstrate that automatic longitudinal control produces significant benefits over human control (an approximately19% reduction in fuel consumption).〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 4 December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment〈/p〉 〈p〉Author(s): Uta Burghard, Elisabeth Dütschke〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Shared mobility can contribute to tackling many of the pressing problems from transport and initiate a system change. But who is attracted by shared mobility and who not? How is this related to the attractiveness of electric driving? What are the perceptions underlying those preferences? We try to answer these questions based on two survey studies from Germany with a focus on carsharing. First, we present findings from an online survey (n = 1548) in one of Germany’s showcase regions for electric vehicles (EVs) to analyse the acceptance of carsharing in society. The data analysis shows that perceived compatibility with daily life is the most important factor related to the attitudes towards carsharing and that social norms also play an important role. Second, we analyse early adopters of electric carsharing, i.e. a combination of both innovations in more detail. We draw on a survey (n = 947) from field trials in Germany. We find that – extending the results of study 1 – the users are a socio-demographically specific group. A segmentation revealed that carsharing with EVs is particularly attractive for younger people who (i) live as a couple but without cars or (ii) are starting a family and use carsharing as a supplement to their own cars. The findings from the second study are in line with the first one and also emphasise that the affinity for carsharing and EVs is closely connected. We conclude the paper by discussing the implications of our findings for the transition to low-carbon mobility.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 67〈/p〉 〈p〉Author(s): Uroš Lešnik, Domen Mongus, David Jesenko〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si28.gif" overflow="scroll"〉〈mrow〉〈msub〉〈mrow〉〈mtext〉PM〈/mtext〉〈/mrow〉〈mrow〉〈mn〉10〈/mn〉〈/mrow〉〈/msub〉〈/mrow〉〈/math〉 particles impose significant risks to human health and the well-being of individuals in general. However, due to the complexity of the inner-correlations between influencing environmental factors, the holistic approach to predictive analytics of 〈math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si28.gif" overflow="scroll"〉〈mrow〉〈msub〉〈mrow〉〈mtext〉PM〈/mtext〉〈/mrow〉〈mrow〉〈mn〉10〈/mn〉〈/mrow〉〈/msub〉〈/mrow〉〈/math〉 concentration levels is a challenging task yet to be undertaken. We base this study on the rationale that a prediction model is suitable for making accurate estimations involving knowledge about the hidden interactions that govern them. In addition to the model’s precision, it is, therefore, beneficial to provide a model that is interpretable, as this can assist in the decision about how and which prevention actions to take. For this purpose, a Genetic Algorithm is proposed that carries out multiple regression analysis by searching for the optimal fictional definition of a prediction model. As such, the obtained model is human interpretable, where the preliminary analysis conducted within this study proved its compliance with the existing studies, while the model itself proved to be considerably more accurate than the present state-of-the-art.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 75〈/p〉 〈p〉Author(s): Anders Nordelöf, Mia Romare, Johan Tivander〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study explores life cycle environmental impacts of city buses, depending on the: (1) degree of electrification; (2) electricity supply mix, for chargeable options; and (3) choice of diesel or hydrogenated vegetable oil (HVO), a biodiesel, for options with combustion engine. It is a case study, which uses industry data to investigate the impact on climate change, a key driver for electrification, and a wider set of impacts, for average operation in Sweden, the European Union and the United States of America. The results show that non-chargeable hybrid electric vehicles provide clear climate change mitigation potential compared to conventional buses, regardless of the available fuel being diesel or HVO. When fueling with HVO, plug-in hybrid and all-electric buses provide further benefits for grid intensities below 200 g CO〈sub〉2〈/sub〉 eq./kWh. For diesel, the all-electric option is preferable up to 750 g CO〈sub〉2〈/sub〉 eq./kWh. This is the case despite batteries and other electric powertrain parts causing an increase of CO〈sub〉2〈/sub〉 emissions from vehicle production. However, material processing to make common parts, i.e. chassis, frame and body, dominates the production load for all models. Consequently, city buses differ from passenger cars, where the battery packs play a larger role. In regard to other airborne pollutants, the all-electric bus has the best potential to reduce impacts overall, but the results depend on the amount of fossil fuels and combustion processes in the electricity production. For toxic emissions and resource use, the extraction of metals and fossil fuels calls for attention.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S1361920919302792-ga1.jpg" width="271" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 75〈/p〉 〈p〉Author(s): Murillo Caldeira dos Santos, Wilson de Castro Hilsdorf〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Approximately 90% of the cargo in the world is carried via maritime transport, making ports a key focus for international trade and transforming port installations into constant objects of academic study. One of the key aspects of port management is the issue of access. With an increase in cargo volumes, many port cities have experienced constant bottlenecks due to the lack of adequate space for port operations. Considering that the terrestrial access problem faced by Port of Santos has not yet been analyzed, this research aims to evaluate the logistical and environmental effectiveness of the organizational method adopted in Santos to address this problem, having as reference the solutions adopted by ports in developed countries. The organization method of terrestrial access adopted in Santos proved to be an effective alternative from a logistics operation perspective with the implementation of the regulating yard. On the other hand, the condition of a port of an emerging country strongly influence the approaches taken to address environmental issues, where cultural and economic issues hamper the adoption of measures to reduce harmful emissions in Santos.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 75〈/p〉 〈p〉Author(s): Xiaodan Xu, H.M. Abdul Aziz, Randall Guensler〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉Electric vehicles (EVs) will play a central role in future energy-efficient and sustainable transportation systems. Compared to the operation of conventional vehicles, EVs provide significantly reduced energy consumption and lower operating costs. With conventional vehicles, fuel use ties directly to the instantaneous energy consumption required to provide motive power to the wheels. Predicting the energy use can be much more complex for EVs with hybridized powertrains because the onboard vehicle systems are trying to balance the provision of power to the wheels as well as manage the state of charge (SOC) of the battery pack. Traditional modeling methodologies for estimating real-world vehicle energy consumption either depend on numerical analysis of laboratory or on-road vehicle test data or the use of full-system simulation tools. Unfortunately, full-system simulation tools suffer from scaling problems in the context of large transportation network, necessitating the development of approaches that support large transportation network projections of modal EV operations and applicable modal energy use rates (energy use for various on-road modes of operation) to predict EV energy consumption.〈/p〉 〈p〉In this study, a new modal-based approach for estimating EV energy consumption is proposed. The modal-based approach considers the variance of vehicle operating conditions and supports energy estimation for large-scale transportation networks. The Department of Energy’s full-system vehicle simulation tool known as Autonomie® is used to generate energy consumption rates for specific simulations of on-road operating conditions. A sample of EV models was first developed in Autonomie® to simulate a wide range of operating conditions and generate energy use rates for selected EVs. Classification and regression tree (CART) analysis was then applied to the simulation output data to generate energy consumption rates under distinct on-road operating conditions, as represented by combinations of vehicle speed, acceleration rate, and battery state of charge (SOC). A large-scale regional travel demand analysis was performed for the Atlanta, GA metropolitan area, integrating a variety of EV market share scenarios. The CART-derived energy consumption rates are then applied to the model-predicted link-by-link traffic attributes to estimate fleet energy consumption. The modeling framework employs MOVES-embedded driving cycles to represent on-road operations for average speed operating conditions and random initial SOC start levels as model inputs. The model results suggest a 50% PHEV market share can achieve a 30% energy savings without significantly adding to electricity load. This modeling approach can be used to assess network-level energy use for a wide-variety of modeled transportation studies, such as evaluating transportation improvement plans, assessing the net impact on the electric grid, and forecasting the potential benefits of electrifying shared-autonomous vehicles under future scenarios.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 76〈/p〉 〈p〉Author(s): Hajar Hajmohammadi, Giampiero Marra, Benjamin Heydecker〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, a new approach for describing the relationship between tailpipe emissions and vehicle movement variables is presented, called generalized additive model for location, scale and shape (GAMLSS). The dataset for this model is second-by-second emission laboratory measurements, following a real driving cycle that were recorded in urban, suburban and motorway areas of London. The GAMLSS emission model estimates each of CO〈sub〉2〈/sub〉, CO and NO〈em〉〈sub〉x〈/sub〉〈/em〉 in each second for two different vehicle types (petrol or diesel) using instantaneous speed and acceleration as the explanatory variables. Comparing the results with current emission models indicates substantial improvement in accuracy and quality of estimation by this approach.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 4 October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment〈/p〉 〈p〉Author(s): Suhong Zhou, Rongping Lin〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Research on the relationship between built environment and PM2.5 has attracted notable attention during the past decades. However, previous studies were less to test the spatial-temporal heterogeneity of on-road PM2.5 and its related factors at micro scale. To this end, collecting high-resolution PM2.5 data by mobile monitoring along different roads in Guangzhou, China, this paper explored the spatial-temporal heterogeneity of the relationship between built environment and on-road PM2.5 during the morning (7–9 am) and evening (7–9 pm) rush hours. Semi-variogram method and geographically weighted regression (GWR) model were utilized to reveal the non-stationarity associations among the large spatial dataset. In terms of temporal heterogeneity, the results showed that the spatial independent radii of on-road PM2.5 were 17 m and 21 m for morning and evening rush hours respectively. The aggregated median value of PM2.5 in the morning rush hours was 34.95 μg/m〈sup〉3〈/sup〉, while the evening was up to 55.49 μg/m〈sup〉3〈/sup〉. There were more significant factors of street conditions impact on on-road PM2.5 in the morning while more significant factors of land use and centrality that reflecting the cumulative effect of daily human activities with smaller buffer thresholds in the evening. In terms of spatial heterogeneity, GWR models achieved much better performance than the global ones of multivariate regression models with lower AICc, RMSE and higher adjusted 〈em〉R〈sup〉2〈/sup〉〈/em〉, explaining 10–69% of variance across different roads and rush hours. There was a high degree of spatial heterogeneity that the leading factors were different along various roads on rush hours. The results indicated that the policies and interventions should be more targeted to improve the on-road air environment and reduce personal exposure according to the spatial-temporal geographical context. It can be adopted to provide more realistic and practical guides for urban planning and environmental pollution control.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 76〈/p〉 〈p〉Author(s): Mohammad S. Roni, Zonggen Yi, John G. Smart〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Recently, major car-sharing service providers have begun to include electric vehicles (EVs) in free-floating car-sharing fleets. For these EVs, downtime due to charging, including time spent traveling to and waiting in queues at charging stations in a sparse charging infrastructure network, is a major barrier to sustainable operation. An intuitive solution to overcome this barrier is to increase the number of fast-charging stations in the fleet service area. This paper studies the relationship between fleet vehicle downtime and the number of charging stations by modeling the fleet operations of a major car-sharing service provider. An integer programming model is developed that jointly optimizes charging station allocation, in terms of the number and location of charging stations, and the assignment of EVs to charging stations. Case study results showed that fleet vehicle charging time comprises 72–75% of the total downtime spent on charging trips. This indicates that charging time, as opposed to travel time or waiting time, is the dominant component of total fleet downtime for charging. The study also shows that by adding 5–20 new charging stations reduces total fleet downtime and travel time during charging trips by 2–4% and 26–49%, respectively. Although adding new charging stations to the fleet service area reduces total charging trip travel time significantly, it does not reduce total downtime significantly. Results also show that if the EV battery state of the charge (SOC) threshold—below which a charging trip is initiated—is less than 18%, not all EVs in the car-sharing fleet can be charged using the existing direct current fast chargers (DCFCs) in the fleet’s service area. This implies that adequate charging infrastructure coverage is required to ensure that EVs of a given range can operate in the car-sharing fleet.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 78〈/p〉 〈p〉Author(s): Thomas Kirschstein〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉Drones are one of the most intensively studied technologies in logistics in recent years. They combine technological features matching current trends in transport industry and society like autonomy, flexibility, and agility. Among the various concepts for using drones in logistics, parcel delivery is one of the most popular application scenarios. Companies like Amazon test drones particularly for last-mile delivery intending to achieve both reducing total cost and increasing customer satisfaction by fast deliveries. As drones are electric vehicles, they are also often claimed to be an eco-friendly mean of transportation.〈/p〉 〈p〉In this paper an energy consumption model for drones is proposed to describe the energy demand for drone deliveries depending on environmental conditions and the flight pattern. The model is used to simulate the energy demand of a stationary parcel delivery system which serves a set customers from a depot. The energy consumed by drones is compared to the energy demand of Diesel trucks and electric trucks serving the same customers from the same depot.〈/p〉 〈p〉The results indicate that switching to a solely drone-based parcel delivery system is not worthwhile from an energetic perspective in most scenarios. A stationary drone-based parcel delivery system requires more energy than a truck-based parcel delivery system particularly in urban areas where customer density is high and truck tours are comparatively short. In rather rural settings with long distances between customers, a drone-based parcel delivery system creates an energy demand comparable to a parcel delivery system with electric trucks provided environmental conditions are moderate.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 78〈/p〉 〈p〉Author(s): Ryan J Wessel〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Comparing vehicle emissions inspection results with vehicle owner income shows that the Arizona vehicle emissions inspection program constrains the vehicle repair decisions of people in the low end of the income distribution more than people in the high end. Individuals who live in areas with lower annual income are both (i) more likely to drive vehicles that fail emissions inspections at a higher average rate, and (ii) more likely to fail emissions inspections conditional on vehicle characteristics. The top income quintile fails emissions inspections 20% less often than the bottom income quintile even when controlling for observable vehicle characteristics. This implies that owner characteristics, in addition to observable vehicle characteristics, have a non-negligible impact on vehicle emissions rates. Therefore, the impact of programs designed to reduce vehicle emissions could be greater if participation were subject to a means test.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 78〈/p〉 〈p〉Author(s): Xueqin Wang, Kum Fai Yuen, Yiik Diew Wong, Kevin X. Li〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Sustainability Development Goals (SDGs) are a comprehensive agenda agreed upon globally that aims to stimulate actions towards economic, environmental and social sustainability. Being one of the key stakeholders, the international maritime industry plays an important role in contributing to global sustainability. By applying the concept of social entrepreneurship (SE), this study aims to examine (1) the basic and extended responsibilities (SDG 1–SDG 16) and (2) the potential collaborations within the value chain (SDG 17) concerning SDG implementation in maritime industry. To achieve these, we conduct a content analysis of sustainability reports published by container shipping liners and terminal operators from 2016 to 2019. More specifically, manual text classification is adopted to categorise the text content of sustainability reports based on 17 SDGs, and automatic text mining is employed to further identify the key roles of maritime industry related to each SDG. A unified framework is proposed, which points to varied motives and levels of comprehensiveness of the sustainability efforts by the maritime industry. This framework reveals the theoretic process of maritime industry's transitional involvement in sustainability from the SE perspective. It also creates managerial implications regarding the resource allocation strategies by maritime industry in meeting SDGs.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 78〈/p〉 〈p〉Author(s): Antonio J. Torija, Zhengguang Li, Rod H. Self〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Several industry leaders and governmental agencies are currently investigating the use of Unmanned Aerial Vehicles (UAVs), or ‘drones’ as commonly known, for an ever-growing number of applications from blue light services to parcel delivery. For the specific case of the delivery sector, drones can alleviate road space usage and also lead to reductions in CO〈sub〉2〈/sub〉 and air pollution emissions, compared to traditional diesel-powered vehicles. However, due to their unconventional acoustic characteristics and operational manoeuvres, it is uncertain how communities will respond to drone operations. Noise has been suggested as a major barrier to public acceptance of drone operations in urban areas. In this paper, a series of audio-visual scenarios were created to investigate the effects of drone noise on the reported loudness, annoyance and pleasantness of seven different types of urban soundscapes. In soundscapes highly impacted by road traffic noise, the presence of drone noise lead to small changes in the perceived loudness, annoyance and pleasantness. In soundscapes with reduced road traffic noise, the participants reported a significantly higher perceived loudness and annoyance and a lower pleasantness with the presence of the same drone noise. For instance, the reported annoyance increased from 2.3 ± 0.8 (without drone noise) to 6.8 ± 0.3 (with drone noise), in an 11-point scale (0-not at all, 10-extremely). Based on these results, the concentration of drone operations along flight paths through busy roads might aid in the mitigation of the overall community noise impact caused by drones.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 78〈/p〉 〈p〉Author(s): Ioannis Kougias, Alexandros Nikitas, Christian Thiel, Sándor Szabó〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Introducing sustainable ways to use energy and transport resources is of paramount importance for creating pathways to more liveable futures. Islands not interconnected to the main grid offer, because of their typically small size, short point-to-point travel distances that suit better than most landscapes the range limitations of today’s electromobile eco-systems. This makes them a unique test-bed that may assist researchers, businesses and policy-makers in developing a better understanding of the diverse opportunities and challenges that come with supporting electric-drive vehicle (EV) infrastructure investments that actively prioritise renewable energy sources (RES). This paper reports the findings of a Q method study that looks into the attitudes of 44 key stakeholders that have a thorough theoretical and empirical knowledge of the existing power and mobility portfolios in such islandic landscapes. Our analysis identifies and presents three distinct groups of stakeholders with different priorities and visions: the ‘Tech Enthusiasts’, the ‘Transform Transport First Supporters’ and the ‘Fiscal Focus Executives’. All our respondents agree on the need for radically transforming the current transport-energy nexus offering. They identify the importance of integrated and clean solutions and recognise that support of pilot applications is more critical than research and development (R&D). They also expect technological breakthroughs to increase market maturities and reduce renewable energy production costs and feel that end-users are still hesitant to buy EVs and need incentives to do so.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: January 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 78〈/p〉 〈p〉Author(s): David L. Greene, Eleftheria Kontou, Brennan Borlaug, Aaron Brooker, Matteo Muratori〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Lack of charging infrastructure is an important barrier to the growth of the plug-in electric vehicle (PEV) market. Public charging infrastructure has tangible and intangible value, such as reducing range anxiety or building confidence in the future of the PEV market. Quantifying the value of public charging infrastructure can inform analysis of investment decisions and can help predict the impact of charging infrastructure on future PEV sales. Estimates of willingness to pay (WTP) based on stated preference surveys are limited by consumers’ lack of familiarity with PEVs. As an alternative, we focus on quantifying the tangible value of public PEV chargers in terms of their ability to displace gasoline use for PHEVs and to enable additional electric (e−) vehicle miles for BEVs, thereby mitigating the limitations of shorter range and longer recharging time. Simulation studies provide data that can be used to quantify e-miles enabled by public chargers and the value of additional e-miles can be inferred from econometric estimates of WTP for increased vehicle range. Functions are synthesized that estimate the WTP for public charging infrastructure by plug-in hybrid and battery electric vehicles, conditional on vehicle range, annual vehicle travel, pre-existing charging infrastructure, energy prices, vehicle efficiency, and household income. A case study based on California’s public charging network in 2017 indicates that, to the purchaser of a new BEV with a 100-mile range and home recharging, existing public fast chargers are worth about $1500 for intraregional travel, and fast chargers along intercity routes are valued at over $6500.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 69〈/p〉 〈p〉Author(s): Erik Fridell, Sebastian Bäckström, Håkan Stripple〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, the contributions to emissions to air related to traffic infrastructure and terminals are analysed for freight transport with different modes. Data on emissions per km road or railway from existing LCA reports are adapted to a selection of road types and one type of railway line. The presented data are for air pollutants, use of primary energy and emissions of green-house gases divided into construction, maintenance and operation phases. These data are then allocated to the traffic-work produced on the infrastructure during its life span. Different allocation methods are suggested for the separate LCA-phases. The research has a focus on freight transport, why data are presented as emissions per vehicle-km for a number of truck and train types. For ports and airports, data are available per tonne of goods over quay or in- and outgoing. These results are then used to calculate the emissions added for infrastructure for freight transport chains. Examples are given showing the magnitude of emissions originating from infrastructure that can be added to tailpipe and other upstream emissions, e.g. fuel and vehicle production. In relation to tailpipe emissions the CO〈sub〉2〈/sub〉 emissions from infrastructure is typically 1–7% for road and around 17% for rail. For air and sea the results will vary significantly; for typical intra-Europe routes we find a contribution from infrastructure of about 3% for air and 21–34% for sea, in relation to emissions from the vessels.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 7 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment〈/p〉 〈p〉Author(s): Tianni Wang, Zhuohua Qu, Zaili Yang, Timothy Nichol, Delia Dimitriu, Geoff Clarke, Daniel Bowden〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper aims to analyse the impacts of climate change to the current and predicted future situations of road transportation in the UK and evaluate the corresponding adaptation plans to cope with them. A conceptual framework of long-term adaptation planning for climate change in road systems is proposed to ensure the resilience and sustainability of road transport systems under various climate risks such as flooding and increased temperature. To do so, an advanced Fuzzy Bayesian Reasoning (FBR) model is first employed to evaluate the climate risks in the UK road transport networks. This modelling approach can tackle the high uncertainty in risk data and thus facilitate the development of the climate adaptation framework and its application in the UK road sector. To examine the feasibility of this model, a nationwide survey is conducted among the stakeholders to analyse the climate risks, in terms of the timeframe of climate threats, the likelihood of occurrence, the severity of consequences, and infrastructure resilience. From the modelling perspective, this work brings novelty by expanding the risk attribute “the severity of consequence” into three sub-attributes including economic loss, damage to the environment, and injuries and/or loss of life. It advances the-state-of-the-art technique in the current relevant literature from a single to multiple tier climate risk modelling structure. Secondly, an Evidential Reasoning (ER) approach is used to prioritise the best adaptation measure(s) by considering both the risk analysis results from the FBR and the implementation costs simultaneously. The main new contributions of this part lie in the rich raw data collected from the real world to provide useful practical insights for achieving road resilience when facing increasing climate risk challenges. During this process, a qualitative analysis of several national reports regarding the impacts posed by climate change, risk assessment and adaptation measures in the UK road sector is conducted for the relevant decision data (i.e. risk and cost). It is also supplemented by an in-depth interview with a senior planner from Highways England. The findings provide road planners and decision makers with useful insights on identification and prioritisation of climate threats as well as selection of cost-effective climate adaptation measures to rationalise adaptation planning.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 69〈/p〉 〈p〉Author(s): Huyen T.K. Le, Ralph Buehler, Steve Hankey〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Local, state, and federal governments promote walking and bicycling in order to reduce emissions and improve public health. Tracking rates of bicycling and walking over time is important for assessing progress towards this goal. In the United States, most data are limited to cross-sectional self-report surveys (e.g., National Household Travel Surveys [NHTS]) or capture only the main commute mode (e.g., American Community Survey [ACS]). This study examines temporal trends (while controlling for spatial factors) of active travel in 13 US metropolitan areas between 2004 and 2016 (with 78% of counts occurring between 2010 and 2016) using repeated counts of bicycle and pedestrian traffic (n = 1319 count locations; 5554 bicycle and 5166 pedestrian counts). We used multilevel mixed-effects models to examine the multi-year trend in bicycling and walking during morning and afternoon peak periods. In the 5 out of 8 models where the temporal trend was statistically significant, we found that, on average, traffic volumes increased at a rate of 2–6% (bicycle) and 2–3% (pedestrian) per year among count locations, holding other variables constant. Presence of bicycle facilities (e.g., bicycle lanes, off-street trails) was positively associated with higher levels of bicycle traffic. Our results based on observed traffic patterns suggest larger increases in bicycling and walking as compared to the trends reported from the NHTS and ACS data. Quantifying the temporal trend from observed counts of traffic may aid policy makers and urban planners in assessing progress towards the goal of increasing bicycling and walking to reduce emissions and increase physical activity.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 70〈/p〉 〈p〉Author(s): Thalis P.V. Zis, Harilaos N. Psaraftis, George Panagakos, Jacob Kronbak〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The 0.1% limit in sulphur content within Sulphur Emission Control Areas as of 1st January 2015 requires that ship operators either use pricier ultra-low sulphur fuel oil, or alternatively install abatement technologies through substantial capital investments. A part of the resulting higher operating costs are passed on to shippers resulting in increased freight rates. These may lead to modal shifts towards rail or road options competing with Ro-Ro operators. Due to the unexpectedly low fuel prices in the period 2014–2016, Ro-Ro operators were relatively unharmed by the new limits, but nascent research has shown that if fuel prices increase some Ro-Ro services may not survive. This paper examines a set of policy options that can mitigate or reverse the negative effects of the low-sulphur regulation. The measures include internalizing external costs of transport, repaying fuel surcharges to shippers, subsidizing technological investments of ship operators, or increasing the landbased costs of transport via levies. To compare their efficacy, total costs are calculated for each measure. The results show that the proposed measures can successfully reduce the negative effects of the regulation but this would entail significant costs. A combination of subsidies towards shippers and ship operators is shown to be effective at reversing potential modal shifts and can be crucial in case of high fuel prices in the near future. The findings of this work can assist operators to develop new strategies and improve the resilience of their network, and regulators designing environmental policies that may have negative implications on certain sectors.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): Benedikt Anderhofstadt, Stefan Spinler〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The transport sector is the third-largest producer of greenhouse gas (GHG) emissions in Germany, but within the scope of the government’s climate action plan, the country aims to cut emissions from transport by at least 40% by 2030. Apart from passenger cars, commercial vehicles including heavy-duty trucks (HDTs) are one of the main contributors of emissions. Eco-innovations such as alternative fuel-powered HDTs could change that but diesel is still by far the prevalent fuel of choice. Hence, what factors affect the purchasing decision and operation of low-emission HDTs and which are the most relevant ones? We employed a Delphi study to answer the question of how 34 factors affect the adoption of alternative fuel-powered HDTs in Germany. Our factors combine cost factors, socioeconomic issues, environmental criteria, operational aspects, and political considerations. According to the experts, a truck’s reliability, an available fueling/charging infrastructure, the possibility to enter low-emission zones as well as current and future fuel costs are key factors when purchasing and operating an alternative fuel-powered HDT. In addition, we identified battery electric (BE), fuel cell electric (FCE), compressed natural gas (CNG) and liquefied natural gas (LNG) as promising technologies to reduce emissions from HDTs. Thus, we analyzed motivators, barriers, and ways to overcome the main barriers when switching from diesel to those technologies. Among others, the experts evaluated the possibility to enter low-emission zones as an important motivator, but the fragmented fueling/charging infrastructure as a main barrier. Subsidies are one promising way to spur the penetration of low-emission HDTs.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): Eva Merico, Adelaide Dinoi, Daniele Contini〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Several studies focused on harbour impact on air quality of port-cities showing that maritime emissions could be comparable to traffic emissions of a medium-size town having relevant impact on air quality nearby the harbours. In order to plan efficient mitigation strategies, environmental and port authorities have an increasing need of reliable tools for investigating the impact of ships traffic and harbour logistics on atmospheric pollutants. In this work a system based on the integration of measurements collected using a network of low-cost on-line sensors with local scale dispersion modelling was developed. It was implemented, as a pilot action, in the information and management software of the Bari harbour (SE Italy). It can operate in near-real-time, in forecast mode, and on archived data for long-term assessments. It was tested studying the impact of the Bari harbour for the year 2018. The lowest impact was observed for CO, being the pollutant with the lowest share of the contribution of ships (between 8% and 68%) compared with the total harbour contribution. The impacts on PM〈sub〉2.5〈/sub〉 and PM〈sub〉10〈/sub〉 are larger arriving up to 11.8% of concentrations in the harbour area with an influence of shipping between 44% and 97%. The impact on SO〈sub〉2〈/sub〉 is almost solely due to ships and it arrives up to 80% in the harbour area. The impact on NO〈sub〉X〈/sub〉 ranges from a few percent in the urban area up to 40% in the harbour area and it is the pollutant of major concern regarding compliance with air quality standards.〈/p〉〈/div〉 〈/div〉 〈div xml:lang="en"〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S1361920919305358-ga1.jpg" width="329" alt="Graphical abstract for this article" title=""〉〈/figure〉〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 70〈/p〉 〈p〉Author(s): Tobias Lindé, Inge Vierth, Kevin Cullinane〈/p〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 70〈/p〉 〈p〉Author(s): Ing-Marie Gren, Annika Jägerbrand〈/p〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 70〈/p〉 〈p〉Author(s): Sanya Carley, Saba Siddiki, Sean Nicholson-Crotty〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The diffusion of plug-in electric vehicles (PEV) is a topic that has received substantial attention in recent years. In part, this heightened interest reflects rapid concurrent developments in policy, technology, and industry strategies designed to spur the uptake of this radical, emerging technology. Governments from all levels are enacting various monetary and non-monetary incentives to encourage PEV adoption; developments in battery technology are likening the performance of PEVs to conventional vehicles; and all major vehicle manufacturers now have a PEV offering. Ultimately, however, the effect of these developments is contingent upon consumer interest. Thus, in this paper we study whether, alongside technology and market developments, consumer interest in PEVs has changed over time. To answer this question, we evaluate the degree to which intent to purchase or lease a battery electric vehicle and plug-in hybrid electric vehicle, respectively, has changed between 2011 and 2017, and how the factors that explain variation in such intent have also changed over time. Our data come from two national surveys of potential car buyers in the 21 largest American cities. Among the key findings that we derive from the analysis are that, among survey respondents, intent to purchase a PEV has increased between 2011 and 2017, and perceptions about the trialability, observability, network effects, and policies explain an increasing share of the variation in intent to purchase as time evolves.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: Available online 5 April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment〈/p〉 〈p〉Author(s): Nicole S. Ngo〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Climate change is projected to worsen weather extremes, such as heat waves and days of heavy precipitation, which could pose serious health and economic risks to U.S. cities. These extreme weather events could also affect urban mobility, since people who walk or bike may shift to public transit or avoid travel if they cannot afford a vehicle. To address these concerns, this study examines the effects of extreme weather events on bus ridership and the extent to which this relationship varies by income and destination. This study analyzes highly detailed micro-level bus data between 2012 and 2017 for a county in the Pacific Northwest using a negative binomial regression model. Results suggest modest reductions in bus ridership on very hot and cold days, as well as on days with heavy rainfall, with impacts differing between weekdays and weekends. Findings also show that bus ridership is more sensitive to extreme weather events in lower-income areas relative to the wealthiest neighborhoods, which may be partly driven by a large university student population who can ride the bus for free. Finally, results show that bus ridership around commercial areas and parks increases on very cold days and days with heavy precipitation, reinforcing the importance of public transit during these weather events. These results suggest extreme weather events affect urban mobility, with greater impacts in lower-income neighborhoods, parks and commercial areas. Transit agencies and policymakers should consider ways to increase accessibility and mobility during these weather events, especially for lower-income households.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): Joanna H. Barnes, Tim J. Chatterton, James W.S. Longhurst〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉This paper presents unique spatial analyses identifying substantial discrepancies in traffic-related emissions generation and exposure by socioeconomic and demographic groups. It demonstrates a compelling environmental and social injustice narrative with strong policy implications for the UK and beyond.〈/p〉 〈p〉In the first instance, this research presents a decadal update for England and Wales to Mitchell and Dorling’s 2003 analysis of environmental justice in the UK. Using 2011 UK Government pollution and emissions data with 2011 UK Census socioeconomic and demographic data based on small area census geographies, this paper demonstrates a stronger relationship between age, poverty, road NO〈sub〉x〈/sub〉 emissions and exposure to NO〈sub〉2〈/sub〉 concentrations. Areas with the highest proportions of under-fives and young adults, and poorer households, have the highest concentrations of traffic-related pollution.〈/p〉 〈p〉In addition, exclusive access to UK annual vehicle safety inspection records (‘MOT’ tests) allowed annual private vehicle NO〈sub〉x〈/sub〉 emissions to be spatially attributed to registered keepers. Areal analysis against Census-based socioeconomic characteristics identified that households in the poorest areas emit the least NO〈sub〉x〈/sub〉 and PM, whilst the least poor areas emitted the highest, per km, vehicle emissions per household through having higher vehicle ownership, owning more diesel vehicles and driving further.〈/p〉 〈p〉In conclusion, the analysis indicates that, despite more than a decade of air quality policy, environmental injustice of air pollution exposure has worsened. New evidence regarding the responsibility for generation of road traffic emissions provides a clear focus for policy development and targeted implementation.〈/p〉 〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): Xiongbin Lin, Jiawen Yang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Transport Impact Assessment (TIA) is one of the promising tools used by many city governments around the world to manage the transport impacts of land development, but how it has been implemented in Chinese cities is rarely studied. This paper attempts to fill this knowledge gap by researching cases of TIA in Shenzhen and Zhongshan in China’s developed Pearl River Delta. Our research reveals that the TIA process enables local planning authorities to better cope with the traffic externalities stemming from various development projects, and to secure resources in advance for green transport modes. However, the effectiveness of this policy tool still falls short in how governments prioritize green transportation and in implementation details. It can be augmented with clearly defined performance measures for green transport modes and active roles played by relevant stakeholders.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 72〈/p〉 〈p〉Author(s): Jinpei Li, Liqun Xu, Di Yao, Yanwu Mao〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Because of the symbolic value of the private car, driving a private car is a signal of wealth and a particular social status, but public transit is considered to be a means of transport for low- and middle-income people in the traditional culture of China, especially in face culture. Some prior studies have verified the impact of the symbolic value of the private car on car use and further indirectly speculated about its impact on public transit use, but these studies have seldom focused on the direct effect of the symbolic value of the private car on public transit use. Based on face-to-face questionnaire survey data from a sample of 323 commuters with experience using buses in Changzhou in 2016, this case study examines the relationship among the symbolic value of the private car and passenger satisfaction with bus services and bus use by using binary logit regression. The empirical results show a stable negative association between the symbolic value of the private car and bus use, while the passenger satisfaction with bus services is positively associated with bus use. These findings imply that improving the public transport services is important for the public transit priority policy, and the policy could be more effective if the Chinese traditional understandings of using public transit and private cars are changed.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 72〈/p〉 〈p〉Author(s): Sehwa Lim, Stephen Pettit, Wessam Abouarghoub, Anthony Beresford〈/p〉

Description: 〈p〉Publication date: July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 72〈/p〉 〈p〉Author(s): Fatemeh Nazari, Abolfazl (Kouros) Mohammadian, Thomas Stephens〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper presents a behavioral model of public, 〈em〉revealed〈/em〉 preferences (RP) for 〈em〉various types of electric vehicles (EVs)〈/em〉 while accounting for 〈em〉a latent (green) travel pattern construct〈/em〉 and 〈em〉charging infrastructure characteristics〈/em〉. Specifically, a two-level nested logit (NL) model is estimated to explain households’ fuel type choice among five alternatives and three nests: (1) battery electric vehicles (BEVs); (2) hybrid vehicles including hybrid electric vehicles (HEVs) and plug-in HEVs (PHEVs); and (3) conventional vehicles including gasoline and diesel vehicles. Further, a latent travel pattern construct which captures a week-long number of trips by non-vehicle travel modes as well as daily vehicle and tollway use is estimated in a structural equation setting and subsequently fed into the NL model. Using a recent RP dataset from the California Household Travel Survey, we identify market segments for alternative fuel types based on households’ socio-economic characteristics, built environment factors concerning public plug-in EV (PEV) charging infrastructure characteristics, latent and observable travel behavior factors of a household vehicle’s principal driver, and vehicle attributes. The results highlight that the number of public PEV charging stations is only significant for households choosing PHEVs and interestingly insignificant in the BEV utility. Furthermore, the sensitivity analysis of the findings reveals that PHEV users are elastic with respect to household vehicle ownership ratio and the latent green travel pattern construct, while BEV users are inelastic to any explanatory variable.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 72〈/p〉 〈p〉Author(s): Stéphanie Potvin, Philippe Apparicio, Anne-Marie Séguin〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Road traffic noise constitutes a major problem for the health of populations exposed to it over extended periods. From a perspective of environmental equity, we focus on the distribution of four segments of the population—children, seniors, low-income individuals and visible minorities—in noise disturbance zones near major traffic routes of the Montreal Metropolitan Community. First, some corridors along these traffic routes with different levels of noise disturbance are defined according to a number of parameters; subsequently, the overrepresentation of the groups studied is assessed with the help of two indices. Next, we attempt to determine whether these groups have access to noise barriers, abatement measures to mitigate the noise. To assess the overrepresentation of the four groups under examination in protected and unprotected noise disturbance zones, multinomial logistic regression models were constructed for the entire territory, and then for six subregions. The results reveal a situation doubly inequitable for low-income persons and, to a lesser extent, for visible minorities. Indeed, these groups more often live close to major traffic routes and are less likely to be protected by noise barriers. In contrast, children are doubly advantaged.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): Long Cheng, Jonas De Vos, Kunbo Shi, Min Yang, Xuewu Chen, Frank Witlox〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The built environment affects individuals’ travel behavior in a variety of dimensions, such as trip generation, mode choice, and travel duration. However, it is not well understood how these effects differ across different socioeconomic groups (e.g. the elderly versus younger adults) and how residential self-selection contributes to these differences. Using the 2013 Nanjing (China) Travel Survey data, this study estimates the differential responsiveness to the variation in residential location for different age groups. The two-step clustering method is applied to characterize two types of residential locations and the propensity score matching approach is utilized to address self-selection effects. We find that, after control for self-selection, residential location effects on travel behavior differ significantly between the elderly (60+ years old) and younger respondents (18–59 years old). Changes in the living environment play a more important role in influencing the elderly’s travel frequency and travel duration than those of younger adults. When we compare the observed effects of residential location, self-selection effects are modest for the elderly while they matter to a great extent for younger adults. In addition, due to differences in residential self-selection, there is an underestimation of residential location effects on the elderly’s travel behavior versus an overestimation of those for younger adults. These findings indicate that overlooking the variation of built environment effects between different age groups may lead to ineffective housing and transportation policy implications.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): Radomir Mijailović, Nenad Marković, Dalibor Pešić, Jelena V. Vlajić〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Improvement of energy efficiency and exhaust emissions reduction are environmental targets of utmost importance in the transport and traffic sectors. The literature suggests that there is a need for the development of a general methodology that can be used to evaluate and compare scenarios for the reduction of the environmental impact caused by fossil-fuel usage of passenger car fleet. We develop such a methodology, which assesses the external costs of four combustion products (carbon dioxide, carbon monoxide, nitrogen oxides and hydrocarbons) as well as fuel consumption costs. In this study, we applied this methodology to evaluate and compare five scenarios. The methodology was tested for the case of the Serbian passenger car fleet. Serbia was selected as a country with the passenger car fleet primarily consisted of fossil-fuelled passenger cars. In addition, Serbia is a country in which rising demand for cars is met through the import of second-hand cars. We found that the only scenario which could result in a positive solution of the given problem is the “reduction of the total number of passenger cars in the fleet of a country” scenario. Moreover, the purchase of new cars and import of second-hand cars cannot result in significant positive effects. The results obtained for the case of Serbia can provide an important insight into the environmental effects of passenger car fleets for countries primarily using fossil-fuelled cars, in which the demand for cars is met mostly through the import of second-hand cars.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): Páraic Carroll, Brian Caulfield, Aoife Ahern〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The research presented in this paper investigates the behavioural response and subsequent appraisal of a range of policy incentives devised to encourage greater use of sustainable travel options within the Greater Dublin Area (GDA). Interventions were assessed by employing four-stage modelling techniques, as a tool to identify signs of mode shifting behaviour from single occupancy vehicle (SOV) use to public transport modes. Extensive modelling work was conducted in collaboration with the National Transport Authority (NTA) of Ireland utilising the National Regional Modelling System (RMS) to represent the sustainable policy changes. Parameter modifications in the mode and destination choice and trip assignment stages were made to account for improvements made to frequency, time and cost attributes of public transport modes included in the model. Subsequent changes in vehicle kilometres travelled of various modes modelled were then utilised to estimate the potential emissions savings. In addition to this, the potential monetary savings generated from a reduction in emissions were calculated. The key results produced from this study found that an increase in the mode share of public transport of up to 2.87% could be achieved in the GDA. Up to 1.76% of which was estimated to come directly from private car trips, as a result of implementing the policy incentives tested. Furthermore, daily emissions savings of up to 431.58 tonnes of CO〈sub〉2〈/sub〉, 0.95 tonnes of NO〈sub〉x〈/sub〉, and 0.046 tonnes of PM〈sub〉2.5〈/sub〉 were also estimated.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): Hyunhong Choi, Yoonmo Koo〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study proposes a vehicle replacement model that considers consumers’ strategic decision-making for the optimal purchase timing of a new vehicle. The model incorporates the effect of the currently owned vehicle (status quo) and future vehicles with different performance and market situations on consumers’ current purchase decisions. By identifying purchase timing, the model endogenously identifies new vehicle buyers for each period and derives the expected sales and stock share of the market. Choice experiments were conducted among 333 South Korean vehicle owners in 2018, and the results were applied to a simulation framework to forecast the future vehicle market (2018–2030). The proposed model showed significantly different results compared to models that ignored the effects of status quo and future vehicles on current purchase decisions. The key findings are as follows. First, consumers tend to prefer the same vehicle type as their status quo vehicle. Second, consumers tend to postpone their purchase of electric vehicles more than they do in the case of conventional vehicles, and they may delay or advance their purchase to the start or end of policies. Finally, market sales expand or shrink based on the existence of and the start or end timing of the policy.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): Pär Pettersson, Pär Johannesson, Bengt Jacobson, Fredrik Bruzelius, Lars Fast, Sixten Berglund〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We propose a novel statistical description of the physical properties of road transport operations by using stochastic models arranged in a hierarchical structure. The description includes speed signs, stops, speed bumps, curvature, topography, road roughness and ground type, with a road type introduced at the top of the hierarchy to group characteristics that are often connected. Methods are described how to generate data on a form (the operating cycle format) that can be used in dynamic simulations to estimate energy usage and CO〈sub〉2〈/sub〉 emissions. To showcase the behaviour of the description, two examples are presented using a modular vehicle model for a heavy-duty truck: a sensitivity study on impacts from changes in the environment, and a comparison study on a real goods transport operation with respect to energy usage. It is found that the stop intensity and topography amplitude have the greatest impact in the sensitivity study (8.3% and 9.5% respectively), and the comparison study implies that the statistical description is capable of capturing properties of the road that are significant for vehicular energy usage. Moreover, it is discussed how the statistical description can be used in a vehicle design process, and how the mean CO〈sub〉2〈/sub〉 emissions and its variation can be estimated for a vehicle specification.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): Yibin Ao, Dujuan Yang, Chuan Chen, Yan Wang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study contributes to the understanding of the impacts of the rural built environment on travel-related CO〈sub〉2〈/sub〉 emissions by considering the mediating effects of household car ownership, travel frequency, travel distance, and individual travel attitudes through structural equation modeling. The travel data were collected from an activity diary survey in rural Sichuan. Geographic information system technology, combined with on-site measurement, was used to obtain data on the built environment. After controlling the socio-demographic factors, the model results corroborate that all built environment variables had significant total effects on car ownership, travel distance, travel frequency, and travel emissions. Specifically, residents living in the village with more accessible markets, higher roads, and higher building density travel a shorter distance and emit less CO〈sub〉2〈/sub〉. Meanwhile, residents living in the village with centralized living style and higher transit and destination accessibility travel less frequently but emit more CO〈sub〉2〈/sub〉. Individual travel attitudes have a limited effect on travel behavior and CO〈sub〉2〈/sub〉 emissions. This study suggests that planners and policymakers should consider shortening the distance between destination/transit and residential areas and increasing road and building densities. Moreover, promoting the construction of bicycling facilities and separate bicycle lanes to encourage rural residents to ride electric bicycles, bicycles, and motorcycles will reduce transport CO〈sub〉2〈/sub〉 emission in Chinese rural areas.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Christine Eisenmann, Patrick Plötz〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The distances travelled by individual cars vary strongly from day to day. This is problematic for electric vehicles since they cannot be used for journeys longer than the all-electric range. At present, long-distance travel is rarely covered by household travel surveys and little is known about the frequency of long-distance car travel on an individual car basis. Here, two methods are compared that estimate the number of days per year with a driving distance larger than a given threshold: a simulation method and a probabilistic method. The simulation method combines a national household travel survey, a car-use survey and a long-distance travel survey and simulates one year of car driving; the resolution of results is car trips over a full year. The probabilistic method uses statistical distribution to estimate the number of days per year with long-distance travel. Both methods are tested on a representative one-week sample of the German Mobility Panel with travel data from over 6000 cars. Our results show that both methods produce similar aggregated results for the distribution of days with long-distance car travel, the maximum mileages, and average long-distance travel frequencies amongst user groups. However, the two methods differ on the level of individual cars. Our findings indicate that long-distance travel behaviour can be estimated on an aggregated level without long observation period data. Both methods can be directly applied to the limited range of electric vehicles and the need for adaptation or fast charging.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Simone I. Ehrenberger, Jennifer B. Dunn, Gerfried Jungmeier, Hewu Wang〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, we aim to assess the potential influence of increased adoption of electric vehicles (EVs) on a well-to-wheel (WTW) basis in the four countries with highest passenger car sales (Germany, the United States, China, and Japan), and Norway which represents a highly renewable energy market on greenhouse gas emissions. To characterize these emissions, we define critical parameters regarding fleet composition, activity, efficiency and fuel production in each country. Overall, with today’s technology at a national average level, on a per km driven basis, battery electric vehicles emit fewer greenhouse gases than conventional vehicles in all countries. Though vehicle energy consumption is similar in all countries, electricity production energy efficiency and greenhouse gas emissions per kWh electricity vary considerably, with Norway and China representing the low and high emitting endpoints, respectively. As electricity generation decarbonizes, EVs have the potential to be lower greenhouse-gas emitting than gasoline vehicles in all countries considered. The complexity of EV analysis across international boundaries, time periods, and environmental media complicates communication of EV benefits to stakeholders. Analysts must continue to address and clearly communicate the influence of EV and electricity production technology advancement into the future on EV impacts on all environmental media (air, water, land).〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Bernd Herrenkind, Alfred Benedikt Brendel, Ilja Nastjuk, Maike Greve, Lutz M. Kolbe〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉To achieve the widespread diffusion of autonomous electric buses (AEBs) and thus harness their environmental potential, a broad acceptance of new technology-based mobility concepts must be fostered. Still, there remains little known about the factors determining their acceptance, especially in the combination of vehicles with alternative fuels and autonomous driving modes, as is the case with AEBs. In this study, we first conducted qualitative research to identify relevant factors influencing individual acceptance of autonomously driven electric buses. We then developed a comprehensive research model that was validated through a survey of 268 passengers of an AEB, operated in regular road traffic in Germany. The results indicate that a mix of individual factors, social impacts, and system characteristics determine an individual’s acceptance of AEBs. Notably, it is important that users perceive AEBs, not only as advantageous, but also trustworthy, enjoyable, and in a positive social light. Our research supplements the existing corpora by demonstrating the importance of individual acceptance and incorporating it to derive policy implications.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Yan-Lai Li, Qiang Yang, Kwai-Sang Chin〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Risk management of hazardous materials (hazmats) road transportation has long been a concern because of the potential hazards that poses to society and the environment. In this work, a systematic and semi-quantitative decision support framework for risk management of hazmats road transportation based on the combination of quality function deployment (QFD), fuzzy analytic hierarchy process (F-AHP), fuzzy failure mode and effect analysis (F-FMEA), and nonlinear goal programming is proposed. The QFD is used innovatively to construct the overall framework, which contains three main components of general risk management: risk identification, risk assessment, and risk control. The F-AHP is used to build a hierarchical risk assessment system and determine the importance rating of each risk factor. The F-FMEA is used to evaluate the potential risks of risk control measures and determine the risk adjustment coefficient of each risk measure, which is used subsequently to modify the fulfillment level of risk measure in the nonlinear goal programming model. To address the inherent vagueness and uncertainty contained in the risk management process, the fuzzy set theory is introduced as an effective tool. An empirical case on risk management of a hazmats transportation company is presented to demonstrate the effectiveness and feasibility of the proposed methodology. Some managerial implications on risk management of hazmats road transportation are provided based on the obtained findings.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): Zhao Zhang, Brian Wolshon, Nelida Herrera, Scott Parr〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Transportation personnel, assets, and systems play important roles during emergencies. Of particular note is the critical function of road networks as lifelines for evacuations, then, after such events, to facilitate the rapid inflow of support personnel and resources needed to assess and repair damage. They also provide access for the safe and rapid return of evacuees. Despite the importance of reentry and repopulation, the role of transportation systems for them has been a relatively lightly researched topic. This paper describes research to analyze the traffic processes associated with post-evacuation reentry and its associated travel time and delay. To examine the most extreme of conditions; this effort also focused on repopulation and reentry after mass evacuations in megaregions. Among the findings of this work were that, as expected, reentry traffic processes generally behave similar to, but in the reverse direction, of evacuations. However, contrary to commonly held belief, they are not identically opposite. Rather, network performance during reentry may often be better than that of evacuation. Another broad finding of the research was that the spatial heterogeneity of traffic distribution across available roadways is a primary factor in determining network performance, meaning the more uniform the spread of on all links, the more efficient the network will operate. A third significant finding of this research was also the importance of the temporal spreading of returnee departure times on network efficiency.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): Yuting Hou〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study explores how the planned polycentric urban form in Singapore influences local residents’ non-work trip frequency of different transport modes and how the travel impacts of access to the planned commercial/activity centers vary between the non-elderly adults (aged 20–54) and older adults (aged 55 and over) of different subgroups. The study applies a categorical variable approach to account for independent effects of aging and its interaction effects with urban form variables while controlling for neighborhood-scale land use characteristics. The results indicate that better access to different tiers of planned urban centers is associated with more walking trips for some age groups of older people but less walking trips for other age groups. Neighborhood-level land use characteristics such as higher density and better street connectivity significantly increase walking trips for all adults with no differential effects across age. This study provides new empirical evidence on the differential travel impacts of urban form between younger adults and older adults of different subgroups. The findings also provide some insights on evaluating the performance of polycentric urban development strategy and land use policies of Singapore in terms of facilitating local residents’ daily mobility.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): Karla Münzel, Laura Piscicelli, Wouter Boon, Koen Frenken〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Carsharing is regarded to play an important part in the transition towards a more sustainable mobility system by changing how cars are used and transportation needs are met. Carsharing adopters own less cars, ride less car kilometers and depend on multiple transportation modes for their travel needs. There has been considerable interest in understanding the characteristics and motives of carsharing adopters. Yet, studies have been mostly limited to small-scale surveys, covering only specific cities or organizations and focusing on traditional B2C carsharing, disregarding the growing popularity of P2P carsharing through online platforms. This study contributes to extant research by investigating whether characteristics and motives differ between B2C and P2P carsharing adopters, and broadening the scope of the analysis to include an entire country (The Netherlands) and different carsharing provider types. First, our findings suggest that B2C and P2P carsharing adopters are rather similar in their characteristics but differ in the frequency in which they make use of carsharing and public transport. Second, we provide novel insights into the characteristics that influence a car owner to become an adopter of P2P carsharing as a provider. We find that car owners who already shared their car informally outside an online platform are also much more likely to provide their car through an online platform. We conclude with describing policy implications of our findings. Regulation should focus on shaping favorable conditions for a connected multi-modal transportation system instead of specific regulations for each carsharing business model.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): René Taudal Poulsen, Helen Sampson〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The abatement of greenhouse gas emissions represents a major global challenge and an important topic for transportation research. Several studies have argued that energy efficiency measures for virtual arrival and associated reduced anchorage time can significantly reduce emissions from ships by allowing for speed reduction on passage. However, virtual arrival is uncommon in shipping. In this paper, we examine the causes for waiting time for ships at anchor and the limited uptake of virtual arrival. We show the difficulties associated with the implementation of virtual arrival and explain why shipping is unlikely to achieve the related abatement potential as assumed by previous studies. Combining onboard observations with seafarers and interviews with both sea-staff and shore-based operational personnel we show how charterers’ commercial priorities outweigh the fuel saving benefits associated with virtual arrival. Moreover, we demonstrate how virtual arrival systems have unintended, negative consequences for seafarers in the form of fatigue. Our findings have implications for the IMO’s greenhouse gas abatement goals.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): Chandra Prakash Garg, Vishal Kashav〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In the Global Maritime Supply Chains (GMSCs), sustainable development and growth of containerized freight (cargo stuffed in maritime containers for transportation) transport system and container port/terminal business have attracted attention of regional governments, financial institutions and regulatory bodies across the globe. Particularly, growing worries about the unpropitious impacts on the environment caused by containerized freight transport industry. The industry has contributed immensely in growth and expansion of global trade and therefore increased trade promises sustainable growth of global port and shipping activities. Competition in liner shipping industry has shrunk profits of the carriers while struggling to grab more market share, which has led them to work upon creating value to the customers in order to gain edge over others. Therefore, this study is conducted from business perspective that how the global container shipping sector can create value to its customers and stakeholders and also go tandem with environmental aspect. The objective of the study is to identify and examine the value creating factors and sub-factors of GMSCs of containerized freight. Data on value creating factors is collected by consulting 57 ports and shipping industry experts globally. We propose FAHP (Fuzzy Analytic Hierarchy Process) framework for evaluating these value creating factors and develop this study which will not just help carriers but also the stakeholders in the containerized freight transport industry to measure their competitive edge over rivals. This study concludes with sensitivity analysis, results and discussions, managerial and practical implications of the conceptual framework.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): Paul Wolfram, Edgar Hertwich〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Light-duty vehicles (LDVs) are responsible for more than one tenth of global energy use and CO〈sub〉2〈/sub〉 emissions and are therefore an important focus in pollution mitigation efforts. Integrated energy models (IEMs) are frequently used to explore cost-optimal climate change mitigation measures for energy supply and demand sectors, such as LDVs. Options include fuel and powertrain switching through efficiency standards, taxation, and technology mandates. This review provides an overview on how LDVs are modeled in 14 popular IEMs. We find that the representation of mitigation options can be enhanced by linking emissions and physical outputs from industry, agriculture, and energy conversion directly to the vehicle life cycle and by more carefully reflecting important factors that influence LDV life cycle emissions. This would allow for a more complete internalization of emissions in the technology mix optimization procedure of IEMs. The results highlight a range of mitigation options currently not considered in most integrated models, such as reducing embodied emissions in infrastructure and vehicle production, reducing methane leakage, or switching to less carbon intensive crude oil grades.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 73〈/p〉 〈p〉Author(s): Junshi Xu, Marc Saleh, An Wang, Ran Tu, Marianne Hatzopoulou〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study presents the development of operating mode (opmode) distributions derived from local drive cycle construction methods developed based on real-world GPS data collection, and their impacts on average-speed emission factors (EFs). A data collection campaign was conducted between March and July 2018 whereby 82 research participants were recruited to record daily driving behaviors in the Greater Toronto and Hamilton Area (GTHA) for a period of one week. A drive cycle construction methodology was employed to build representative drive cycles based on micro-trips. The constructed drive cycles were compared with the interpolated drive cycles derived from the default database of the USEPA MOVES model. The results indicate that the MOVES default opmode distributions lead to higher average-speed EFs than the ones derived from local data. The difference between two drive cycle construction methods was also evaluated by comparing the variability in opmode distributions and the resulting average speed EFs. We observed that EFs were similar within each speed category, and the variation in cumulative opmode distributions was highest for an average speed of 40 mph. Moreover, a Monte Carlo Simulation was conducted to generate EF distributions based on local opmodes, further illustrating that local drive cycles generated significantly lower emission estimates than those based on the default database of MOVES. Finally, the minimum number of GPS data points required to develop a local opmode database with adequate variability was determined, illustrating that 4400–19,300 s were needed to generate robust distributions for different speed categories and road types.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Jiangping Zhou, Yuling Yang, Peiqin Gu, Ling Yin, Fan Zhang, Fang Zhang, Dong Li〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉TODness, i.e., the extent to which the existing conditions of TOD sites meet agreed-upon TOD standards often requires substantial investment and efforts. Given this, it is legitimate and understandable that decision-makers expect as many positive outcomes from TODness (or TODs) as possible. Non-traditional data (NTD) has provided more opportunities for us to develop (new) indicators for TODness and expected outcomes that we have for TODness. NTD, could, for instance, be used to formulate indicators across more spatiotemporal resolutions and samples and measure new expected outcomes, e.g., smartphone users per hour on weekdays by metro station across a city. Based on case study of Shenzhen, China, this paper introduces indicators for TODness and expected outcomes (partially) based on NTD. Through (spatial) regressions, it identifies the specific TODness (both at the site and regional levels) or station (area) characteristics that have the most impacts on different expected outcomes on weekdays and weekends. The findings and results can on the one hand revalidate the known relationships between expected outcomes in the existing literature and TODness and on the other hand reveal new relationships between the two, which can serve as extra references for TOD-related plan formulation, evaluation and decision-making.〈/p〉〈/div〉 〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part D: Transport and Environment, Volume 74〈/p〉 〈p〉Author(s): Qunshan Zhao, Scott B. Kelley, Fan Xiao, Michael J. Kuby〈/p〉 〈div xml:lang="en"〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Electric drive vehicles (plug-in electric vehicle or hydrogen fuel cell vehicles) have been promoted by governments to foster a more sustainable transportation future. Wider adoption of these vehicles, however, depends on the availability of a convenient and reliable refueling/recharging infrastructure. This paper introduces a path-based, multi-scale, scenario-planning modeling framework for locating a system of alternative-fuel stations. The approach builds on (1) the Flow Refueling Location Model (FRLM), which assumes that drivers stop along their origin-destination routes to refuel, and checks explicitly whether round trips can be completed without running out of fuel, and (2) the Freeway Traffic Capture Method (FTCM), which assesses the degree to which drivers can conveniently reach sites on the local street network near freeway intersections. This paper extends the FTCM to handle cases involving clusters of nearby freeway intersections, which is a limitation of its previous specification. Then, the cluster-based FTCM (CFTCM) is integrated with the FRLM and the DFRLM (FRLM with Deviations) to better conduct detailed geographic optimization of this multi-scale location planning problem. The main contribution of this research is the introduction of a framework that combines multi-scale planning methods to more effectively inform the early development stage of hydrogen refueling infrastructure planning. The proposed multi-scale modeling framework is applied to the Hartford, Connecticut region, which is one of the next areas targeted for fuel-cell vehicle (FCV) market and infrastructure expansion in the United States. This method is generalizable to other regions or other types of fast-fueling alternative fuel vehicles.〈/p〉〈/div〉 〈/div〉