ALBERT

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 128〈/p〉 〈p〉Author(s): Xiaotian Wang, Xin Wang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Reservation-based parking systems have the merit of eliminating vehicle cruising for parking. While many long-period (e.g., daily) parking reservation services are already in use, short-period (e.g., hourly) parking reservation remains a huge challenge due to the high uncertainty of customer arrivals and departures. To mitigate the service failure caused by random late departures of customers, we propose a new flexible reservation mechanism in which the reservation is no longer restricted to a specific location at a specific time, but tolerates predetermined spatiotemporal flexibility instead. With a pricing instrument designed for such parking flexibility, customers can coordinate to significantly reduce the reservation failure rate, resulting in an optimal system equilibrium benefiting the entire society. Due to the complex nature of this system, a continuum approximation framework is used to provide tractable analysis for a large-scale urban parking system. We can successfully provide accurate system management decision support with a bounded optimality gap and analytical insights.〈/p〉〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 128〈/p〉 〈p〉Author(s): Li Li, Saif Eddin Jabari〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉Decentralized intersection control techniques have received recent attention in the literature as means to overcome scalability issues associated with network-wide intersection control. Chief among these techniques are backpressure (BP) control algorithms, which were originally developed of for large wireless networks. In addition to being light-weight computationally, they come with guarantees of performance at the network level, specifically in terms of network-wide stability. The dynamics in backpressure control are represented using networks of point queues and this also applies to all of the applications to traffic control. As such, BP in traffic fail to capture the spatial distribution of vehicles along the intersection links and, consequently, spill-back dynamics.〈/p〉 〈p〉This paper derives a position weighted backpressure (PWBP) control policy for network traffic applying continuum modeling principles of traffic dynamics and thus capture the spatial distribution of vehicles along network roads and spill-back dynamics. PWBP inherits the computational advantages of traditional BP. To prove stability of PWBP, (i) a Lyapunov functional that captures the spatial distribution of vehicles is developed; (ii) the capacity region of the network is formally defined in the context of macroscopic network traffic; and (iii) it is proved, when exogenous arrival rates are within the capacity region, that PWBP control is network stabilizing. We conduct comparisons against a real-world adaptive control implementation for an isolated intersection. Comparisons are also performed against other BP approaches in addition to optimized fixed timing control at the network level. These experiments demonstrate the superiority of PWBP over the other control policies in terms of capacity region, network-wide delay, congestion propagation speed, recoverability from heavy congestion (outside of the capacity region), and response to incidents.〈/p〉 〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 128〈/p〉 〈p〉Author(s): Jian Wang, Siyuan Gong, Srinivas Peeta, Lili Lu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Recently, model predictive control (MPC)-based platooning strategies have been developed for connected and autonomous vehicles (CAVs) to enhance traffic performance by enabling cooperation among vehicles in the platoon. However, they are not deployable in practice as they require the embedded optimal control problem to be solved instantaneously, with platoon size and prediction horizon duration compounding the intractability. Ignoring the computational requirements leads to control delays that can deteriorate platoon performance and cause collisions between vehicles. To address this critical gap, this study first proposes an idealized MPC-based cooperative control strategy for CAV platooning based on the strong assumption that the problem can be solved instantaneously. It also proposes a solution algorithm for the embedded optimal control problem to maximize platoon performance. It then develops two approaches to deploy the idealized strategy, labeled the deployable MPC (DMPC) and the DMPC with first-order approximation (DMPC-FOA). The DMPC approach reserves certain amount of time before each sampling time instant to estimate the optimal control decisions. Thereby, the estimated optimal control decisions can be executed by all the following vehicles at each sampling time instant to control their behavior. However, under the DMPC approach, the estimated optimal control decisions may deviate significantly from those of the idealized MPC strategy due to prediction error of the leading vehicle's state at the sampling time instant. The DMPC-FOA approach can significantly improve the estimation performance of the DMPC approach by capturing the impacts of the prediction error of the leading vehicle's state on the optimal control decisions. An analytical method is derived for the sensitivity analysis of the optimal control decisions. Further, stability analysis is performed for the idealized MPC strategy, and a sufficient condition is derived to ensure its asymptotic stability under certain conditions. Numerical experiments illustrate that the control decisions estimated by the DMPC-FOA approach are very close to those of the idealized MPC strategy under different traffic flow scenarios. Hence, DMPC-FOA can address the issue of control delay of the idealized MPC strategy effectively and can efficiently coordinate car-following behaviors of all CAVs in the platoon to dampen traffic oscillations. Thereby, it can be applied for real-time cooperative control of a CAV platoon.〈/p〉〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 128〈/p〉 〈p〉Author(s): Evženie Suzdaleva, Ivan Nagy〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper deals with the task of modeling the driving style depending on the driving environment. The model of the driving style is represented as a two-layer mixture of normal components describing data with two pointers: outer and inner. The inner pointer indicates the actual driving environment categorized as “urban”, “rural” and “highway”. The outer pointer through the determined environment estimates the active driving style from a fuel economy point of view as “low consumption”, “middle consumption” and “high consumption”. All of these driving styles are assumed to exist within each driving environment due to the two-layer model. Parameters of the model and the driving style are estimated online, i.e., while driving using a recursive algorithm under the Bayesian methodology. The main contributions of the presented approach are: (i) the driving style recognition within each of urban, rural and highway environments as well as in the case of switching among them; (ii) the two-layer pointer, which allows us to incorporate the information from continuous data into the model; (iii) the potential use of the data-based model for other measurements using corresponding distributions. The approach was tested using real data.〈/p〉〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 128〈/p〉 〈p〉Author(s): Da Xu, Xiaolei Guo, Guoqing Zhang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We study the optimal single-step coarse toll design problem for the bottleneck model where the toll level and tolling duration have maximum acceptable upper bounds and the unconstrained optimal solution exceeds the upper bounds. We consider proportional user heterogeneity where users’ values of time and schedule delay vary in fixed proportions. Three classic coarse tolling models are studied, the ADL, Laih and braking models. In the ADL model, untolled users form a mass arrival at the bottleneck following the last tolled user. In the Laih model, there is a separated waiting facility for untolled users to wait until the toll ends. In the braking model, untolled users can choose to defer their arrival at the bottleneck to avoid paying the toll. We find that, in the ADL and the Laih models, the optimal solution chooses the maximum acceptable toll level and tolling duration. The ADL model further requires the tolling period to be started as late as possible to eliminate the queue at the toll ending moment. In the braking model, if the upper bound of the tolling duration is too small, no toll should be charged. Otherwise the optimal solution chooses the maximum acceptable tolling duration and may choose a toll price less than the maximum acceptable level.〈/p〉〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 128〈/p〉 〈p〉Author(s): Shuqin Li, Shuai Jia〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Traffic congestion in seaports can lead to uncontrolled execution of berth plans, causing severe vessel delays and long waiting times. In this paper, we schedule the vessel traffic of a seaport by optimizing the utilization of the navigation channel and the anchorage areas in the terminal basin. We model the traffic scheduling problem as a mixed integer linear program (MILP), which takes as inputs the physical layout of a seaport and the berth plans devised by the terminal operators, to minimize the berthing and departure delays of vessels and the number of vessels that cannot berth or depart successfully. We reformulate the MILP into a more compact set-partitioning formulation, develop a column generation algorithm for solving the problem, and propose three performance enhancement strategies, namely, a row generation method, a pricing problem reduction method, and a heuristic pricing method, to accelerate the convergence of the column generation algorithm. Computational performance of the proposed algorithm is evaluated on benchmark instances that are generated from the physical layout and operational data of the Yangshan Deep-water Port in Shanghai.〈/p〉〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 127〈/p〉 〈p〉Author(s): 〈/p〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 128〈/p〉 〈p〉Author(s): Yadong Wang, Qiang Meng, Peng Jia〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Container shipping companies usually alter their shipping networks in response to the seasonally changing shipping demand and freight rate. Rather than redesigning their shipping networks from scratch, they often choose to make small adjustments to the shipping routes by skipping some ports or adding additional calls to several ports. Inspired by above industrial practice in shipping network alteration, this study solves the port call adjustment problem (PCAP) to determine which port calls should be removed and which should be inserted for each route of a shipping network under the new shipping market patterns. A two-phase solution method is developed for the PCAP. In Phase 1, the candidate port calls for removal and insertion operations in each shipping route are determined. In Phase 2, the port call adjustment strategy is obtained by solving a mixed integer linear programming (MILP) model to select the port calls from these candidates identified in Phase 1 for actual removal and insertion operations. Considering the difficulties in solving the MILP model efficiently, two heuristic methods are also proposed to give near-optimal solutions in an acceptable computational time. Numerical experiments demonstrate that the proposed two-phase method is able to find a port call adjustment strategy that significantly reduces the operating cost.〈/p〉〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 128〈/p〉 〈p〉Author(s): Yang Zhou, Meng Wang, Soyoung Ahn〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, a serial distributed model predictive control (MPC) approach for connected automated vehicles (CAVS) is developed with local stability (disturbance dissipation over time) and multi-criteria string stability (disturbance attenuation through a vehicular string). Two string stability criteria are considered within the proposed MPC: (i) the 〈em〉l〈/em〉〈sub〉∞〈/sub〉-norm string stability criterion for attenuation of the maximum disturbance magnitude and (ii) 〈em〉l〈/em〉〈sub〉2〈/sub〉-norm string stability criterion for attenuation of disturbance energy. The 〈em〉l〈/em〉〈sub〉∞〈/sub〉-norm string stability is achieved by formulating constraints within the MPC based on the future states of the leading CAV, and the 〈em〉l〈/em〉〈sub〉2〈/sub〉-norm string stability is achieved by proper weight matrix tuning over a robust positive invariant set. For rigor, mathematical proofs for asymptotical local stability and multi-criteria string stability are provided. Simulation experiments verify that the distributed serial MPC proposed in this study is effective for disturbance attenuation and performs better than traditional MPC without stability guarantee.〈/p〉〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 128〈/p〉 〈p〉Author(s): Min Xu, Qiang Meng〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study aims to determine the electric vehicle fleet size for one-way carsharing services by maximizing the profit of carsharing operators while taking into account the vehicle relocation operations and nonlinear electric vehicle charging profile. We formulate a set partitioning model for the considered problem. A tailored branch-and-price (B&P) approach is proposed to find the exact optimal solution of the model. In particular, an effective multi-label correcting method is developed to solve the pricing problem (i.e., generate columns) within the B&P approach. A novel non-dominated charging strategy is put up to avoid the exponential growth of labels caused by the allowance of partial charging with a nonlinear charging profile. In addition to the B&P approach, two heuristic methods are put forward for solving the large-scale problems or reinforcing the B&P approach. Numerical experiments with randomly generated instances and a case study based on a one-way carsharing operator in Singapore are conducted to further assess the efficiency and applicability of the proposed solution methods. The effects of several key parameters, i.e., the fixed cost of EV, relocation cost, electricity cost, service charge, EV driving range, the charging efficiency, and the number of rentals on the performance of a one-way electric carsharing system are also examined.〈/p〉〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 128〈/p〉 〈p〉Author(s): Gert-Jaap Polinder, Thomas Breugem, Twan Dollevoet, Gábor Maróti〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, we consider the Robust Periodic Timetabling Problem (RPTP), the problem of designing a periodic timetable that can easily be adjusted in case of small periodic disturbances. We develop a solution method for a parametrized class of uncertainty regions. This class relates closely to uncertainty regions known in the robust optimization literature, and naturally defines a metric for the robustness of the timetable. The proposed solution method combines a linear decision rule with well-known reformulation techniques and cutting-plane methods. We show that the RPTP can be solved for practical-sized instances by applying the solution method to practical cases of Netherlands Railways (NS). In particular, we show that the trade-off between the efficiency and robustness of a timetable can be analyzed using our solution method.〈/p〉〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 128〈/p〉 〈p〉Author(s): Gizem Ozbaygin, Martin Savelsbergh〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Branch-and-price has established itself as an effective solution methodology for a wide variety of planning problems. We investigate its potential as a solution methodology for solving 〈em〉operational〈/em〉 problems. Specifically, we explore its potential in the context of a dynamic variant of the vehicle routing problem with roaming delivery locations, in which customer itineraries may change during the execution of a planned delivery schedule, which, in turn, may cause the planned delivery schedule to become suboptimal or even infeasible. We propose an iterative solution framework in which an active delivery schedule is re-optimized whenever a customer itinerary update is revealed. We use a branch-and-price algorithm for solving the planning problem (to obtain an initial delivery schedule) as well as the re-optimization problems (to obtain modified delivery schedules). As the re-optimization problems are solved during the execution of the (active) delivery schedule, it is critical to produce solutions quickly. This is accomplished by re-using, suitably modified, columns generated during preceding branch-and-price solves. The results of our computational experiments demonstrate the viability of using branch-and-price for solving operational problems and the benefit (necessity) of re-using information from previous solves.〈/p〉〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 128〈/p〉 〈p〉Author(s): Shuaian Wang, Ran Yan, Xiaobo Qu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Maritime transportation plays a pivotal role in the economy and globalization, while it poses threats and risks to the maritime environment. In order to maintain maritime safety, one of the most important mitigation solutions is the Port State Control (PSC) inspection. In this paper, a data-driven Bayesian network classifier named Tree Augmented Naive Bayes (TAN) classifier is developed to identify high-risk foreign vessels coming to the PSC inspection authorities. By using data on 250 PSC inspection records from Hong Kong port in 2017, we construct the structure and quantitative parts of the TAN classifier. Then the proposed classifier is validated by another 50 PSC inspection records from the same port. The results show that, compared with the Ship Risk Profile selection scheme that is currently implemented in practice, the TAN classifier can discover 130% more deficiencies on average. The proposed classifier can help the PSC authorities to better identify substandard ships as well as to allocate inspection resources.〈/p〉〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 128〈/p〉 〈p〉Author(s): Paolo Delle Site, Karim Kilani, Valerio Gatta, Edoardo Marcucci, André de Palma〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The paper considers random utility models that use a single common vector of random utilities for the computation of best, worst and best–worst choice probabilities, i.e. consistent models. Choice probabilities are derived for two distributions of the random terms: i.i.d. extreme value, i.e. Logit, and multivariate normal, i.e. Probit. We prove strict log-concavity of the likelihood, with respect to the coefficients of the systematic utilities, for best, worst and best–worst choice probabilities in Logit, and for best and worst choice probabilities in Probit, under a mild necessary and sufficient condition of absence of perfect multicollinearity in the matrix of alternative and individual characteristics. This condition parallels that in ordinary least squares linear regression models. The hypothesis of equality of the utility coefficients of best choice models and of worst choice models is tested with data on mode choice, collected for the assessment of user responses to urban congestion charging policies. The numerical results show, in both Logit and Probit, statistically significant differences between utility coefficients of best and worst models. The estimations based on worst choice data exhibit coefficient attenuation and higher mean values of travel time savings with larger standard errors.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 1 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological〈/p〉 〈p〉Author(s): Koki Satsukawa, Kentaro Wada, Takamasa Iryo〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The aim of this study is to analyze the stability of dynamic user equilibrium (DUE) with fixed departure times in unidirectional networks. Specifically, stochastic stability, which is the concept of stability in evolutionary dynamics subjected to stochastic effects, is herein considered. To achieve this, a new approach is developed by synthesizing the three concepts: the decomposition technique of DUE assignments, the weakly acyclic game, and the asymptotic analysis of the stationary distribution of perturbed dynamics. Specifically, we first formulate a DUE assignment as a strategic game (DUE game) that deals with atomic users. We then prove that there exists an appropriate order of assigning users for ensuring equilibrium in a unidirectional network. With this property, we establish the relationship between DUE games in unidirectional networks and weakly acyclic games. The convergence and stochastic stability of better response dynamics in the DUE games are then proved based on the theory of weakly acyclic games. Finally, we observe the properties of the convergence and stability from numerical experiments. The results show that the strict improvement of users’ travel times by the applied evolutionary dynamics is important for ensuring the existence of a stochastically stable equilibrium in DUE games.〈/p〉〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 118〈/p〉 〈p〉Author(s): Qian-Wen Guo, Shumin Chen, Paul Schonfeld, Zhongfei Li〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We address optimal rail transit investment issues considering time-inconsistent preferences and population uncertainty. Instead of adopting the typical real options approach which assumes that authorities possess a constant discount rate over time, we propose an extension of real options analysis by modeling authorities’ intertemporal choices with a quasi-hyperbolic discount function. Depending on the assumption about the strategies guiding the behaviors of future authorities, we consider three types of authorities, namely time-consistent authority, naïve authority and sophisticated authority, of which the latter two are time-inconsistent. First, an optimal transit investment timing model is proposed. Then, solutions for the above three types of authorities are derived and compared. We demonstrate the performance of the proposed model by conducting numerical tests and applying it to Dalian, China. Main findings include: (1) an authority with time-inconsistent preferences makes decisions earlier than a standard, time-consistent authority; (2) the sophisticated authority invests earlier than the naïve authority. Other implications of considering time-inconsistent preferences are also identified.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 122〈/p〉 〈p〉Author(s): 〈/p〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 123〈/p〉 〈p〉Author(s): Ángel Corberán, Mercedes Landete, Juanjo Peiró, Francisco Saldanha-da-Gama〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This work focuses on a broad class of uncapacitated 〈em〉p〈/em〉-hub median problems that includes non-stop services and setup costs for the network structures. In order to capture both the single and the multiple allocation patterns as well as any intermediate case of interest, we consider the so-called 〈em〉r〈/em〉-allocation pattern with 〈em〉r〈/em〉 denoting the maximum number of hubs a terminal can be allocated to. We start by revisiting an optimization model recently proposed for the problem. For that model, we introduce several families of valid inequalities as well as optimality cuts. Moreover, we consider a relaxation of the model that contains several sets of set packing constraints. This motivates a polyhedral study that we perform and that leads to the identification of many families of facets and other valid inequalities to the relaxed problem that, in turn, provide valid inequalities for the original model. Some of these families are too large for being handled directly. For those cases, separation algorithms are also presented. Finally, we gather all the above elements in a branch-and-cut procedure that we devise and implement for tackling the problem. The methodological developments proposed are tested computationally using data generated from the well-known AP data set.〈/p〉〈/div〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 123〈/p〉 〈p〉Author(s): Shaolong Hu, Chuanfeng Han, Zhijie Sasha Dong, Lingpeng Meng〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉As an important aspect in disaster operations management, relief distribution has been challenged by lots of factors, such as unpredictable occurrence time, intensity and location of secondary disasters (e.g. aftershocks and landslides, which usually occur after an earthquake), and availability of vehicles. A multi-stage stochastic programming model is developed for disaster relief distribution with consideration of multiple types of vehicles, fluctuation of rental, and the state of road network. The state of road network is characterized using uncertain and dynamic road capacity. The scenario tree is employed to represent the uncertain and dynamic road capacity, and demonstrate the decision process of relief distribution. A progressive hedging algorithm (PHA) is proposed for solving the proposed model in large-scale size. Based on a real-world case of Yaan earthquake in China, numerical experiments are presented to study the applicability of the proposed model and demonstrate the effectiveness of the proposed PHA. Useful managerial insights are provided by conducting numerical analysis.〈/p〉〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 118〈/p〉 〈p〉Author(s): Shuaian Wang, Wei Zhang, Xiaobo Qu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study deals with boarding/alighting congestion of congested commuter train stations at central business district (CBD), in which the additional fares are determined to shift an appropriate number of passengers to board/alight at the neighboring uncongested stations on the railway line. A bi-objective model is investigated to minimize both fare increases of the congested stations, while alleviating their boarding/alighting congestion to a certain level simultaneously. The existence of the unique Pareto-optimal solution is proven mathematically in the absence of explicit demand functions. A trial-and-error fare design scheme is proposed to identify the Pareto-optimal solution. An illustrative study demonstrates the effectiveness of the trial-and-error scheme.〈/p〉〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 118〈/p〉 〈p〉Author(s): Jingxu Chen, Shuai Jia, Shuaian Wang, Zhiyuan Liu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Container liner shipping network alteration is a practical manner of shipping network design, which aims to make minor modifications to ameliorate the existing network. In a generic liner shipping network with butterfly ports, each ship route is separated into a set of subloops on the basis of its structure and internal butterfly ports. Reversing the subloop directions has an impact on the network-wide cost including inventory cost, transshipment cost, and slot-purchasing cost. This paper proposes a new destination-based nonlinear model for the subloop-based reversal of port rotation directions with the objective of minimizing the overall network-wide cost. We prove that the addressed problem is NP-hard. Next, the model is transformed to an equivalent mixed-integer linear programming model. Based on the structure of the reformulated model, we develop a Benders decomposition (BD) algorithm and a metaheuristic method to solve practical-size instances. Three acceleration strategies are incorporated into the BD algorithm, which are adding Pareto-optimal cuts, updating big-M coefficients and generating combinatorial Benders cuts. Case studies based on three small examples and an Asia-Europe-Oceania liner shipping network with a total of 46 ports are conducted. Results show that the problem could be efficiently solved by the accelerated BD algorithm and the optimization of subloop directions is conducive to decreasing the network-wide cost especially the inventory cost.〈/p〉〈/div〉

Description: 〈p〉Publication date: December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 118〈/p〉 〈p〉Author(s): 〈/p〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 119〈/p〉 〈p〉Author(s): 〈/p〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 120〈/p〉 〈p〉Author(s): Paola Pellegrini, Raffaele Pesenti, Joaquin Rodriguez〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The real-time Railway Traffic Management problem consists in finding suitable train routes and schedules to minimize delay propagation due to traffic perturbations. RECIFE-MILP is a mixed integer linear programming based heuristic for this problem which has proven to be effective in various contexts. However, when instances are very large or difficult, the performance of the algorithm may worsen. In this paper, we propose valid inequalities to boost the performance of RECIFE-MILP. These valid inequalities link the routing and scheduling binary variables. We also provide an instance in which they are able to represent all the facets of the projection of the convex hull of the problem in the subspace of the binary variables. Moreover, they allow reformulating the model based on a reduced number of scheduling binary variables. In an experimental analysis based on realistic instances representing traffic in four French infrastructures, we observe that the merit of addition of valid inequalities depends on the specific case-study at hand, and that the reduction of the number of binary variables in general boosts the performance of RECIFE-MILP significantly.〈/p〉〈/div〉

Description: 〈p〉Publication date: January 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 119〈/p〉 〈p〉Author(s): Nikolai W.F. Bode, Mohcine Chraibi, Stefan Holl〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The interactions between individual pedestrians can lead to emergent effects, such as the formation of lanes in bidirectional flows. Here, we expose properties of an emergent effect at a macroscopic level, namely interactions between pedestrian streams that arise when pedestrians walk into and through four-way intersections from different directions. We propose non-spatial models for the number of pedestrians from different streams inside an intersection. Each model encodes a different hypothesis for how streams interact and can produce dynamics fundamentally distinct from the other models. By fitting our models to large experimental data sets and determining which model explains the data best, we determine when and how entire streams of pedestrians start to interact. We find that as arrival rates increase, streams start to interact and compete for space. Our results suggest that these interactions result in an even balance of pedestrian numbers across two orthogonally intersecting streams. Neither of the streams can dominate. In contrast, for four intersecting streams, our findings suggest that jams in some streams can coincide with higher flow rates in other streams and that the relative dominance of streams can switch stochastically. By adapting existing methodology, we thus present a coherent conceptual approach for investigating emergent effects in temporal dynamics at aggregated levels in pedestrian flows that could be applied to other scenarios. Our approach is flexible and uses easily measured quantities, making it highly suitable for observational data in different scenarios or deployment in applications.〈/p〉〈/div〉 〈h5〉Graphical abstract〈/h5〉 〈div〉〈p〉〈figure〉〈img src="https://ars.els-cdn.com/content/image/1-s2.0-S0191261518305253-fx1.jpg" width="301" alt="Image, graphical abstract" title="Image, graphical abstract"〉〈/figure〉〈/p〉〈/div〉

Description: 〈p〉Publication date: February 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 120〈/p〉 〈p〉Author(s): Mogens Fosgerau, Gege Jiang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper sets up a rational inattention model for the choice of departure time for a traveler facing random travel time. In this model, the traveler chooses in advance an information strategy for the travel time outcome, and then chooses departure time each day given the information received that day. The model describes how cheaper information allows the traveler to expand his/her consideration set and adapt more flexibly to changing conditions. This increases the traveler's payoff. The marginal cost of travel time variability is always positive. The ability to choose the information strategy reduces the cost of travel time variability compared to neoclassical travelers whose information is exogenously given.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 19 December 2018〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological〈/p〉 〈p〉Author(s): Rafał Kucharski, Guido Gentile〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉We present the Information Comply Model (ICM) which extends the framework for macroscopic within-day DTA proposed by Gentile (2016) to represent the rerouting of drivers wrt a single traffic event. Rerouting is reproduced as a two-stage process: first, drivers become aware about the event and its consequences on traffic; second, drivers may decide to change path. At each arc, unaware drivers have a probability of being informed by multiple ATIS sources (radio, VMS, mobile apps), which depends not only on devise penetration rates, but also on users space and time coordinates wrt the position and interval of the event. At each node, aware drivers, who are somehow reluctant to change, may finally modify their path based on a random rerouting utility, which is composed of expected gains and avoided losses. ICM is thus capable of representing the evolution of rerouting phenomena in time and space when the information about a traffic event and its consequences on congestion spread among drivers and onto the network.〈/p〉 〈p〉This way, ICM extends the concept of dynamic user equilibrium to a case of imperfect information related to availability and awareness rather than to individual perception, as well as to a case of bounded rationality with prudent drivers. Besides the model architecture and specification, this paper provides a workable methodology which can be applied both off-line for transport planning and in real-time for traffic management on large size networks.〈/p〉 〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 129〈/p〉 〈p〉Author(s): Xuan Di, Xuegang Jeff Ban〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Modeling congestion effects arising from multiple travel modes, shared mobility modes in particular, is non-trivial because of the complex interactions among diverse agents and distinct traffic flow compositions. This research aims to provide a theoretical framework of generic traffic network equilibria to unify these services and hopefully become a step stone to modeling shared mobility services in congested road network. In the proposed framework, we mainly focus on three modes: driving solo, ridesharing, and e-hailing service. The four types of traffic flows are: personal vehicle drivers, e-hailing drivers, ridesharing riders, and e-hailing passengers. The first two flows contribute to traffic congestion while the latter two do not. To capture their interactions, a super extended network is created with four copied networks each of whom represents one type of traffic flow. The equilibrium of new mobility systems can then be reformulated as a quasi-variational inequality and solution existence is discussed. The numerical results are tested in both Braess network and Sioux Falls network to illustrate the impact of different parameters on equilibrium outcomes, including modal cost, system travel time and deadhead miles. The results of this model will help assist transportation planners in making policy and regulation decisions regarding shared mobility services.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 129〈/p〉 〈p〉Author(s): Jia Yao, Wenhua Huang, Anthony Chen, Zhanhong Cheng, Shi An, Guangming Xu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper demonstrates a counter-intuitive phenomenon that “paradox links” (i.e. marginally improving or adding these links will increase a system's cost) can sometimes decrease a system's cost. It can be expressed that simultaneously improving the paradox link to a certain threshold (rather than only marginal improvement) or adding more paradox links may counter-intuitively avoid the paradox. Here, we refer this phenomenon as the “non-monotonicity” of the paradox with regard to the degree of link improvement and the number of additional paradox links. Firstly, a formal definition of "non-monotonicity" property of paradox in a rigorous mathematical manner is proposed. Then this non-monotonicity property is demonstrated to widely exist in the user equilibrium (UE), the stochastic assignment, and the stochastic user equilibrium (SUE) models by two simple networks, where the underlying reasons for this phenomenon in different scenarios are analyzed and compared. Finally, the non-monotonicity of the traffic paradox is corroborated in a road sub-network of Harbin. The conclusions of this study provide new insights into features of traffic paradoxes and new ideas to eliminate them.〈/p〉〈/div〉

Description: 〈p〉Publication date: November 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 129〈/p〉 〈p〉Author(s): Bumjoon Bae, Yuandong Liu, Lee D. Han, Hamparsum Bozdogan〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉When traffic flow exceeds capacity because of demand fluctuations, crashes, work zones, and special events, a traffic queue is formed on a highway. Traffic queues cause potentially hazardous situations at the end of the queue where drivers unexpectedly face slowed or stopped traffic while approaching at high speed. Therefore, detecting a queue is vital for protecting it. This study presents a real-time spatio-temporal traffic queue detection algorithm that builds on traffic flow fundamentals combined with a statistical pattern recognition procedure. Using flow-density data, traffic flow phase is classified as either congested or uncongested flow in a probabilistic manner, based on Gaussian mixture models for each location in such a way that detects the traffic phase transitions. The proposed detection algorithm was applied to detect traffic queues using traffic detector data from Interstate 40 in Knoxville, Tennessee. The detection results show that the algorithm detects queues successfully by accounting for varying queueing conditions and different queue types. In addition, the proposed algorithm performed better than speed threshold methods in the literature.〈/p〉〈/div〉

Description: 〈p〉Publication date: December 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 130〈/p〉 〈p〉Author(s): Yongxiang Zhao, Tuantuan Lu, Wenliang Su, Peng Wu, Libi Fu, Meifang Li〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The pedestrian movement in the crowds is a paradigmatic example of collective motion where social interactions play an important role. The psychological behaviors of pedestrians underlying crowd movements are usually based on intuitive assumptions, and so far a quantitative measurement of social repulsive force in pedestrian movements has been rarely reported. In this work, we perform different types of human experiments in face-to-face and face-to-back situations as well as walking, running and blind conditions to indirectly measure the social repulsive force based on the human physiological response to stress, i.e., the skin conductance response (SCR). It is demonstrated that the social repulsive force tends to increase with the moving speed of participants, and is much stronger in the face-to-face orientation compared to that in the face-to-back orientation. As interesting outcomes, a relationship between SCR amplitude and interpersonal distances is also observed, and statistical results show that the logistic functional form has a better fit to the measurement data of SCR amplitude than the classical exponential function due to the existence of a diminishing marginal utility in human psychology. Moreover, the observed repulsive force coefficients in running experiment slightly exceed those in walking experiment because faster running speed will cause more serious body conflict, thereby leading to a higher physiological arousal level. Especially, the social repulsive forces under the condition of zero visibility only occur where there is a body contact, which are significantly higher than those in walking and running experiments because of the panic psychology and unexpected danger in a blind environment. These experimental findings are further confirmed by numerical simulations performed by solving a modified social force model that incorporates logistic repulsive forces. The simulated velocity distributions in different types of psychological situations all demonstrate remarkable consistence with the experimental results. Therefore, this work establishes a direct link between behavioral responses and cognitive effort, and gives new insights into pedestrian dynamics from a social psychological perspective.〈/p〉〈/div〉

Description: 〈p〉Publication date: March 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 133〈/p〉 〈p〉Author(s): Danlin Yu, Daisuke Murakami, Yaojun Zhang, Xiwei Wu, Ding Li, Xiaoxi Wang, Guangdong Li〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The construction of high-speed rail in China was initially a direct response to the increasing demand of up-to-date infrastructure. It is commonly understood that the construction of HSR has significant wider economic impact on local development. The benefits of HSR are represented by the accessibility to the HSR stations. Our study defines accessibility to HSR with a simple distance measure and a transportation network measure that considers travel from the center of the county through different grades of roads to the nearest HSR stations. For better understanding, we estimate both global and local (i.e., location-specific) impacts from HSR, using per capital GDP as a representation of the wider economic impact. With access to a panel dataset from 2008 to 2015 of regional socioeconomic indicators at the county-level units in China, the current study employs an eigenvector based spatial filtering (ESF) approach with and without spatially varying coefficients in an attempt to establish potential global and local relationships between HSR accessibility and county-level regional development. The analysis result suggests that it is likely that HSR accessibility might significantly contribute to regional development. A 10% decrease of the travel time to the nearest HSR station could bring about 0.44% (locally ranging from 0.28% to 3.1%) increase in local GDP per capita at the county level, 〈em〉ceteris paribus〈/em〉. The panel analysis suggests that the continued development of HSR construction in China will have long-term and sustainable support to local economic development. This is especially important to the relatively underdeveloped regions in the North and West China.〈/p〉〈/div〉

Description: 〈p〉Publication date: March 2020〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 133〈/p〉 〈p〉Author(s): Saijun Shao, Su Xiu Xu, George Q. Huang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We study a less-than-truckload (LTL) transportation service procurement (TSP) in the waste collection industry, where shippers make small-volume requests and a single carrier optimizes the collection routes to realize maximum profitability. In our proposed auction-based waste collection synchronization (A-WCS) mechanism, the carrier plays a role as the auctioneer to decide on who wins the bids and the corresponding payments while the shippers act as the bidders. This is attributed to the carrier-centric structure where a carrier has to consolidate multiple LTL shipping requests so as to provide cost-effective services. Furthermore, a single shipper (e.g., a construction site) may generate multiple types of waste and highly desires for a synchronous service, requiring multiple vehicles dedicated for different waste types to arrive almost simultaneously. The synchronization is beneficial to prevent repeated handling and reduce disruption caused to the minimum. The synchronization requirements are innovatively factored by incorporating time windows into each customer bid. The A-WCS mechanism can encourage truthful bidding from shippers and obtain fair payments for both sides, therefore can benefit the market in the long run. A-WCS problems are extremely difficult to solve due to the integration of two combinatorial problems. We address the A-WCS with a two-layered algorithm, where the variable neighborhood search (VNS) is purposed to search auction allocations in the upper layer and tabu search (TS) is conducted to generate efficient vehicle routes in the lower layer. The capability of our algorithm is demonstrated by an extensive computational study, comparing with a number of state-of-the-art exact and heuristic approaches. Finally, a number of managerial implications for the practitioners are obtained, with insights into the impacts caused by changes in market size, task complexity, customer distribution pattern, and auction frequency.〈/p〉〈/div〉

Description: 〈p〉Publication date: December 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 130〈/p〉 〈p〉Author(s): Jinyan Sang, Zhi-Chun Li, William H.K. Lam, S.C. Wong〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper proposes a novel model of the design of a build-operate-transfer (BOT) contract for integrated rail and property (〈em〉R 〈/em〉+ 〈em〉P〈/em〉) development when the size of future urban population is uncertain. A real-option approach is adopted to accurately capture the potential economic value of a BOT investment project under uncertainty and its externality effects on urban spatial structure. The proposed model is formulated as a two-stage problem. The first stage of the model optimizes the concession period and rail line parameters (including rail line length, and number and locations of stations) through a Nash bargaining game between a private investor and the government. The second stage determines the headways and fares during the private operation and after transferring the BOT project to the government. The private investor's objective is to maximize its own net profit received during the concession period, whereas the government aims to maximize social welfare over the whole life-cycle of the project. The proposed model is extended to explore the effects of future population jumps due to non-recurrent random events and station deployments with even and uneven station spacings. The results show that compared with the rail-only scheme, the 〈em〉R 〈/em〉+ 〈em〉P〈/em〉 scheme can lead to a win-win situation for the government and private investor. In the BOT contract design, ignoring the effects of population jumps and using an average (or even) station spacing as an estimate of actual station deployment can cause a large bias of the parameter values designed in the contract and an underestimate of project values in terms of expected net profit and expected social welfare.〈/p〉〈/div〉

Description: 〈p〉Publication date: March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 121〈/p〉 〈p〉Author(s): 〈/p〉

Description: 〈p〉Publication date: April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 122〈/p〉 〈p〉Author(s): Stéphane Mollier, Maria Laura Delle Monache, Carlos Canudas-de-Wit, Benjamin Seibold〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this article we introduce a new traffic flow model for a dense urban area. We consider a two-dimensional conservation law in which the velocity magnitude is given by the fundamental diagram and the velocity direction is constructed following the network geometry and assuming we do not have precise information of drivers trajectories. We validate the model using synthetic data from Aimsun and propose a reconstruction technique to recover the 2D density from the data of individual vehicles. A comparison between the model and the data is shown.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 122〈/p〉 〈p〉Author(s): Liang Zheng, Xinfeng Xue, Chengcheng Xu, Bin Ran〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The equity of right-of-way is an important topic in traffic management and control. With the balance consideration of traffic equity and efficiency, which are respectively evaluated by the Atkinson index and average travel time, this study proposes a bi-objective signal timing simulation-based optimization (SO) model under uncertainties, and solve it by a bi-objective stochastic simulation-based optimization (BOSSO) method. In this method, two types of surrogate models (i.e., regressing Kriging model and quadratic regression model) are used to capture the complicated mapping relationship between decision variables and bi-objectives, respectively in the whole variable domain and in the local trust-region. Meanwhile, the incorporation of the global regressing Kriging model and an adaptive selector helps to predict bi-objective values of untested samples and re-estimate simulated samples in the local trust-region, which can save great computational costs and smooth stochastic noises. Moreover, the non-interactive role of a decision maker is taken to generate more Pareto optimal solutions around his/her desired bi-objective values. Through the algorithm comparison for a benchmark bi-objective stochastic optimization problem, the proposed BOSSO method is validated to outperform three other counterparts (i.e., NSGA-II, BOTR and BOEGO) under the same simulation costs. In real-field experiments, an urban road network with 15 signalized and five non-signalized intersections in Changsha, China is modeled by VISSIM. After the well calibration of the microscopic traffic simulation model, the network-wide bi-objective signal timing stochastic SO problems with and without coordination are solved by BOSSO. Numerical results indicate that compared with the real-field case, the average travel time and Atkinson index are reduced respectively by at most 13.48% and 23.49% for optimized non-coordinated signal plans, and respectively by at most 25.58% and 2.83% for optimized coordinated ones. It is further validated that under variable traffic volumes, the non-coordinated signal plan can well improve both traffic efficiency and equity, and the coordinated one is capable to improve traffic efficiency at a larger degree but sacrifice traffic equity. Moreover, the balance analyses show the existence of competing relationship between bi-objectives, and BOSSO is confirmed to outperform NSGA-II, BOTR and BOEGO in searching the better Pareto optimal signal plans under the same budged simulations. In conclusion, BOSSO is promising to address bi-objective optimization problems characterized by costly evaluation, high dimensions and stochastic noises.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 122〈/p〉 〈p〉Author(s): Guilhem Mariotte, Ludovic Leclercq〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉Large-scale traffic flow models based on the Network Macroscopic Fundamental Diagram (MFD) are usually grounded on the bathtub analogy and a conservation equation for vehicle accumulation inside a given urban area. Recent studies have proposed a different approach where the MFD defines the spatial mean speed that is shared by all vehicles in a region while their traveling distance is tracked individually. The former approach is also referred to as “accumulation-based” while the latter is usually named “trip-based”. While extensive studies of both model properties have been carried out for the single reservoir case (a unique region), the multi-reservoir setting still requires some research effort in particular to clearly understand how inflow merge at a reservoir entry and outflow diverge at exit should be managed. These two components play a significant role in the evolution of the whole system, when flows are exchanged between multiple reservoirs. One of the crucial questions is to ensure that congestion properly propagates backwards through a succession of reservoirs when oversaturated situations are observed.〈/p〉 〈p〉In this paper, we propose a thorough analysis of how to handle congestion propagation in the accumulation-based framework with several trip lengths or categories, e.g. internal and external trips. This allows to derive a congestion propagation model for the trip-based approach in a multi-reservoir setting. Based on theoretical considerations and simulation studies, we develop a consistent framework to restrict the inflow and adapt to oversaturated traffic conditions in a reservoir including several trip lengths. Two inflow merging schemes are investigated. The first one is inspired from the existing literature and shares the available supply based on the demand flow ratio at the entry boundary. It is called “exogeneous” in contrast to the second “endogenous” scheme, which shares the supply with respect to the internal accumulation ratio on the different routes. At the reservoir exit, a new outflow diverging scheme is also introduced to better reproduce the effect of queuing vehicles that are prevented from exiting the reservoir when congestion spills back from neighboring reservoirs. Compared to the conventional outflow model, our new approach proves to avoid unrealistic gridlocks when the reservoir becomes oversaturated. Both entry and exit flow models are investigated in details considering the accumulation-based and trip-based frameworks. Finally, the most consistent approach is compared with two other existing MFD models for multiple reservoirs. This demonstrates the importance of properly handling entry and exit flows at boundaries.〈/p〉 〈/div〉

Description: 〈p〉Publication date: April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 122〈/p〉 〈p〉Author(s): Hiroki Yamamoto, Daichi Yanagisawa, Claudio Feliciani, Katsuhiro Nishinari〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉This study investigated the body-rotation behavior adopted by pedestrians to avoid others while moving in congested areas. In such scenarios, body orientation often differs from walking direction, e.g., a pedestrian may step sideways.〈/p〉 〈p〉The deviation between body orientation and walking direction during collision avoidance was studied by quantitatively evaluating the body rotation for counter-flows in narrow corridors. Simple experiments, in which two pedestrians passed each other, were conducted. It was found that pedestrians rotated their bodies when the corridor width was smaller than the sum of the widths of the two pedestrians. This behavior was explained by analyzing the geometry of two ellipses circumscribing each other in a narrow corridor. A preliminary model was developed, and the deviation between the body orientation and walking direction during passing was successfully simulated.〈/p〉 〈p〉Finally, a cross-flow experiment, which is much more complex and realistic than the passing experiments, was performed; it was confirmed that body rotation behavior is also a critical factor in complex and realistic scenarios.〈/p〉 〈/div〉

Description: 〈p〉Publication date: April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 122〈/p〉 〈p〉Author(s): Ramin Raeesi, Konstantinos G. Zografos〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper introduces the Steiner Pollution-Routing Problem (SPRP) as a realistic variant of the PRP that can take into account the real operating conditions of urban freight distribution. The SPRP is a multi-objective, time and load dependent, fleet size and mix PRP, with time windows, flexible departure times, and multi-trips on congested urban road networks, that aims at minimising three objective functions pertaining to (i) vehicle hiring cost, (ii) total amount of fuel consumed, and (iii) total makespan (duration) of the routes. The paper focuses on a key complication arising from emissions minimisation in a time and load dependent setting, corresponding to the identification of the full set of the eligible road-paths between consecutive truck visits a priori, and to tackle the issue proposes new combinatorial results leading to the development of an exact Path Elimination Procedure (PEP). A PEP-based Mixed Integer Programming model is further developed for the SPRP and embedded within an efficient mathematical programming technique to generate the full set of the non-dominated points on the Pareto frontier of the SPRP. The proposed model considers truck instantaneous Acceleration/Deceleration (A/D) rates in the fuel consumption estimation, and to address the possible lack of such data at the planning stage, a new model for the construction of reliable synthetic spatiotemporal driving cycles from available macroscopic traffic speed data is introduced. Several analyses are conducted to: (i) demonstrate the added value of the proposed approach, (ii) exhibit the trade-off between the business and environmental objectives on the Pareto front of the SPRP, (iii) show the benefits of using multiple trips, and (iv) verify the reliability of the proposed model for the generation of driving cycles. A real road network based on the Chicago's arterial streets is also used for further experimentation with the proposed PEP algorithm.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 122〈/p〉 〈p〉Author(s): Yang Yu, Sihan Wang, Junwei Wang, Min Huang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Heterogeneous fleet vehicles can be used to reduce carbon emissions. We propose an improved branch-and-price (BAP) algorithm to precisely solve the heterogeneous fleet green vehicle routing problem with time windows (HFGVRPTW). In the improved BAP, to speed up the solution for the pricing problem, we develop a multi-vehicle approximate dynamic programming (MVADP) algorithm that is based on the labeling algorithm. The MVADP algorithm reduces labels by integrating the calculation of pricing problems for all vehicle types. In addition, to rapidly obtain a tighter upper bound, we propose an integer branch method. For each branch, we solve the master problem with the integer constraint by the CPLEX solver using the columns produced by column generation. We retain the smaller of the obtained integer solution and the current upper bound, and the branches are thus reduced significantly. Extensive computational experiments were performed on the Solomon benchmark instances. The results show that the branches and computational time were reduced significantly by the improved BAP algorithm.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 21 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological〈/p〉 〈p〉Author(s): Reza Mohajerpoor, Meead Saberi, Hai L. Vu, Timothy M. Garoni, Mohsen Ramezani〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Perimeter control is an effective city-scale solution to tackle congestion problems in urban networks. To accommodate the unpredictable dynamics of congestion propagation, it is essential to incorporate real-time robustness against travel demand fluctuations into a pragmatic perimeter control strategy. This paper proposes robust perimeter control algorithms based on partial information feedback from the network. The network dynamics are modeled using the concept of the Macroscopic Fundamental Diagram (MFD), where a heterogeneously congested network is assumed to be partitioned into two homogeneously congested regions, and an outer region that acts as demand origin and destination. The desired operating condition of the network is obtained by solving an optimization program. Observer-based 〈em〉H〈/em〉〈sub〉∞〈/sub〉 proportional (P) and proportional-integral (PI) controllers are designed based on Lyapunov theory, to robustly regulate the accumulation of each region and consequently to maximize the network outflow. The controller design algorithms further accommodate operational constraints by guarantying: (i) the boundedness of the perimeter control signals and (ii) a bounded offset between the perimeter control signals. Control parameters are designed off-line by solving a set of linear matrix inequalities (LMI), which can be solved efficiently. Comprehensive numerical studies conducted on the nonlinear model of the network highlight the effectiveness of the proposed robust control algorithms in improving the congestion in the presence of time-varying disturbance in travel demand.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 122〈/p〉 〈p〉Author(s): Chunhui Yu, Weili Sun, Henry X. Liu, Xiaoguang Yang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Reservation-based methods with simple policies such as first-come-first-service (FCFS) have been proposed in the literature to manage connected and automated vehicles (CAVs) at isolated intersections. However, a comprehensive analysis of intersection capacity and vehicle delay under FCFS-based control is missing, especially under high traffic demand. To address this problem, this study adopts queueing theory and analytically shows that such method is incapable of handling high demand with multiple conflicting traffic streams. Furthermore, an optimization model is proposed to optimally serve CAVs arriving at an intersection for delay minimization. This study then compares the performance of the proposed optimization-based control with reservation-based control as well as conventional vehicle-actuated control at different demand levels. Simulation results show that the proposed optimization-based control performs best and it has noticeable advantages over the other two control methods. The advantages of reservation-based control are insignificant compared with vehicle-actuated control under high demand.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 122〈/p〉 〈p〉Author(s): Claudia Bongiovanni, Mor Kaspi, Nikolas Geroliminis〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In the Dial-a-Ride-Problem (DARP) a fleet of vehicles provides shared-ride services to users specifying their origin, destination, and preferred arrival time. Typically, the problem consists of finding minimum cost routes, satisfying operational constraints such as time-windows, origin-destination precedences, user maximum ride-times, and vehicle maximum route-durations. This paper presents a problem variant for the DARP which considers the use of electric autonomous vehicles (e-ADARP). The problem covers battery management, detours to charging stations, recharge times, and selection of destination depots, along with classic DARP features. The goal of the problem is to minimize a weighted objective function consisting of the total travel time of all vehicles and excess ride-time of the users. We formulate the problem as a 3-index and a 2-index mixed-integer-linear program and devise a branch-and-cut algorithm with new valid inequalities derived from e-ADARP properties. Computational experiments are performed on adapted benchmark instances from DARP literature and on instances based on real data from Uber Technologies Inc. Instances with up to 5 vehicles and 40 requests are solved to optimality.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 122〈/p〉 〈p〉Author(s): Zheng Wang, Jiuh-Biing Sheu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The vehicle routing problem with drones (VRPD) is an extension of the classic capacitated vehicle routing problem, where not only trucks but drones are used to deliver parcels to customers. One distinctive feature of the VRPD is that a drone may travel with a truck, take off from its stop to serve customers, and land at a service hub to travel with another truck as long as the flying range and loading capacity limitations are satisfied. Routing trucks and drones in an integrated manner makes the problem much more challenging and different from classical vehicle routing literature. We propose a mixed integer programming model, and develop a branch-and-price algorithm. Extensive experiments are conducted on the instances randomly generated in a practical setting, and the results demonstrate the good computational performance of the proposed algorithm. We also conduct sensitivity analysis on a key factor that may affect the total cost of a solution.〈/p〉〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 126〈/p〉 〈p〉Author(s): Samuel Pelletier, Ola Jabali, Gilbert Laporte〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Compared with conventional freight vehicles, electric freight vehicles create less local pollution and are thus generally perceived as a more sustainable means of goods distribution. In urban areas, such vehicles must often perform the entirety of their delivery routes without recharging. However, their energy consumption is subject to a fair amount of uncertainty, which is due to exogenous factors such as the weather and road conditions, endogenous factors such as driver behaviour, and several energy consumption parameters that are difficult to measure precisely. Hence we propose a robust optimization framework to take into account these energy consumption uncertainties in the context of an electric vehicle routing problem. The objective is to determine minimum cost delivery routes capable of providing strong guarantees that a given vehicle will not run out of charge during its route. We formulate the problem as a robust mixed integer linear program and solve small instances to optimality using robust optimization techniques. Furthermore, we develop a two-phase heuristic method based on large neighbourhood search to solve larger instances of the problem, and we conduct several numerical tests to assess the quality of the methodology. The computational experiments illustrate the trade-off between cost and risk, and demonstrate the influence of several parameters on best found solutions. Furthermore, our heuristic identifies 42 new best solutions when tested on instances of the closely related robust capacitated vehicle routing problem.〈/p〉〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 126〈/p〉 〈p〉Author(s): Carlos F. Daganzo, Yanfeng Ouyang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The paper presents a general analytic framework to model transit systems that provide door-to-door service. The model includes as special cases 〈em〉non-shared taxi〈/em〉 and 〈em〉demand responsive transportation〈/em〉 (〈em〉DRT〈/em〉). In the latter we include both, paratransit services such as 〈em〉dial-a-ride〈/em〉 (〈em〉DAR〈/em〉), and the form of ridesharing (〈em〉shared taxi〈/em〉) currently being used by crowd-sourced taxi companies like Lyft and Uber. The framework yields somewhat optimistic results because, among other things, it is deterministic and does not track vehicles across space. By virtue of its simplicity, however, the framework yields approximate closed form formulas for many cases of interest.〈/p〉〈/div〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 123〈/p〉 〈p〉Author(s): Sepehr Ghader, Carlos Carrion, Lei Zhang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, we formulate the autoregressive continuous logit model as a novel continuous choice model capable of representing correlations across alternatives in the continuous spectrum. We formulate this model by considering two approaches: combining a discrete-time autoregressive process of order one (i.e., a linear stochastic difference equation) with the continuous logit model, which leads to the discrete-time autoregressive continuous logit; and combining a continuous-time autoregressive process (i.e., a linear stochastic differential equation), known in the stochastic process literature as Ornstein-Uhlenbeck process with the continuous logit model, which leads to the continuous-time autoregressive continuous logit. The autoregressive nature of the model is in its error structure, allowing correlations in unobserved heterogeneity. For both approaches, we study their properties numerically. We also compare both approaches to highlight their relation to each other.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 4 April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological〈/p〉 〈p〉Author(s): Wei Liu, Wai Yuen Szeto〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This study estimates and manages the stochastic traffic dynamics in a bi-modal transportation system, and gives hints on how increasing data availability in transport and cities can be utilized to estimate transport supply functions and manage transport demand simultaneously. In the bi-modal system, travelers’ mode choices are based on their perceptions of the two travel modes: driving or public transit. Some travelers who have access to real-time road (car) traffic information may shift their mode based on the information received (note that real-time information about public transit departures/arrivals is not considered here). For the roadway network, the within-day traffic evolution is modeled through a Macroscopic Fundamental Diagram (MFD), where the flow dynamics exhibits a certain level of uncertainty. A non-parametric approach is proposed to estimate the MFD. To improve traffic efficiency, we develop an adaptive pricing mechanism coupled with the learned MFD. The adaptive pricing extends the study of Liu and Geroliminis (2017) to the time-dependent case, which can better accommodate temporal demand variations and achieve higher efficiency. Numerical studies are conducted on a one-region theoretical city network to illustrate the dynamic evolution of traffic, the MFD learning framework, and the efficiency of the adaptive pricing mechanism.〈/p〉〈/div〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 123〈/p〉 〈p〉Author(s): Wen-Xiang Wu, Hai-Jun Huang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In this paper, we propose an intuitive, non-anticipative, partially decentralized, and adaptive combined strategy for managing evacuation routes with limited inputs so as to minimize the system clearance time. This strategy is intuitive due to the use of simple and transparent rules, non-anticipative because it relies on readily available information only, partially decentralized because only the upstream ramps are coordinately optimized, and adaptive due to the self-renewal with traffic condition. It is a combined strategy because it may include priority control strategy or proportional control strategy. Our approach is robust in the sense that it can be easily implemented, and can deal with not only real-time data but also predictive information. Numerical results show that the proposed strategy works effectively and can serve as a simple evacuation tool for regulating ramp discharge flows.〈/p〉〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 126〈/p〉 〈p〉Author(s): Johan Högdahl, Markus Bohlin, Oskar Fröidh〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Minimal travel time and maximal reliability are two of the most important properties of a railway transportation service. This paper considers the problem of finding a timetable for a given set of departures that minimizes the weighted sum of scheduled travel time and expected delay, thereby capturing these two important socio-economic properties of a timetable. To accurately represent the complex secondary delays in operational railway traffic, an approach combining microscopic simulation and macroscopic timetable optimization is proposed. To predict the expected delay in the macroscopic timetable, a surrogate function is formulated, as well as a subproblem to calibrate the parameters in the model. In a set of computational experiments, the approach increased the socio-economic benefit by 2–5% and improved the punctuality by 8–25%.〈/p〉〈/div〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 123〈/p〉 〈p〉Author(s): C. Angelo Guevara, Stephane Hess〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉It is common practice to build Stated Preference (SP) attributes and alternatives from observed Revealed Preference (RP) choices with a view to increasing realism. While many surveys pivot all alternatives around an observed choice, others use more adaptive approaches in which changes are made depending on what alternative was chosen in the RP setting. For example, in SP-off-RP data, the alternative chosen in the RP setting is worsened in the SP setting and other alternatives are improved to induce a change in behaviour. This facilitates the creation of meaningful trade-offs or tipping points but introduces endogeneity. This source of endogeneity was largely ignored until Train and Wilson (T&W) proposed a full information maximum likelihood (FIML) solution that can be implemented with simulation. In this article, we propose a limited information maximum likelihood (LIML) approach to address the SP-off-RP problem using a method which does not need simulation, can be applied with standard software and uses data that is already available for the stated problem. The proposed method is an application of the control-function (CF) method to correct for endogeneity in discrete choice models, using the RP attributes as instrumental variables. We discuss the theoretical and practical advantages and disadvantages of the CF and T&W methods and illustrate them using Monte Carlo and real data. Results show that, while the T&W method may be more efficient in theory, it may however fail to retrieve consistent estimators when it does not account properly for the data generation process if, e.g., an exogenous source of correlation among the SP choice tasks exists. On the other hand, the CF is more robust, i.e. less sensitive, to the data generation process assumptions, and is considerably easier to apply with standard software and does not require simulation, facilitating its adoption and the more extensive use of SP-off-RP data.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 26 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological〈/p〉 〈p〉Author(s): Yang Zhou, Soyoung Ahn, Meng Wang, Serge Hoogendoorn〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper presents a car-following control strategy of connected automated vehicles (CAVs) to stabilize a mixed vehicular platoon consisting of CAVs and human-driven vehicles. This study first establishes a string stability criterion for a mixed vehicular platoon. Specifically, a mixed vehicular platoon is decomposed into “subsystems” that are all possible sequential subsets of the platoon. String stability is then defined as the “head-to-tail” string stability for all subsystems: the magnitude of a disturbance is not amplified from the first vehicle to the last vehicle of each subsystem. Based on this definition, distributed frequency-domain-based CAV control is proposed to increase the number of head-to-tail string stable subsystems and consequently dampen stop-and-go disturbances drastically. Specifically, an H-infinity control problem is formulated, where the maximum disturbance “damping ratios” in each subsystem is minimized within the predominant acceleration frequency boundaries of human-driven vehicles. Simulation experiments, embedded with real human-driven vehicle trajectories, were conducted, and results show that the proposed control can effectively dampen stop-and-go disturbances.〈/p〉〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 126〈/p〉 〈p〉Author(s): Anshuman Sharma, Zuduo Zheng, Ashish Bhaskar, Md. Mazharul Haque〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper incorporates the driver compliance behaviour into a connected vehicle driving strategy (CVDS) that can be integrated with traditional car-following (CF) models to better describe the connected vehicle CF behaviour. Driver compliance, a key human factor for the success of connected vehicles technology, is modelled using a celebrated theory of decision making under risk – the Prospect theory (PT). The reformulated value and weighting functions of PT are consistent with the driver compliance behaviour and also preserve the integral elements of PT. Furthermore, the connected vehicle trajectory data collected from a carefully designed advanced driving simulator experiment are utilised to calibrate CVDS integrated with Intelligent Driver Model (IDM), i.e., CVDS-IDM. The calibration results reveal that drivers in the connected environment drive safely and efficiently. Moreover, the CVDS-IDM can successfully model and predict the CF dynamics of connected vehicles and is more behaviourally and numerically sound than a traditional CF model.〈/p〉〈/div〉

Description: 〈p〉Publication date: June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 124〈/p〉 〈p〉Author(s): Saeid Rasulkhani, Joseph Y.J. Chow〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We propose a generalized market equilibrium model using assignment game criteria for evaluating transportation systems that consist of both operators’ and users’ decisions. The model finds stable pricing, in terms of generalized costs, and matches between user populations in a network to set of routes with line capacities. The proposed model gives a set of stable outcomes instead of single point pricing that allows operators to design ticket pricing, routes/schedules that impact access/egress, shared policies that impact wait/transfer costs, etc., based on a desired mechanism or policy. The set of stable outcomes is proven to be convex from which assignment-dependent unique user-optimal and operator-optimal outcomes can be obtained. Different user groups can benefit from using this model in a prescriptive manner or within a sequential design process. We look at several different examples to test our model: small examples of fixed transit routes and a case study using a small subset of taxi data in NYC. The case study illustrates how one can use the model to evaluate a policy that can require passengers to walk up to 1 block away to meet with a shared taxi without turning away passengers.〈/p〉〈/div〉

Description: 〈p〉Publication date: May 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 123〈/p〉 〈p〉Author(s): 〈/p〉

Description: 〈p〉Publication date: June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 124〈/p〉 〈p〉Author(s): Robin Lindsey, André de Palma, Hugo E. Silva〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Individual users of transportation facilities often control a significant share of total traffic. Examples include airlines, rail and maritime freight shippers, urban goods delivery companies, taxi companies, and ride-sharing companies. These users have an incentive to internalize the congestion delays their own vehicles impose on each other by adjusting the timing of their trips. We investigate simultaneous trip-timing decisions by large users and small users in a dynamic model of congestion. Unlike previous work, we allow for heterogeneity of trip-timing preferences and for the presence of small users such as individual commuters and fringe airlines. We derive the optimal fleet departure schedule for a large user as a best-response to the aggregate departure rate of other users. We show that when the vehicles in a large user’s fleet have sufficiently diverse preferred arrival times, there may exist a pure-strategy Nash-equilibrium (PSNE) in which the large user schedules vehicles when there is a queue. This highlights that the problem of non-existence of a PSNE identified in Silva et al. (2016) for the case of symmetric large users hinges on the assumption that all vehicles in each fleet have the same preferred arrival time. We also develop some examples to identify under what conditions a PSNE exists, and when the large user departs. The examples illustrate how self-internalization of congestion by a large user can affect the nature of equilibrium and the travel costs that it and other users incur.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 15 March 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological〈/p〉 〈p〉Author(s): Pengfei Wang, Hongzhi Guan, Peng Liu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper models and solves the optimal allocation-pricing of reservable parking resources and the pricing of unreservable parking resources, respectively. For reservable parking facility, a MP-DGS (modified proxy Demange-Gale-Sotomayor) mechanism and combinatorial system (integration of direct and evolutionary methods) are adopted to maximize the social surplus through optimizing the allocation-pricing of parking permits. As a result, it is found that: (i) the proposed approaches not only simplify the users’ bidding procedures but also ensure the users express their preference truthfully even under the situation of non-optimal parking permits allocation; (ii) in homogeneous case (parking periods for all users are the same), it is theoretically demonstrated that the MP-DGS mechanism is more efficient than the traditional mechanisms in the worst-case scenario; (iii) in heterogeneous case (users are heterogeneous in desired parking timing and duration), time-dependent parking permits are taken into account. The ranking of the algorithm time complexity in the worst-case scenario is that direct method = evolutionary method  〈  Leonard mechanism = VCG (Vickrey-Clarke-Groves) mechanism, and the combinatorial system not only solves out the optimal allocation-pricing results effectively but also ensures the optimal results can be obtained in a shorter time. In addition, for unreservable parking facility, we formulate a dynamic social optimum as a stochastic control problem and then obtain a region-based optimal dynamic parking pricing. Through theoretical analysis, it is revealed that depending on the realization of the queue length due to the cruising-for-parking, the region-based optimal dynamic parking pricing can be divided into two patterns, furthermore, each pattern results in a “bang-bang” control.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 122〈/p〉 〈p〉Author(s): Jing-Peng Wang, Xuegang (Jeff) Ban, Hai-Jun Huang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper investigates the dynamic ridesharing with the variable-ratio charging-compensation scheme (VCS) in morning commute, with the continuous-time point-queue model applied to a single bottleneck. The optimal VCS without imposing road pricing when the ridesharing platform minimizes the disutility or maximizes its profit is analyzed. It is found that the user equilibrium coincides with the system optimum when the platform minimizes the system disutility with VCS, and the corresponding platform's profit is negative with high travel demand. Considering this, the optimal VCS when the platform minimizes the system disutility with zero profit is examined. Moreover, to ensure ridesharing participants commute with no queue, they need to depart at the two tails of the departure time window. Under that case, the optimal VCS are investigated with desirable objectives of the ridesharing platform. The analytical results indicate there should be fewer commuters involved in ridesharing when the platform maximizes its profit compared to that when the platform minimizes the system disutility with zero profit.〈/p〉〈/div〉

Description: 〈p〉Publication date: April 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 122〈/p〉 〈p〉Author(s): Çağatay Iris, Jasmine Siu Lee Lam〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The performance of a container terminal heavily relies on how efficiently the quayside resources, which are mainly berth and quay cranes, are used. The quayside related planning problems face uncertainty in various parameters, and this makes the efficient planning of these operations even more complicated. This study aims at developing a recoverable robust optimization approach for the weekly berth and quay crane planning problem. In order to build systematic recoverable robustness, a proactive baseline schedule with reactive recovery costs has been suggested. The uncertainty of vessel arrivals and the fluctuation in the container handling rate of quay cranes are considered. The baseline schedule includes berthing positions, times and quay crane assignments for all vessels along with vessel-specific buffer times and buffer quay cranes. The problem also introduces recovery plans for each scenario. The objective is to minimize the cost of baseline schedule, the recovery costs from the baseline schedule and the cost of scenario solutions for different realizations of uncertain parameters. A mathematical model and an adaptive large neighborhood based heuristic framework are presented to solve the novel problem. Computational results point out the strength of the solution methods and practical relevance for container terminals.〈/p〉〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 126〈/p〉 〈p〉Author(s): 〈/p〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 128〈/p〉 〈p〉Author(s): Wen-Long Jin, Qinglong Yan〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉 〈p〉Observations suggest that the First-In-First-Out (FIFO) principle is usually violated on multi-lane roads. Jin (2017) formulated and solved unifiable multi-commodity kinematic wave models, when different commodities have the same contributions to overall traffic congestion (unifiable) but may travel at different speeds (non-FIFO). However, the construction of unifiable multi-commodity fundamental diagrams and the assumption of concave or convex commodity flow proportion functions are purely mathematical and lack behavioral explanations. Thus the existing formulation is only of pure mathematical and theoretical interests and too complicated for real-world calibration, validation, or applications.〈/p〉 〈p〉In this study, we present a new formulation of unifiable multi-commodity kinematic wave models to address the aforementioned limitations. We first introduce a new variable for the relative speed ratios of different commodities and particularly discuss constant relative speed ratios. The relative speed ratios are physically, behaviorally, and economically meaningful since they characterize drivers’ relative aggressiveness, values of times, and other features. We then present unifiable multi-commodity fundamental diagrams based on the relative speed ratios, which can be used to derive the mathematical generating functions in Jin (2017). Then we show that non-FIFO multi-commodity kinematic wave model is a system of non-strictly hyperbolic conservation laws and solve the Riemann problem for a two-commodity system with constant relative speed ratios, in which the commodity flow proportion function is either concave or convex. We also present an empirical evidence for the existence of unifiable multi-commodity fundamental diagrams with constant relative speed ratios, which help to demonstrate the advantage of the new formulation. In summary, the new formulation is as general as the original formulation, but physically more meaningful, theoretically easier to solve, and empirically simpler to calibrate. Finally we conclude the study with discussions on potential future applications.〈/p〉 〈/div〉

Description: 〈p〉Publication date: Available online 16 August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological〈/p〉 〈p〉Author(s): Zuo-Jun Max Shen, Bo Feng, Chao Mao, Lun Ran〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Electric vehicles (EVs) are widely considered to be a solution to the problems of increasing carbon emissions and dependence on fossil fuels. However, the adoption of EVs remains sluggish due to range anxiety, long charging times, and inconvenient and insufficient charging infrastructure. Various problems with EV service operations should be addressed to overcome these challenges. This study reviews the state-of-the-art mathematical modeling-based literature on EV operations management. The literature is classified according to recurring themes, such as EV charging infrastructure planning, EV charging operations, and public policy and business models. In each theme, typical optimization models and algorithms proposed in previous studies are surveyed. The review concludes with a discussion of several possible questions for future research on EV service operations management.〈/p〉〈/div〉

Description: 〈p〉Publication date: October 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 128〈/p〉 〈p〉Author(s): Yikang Hua, Dongfang Zhao, Xin Wang, Xiaopeng Li〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉We propose an innovative framework to deploy a one-way Electric Vehicle (EV) sharing system that serves an urban area. For the first time, long-term infrastructure planning (charging station location and fleet distribution) and real-time fleet operations (relocation and charging decisions) are jointly optimized under time-varying uncertain demand. This substantially advances EV sharing system efficiency and yields a practical management strategy. We propose a multistage stochastic model to address the critical challenge of time-varying uncertain demand. An accelerated solution algorithm is developed to conquer the curse of dimensionality in integer infrastructure planning decisions. Meaningful insights are delivered through hypothetical numerical experiments and a realistic case study with EV sharing service in the New York City.〈/p〉〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 127〈/p〉 〈p〉Author(s): Samuela Carosi, Antonio Frangioni, Laura Galli, Leopoldo Girardi, Giuliano Vallese〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Planning a public transportation system is a complex process, which is usually broken down in several phases, performed in sequence. Most often, the trips required to cover a service with the desired frequency (headway) are decided early on, while the vehicles needed to cover these trips are determined at a later stage. This potentially leads to requiring a larger number of vehicles (and, therefore, drivers) that would be possible if the two decisions were performed simultaneously. We propose a multicommodity-flow type model for integrated timetabling and vehicle scheduling. Since the model is large-scale and cannot be solved by off-the-shelf tools with the efficiency required by planners, we propose a diving-type matheuristic approach for the problem. We report on the efficiency and effectiveness of two variants of the proposed approach, differing on how the continuous relaxation of the problem is solved, to tackle real-world instances of bus transport planning problem originating from customers of 〈em〉M.A.I.O.R.〈/em〉, a leading company providing services and advanced decision-support systems to public transport authorities and operators. The results show that the approach can be used to aid even experienced planners in either obtaining better solutions, or obtaining them faster and with less effort, or both.〈/p〉〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 127〈/p〉 〈p〉Author(s): Mads Paulsen, Thomas Kjær Rasmussen, Otto Anker Nielsen〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Copenhagen is world-known for its large proportion of cyclists, forming a diverse group with a large variation of equipment and physical abilities. This leads to a considerable speed heterogeneity which needs to be taken into account when modelling the traffic on dedicated bicycle paths. Nevertheless, existing studies on bicycle traffic simulation have either neglected such speed heterogeneity altogether or modelled it by dividing cyclists into a few discrete classes ignoring the entirety of the speed distribution. This paper proposes an efficient bicycle traffic simulation model with continuously speed heterogeneous cyclists and corresponding congestion effects. Based on individual-specific desired speeds and headway distance preferences, the model shows realistic speed-flow relationships validated with on-site observations while being capable of delaying rapid cyclists more often than slower ones in moderate traffic flows. The scalability of the model allows it to be large-scale applicable for network loading purposes, and thus suitable for evaluating impacts of cycling related infrastructure investments.〈/p〉〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 127〈/p〉 〈p〉Author(s): Carlos Armando Zetina, Ivan Contreras, Jean-François Cordeau〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper extends classic fixed-charge multicommodity network design by explicitly considering demand elasticity with respect to routing cost in a profit maximization context with service commitments. Demand quantity is determined by a spatial interaction model that accounts for routing costs, thus capturing the trade-off between infrastructure investment, efficient routing, and increased revenue. A numerical example is presented to demonstrate the added value of incorporating demand elasticity in profit-oriented network design problems. An arc-based and a path-based formulation, both with the flexibility of incorporating O/D pair selection by means of network and data transformations, are presented. The arc-based formulation is solved using state-of-the-art global optimization software while the path-based formulation serves as the basis for a hybrid matheuristic that combines a slope scaling metaheuristic and column generation. Computational experience shows the hybrid matheuristic to be superior in terms of solution quality and computation time.〈/p〉〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 127〈/p〉 〈p〉Author(s): Leonardo J. Basso, Fernando Feres, Hugo E. Silva〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉The penetration of BRT systems has been increasing fast, although there have been many reports of heavy queuing to board the buses. We propose a dynamic congestion approach that endogenously models queuing both on the road and at BRT stations, which are the center of our interest. We show analytically that, if capacity is perfectly divisible, implementing a BRT is always efficient (it decreases total social cost), while we show numerically that if capacity is not perfectly divisible, a BRT is in most cases efficient. Moreover, BRT can induce a Pareto Improvement where both time costs and public transport operating costs decrease. Compared to the optimum when buses run in mixed traffic, the optimal BRT system has: (i) Shorter period of bus operation and car-peak period, (ii) larger frequency and, very importantly, (iii) more boarding delays, i.e. longer queues at bus stops. Point (ii) implies that, while for some level of demands it may be optimal not to provide any public transport service under mixed traffic, with a BRT it may well be worthwhile.〈/p〉〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 127〈/p〉 〈p〉Author(s): Fei Yan, Rob M.P. Goverde〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Rail systems have been developing rapidly in recent years aiming at satisfying the growing passenger demand and shortening passenger travel time. The line planning problem (LPP) and train timetabling problem (TTP) are two key issues at the strategic level and tactical level, laying the foundation of a high-level service quality for railway operation. In this paper, a multi-frequency LPP (MF-LPP) model and a multi-period TTP (MP-TTP) model are introduced for direct connections, with consideration of both periodic and aperiodic nature to meet strongly heterogeneous train services and reduce the capacity loss of train operating companies. A combined LPP and TTP method is designed considering timetable robustness, timetable regularity, and passenger travel time. For a given line pool, a multi-objective mixed integer linear programming model for the MF-LPP is formulated to obtain a line plan with multiple line frequencies by minimizing travel time, empty-seat-hour and the number of lines. Using the acquired line plan from the previous step, a MP-TTP model is proposed to achieve the minimal travel time, the maximal timetable robustness and the minimal number of overtakings. The two models work iteratively with designed feedback constraints to find a better plan for the rail transport system. Numerical experiments are applied to verify the performance of the proposed model and solution approach.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 11 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological〈/p〉 〈p〉Author(s): Xiaolei Wang, Wei Liu, Hai Yang, Dan Wang, Jieping Ye〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉In today's world, massive on-demand mobility requests are dispatched every hour on ride-sourcing platforms, however, customers later cancel quite a number of these confirmed orders. This paper makes the first attempt to look into this customer confirmed-order cancellation behaviour based on a two-month, hourly average dataset of Didi Express in Shanghai provided by Didi Chuxing. The mean ride distance and pick-up distance of cancelled orders are observed to be obviously longer than those of completed orders of the same time period, reflecting an obvious impact of travel cost on customer decisions of order cancellation. However, the correlation between the mean customer confirmed-order cancellation rate (COCR) and the mean customer waiting time for pick-up of cancelled orders is significantly negative. Shanghai, like many other cities around the world, has coupled ride-sourcing and taxi markets, and as such, this counter-intuitive phenomenon can be explained as an outcome of the lower (higher) chance of meeting vacant taxis while waiting for pick-up during peak (non-peak) hours. We formulate COCR as a function of customer waiting time for ride-sourcing vehicles and cruising taxis, the penalty strategy by the platform for cancellation of confirmed orders, and customers’ own characteristics (i.e., ride distance, value of time, perceived psychological cost of order cancellation, additional safety concern over ride-sourcing), and propose a system of nonlinear equations to depict the complex interactions between the ride-sourcing and taxi markets considering the probability of ride-sourcing cancellation after order confirmation. With the proposed model, we replicate the observed lower COCR under a higher demand rate and longer waiting time for pick-up through numerical examples, and highlight the potential improvement of platform profit that can be achieved by appropriately designed penalty/compensation strategies.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 10 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological〈/p〉 〈p〉Author(s): Michiel C.J. Bliemer, S. Travis Waller, Michael G.H. Bell, Mark D. Hickman〈/p〉

Description: 〈p〉Publication date: Available online 4 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological〈/p〉 〈p〉Author(s): Guido Cantelmo, Moeid Qurashi, A. Arun Prakash, Constantinos Antoniou, Francesco Viti〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Time-dependent Origin–Destination (OD) demand flows are fundamental inputs for Dynamic Traffic Assignment (DTA) systems and real-time traffic management. This work introduces a novel state-space framework to estimate these demand flows in an online context. Specifically, we propose to explicitly include trip-chaining behavior within the state-space formulation, which is solved using the well-established Kalman Filtering technique. While existing works already consider structural information and recursive behavior within the online demand estimation problem, this information has been always considered at the OD level. In this study, we introduce this structural information by explicitly representing trip-chaining within the estimation framework. The advantage is twofold. First, all trips belonging to the same tour can be jointly calibrated. Second, given the estimation during a certain time interval, a prediction of the structural deviation over the whole day can be obtained without the need to run additional simulations. The effectiveness of the proposed methodology is demonstrated first on a toy network and then on a large real-world network. Results show that the model improves the prediction performance with respect to a conventional Kalman Filtering approach. We also show that, on the basis of the estimation of the morning commute, the model can be used to predict the evening commute without need of running additional simulations.〈/p〉〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 126〈/p〉 〈p〉Author(s): Seyed Shahab Mofidi, Jennifer A. Pazour〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉This paper proposes and evaluates a new hierarchical approach to peer-to-peer logistics platforms, recasting the platform’s role as one providing personalized menus of requests to freelance suppliers. A bilevel optimization formulation explicitly models the two stage decision process: first, the platform determines which set of requests to recommend to which suppliers, and second, suppliers have a choice to select which request (if any) to fulfill. By harnessing the problem’s structure, the computationally expensive mixed-integer linear bilevel problem is transformed into an equivalent single-level problem that is computationally superior. A computational study based on ride-sharing quantifies the value of providing suppliers with choices. When a platform’s knowledge of suppliers’ selections is imperfect, our hierarchical approach outperforms existing recommendation methods, namely, centralized, many-to-many stable matching, and decentralized approaches. We show that a platform’s lack of knowledge over suppliers’ selections can be compensated by providing choices in environments with either inflexible suppliers or when suppliers’ utilities have higher variance than the platform’s utilities. In these environments, providing choices and recommending alternatives to more than one supplier can be beneficial to not only the platform, but also freelance suppliers and demand requests.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 4 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological〈/p〉 〈p〉Author(s): Zhiwei Chen, Xiaopeng Li, Xuesong Zhou〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Time-varying capacity design holds an opportunity to reduce the energy consumption of urban mass transit systems, e.g., urban rail transits, bus rapid transits, modular autonomous vehicles. In this paper, we investigate the joint design of dispatch headway and vehicle capacity for one to one shuttle systems with oversaturated traffic to achieve the optimal tradeoff between general vehicle dispatching cost (mainly comprised of vehicle energy consumption) and customer waiting cost. We propose a continuum approximation model from a macroscopic point of view to reveal fundamental analytical insights into the optimal design. By introducing the concept of a preferred virtual arrival demand curve at the origin station, we prove that the investigated problem with possibly oversaturated traffic can be equivalently solved with a simpler revised problem where only unsaturated traffic is present. With this property, we decompose the original problem into a set of independent unit-time revised unsaturated problems that can be analytically solved in each neighborhood across the operational horizon. With two sets of numerical experiments, we show that the CA model offers near-optimum solutions with negligible errors very efficiently and we also verify the theoretical properties. Also, the effectiveness of time-varying vehicle capacity design is demonstrated in shuttle systems under both saturated and unsaturated traffic. Overall, the proposed CA model contributes to the CA methodology literature by extending the CA method for traditional transit dispatching problems with unsaturated traffic to the joint design of dispatch headway and vehicle capacity considering oversaturated traffic, adjustable vehicle capacities and other factors (e.g. minimum dispatch headway).〈/p〉〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 127〈/p〉 〈p〉Author(s): J. Zhang, M. Meng, David, Z.W. Wang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉To achieve bike relocation〈sup〉1〈/sup〉 through travellers’ spontaneous behaviour in dockless bike sharing systems, an innovative dynamic pricing scheme with negative prices is introduced. In normal situation, users pay a positive price to operators for using a bike. However, when imbalanced distribution of bikes occurs in the system, users who cycle from the oversupplied area to undersupplied area will receive monetary reward from the operator, i.e., negative pricing applies. A user equilibrium dynamic traffic assignment model is developed to capture travellers’ mode-path choice behaviour in response to the proposed dynamic pricing strategy. Travellers can either use a single transportation mode (e.g. walking, cycling and bus) or take multiple modes to complete their trips. The user equilibrium travel pattern is formulated as a variational inequality problem and then solved by a path-flow swapping algorithm. Two numerical examples are conducted to demonstrate that the proposed dynamic pricing strategy with negative prices is effective in terms of attracting users as well as achieving a more balanced bike repositioning, especially when the number of bikes provided in the system is limited.〈/p〉〈/div〉

Description: 〈p〉Publication date: September 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 127〈/p〉 〈p〉Author(s): Yue Bao, Erik T. Verhoef, Paul Koster〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Tradable credit schemes offer a potentially efficient, revenue-neutral policy alternative to classical dynamic pricing of congestion externalities. We show in this paper that the resulting equilibrium may not be unique for particular models of congestion, including the first-best solution for the conventional Vickrey's bottleneck model. This can have substantial detrimental impacts on social welfare and social acceptance of tradable credit schemes. The reason underlying this result is that the credit supply-demand condition can be satisfied for a continuum of credit prices. This is because any marginal change in the credit price will be matched by a compensating change in queuing times, keeping user price fixed but deviating from the first-best optimum in which no queueing should occur. We find that the problem of non-uniqueness does not occur for the dynamic flow congestion model proposed by Chu. A unique equilibrium can be obtained in the bottleneck model if the buying and selling of credits with a bank is allowed, against a pre-determined price. Credits are then still tradable so that the use can deviate from the initial distribution, but the credit price is determined by the perfectly elastic demand and supply from the bank.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 13 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological〈/p〉 〈p〉Author(s): Mehdi Nourinejad, Mohsen Ramezani〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Ride-sourcing is a prominent transportation mode because of its cost-effectiveness and convenience. It provides an on-demand mobility platform that acts as a two-sided market by matching riders with drivers. The conventional models of ride-sourcing systems are equilibrium-based, discrete, and suitable for strategic decisions. This steady-state approach is not suitable for operational decision-making where there is noticeable variation in the state of the system, denying the market enough time to balance back into equilibrium. We introduce a dynamic non-equilibrium ride-sourcing model that tracks the time-varying number of riders, vacant ride-sourcing vehicles, and occupied ride-sourcing vehicles. The drivers are modeled as earning-sensitive, independent contractor, and self-scheduling and the riders are considered price- and quality of service-sensitive such that the supply and demand of the ride-sourcing market are endogenously dependent on (i) the fare requested from the riders and the wage paid to the drivers and (ii) the rider’s waiting time and driver’s cruising time. The model enables investigating how the dynamic wage and fare set by the ride-sourcing service provider affect supply, demand, and states of the market such as average waiting and search time especially when drivers can freely choose their work shifts. Furthermore, we propose a controller based on the model predictive control approach to maximize the service provider’s profit by controlling the fare requested from riders and the wage offered to drivers to satisfy a certain quality of market performance. We assess three pricing strategies where the fare and wage are (i) time-varying and unconstrained, (ii) time-varying and constrained so that the fare is higher than the wage such that the instantaneous profit is positive, and (iii) time-invariant and fixed. The proposed model and controller enable the ride-sourcing service provider to offer a wage to the drivers that is higher than the fare requested from the riders. The result demonstrates that this myopic loss can potentially lead to higher overall profit when customer demand (i.e., riders who may opt to use the ride-sourcing system) increases while the supply of ride-sourcing vehicles decreases simultaneously.〈/p〉〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 126〈/p〉 〈p〉Author(s): Wai Wong, Shengyin Shen, Yan Zhao, Henry X. Liu〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉With more connected vehicles (CVs) in the networks, the big data era leads to the availability of abundant data from CVs. CV penetration rate is the fundamental building block of tremendous applications, such as traffic data estimation, CV-based adaptive signal control and origin-destination estimation. While CV penetration rate is a random variable unknown in nature, the current estimation method of penetration rate mainly relies on two sources of data —detector and CV data. Penetration rate across the link is computed as CV flow divided by all traffic flow over a certain period of time. However, the current method is constrained by availability and quality of detector data. This paper proposes a simple, analytical, non-parametric, and most importantly, unbiased single-source data penetration rate (SSDPR) estimation method for estimating penetration rate solely based on CV data. It subtly and simultaneously fuses two estimation mechanisms—(1) the measurement of the probability of the first vehicle in a queue being a CV and (2) the direct estimation of the penetration rate of a sample queue—to constitute a single estimator to handle all the possible sample queue patterns. Applicability of the proposed method is not confined to a specific arrival pattern. It solely utilizes the number of the observed CVs and the number of vehicles before the last observed CV in a sample queue. Combining with bridging the queue algorithm, the proposed SSDPR estimation method is extended to overflow or oversaturated conditions. Simulation results show that the proposed method is able to accurately estimate penetration rate as low as 0.1% for all the situations considered. To illustrate the applicability of the proposed method, a case study of fundamental diagram estimation of a link without being installed with any detector is presented.〈/p〉〈/div〉

Description: 〈p〉Publication date: Available online 13 June 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological〈/p〉 〈p〉Author(s): Takamasa Iryo, Michael J. Smith, David Watling〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Stability of equilibria in transport systems has been discussed for decades. Even in deterministic cases, where stochasticity is ignored, stability is not a general property; a counterexample has been found in (within-day) dynamic traffic assignment problems. Instability can be a source of uncertainty of travel time and although pricing may stabilise an unstable transport system, pricing is not always acceptable to the public. This study aims to develop a pricing strategy that stabilises a transport system 〈em〉with minimum tolls〈/em〉. We show that with our stabilising pricing system tolls are bounded above and converge to zero when the error in estimation of a no-toll equilibrium converges to zero. We then show that the proposed toll scheme stabilises a wide range of evolutionary dynamics. We also propose a heuristic procedure to minimise the toll level. The procedure can also be viewed as a method of finding a possibly unstable equilibrium solution of a transport system. This suggests that, while we have not provided a rigorous proof, we may be able to find an equilibrium solution of any transport problem including problems which arise in dynamic traffic assignment (DTA); in these DTA cases, how to construct a solution algorithm that always converges to an equilibrium solution is still an open question. The methods proposed here will be extended so that they apply in more realistic behavioural settings in future work.〈/p〉〈/div〉

Description: 〈p〉Publication date: July 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 125〈/p〉 〈p〉Author(s): 〈/p〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 126〈/p〉 〈p〉Author(s): Antoine Petit, Chao Lei, Yanfeng Ouyang〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉Traditional bus bunching control methods (e.g., adding slack to schedules, adapting cruising speed), in one way or another, trade commercial speed for better system stability and, as a result, may impose the burden of additional travel time on passengers. Recently, a dynamic bus substitution strategy, where standby buses are dispatched to take over service from late/early buses, was proposed as an attempt to enhance system reliability without sacrificing too much passenger experience. This paper further studies this substitution strategy in the context of multiple bus lines under either time-independent or time-varying settings. In the latter scenario, the fleet of standby buses can be dynamically utilized to save on opportunity costs. We model the agency’s substitution decisions and retired bus repositioning decisions as a stochastic dynamic program so as to obtain the optimal policy that minimizes the system-wide costs. Numerical results show that the dynamic substitution strategy can benefit from the “economies of scale” by pooling the standby fleet across lines, and there are also benefits from dynamic fleet management when transit demand varies over time. Numerical examples are presented to illustrate the applicability and advantage of the proposed strategy. The substitution strategy not only holds the promise to outperform traditional holding methods in terms of reducing passenger costs, they also can be used to complement other methods to better control very unstable systems.〈/p〉〈/div〉

Description: 〈p〉Publication date: August 2019〈/p〉 〈p〉〈b〉Source:〈/b〉 Transportation Research Part B: Methodological, Volume 126〈/p〉 〈p〉Author(s): Takamasa Iryo, David Watling〈/p〉 〈h5〉Abstract〈/h5〉 〈div〉〈p〉It is well known that uniqueness and stability are guaranteed properties of traffic equilibria in static user-equilibrium traffic assignment problems, if the link travel utilities are assumed to be strictly monotonically decreasing with respect to the link traffic volumes. However, these preferable properties may not necessarily hold in a wide range of transport problems with complex interactions, e.g. asymmetric interactions (including dynamic traffic assignment), social interactions, or with economies of scale. This study aims to investigate such solution properties of transport models with complex interactions between users. Generic formulations of models are considered in this study, both for utility functions and for the evolutionary dynamics relevant to the stability analysis. Such an analysis for a generic formulation is mathematically challenging due to the potential non-differentiability of the dynamical system, precluding the application of standard analyses for smooth systems. To address this issue, this study proposes a transport system with two alternatives and two user groups. While it is a simple model whose dynamics can be depicted on a plane, it also includes the core components of transport models, i.e. multiple choices and user-classes. This study classifies all possible formulations into nine cases with respect to the signs (i.e. positive or negative) of interactions between users. Then, the evolutionary dynamics of each case is mathematically analysed to examine stability of equilibria. Finally, the solution properties of each case is revealed. Multiple equilibria exist in many cases. In addition, cases with no stable equilibrium are also found, yet even in such cases we are able to characterise the circumstances in which the different kinds of unstable behaviour may arise.〈/p〉〈/div〉