Article
Economics
Tongfei Li, Min Xu, Huijun Sun, Jie Xiong, Xueping Dou
Summary: In this study, a generalized stochastic user equilibrium model is developed to analyze travelers' mode and route choice behavior in urban traffic systems with ridesharing programs. The proposed model considers travelers' heterogeneity in terms of car ownership and value of time, and their limited perceived information based on the stochastic user equilibrium principle. The decision-making problem of ridesharing compensation is also addressed, aiming to minimize total travel cost and vehicular air pollution emissions. A bi-objective optimization model and two single-objective optimization models are proposed, and a genetic algorithm is used to generate Pareto-optimal solutions. Numerical experiments demonstrate the effectiveness of the proposed model and algorithm in mitigating traffic congestion and pollution emissions.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2023)
Article
Economics
Xiaolei Wang, Jun Wang, Lei Guo, Wei Liu, Xiaoning Zhang
Summary: A new modeling approach for ridesharing user equilibrium (RUE) was proposed, which transforms the problem into a convex programming problem by redefining feasible driver trajectories and ridesharing market equilibrium conditions. The algorithm effectively avoids path enumeration and can be implemented on large networks, with theoretical analysis and numerical demonstrations on the impact of problem size on computational efficiency.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Article
Engineering, Electrical & Electronic
Chao Sun, Haodong Jing, Taolue Chen, Menghui Li, Peng Zhang
Summary: In this paper, a traffic assignment algorithm called the route-based incremental equilibrium assignment (IEA) method is proposed to achieve a less complex methodology and implementation than current algorithms. The IEA method iteratively performs incremental assignment and new origin-destination (O-D) demand extraction. It is further extended to solve the stochastic user equilibrium (SUE) and reliability-based user equilibrium (RUE) models, demonstrating its effectiveness.
IET INTELLIGENT TRANSPORT SYSTEMS
(2023)
Article
Economics
Ruqing Huang, Lee D. Han, Zhongxiang Huang
Summary: This paper presents an unconventional equilibrium flow model to analyze travelers' route choice behavior, using path residual capacity as the quantity signal. The proposed model and solution algorithm are shown to be feasible and effective, and can capture route choice behaviors that have not been modeled in previous studies.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Computer Science, Interdisciplinary Applications
Haoning Xi, Yili Tang, S. Travis Waller, Amer Shalaby
Summary: Mobility-as-a-Service (MaaS) is an emerging business model that integrates various travel modes into a single on-demand mobility service. This study proposes a MaaS ecosystem that provides both mobility and instant delivery services by sharing the same multimodal transport system. A bilaterial surcharge-reward scheme (BSRS) is introduced to manage the integrated mobility and delivery demand, and a solution algorithm is developed to optimize the system equilibrium costs.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(2023)
Article
Management
Muqing Du, Heqing Tan, Anthony Chen
Summary: This paper explores a novel step size determination scheme, the Barzilai-Borwein step size, and applies it to solving the stochastic user equilibrium problem. Experimental results demonstrate that the BB step size outperforms current step size strategies in terms of computational efficiency and robustness.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Sam O'Neill, Ovidiu Bagdasar, Stuart Berry, Nicolae Popovici, Ramachandran Raja
Summary: This paper presents a method of considering multiple objectives simultaneously in selfish routing of network flow. By manipulating free parameters such as speed limits, the behavior of road users is coerced to reconcile conflicts between multiple objectives. The results show that small parameter adjustments can lead to solutions that Pareto dominate other solutions.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2022)
Article
Energy & Fuels
Ke Liu, Yanli Liu
Summary: As the number of electric vehicles (EVs) connected to the grid increases, there is a need to accurately predict the spatial-temporal distribution of EV charging load synchronized with traffic states. This paper proposes a novel method based on stochastic user equilibrium (SUE) and trip chain to achieve this prediction. The proposed method effectively reflects the charging and trip characteristics of different EV types while ensuring reachability, and accurately predicts overall and individual EV travel costs and total charging loads in detailed synchronous traffic states. The method shows stable convergence and remarkable prediction effectiveness, even during peak load hours and high EV penetration scenarios.
Article
Economics
Terry L. Friesz, Ke Han, Amir Bagherzadeh
Summary: This paper presents sufficient conditions for convergence of projection and fixed-point algorithms used to compute dynamic user equilibrium with elastic travel demand, without the need for strongly monotone increasing path delay operators. Instead, weakly monotone increasing path delay operators and strongly monotone decreasing inverse demand functions are assumed. The Lipschitz continuity of path delay is a mild regularity condition, allowing for convergence even with nonmonotone delay operators under certain conditions.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Article
Transportation
Guangchao Wang, Kebo Tong, Anthony Chen, Hang Qi, Xiangdong Xu, Shoufeng Ma
Summary: This study investigates the impacts of the least perceived travel cost on the stochastic user equilibrium problem. The Weibit SUE models with a positive location parameter reduce perception variances route-specifically and resolve the scale insensitivity issue. Numerical results confirm the analytical results and demonstrate the efficiency and robustness of the proposed solution algorithm.
TRANSPORTMETRICA A-TRANSPORT SCIENCE
(2023)
Article
Transportation Science & Technology
Nam H. Hoang, Manoj Panda, Hai L. Vu, Dong Ngoduy, Hong K. Lo
Summary: This study focuses on a transport network with two types of users, selfish and cooperative. Selfish users aim to minimize their travel time, while cooperative users aim to maximize their class's aggregate throughput or minimize their total travel time. A new framework is proposed to study the route choices and network performance of the two classes of users.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Transportation Science & Technology
Qiumin Liu, Rui Jiang, Wei Liu, Ziyou Gao
Summary: This study extends existing stochastic bottleneck model studies by considering a more general distribution of the bottleneck capacity. The results show that the mean travel cost and the mean total travel time may vary with the capacity degradation probability and level. It is also found that the mixed capacity distribution outperforms the binary capacity distribution in evaluating the departure/arrival pattern and mean travel cost.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Economics
Zhehao Huang, Hao Dong, Shuaishuai Jia
Summary: This paper formulates an equilibrium carbon price by setting up a stochastic equilibrium model, revealing the intrinsic link of carbon price to other variables and parameters. The research finds that the carbon price jumps at the deadline of the abatement period and is affected by the economic growth rate and negative effect of climate warming, leading to bifurcation phenomena. These findings are of great importance for achieving the abatement target.
Article
Transportation Science & Technology
Jinxiao Duan, Daqing Li, Hai-Jun Huang
Summary: This paper investigates the impact of route choice behavior on the reliability of traffic networks against cascading failures. A two-level cascading failure model is proposed to study the patterns of route choices during the evolution of traffic jams. The study finds that modifying travelers' route choices can improve network reliability, but stochastic perception errors of travel time or risk preferences to probabilistic travel time can decrease reliability. Additionally, recovering overload failures from failed states can enhance the reliability of traffic networks.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Economics
Fang Zhang, Jian Lu, Xiaojian Hu
Summary: This paper examines the design problem of tradable credit schemes, considering transaction costs and social equity. The equilibrium problem is formulated as a variational inequality, and a credit scheme design problem with equity constraints is proposed to maximize total social welfare. Results show that transaction costs can negatively impact travel disutility for low-VOT users, and implementing equity constraints can address inequities.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2021)
Article
Management
David Rey, Michael W. Levin, Vinayak V. Dixit
Summary: The study introduces novel online mechanisms for traffic intersection auctions where users bid for priority service. Two Markov chain models are proposed to determine the expected waiting time of participants in the auction, along with a mechanism to calculate incentive-compatible payments in the dynamic sense, maximizing social welfare in the long run. Findings suggest that the proposed online mechanisms are incentive-compatible in the dynamic sense, in contrast to static incentive-compatible mechanisms that may lead to misreporting by users.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Engineering, Civil
Wei Wu, Yang Liu, Wei Liu, Fangni Zhang, Vinayak Dixit, S. Travis Waller
Summary: Most existing studies on AIM focus on algorithms for resolving conflicts among vehicles, while this paper proposes optimizing entrance and exit lanes to improve traffic efficiency. Two methods are developed for optimizing entering time and route choices, and a heuristic approach is adopted for real-time applicability.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Industrial
Milad Haghani, Ali Behnood, Vinayak Dixit, Oscar Oviedo-Trespalacios
Summary: This study analyzes the landscape and temporal trends of road safety research in low- and middle-income countries, highlighting the disproportionate representation of road users in road trauma statistics and the lack of progress in reducing deaths compared to high-income countries. The research emphasizes the need to intensify road safety research in LMICs to generate local knowledge and develop initiatives tailored to their unique needs. Additionally, the study identifies underrepresented areas of road safety research and examines patterns of authorship and co-authorship in LMIC studies. Efforts are hoped to invigorate road safety research and promote international collaborations in this field.
Article
Economics
Mingyou Ma, Fangni Zhang, Wei Liu, Vinayak Dixit
Summary: This study conducts a game theoretical analysis of metro-integrated logistics systems (MILS) and finds that introducing MILS has the potential to improve the performance of both metro company and logistics company.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2022)
Article
Multidisciplinary Sciences
Vinayak Dixit, Sisi Jian
Summary: Drive cycles play a crucial role in energy consumption, emissions, and safety in vehicle systems. A quantum Fourier transform-based algorithm for drive cycle frequency estimation is proposed and proven to be exponentially faster than the classical Fourier transform and consistent in results. Additionally, a simple method is suggested to mitigate noise in quantum computers.
SCIENTIFIC REPORTS
(2022)
Article
Economics
Enrica Carbone, Vinayak V. Dixit, E. Elisabet Rutstrom
Summary: This study examines reactions to congestion pricing in the commercial sector using a sequential experimental game. The findings show that congestion pricing leads to commercial activities relocating, and the adjustment process is costly to merchants. Consumer choices and reactions are also influenced.
THEORY AND DECISION
(2022)
Article
Environmental Sciences
Sai Chand, Zhuolin Li, Abdulmajeed Alsultan, Vinayak V. Dixit
Summary: This study explores the impact of various factors on vehicle crash duration and frequency at a macro-level, including demographic, vehicle utilization, environmental, and responder variables, as well as street network features. The analysis of over 95,000 vehicle crash records reveals that income, driver experience, and exposure have both positive and negative effects on crash duration, and that regions with a dense road network have shorter duration but higher frequency.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2022)
Article
Geosciences, Multidisciplinary
Chence Niu, Tingting Zhang, Divya Jayakumar Nair, Vinayak Dixit, Pamela Murray-Tuite
Summary: This study analyzes the speed fluctuation of real-world networks and evaluates the quantitative relationship between resilience and graph-based metrics and link attributes. The results indicate that graph-based metrics and attributes have a high impact on network resilience, but the relevance of different metrics and attributes to link resilience is different.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2022)
Article
Transportation
Sai Chand, Zhuolin Li, Vinayak V. Dixit, S. Travis Waller
Summary: This study investigates the impact of various factors on the duration of reported vehicle breakdowns at a macro-level, finding that street network characteristics and certain socio-economic factors have significant effects on the duration of breakdowns.
INTERNATIONAL JOURNAL OF TRANSPORTATION SCIENCE AND TECHNOLOGY
(2022)
Article
Engineering, Civil
Amolika Sinha, Daniel Bassil, Sai Chand, Navreet Virdi, Vinayak Dixit
Summary: The study investigates the impact of connected automated buses in a mixed fleet with connected automated vehicles on the performance of urban transport systems. Results show that connected automated buses can significantly reduce travel time and standstill times, while also decreasing forced lane changes between vehicles and improving road safety.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Siroos Shahriari, Edward N. Robson, Jason Wang, Vinayak V. Dixit, S. Travis Waller, Taha H. Rashidi
Summary: Traditional transport models often do not account for broader changes in the economy, so there is a need for an integrated CGE and transport model to quickly assess the economic impacts of transport projects and policies.
Article
Transportation Science & Technology
Zesheng Cheng, Taha Hossein Rashidi, Sisi Jian, Mojtaba Maghrebi, Steven Travis Waller, Vinayak Dixit
Summary: This paper develops an innovative approach to estimating the actual demand at a carsharing station using carsharing records, spatio-temporal correlated variables, and emerging data sources. The paper also provides recommendations related to the operation policies of the service providers based on the analysis results.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Geosciences, Multidisciplinary
Chence Niu, Divya Jayakumar Nair, Tingting Zhang, Vinayak Dixit, Pamela Murray-Tuite
Summary: This study explores a novel graph-based connectivity index for road networks to measure the impact on global wildfire fatality events. The findings show a significant and systematic relationship between fatalities and a calibrated connectivity index across different wildfire events. This simple graph theoretic measure can assist planners in reducing vulnerability and increasing resilience in wildfire-prone areas.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2022)
Article
Engineering, Industrial
Maziar Yazdani, Mohammad Mojtahedi, Martin Loosemore, David Sanderson, Vinayak Dixit
Summary: This paper addresses the increasing frequency and severity of floods and their impact on hospitals. It proposes an innovative hospital evacuation model that combines a flood simulator and a mathematical model to facilitate optimal evacuation planning under uncertain flood conditions. The model is validated through a case study in New South Wales, Australia, and it is found to generate effective plans for hospital evacuation in the shortest time possible during flood emergencies.
Article
Engineering, Civil
Chence Niu, Sisi Jian, Divya Nair, Vinayak Dixit
Summary: Extreme events, such as disasters and severe road accidents, have become common and pose a threat to many lives. Efficient evacuation is crucial, necessitating planning and development of transport infrastructure resiliency. This study formulates a bi-level multi-objective model to optimize pre-disaster investment in the road network considering different levels of disaster damage. Using realistic speed data, the study explores the relationship between vulnerability and reliability to make informed investment decisions. The findings provide a theoretical basis for authorities to make pre-disaster road network investments.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Transportation Science & Technology
Yue Zhao, Liujiang Kang, Huijun Sun, Jianjun Wu, Nsabimana Buhigiro
Summary: This study proposes a 2-population 3-strategy evolutionary game model to address the issue of subway network operation extension. The analysis reveals that the rule of maximum total fitness ensures the priority of evolutionary equilibrium strategies, and proper adjustment minutes can enhance the effectiveness of operation extension.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Hongtao Hu, Jiao Mob, Lu Zhen
Summary: This study investigates the challenges of daily storage yard management in marine container terminals considering delayed transshipment of containers. A mixed-integer linear programming model is proposed to minimize various costs associated with transportation and yard management. The improved Benders decomposition algorithm is applied to solve the problem effectively and efficiently.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Zhandong Xu, Yiyang Peng, Guoyuan Li, Anthony Chen, Xiaobo Liu
Summary: This paper studied the impact of range anxiety among electric vehicle drivers on traffic assignment. Two types of range-constrained traffic assignment problems were defined based on discrete or continuous distributed range anxiety. Models and algorithms were proposed to solve the two types of problems. Experimental results showed the superiority of the proposed algorithm and revealed that drivers with heightened range anxiety may cause severe congestion.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Chuanjia Li, Maosi Geng, Yong Chen, Zeen Cai, Zheng Zhu, Xiqun (Michael) Chen
Summary: Understanding spatial-temporal stochasticity in shared mobility is crucial, and this study introduces the Bi-STTNP prediction model that provides probabilistic predictions and uncertainty estimations for ride-sourcing demand, outperforming conventional deep learning methods. The model captures the multivariate spatial-temporal Gaussian distribution of demand and offers comprehensive uncertainty representations.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Benjamin Coifman, Lizhe Li
Summary: This paper develops a partial trajectory method for aligning views from successive fixed cameras in order to ensure high fidelity with the actual vehicle movements. The method operates on the output of vehicle tracking to provide direct feedback and improve alignment quality. Experimental results show that this method can enhance accuracy and increase the number of vehicles in the dataset.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
Article
Transportation Science & Technology
Mohsen Dastpak, Fausto Errico, Ola Jabali, Federico Malucelli
Summary: This article discusses the problem of an Electric Vehicle (EV) finding the shortest route from an origin to a destination and proposes a problem model that considers the occupancy indicator information of charging stations. A Markov Decision Process formulation is presented to optimize the EV routing and charging policy. A reoptimization algorithm is developed to establish the sequence of charging station visits and charging amounts based on system updates. Results from a comprehensive computational study show that the proposed method significantly reduces waiting times and total trip duration.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2024)
