Article
Transportation Science & Technology
Bangyang Wei, Xiang Zhang, Wei Liu, Meead Saberi, S. Travis Waller
Summary: This study investigates the road capacity allocation scheme and step tolling-rewarding scheme for carpooling. The proposed capacity allocation schemes reserve road service capacity during designated time windows for specific carpooling vehicles, and the study models the potential braking or tactical waiting behavior due to temporal changes of right-of-way under the capacity allocation schemes. By integrating the step tolling-rewarding scheme with the capacity allocation scheme, the study manages the carpooling choices and reduces total system cost. Numerical studies are presented to illustrate the analytical results. The findings suggest that carpooling should not be rewarded in some occasions to improve system efficiency.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Engineering, Civil
Ling-Ling Xiao, Tian-Liang Liu, Hai-Jun Huang
Summary: This study proposes two tradable parking permit schemes for managing morning commute with different modes of transportation. The research finds that the prices of parking permits decrease as parking supply decreases, with solo drivers paying more than carpoolers. Additionally, a tradable undifferentiated parking permit scheme with uniform price is more efficient than a tradable differentiated scheme, but it significantly changes the permit-holding order when parking supply is low.
Article
Economics
Zhe-Yi Tang, Li-Jun Tian, David Z. W. Wang
Summary: This study examines the impacts of shared autonomous vehicles on urban mobility and parking availability, and analyzes how to regulate the market in the presence of parking space constraints. It provides analytical propositions and numerical examples for different market factors, deriving system optimal solutions based on transit fare levels. The results show the importance of managing parking supply and additional SAV costs in achieving system optimality.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2021)
Article
Economics
Yulan Fu, Chenlan Wang, Tian-Liang Liu, Hai-Jun Huang
Summary: This study extends the existing bottleneck model with ridesharing by involving commuters' parking competition. The equilibrium solution shows that parking density and price can significantly affect commuters' ridesharing choices and arrival times. An optimal parking density and a parking fee discount for ridesharing scheme are proposed to alleviate congestion, with potential savings of up to 50% of system costs.
RESEARCH IN TRANSPORTATION ECONOMICS
(2021)
Article
Economics
Zhihui Huang, Jiancheng Long, W. Y. Szeto, Haoxiang Liu
Summary: This paper proposes a park-and-ride-sharing (P&RS) system to manage morning peak hour congestion in a monocentric linear city. It analyzes the equilibrium ride-sharing matching patterns and traffic flow patterns, as well as designs parking charge schemes to minimize total system cost (TSC) under government management of all parking lots. Numerical examples are provided to illustrate the effectiveness of the proposed bottleneck model with P&RS and the designed parking charge schemes.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Article
Economics
Ling-Ling Xiao, Tian-Liang Liu, Hai-Jun Huang, Ronghui Liu
Summary: Recent studies have shown that appropriate spatial allocation of bottleneck capacity can reduce total trip costs, but the effectiveness of temporal allocation is still unclear. This paper investigates the impacts of temporal and temporal-spatial bottleneck capacity allocation on morning commute patterns, finding that optimal capacity allocations depend on accurate estimation of commuters' extra carpool costs.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
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
Transportation
Mehdi Nourinejad, Mahyar Amirgholy
Summary: This paper investigates the impact of autonomous vehicles on parking behavior and proposes parking pricing strategies and supply design schemes for system optimization.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2022)
Article
Green & Sustainable Science & Technology
Zipeng Zhang, Ning Zhang
Summary: This paper extends Vickrey's point-queue model to study ridesharing behavior during a morning commute with uncertain bottleneck location, finding two congestion cases and four dynamic departure patterns. Results suggest that the dynamic property of the mixed commuters equilibrium varies with endogenous penetration rates and schedule differences between pickup and work.
Article
Green & Sustainable Science & Technology
Zipeng Zhang, Ning Zhang
Summary: This paper extends Vickrey's model to study the early bird parking mechanism during morning commute peak hours, analyzing how commuters choose departure times and conditions for user equilibrium. The results show that fare incentives are more effective in reducing queues, and adjusting parking pricing gaps can increase incremental parking revenue.
Article
Operations Research & Management Science
Dongdong He, Yang Liu, Qiuyan Zhong, David Z. W. Wang
Summary: This paper examines the impact of staggering policy on traffic congestion and social welfare in the morning commute problem with both household commuters and individual commuters. The results show that optimizing the schedule gap between work and school start times can significantly improve social welfare. A Pareto frontier is derived to provide policymakers with an optimal staggering policy for system performance. Furthermore, the capacity expansion paradox is re-examined, and it is found that expanding the capacity at the downstream bottleneck can reduce the total system cost.
TRANSPORTATION SCIENCE
(2022)
Article
Operations Research & Management Science
Wei Wu, Wei Liu, Fangni Zhang, Vinayak Dixit
Summary: A new flexible parking reservation scheme is proposed in this study, allowing commuters to retain their reservation by paying additional fees if they arrive later than the expiration time. Comparing to existing literature, the proposed scheme is more practical and can further reduce total social cost. The efficiency gain of the proposed scheme is also quantified analytically and numerically.
NETWORKS & SPATIAL ECONOMICS
(2021)
Article
Social Sciences, Interdisciplinary
Zhanzhi Liao, Jian Wang, Yuanyuan Li, Xiaowei Hu
Summary: This study investigates the morning commute problem and proposes a joint decision-making framework for morning commuters regarding departure time and parking choices in order to alleviate traffic congestion and improve social welfare. The integration of a time-varying tradable credit scheme is explored to further enhance the efficiency of the system.
Article
Economics
Xiao Han, Yun Yu, Zi-You Gao, H. Michael Zhang
Summary: This paper examines the impact of uncertainty on transportation systems and travel costs, as well as the welfare effects of providing travel information in different scenarios. The results show that providing accurate information can improve welfare under certain traffic conditions, but may reduce welfare in specific situations. Factors such as the correlation between traffic conditions, frequency and severity of bottleneck drops, and the relationship between free-flow travel time and bottleneck capacity significantly affect the welfare effects of providing pre-trip information.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Article
Economics
Xiang Zhang, Wei Liu, Michael Levin, S. Travis Waller
Summary: This study investigates the morning commuting and parking patterns of autonomous vehicles (AVs) under different spatial road capacity allocation schemes. The study analyzes equilibrium departure/arrival and parking patterns for AVs subject to spatial road capacity allocation. The study also examines optimal capacity allocation strategies under both user equilibrium and system optimum AV traffic patterns to minimize the total system travel cost.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2023)
Article
Transportation
Guangming Xu, Yanqin Chen, Wei Liu
Summary: This article proposes a multi-objective bi-level model that jointly optimizes the locations of Park-and-Ride facilities and the Alternate Traffic Restriction (ATR) scheme to address traffic congestion. The proposed model is solved using a non-dominated sorting genetic algorithm and a gradient project algorithm.
TRANSPORTMETRICA A-TRANSPORT SCIENCE
(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
Zhenwei Gong, Fangni Zhang, Wei Liu, Daniel J. Graham
Summary: This paper investigates the effect of airport expansion on air traffic and its implications on airport congestion, airline competition, and social welfare under various administrative regimes, airline market structures, and passenger demand patterns. The analysis suggests that airport capacity expansion may lead to over-scheduled flights and increased congestion, especially in less competitive airline markets. Furthermore, the objective of the airport operator (i.e., profit-maximization, social welfare-maximization, or budget-constrained social welfare-maximization) affects the likelihood of congestion. Market power in airlines allows them to internalize a portion of airport congestion, while leader airlines with knowledge of follower responses manipulate airfare to maximize profits. Additionally, increasing airport charges always reduce aggregate traffic volume under different market structures and fixed airport capacity.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2023)
Article
Economics
Haoning Xi, Wei Liu, S. Travis Waller, David A. Hensher, Philip Kilby, David Rey
Summary: In the context of Mobility-as-a-Service (MaaS), the transportation sector is shifting towards user-centric business models that prioritize user experience and customized mobility solutions. This study proposes an auction-based mechanism and optimization models for the demand-side management of MaaS systems. The mechanism allows users to bid for mobility services based on their willingness to pay and experience-related preferences, and the optimization models aim to maximize social welfare by optimally allocating mobility resources in real-time. Extensive simulations using realistic mobility data demonstrate the benefits of the proposed mechanism.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2023)
Article
Environmental Studies
Bangyang Wei, Bo Du, Meead Saberi, S. Travis Waller, Wei Liu
Summary: This study investigates the strategy of allocating road space as parking for electric ride-sourcing vehicles (ERVs) to reduce cruising. The results show that providing parking increases ride-sourcing demand, reduces charging demand, and increases profit and social welfare.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2023)
Article
Economics
Xiang Zhang, Wei Liu, Michael Levin, S. Travis Waller
Summary: This study investigates the morning commuting and parking patterns of autonomous vehicles (AVs) under different spatial road capacity allocation schemes. The study analyzes equilibrium departure/arrival and parking patterns for AVs subject to spatial road capacity allocation. The study also examines optimal capacity allocation strategies under both user equilibrium and system optimum AV traffic patterns to minimize the total system travel cost.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2023)
Review
Transportation
Can Li, Lei Bai, Lina Yao, S. Travis Waller, Wei Liu
Summary: Transportation is crucial for the economy and urban development, but it faces challenges in terms of efficiency, sustainability, resilience, and intelligence. Reinforcement Learning (RL) has emerged as a useful approach for smart transportation applications, allowing autonomous decision-makers to learn from experiences and make optimal actions in complex environments. This paper conducts a bibliometric analysis to understand the development of RL-based methods in transportation applications and provides a comprehensive literature review on the specific topics. Future research directions for RL applications and developments are also discussed.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Economics
Mingyou Ma, Yuhui Chen, Wei Liu, S. Travis Waller
Summary: This paper proposes a bi-level model to explore mode choice and operation decisions in a multi-modal transportation system. The model considers heterogeneity in travelers' value of time and compares deterministic user equilibrium and stochastic user equilibrium. The two operators optimize their decisions based on the equilibrium and aim to maximize profit or minimize system cost. Results show that the SUE model provides a more conservative estimate and that appropriate operation decisions can reduce system cost and increase the ride-sourcing company's profit. Sensitivity analysis suggests dispatching more vehicles to remote areas to improve service quality.
Article
Computer Science, Interdisciplinary Applications
Guangming Xu, Jing Guo, Linhuan Zhong, Fangni Zhang, Wei Liu
Summary: This study investigates the potential of implementing express delivery services on the high-speed railway with specified time windows and optimizes the train capacity allocation scheme to maximize profit. It proposes an integer linear programming model and a two-stage stochastic programming model to handle deterministic and stochastic demand cases respectively. The method's effectiveness is demonstrated through applications on small and actual high-speed railway networks.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Transportation Science & Technology
Zhuoye Zhang, Wei Liu, Fangni Zhang
Summary: This paper investigates the joint network equilibrium of parking and travel route choices in the future mobility paradigm with mixed traffic of private and shared autonomous vehicles. A bi-level model is developed to optimize the OD-SAV service fare and flow. The joint equilibrium of travel and parking can be modeled as a Variational Inequalities problem.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Transportation Science & Technology
Mingyou Ma, Fangni Zhang, Wei Liu, Vinayak Dixit
Summary: This paper presents a model of a public transit system that combines passenger and urban freight services, known as urban co-modality, and examines the overall impacts of co-modality on existing urban freight forwarding, carrier, and transit services. The analysis considers a system with one transit operator, one freight forwarder, and one freight carrier, and determines the conditions under which co-modal operations can benefit all three operators as well as freight customers and passengers. The results show that in a non-cooperative setting, the freight carrier may experience profit loss due to reduced allocation of freight units, while the freight forwarder and transit operator can benefit from co-modality. Furthermore, achieving a Pareto-improving co-modal system requires the operators to reduce service fares and co-modal transportation prices.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Economics
Guangming Xu, Yihan Liu, Yihan Gao, Wei Liu
Summary: This paper examines the integrated optimization of train stopping plan and seat allocation scheme in railway systems, and proposes a mathematical model and solution approach using mixed-integer linear programming to maximize the system net benefit.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2023)
Article
Transportation
Ali Najmi, Travis Waller, Wei Liu, Taha H. Rashidi
Summary: This paper proposes a mobility system that combines ridesharing and an Activity Travel Pattern (ATP) generator to enhance participants' mobility experiences. It improves ridesharing systems and explores the relationship between ridesharing and participants' ATPs. Numerical examples show that incorporating ATP-based announcements increases match rates and attractiveness of ridesharing. ATP-based participants play a significant role in finding matches and saving distance. The study highlights the importance of tour gyration in ridesharing system performance and encourages participants with distant activities to join as ATP-based participants.
TRANSPORTMETRICA A-TRANSPORT SCIENCE
(2023)
Article
Transportation Science & Technology
Bolong Zhou, Wei Liu, Hai Yang
Summary: This study examines the multi-depot location-routing problems of unmanned aerial vehicles (UAVs) for urban monitoring (MDLRP-UM). The proposed solution method combines an iterative algorithm with a tailored adaptive large neighborhood search (ALNS) based heuristic algorithm to solve the master and sub-problems, resulting in an efficient and effective approach for solving MDLRP-UM.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Engineering, Civil
Wenbo Sun, Fangni Zhang, Wei Liu, Qingying He
Summary: This paper investigates the potential of improving overall traffic and energy efficiency by controlling a proportion of connected and autonomous vehicles (CAVs) in a mixed traffic corridor. The proposed control framework shows promising results in numerical studies, demonstrating its effectiveness in improving road throughput.
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)
