Article
Economics
Peng-Cheng Xu, Qing-Chang Lu, Chi Xie, Taesu Cheong
Summary: This study investigates the resilience evaluation of interdependent networks. A model is developed to quantify the impacts of network interdependency on the resilience of interdependent transit networks, considering interdependency relations, network topology, flow characteristics, and demand distribution. The model is applied to the metro and bus networks of Xi'an, China. Results show that node degree heterogeneity in topology, bidirectional function dependency among networks, and flow matching between networks are important factors influencing network resilience.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2024)
Article
Economics
Xingxing Fu, Dea van Lierop, Dick Ettema
Summary: This study investigates the relationship between multimodality and perceived transport adequacy and accessibility. The results show that multimodality is burdensome, especially for car-dependent individuals, and leads to lower perceived achievement or accessibility for those with limited access to a car.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(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
Economics
Henrik Johansson Rehn, Lars E. Olsson, Margareta Friman
Summary: This paper presents the Framework of RoUtIne Transitions in daily travel (FRUIT), which analyzes the impact of life events on travel behavior changes and identifies the critical phases in this process. By integrating theories and concepts, the framework provides a theoretical basis for interventions aimed at improving sustainable travel. The applicability of FRUIT is illustrated through an empirical case, and the implications for future research and policy are discussed.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2024)
Article
Economics
Valeria Bernardo, Xavier Fageda, Jordi Teixido
Summary: The study finds that flight ticket taxes have a significant impact on low-cost airlines' supply and carbon emissions, resulting in a decrease of 12% in the number of flights and a 14% reduction in carbon emissions. Additionally, the burden of the taxes is higher for passengers paying low fares, affecting avoidable flights more significantly.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(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
Economics
Songyot Kitthamkesorn, Anthony Chen, Seungkyu Ryu, Sathaporn Opasanon
Summary: The study introduces a new mathematical model to determine the optimal location of park-and-ride facilities, addressing the limitations of traditional models and considering factors such as route similarity and user heterogeneity.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(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
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
Economics
Jeppe Rich, James Fox
Summary: Many transport models allocate all costs to the car driver without considering the cost sharing among passengers. This paper questions this premise and argues that cost sharing can occur in various forms, which should be properly accounted for in transport models. The empirical evidence from Denmark suggests that not accounting for cost sharing may result in biased cost elasticities and occupancy rates.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2024)
Article
Economics
Jorik Grolle, Barth Donners, Jan Anne Annema, Mark Duinkerken, Oded Cats
Summary: High-speed rail is considered a promising alternative for long-distance travel, but the current state of the European HSR network is poorly connected. This study presents a customized version of network design and frequency setting problem for HSR, and analyzes the performance under various policies and design variables. The results show that considering externalities leads to more extensive networks and mode shifts, but requires high public investments. The importance of network integration and cross-border cooperation is highlighted. The findings aim to contribute to the design of an attractive and competitive European HSR network.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2024)
Article
Economics
Mounisai Siddartha Middela, Gitakrishnan Ramadurai
Summary: This study addresses the research gaps in understanding the effect of regression models, measurement period, and spatial dependence on Freight Trip Generation (FTG) modeling and freight-related policies. The results show that the spatial Zero-Inflated Negative Binomial (ZINB) model is the best for daily and weekly Freight Trip Production (FTP), while the non-spatial Negative Binomial (NB) model is the best for daily and weekly Freight Trip Attraction (FTA). The study also highlights the importance of considering spatial dependence and using count models with a week as the measurement period.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(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)
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
Hao Chen, Xi Zhang, Wenyan Yang, Yiwei Lin
Summary: This paper systematically investigates pedestrian trajectory prediction through a data-driven stacking fusion approach. The proposed Att-LSTM and MSFM models outperform existing methods in terms of pedestrian trajectory prediction. The results show that the stacking fusion model has great feasibility for improving pedestrian safety and traffic efficiency in autonomous vehicles.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Tao Jia, Chenxi Cai
Summary: This paper proposes a novel attention-based spatiotemporal deep learning model for predicting short-term turning traffic flow in the city. Experimental results show that the model outperforms current state-of-the-art models in estimating turning traffic flow.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Yueyi Han, Congcong Bai, Sheng Jin, Rujie Wang, Dongfang Ma
Summary: In this paper, a novel two-lane car-following model is proposed, considering the driver's visual effect. The driver's behavior changes are directly simulated based on visual information, and an improved time-to-collision (TTC) calculation is introduced. The model is formulated using the optimal velocity model framework, and its stability is analyzed through theoretical analysis and numerical simulation. The proposed model is validated and calibrated using NGSIM trajectory data, showing better fitting effect compared to other models. The findings of this study can contribute to the design of control strategies for future intelligent connected vehicles in multi-lane environments.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Hao Hu, Xiang Li, Minghu Ha, Xiaosheng Wang, Changjing Shang, Qiang Shen
Summary: Reasonable transportation risk models are important for the green reform of the hazardous material logistics industry. To address the shortcomings of existing models, two novel two-stage programming models are developed that consider weight variety in risk measures. Experimental investigations show that the proposed models achieve a good balance between overall risk and local risk.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
Mingyang Li, Jinjun Tang, Jie Zeng, Helai Huang
Summary: Flex-route transit, as a promising transportation mode in low-demand areas, has received considerable attention in the transportation research field. However, the reliability and development of flex-route transit services are affected by unexpectedly high demand levels caused by travel uncertainty. This study proposes a Kriging-based global optimization method using a Pareto-based multipoint sampling strategy to solve the problem of meeting point location selection, which substantially influences the performance of the meeting point strategy. The optimization results using a real-life flex-route transit service show that the proposed algorithm can improve the performance of flex-route transit services under unexpectedly high demand levels.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Transportation
JuYeong Lee, JiIn Kwak, YongKyung Oh, Sungil Kim
Summary: Traffic incidents have a common impact on urban traffic networks, but predicting their effects is challenging due to network complexity and the dynamic characteristics of traffic data. In this study, we developed a novel method to quantify the impacts of traffic incidents and identify influential features that affect individual incidents.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
