Article
Transportation Science & Technology
Cong Quoc Tran, Mehdi Keyvan-Ekbatani, Dong Ngoduy, David Watling
Summary: This paper discusses the possibility of wireless charging while driving and how to promote the market penetration of electric vehicles by optimizing the deployment of wireless charging lanes on the network. A multi-class dynamic system optimal model is adopted to compute an approximate representation of dynamic traffic flow, and the charging location problem is addressed through a mixed-integer linear program.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Engineering, Multidisciplinary
Lingjuan Chen, Yu Wang, Dongfang Ma
Summary: The study proposes a bounded-rational day-to-day dynamic learning and adjustment model for travellers, taking navigation information into account. By updating travellers' departure time with real-time navigation guidance and historical experience, the accuracy of route choice is improved. The model converges to a spatial-temporal oscillating equilibrium instead of a fixed-point stable status, providing insights on improving prediction accuracy of traffic state in urban street networks.
MATHEMATICAL PROBLEMS IN ENGINEERING
(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
Computer Science, Information Systems
Zhanzhong Wang, Shuoqi Wang
Summary: The research proposes a real-time dynamic route optimization model based on predictive control, which uses a unique method to obtain the optimal solution and achieves real-time dynamic route selection by switching among static shortest routes. It has good innovation and practical applications.
Article
Engineering, Civil
Markus Friedrich, Matthias Schmaus, Jonas Sauer, Tobias Zundorf
Summary: This paper investigates existing departure time models for a schedule-based transit assignment and their parametrization. It suggests using 1-minute intervals and introduces the concept of adaptation time. The study found that longer time intervals led to arbitrary run volumes, indicating the need for a nonlinear evaluation function to better describe passenger behavior.
TRANSPORTATION RESEARCH RECORD
(2021)
Article
Computer Science, Artificial Intelligence
Xiao-Cheng Liao, Wei-Neng Chen, Ya-Hui Jia, Wen-Jin Qiu
Summary: This article proposes a decentralized control approach to solve large-scale efficient dynamic traffic assignment problem. The method transforms the traffic assignment problem into a routing rule generation problem and uses a genetic programming hyper-heuristic algorithm to generate the optimal routing rule. Experimental results demonstrate the effectiveness of the method in urban-scale traffic networks.
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE
(2023)
Article
Engineering, Aerospace
Lei Yang, Jue Huang, Qi Gao, Yi Zhou, Minghua Hu, Hua Xie
Summary: This paper investigates the issue of air traffic control workload in the Free Route Airspace (FRA). A complexity indicator system is constructed and the XGBoost algorithm is used to predict the workload. A two-stage sector boundary optimization method is proposed to achieve the goal of balancing the workload.
Article
Transportation
Islam Kamel, Md Sami Hasnine, Amer Shalaby, Khandker Nurul Habib, Baher Abdulhai
Summary: This paper presents a large-scale integrated modelling framework that captures the relationships between travel mode choice, departure time choice, and route choices. A case study of replacing the current flat transit fare in the City of Toronto with a time-based transit fare structure is presented, showing the effects on transit users' behavior and transit vehicles crowdedness.
CASE STUDIES ON TRANSPORT POLICY
(2021)
Article
Automation & Control Systems
Tianyang Zhao, Haoyuan Yan, Xiaochuan Liu, Zhaohao Ding
Summary: The electrification of vehicles has strengthened the interaction between power systems and transportation systems, resulting in the formation of coupled transportation power systems (CTPSs). A novel optimal traffic power flow (OTPF) problem is proposed to analyze the spatial and temporal congestion propagation on CTPSs. This problem considers congested roads, transmission lines, and charging stations. The spatial and temporal distribution of electric vehicles (EVs) on roads and charging stations, connected by multilayer time-space networks (TSNs), is used to depict the traffic flow. The distribution is obtained by optimizing the charging, discharging, routing, and origin-destination pairing of EV fleets on TSNs, while the power flow is captured using dynamic optimal power flow problems with security constraints. An algorithm combining the alternating direction multiplier method with the convex-concave procedure is proposed to solve OTPFs. The results validate the effectiveness of the proposed scheme for managing congestion on CTPSs.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Multidisciplinary
A. Rasaizadi, S. Seyedabrishami
Summary: This study employed a joint model using copula functions to explore the interdependency between departure time and destination choices. Results suggested that there were common unobserved factors and observed factors between these decisions.
Article
Engineering, Aerospace
Eri Itoh, Mihaela Mitici, Michael Schultz
Summary: Reducing the length of departure queues at runway entry points is crucial for reducing aircraft traffic congestion and fuel consumption at airports. This study proposes a model that utilizes a time-varying fluid queue to determine aircraft waiting time in the departure queue and evaluate effective control approaches for assigning suitable holds.
Article
Transportation Science & Technology
Xavier Ros-Roca, Lidia Montero, Jaume Barcelo, Klaus Noekel, Guido Gentile
Summary: Dynamic traffic models require dynamic inputs, one of which is the Dynamic Origin-Destinations (OD) matrices. This paper proposes a new constrained non-linear optimization model to estimate the OD matrices using recorded commercial data, eliminating the need for a bilevel iterative process and traffic assignment. The performance of the model is validated and computational results are presented.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Engineering, Civil
Massimo Di Gangi, David Watling, Rosa Di Salvo
Summary: This paper describes a decision support evacuation approach that predicts the time-evolution of the probability of evacuating users and analyzes risk factors in an evacuation scenario.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Transportation
Zhanhong Cheng, Jia Yao, Anthony Chen, Shi An
Summary: This paper investigates the conditions and characteristics of stochastic traffic assignment paradoxes in three models: multinomial logit, multinomial weibit, and multiplicative hybrid, finding that the multiplicative hybrid model fits the data the best. The study suggests that the other two models exhibit inherent tendencies, and the paradoxical links identified by the multiplicative hybrid model are a compromise of the other two models.
TRANSPORTMETRICA A-TRANSPORT SCIENCE
(2022)
Article
Green & Sustainable Science & Technology
Yong Lin
Summary: DynasTIM is a decision support software system for real-time online simulation, prediction and optimization of dynamic traffic flows in urban or expressway networks. It is based on the principle of dynamic traffic assignment and has shown good matching accuracy with real surveillance flows. The signal optimization method implemented by DynasTIM has the potential to reduce average travel delay by about 13%.
