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
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
Engineering, Civil
Dawei Li, Min Yang, Cheng-Jie Jin, Gang Ren, Xianglong Liu, Haode Liu
Summary: In the MaaS age, route choices have evolved from single mode paths to combined routes utilizing multiple travel modes in multi-modal transportation systems. The MLK model explicitly considers correlations of unobserved utilities of combined routes, addressing the generalized path overlapping problem. Numerical studies show that the model significantly impacts both individual route choice predictions and aggregated traffic flows at equilibrium.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2021)
Article
Transportation Science & Technology
Yijiang Li, John-Paul Clarke, Santanu S. Dey
Summary: This paper proposes a column generation-based approach to solve the airport flight-to-gate assignment problem, utilizing the submodularity property to efficiently solve pricing problems and improving the efficiency of solving large-sized instances with the use of rolling horizon and block decomposition algorithms.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Mathematics
Carlos-Ivan Paez-Rueda, Arturo Fajardo, Manuel Perez, German Yamhure, Gabriel Perilla
Summary: This paper presents improved algorithms for solving the Minimum Span Frequency Assignment Problem in mobile communication systems. Through evaluation on twenty benchmark cases, the modified algorithms demonstrate superior performance compared to traditional algorithms with comparable computational complexity.
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
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
Computer Science, Artificial Intelligence
Raed Abu Zitar, Laith Abualigah, Frederic Barbaresco, Amal ElFallah Seghrouchni
Summary: This research focuses on the multi-track measurement assignment problem in drone detection and tracking. Measurements and tracks are simulated using the Linear Kalman Filter, and an optimized measurement/track assignment is sought. Evolutionary-based metaheuristic algorithms, including a modified Arithmetic Optimization Algorithm, are used to efficiently solve this computationally explosive problem. Simulations and comparisons demonstrate the effectiveness of the proposed method in solving the drone's measurements and track assignment problem.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Interdisciplinary Applications
Xiang Zhang, Steven Travis Waller, Dung-Ying Lin
Summary: This study is the first in the literature to examine the Braess paradox considering parking behavior in the autonomous vehicle (AV) environment and model the network design problem for the autonomous transportation system (NDP-ATS). It shows the existence of two distinct Braess paradoxes in AV traffic networks and develops a bi-level programming model to avoid the deterioration caused by these paradoxes. The results highlight the efficacy of the modeling framework for infrastructure development and policy assessment for AV traffic.
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
(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
Management
Guoyuan Li, Anthony Chen
Summary: This paper proposes a strategy-based transit stochastic user equilibrium (SUE) model that considers capacity and number-of-transfers constraints in an urban congested transit network. The model uses a route-section-based method for network representation and assumes passengers' route choice behavior obeys the logit model. The transit line capacity and maximum number-of-transfers constraints are considered, and the problem is formulated as a variational inequality (VI) problem. A transit path-set generation procedure is proposed, and the asymmetric cost function is solved using the diagonalization method.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Economics
Hemant Suman, Homero Larrain, Juan Carlos Munoz
Summary: The study aims to measure the error induced by simplification and understand how it misrepresents passenger flows and bus occupation rates. By optimizing a set of test scenarios using a naive approach and obtaining benchmark passenger assignment, the comparison reveals potential unrealistic aspects of the naive approach in network design. This highlights the importance of verifying the results with a passenger assignment model before implementation.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2021)
Article
Economics
Yuki Oyama, Yusuke Hara, Takashi Akamatsu
Summary: This study fills the research gap by establishing a Markovian traffic equilibrium assignment based on the network generalized extreme value (NGEV) model. The study provides the necessary theoretical developments for the NGEV equilibrium assignment, including the formulation and solution under the same path algebra as traditional models. Equivalent optimization formulations are also presented, allowing for efficient solution algorithms. The numerical experiments demonstrate the excellent convergence and complementary relationship of the proposed algorithms.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2022)
Article
Metallurgy & Metallurgical Engineering
Dong-mei Yan, Jian-hua Guo
Summary: This paper proposes a cumulative prospect value (CPV)-based generalized nested logit (GNL) stochastic user equilibrium (SUE) model to address key issues in traffic assignment. Empirical tests demonstrate that the model can effectively handle rational and overlapping path issues, and is applicable for large road networks.
JOURNAL OF CENTRAL SOUTH UNIVERSITY
(2021)
Article
Management
Zhiyuan Liu, Xinyuan Chen, Jintao Hu, Shuaian Wang, Kai Zhang, Honggang Zhang
Summary: This paper introduces a new parallel computing algorithm to solve the user equilibrium problem. Existing solution algorithms in transportation research can be classified into three categories: link-based, path-based, and origin-based. This paper proposes an alternating direction method of multipliers (ADMM) algorithm, which is different from these categories. It utilizes the origin-based formulation of the problem and eliminates the flow conservation conditions through an augmented Lagrangian function. The network links are grouped into different blocks for the ADMM, and a novel approach is developed for this link grouping problem.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
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
Management
Guoyuan Li, Anthony Chen
Summary: This paper proposes a strategy-based transit stochastic user equilibrium (SUE) model that considers capacity and number-of-transfers constraints in an urban congested transit network. The model uses a route-section-based method for network representation and assumes passengers' route choice behavior obeys the logit model. The transit line capacity and maximum number-of-transfers constraints are considered, and the problem is formulated as a variational inequality (VI) problem. A transit path-set generation procedure is proposed, and the asymmetric cost function is solved using the diagonalization method.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Economics
Rui Yao, Shlomo Bekhor
Summary: Choice set generation is a challenging task due to the unknown consideration set and the large size of the full choice set. The proposed variational autoencoder approach aims to maximize the likelihood of including chosen alternatives in the choice set and infer the underlying generation process. This paper introduces the generalized extreme value (GEV) model with implicit availability/perception (IAP) and applies it to the VAE method for choice modeling. Simulation experiments and real dataset analysis demonstrate the effectiveness of the approach in reproducing true values and achieving better performance compared to other methods.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2022)
Article
Transportation
Ruiya Chen, Xiangdong Xu, Anthony Chen, Xiaoning Zhang
Summary: This paper presents a conservative expected travel time approach, called MCET, for reporting reliable waiting time information in app-based transportation services, addressing the issues of existing information provision forms.
TRANSPORTMETRICA A-TRANSPORT SCIENCE
(2023)
Article
Transportation
Ruiya Chen, Xiangdong Xu, Anthony Chen, Chao Yang
Summary: Travel time variability poses challenges to reporting travel time information. This paper proposes a conservative expected travel time approach to enhance information reliability and simplicity.
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2023)
Article
Engineering, Civil
Mai Sirhan, Shlomo Bekhor, Arieh Sidess
Summary: This paper develops and trains a deep artificial neural network (DNN) model to predict the pavement condition index (PCI) values. The DNN model outperforms traditional prediction methods, such as linear and nonlinear regression, in terms of accuracy. The most influential variables for PCI prediction are found to be distresses related to alligator cracking, swelling, rutting, and potholes.
JOURNAL OF TRANSPORTATION ENGINEERING PART B-PAVEMENTS
(2022)
Article
Engineering, Civil
Kaipeng Wang, Pu Wang, Zhiren Huang, Ximan Ling, Fan Zhang, Anthony Chen
Summary: In this study, a two-step model is developed to predict passenger travel demand in expanding subways and tested in an actual subway. Results show that the proposed model achieves higher prediction accuracy than the benchmark models.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Economics
Yu Gu, Anthony Chen, Xiangdong Xu
Summary: This study proposes an optimization-based approach to rank the importance of link combinations and analyze network vulnerability in extreme and near-extreme cases of disruption. A vulnerability envelope concept is used, which considers the worst and best network performance under multiple-link disruptions. The results demonstrate that the consideration of near-extreme cases yields additional valuable information that is not generated by the traditional vulnerability analysis.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2023)
Article
Transportation Science & Technology
Yu Gu, Anthony Chen
Summary: This study proposes an advanced equilibrium mode choice model to analyze the mode choice behavior of emerging customized bus (CB) services. The model considers the unique characteristics of CB services, including seat reservation and loyalty scheme. The results demonstrate the importance of considering passenger loyalty and managing mode similarity and heterogeneity when modeling emerging CB services.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Environmental Studies
Zhuowei Wang, Jiangbo Yu, Guoyuan Li, Chengxiang Zhuge, Anthony Chen
Summary: This study investigates the feasibility and policy implications of achieving carbon neutrality in Hong Kong's public transportation through a competitive bus-market mechanism. A dynamic bus-market evolution model is established using the system dynamics method, which incorporates a generalized Lotka-Volterra model and discrete choice model. The results suggest that relying on business-as-usual policies and market evolution may not be sufficient to achieve the desired level of zero-emission buses, and long-term subsidies for hydrogen buses and support for hydrogen stations are effective measures to promote the hydrogen bus market.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2023)
Article
Geography
Ho-Yin Chan, Yingying Xu, Anthony Chen, Xintao Liu, Kason Ka Ching Cheung
Summary: This article introduces a proof-of-concept designer-in-the-loop schematic map drawing tool, which combines manual and automated approaches to provide technical interactivity between the user and the computer. Compared to existing methods, the proposed approach is more compatible with the framework of effective map design from psychological and aesthetic perspectives, and offers a range of options based on user preferences.
TRANSACTIONS IN GIS
(2023)
Article
Environmental Studies
Shiqi Wang, Yuze Li, Anthony Chen, Chengxiang Zhuge
Summary: This paper develops a data-driven micro-simulation optimization model for deploying charging infrastructure for a large-scale electric bus network. The model considers both traditional charging posts and wireless charging lanes. The results show that deploying both charging posts and WCLs leads to higher levels of service, energy savings, and reduced emissions compared to deploying only charging posts, although the total costs are slightly higher. Sensitivity analysis confirms that parameters associated with electric buses and charging facilities significantly influence the model outputs.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2023)
Article
Economics
Zhandong Xu, Anthony Chen, Xiaobo Liu
Summary: This paper presents a continuous time surplus maximization bi-objective user equilibrium (C-TSmaxBUE) model, in which the users' variability toward the time and toll trade-off in a tolled road network is explicitly considered. The model assigns different users with different ratios of the time saved per unit of money (RTSMs), and infinite indifference curves are generated by considering continuously distributed RTSMs in the population. A path-based single-boundary adjustment (SBA) algorithm is developed to solve the problem, which adjusts RTSM boundaries and path flows simultaneously. Numerical results demonstrate the equilibrium flow pattern and the efficiency of the SBA algorithm in obtaining high-quality equilibrium solutions.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2023)
Article
Economics
Umer Mansoor, Arshad Jamal, Junbiao Su, N. N. Sze, Anthony Chen
Summary: Motorcycle crashes cause a significant number of fatalities and severe injuries worldwide, especially in developing countries. Machine learning methods have been found to provide better prediction performance, but with weaker interpretability. This study aims to compare the consistency of risk factors identified by statistical models and machine learning methods in analyzing motorcycle crash severity.
Proceedings Paper
Computer Science, Artificial Intelligence
Muqing Du, Jiankun Zhou, Anthony Chen
Summary: In this study, a weibit-based SUE model was proposed to address the stochastic ridesharing user equilibrium problem. The model considers the conversion of travelers among three modes and the relationship between the number of ridesharing drivers and passengers, as well as a non-additive path cost function.
2022 IEEE 25TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC)
(2022)
