Article
Computer Science, Artificial Intelligence
Wenlong Zhu, Junting Zhang, Shunqiang Ye, Wanli Xiang
Summary: This paper investigates Braess Paradox under the bi-objective user equilibrium, introducing the definition and occurrence conditions of the paradox. Analytical properties of the bi-objective user equilibrium solutions and the conditions for the occurrence of Braess Paradox are explored on a classical Braess network. The study proves that the occurrence conditions of Braess Paradox are dependent upon link performance parameters and travel demand.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Industrial
Xi Zhang, Haicheng Tu, Jianbo Guo, Shicong Ma, Zhen Li, Yongxiang Xia, Chi Kong Tse
Summary: This paper studies how to enhance power grid resilience and achieve quick recovery after extreme events by adjusting the operating modes of the grid and reconfiguring its components. A double-loop optimization strategy is proposed, utilizing an interior point method and a genetic algorithm to find the optimal topology for coordinating available resources most effectively.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Physics, Multidisciplinary
Stefan Bittihn, Andreas Schadschneider
Summary: The study investigates whether drivers can change the classic Braess' paradox situation through traffic information available in modern traffic networks.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Computer Science, Hardware & Architecture
Mauro Passacantando, Giorgio Gnecco, Yuval Hadas, Marcello Sanguineti
Summary: This study introduces a new framework to investigate Braess' paradox, by utilizing cooperative games with transferable utility to evaluate the contribution of network resources to overall network performance.
Article
Physics, Multidisciplinary
Aihu Wang, Yuanhua Tang, Yasir Tariq Mohmand, Pei Xu
Summary: This research aims to detect the effects of closing and expanding paradox links in transportation and find effective measures to avoid Braess Paradox. The results show that higher capacity worsens Braess Paradox for monotonic links, even if the link capacity is increased infinitely. However, for non-monotonic links, adjusting the link capacity can avoid Braess Paradox. Expanding road infrastructure does not necessarily lead to a significant improvement in travel efficiency.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2022)
Article
Engineering, Industrial
Muhammad Hasan Ashraf, Yuwen Chen, Mehmet G. Yalcin
Summary: Third-party logistics in the U.S. has been declared essential and continues operations amid the pandemic. Demand for e-commerce deliveries has increased due to lockdowns and public preference. Expanding hub capacities may lead to the Braess Paradox. Different layouts are impacted differently, and the study provides insights for improving hub performances.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2022)
Article
Computer Science, Information Systems
Xiaosong Yu, Lu Lu, Yongli Zhao, Feng Wang, Avishek Nag, Xinghua Li, Jie Zhang
Summary: With the rise of cloud services, demands for bandwidth-intensive applications have increased, leading to a more diversified development of application services. Optical network virtualization and flexible-grid elastic optical networks are considered key technologies for the future Internet infrastructure, with the co-existence of fixed/flexible grid optical networks presenting new challenges and solutions for virtual optical network provisioning.
Article
Automation & Control Systems
Julian Barreiro-Gomez
Summary: This study examines the crowd evacuation problem using a stochastic receding-horizon differential game. Two main directions are studied: considering local congestion terms to avoid congestion formation, and considering both local and global congestion terms for crowd aversion during evacuation. The solution to these problems is presented using semi-explicit methods by solving the corresponding Hamilton-Jacobi-Bellman backward Partial Differential Equation (PDE). The study also discusses the evacuation Braess paradox and provides a concrete example. Numerical examples are presented for a case study with multiple rooms and exits, comparing the results of the two stochastic differential-game approaches.
Article
Automation & Control Systems
Mark Jeeninga
Summary: This paper investigates the feasibility of power flow in DC power grids with constant-power loads. The concept of Braess' paradox is introduced and its occurrence in practical power grids is demonstrated. To address this paradox, bounded parametric uncertainties in power lines are considered, and a simple yet conservative condition is provided to ensure feasible power flow under these uncertainties.
SYSTEMS & CONTROL LETTERS
(2022)
Article
Computer Science, Information Systems
Sotirios Dimos, Dimitris Fotakis, Thanasis Lianeas, Kyriakos Sergis
Summary: This research utilizes an approximate version of Caratheodory's theorem to efficiently approximate the best subnetwork on selfish routing instances. The algorithm runs on networks with short paths and provides the first polynomial-time approximation scheme.
INFORMATION PROCESSING LETTERS
(2023)
Review
Economics
Jia Yao, Ziyi Cheng, Anthony Chen
Summary: This paper reviews the studies on traffic paradoxes published from 1968 to 2022 using a bibliometric analysis approach. The results help researchers, planners, and engineers in the transportation field to systematically and comprehensively understand the theme of traffic paradoxes.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2023)
Article
Green & Sustainable Science & Technology
Le Zhang, Lijing Lyu, Shanshui Zheng, Li Ding, Lang Xu
Summary: Route game is an effective method to alleviate traffic congestion, but traditional methods based on potential functions are not suitable for real-time traffic. This paper proposes a matched Q-learning algorithm to generate approximate Nash equilibrium for the classic route game in real-time traffic.
Article
Engineering, Electrical & Electronic
Qinfei Long, Junhong Liu, Feng Liu, Yunhe Hou
Summary: To mitigate failure risk, a dynamic thermal rating (DTR) sensor can be placed in transmission lines. This paper proposes a submodular optimization-based DTR placement model that considers Braess paradox. A model based on Markov probability and important sampling weight techniques is utilized to quantify failure risk efficiently. The risk model is then applied to analyze the conditions for Braess paradox and reformulate the risk mitigation model with estimation error. A computationally efficient algorithm is designed to solve this nonmonotone submodular optimization, providing a provable approximation guarantee.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Transportation Science & Technology
Khoa D. Vo, William H. K. Lam, Zhi-Chun Li
Summary: This paper presents a novel household-oriented activity-based mixed-equilibrium model for estimating individual and household activity-travel choices in multimodal transportation networks with interactions between private car and public transit modes. The model utilizes a logit-based stochastic choice model to capture mixed equilibrium, converting the time-dependent activity-travel scheduling problem into an equivalent static traffic assignment problem. The conditions for the existence and uniqueness of a solution to the equivalent variational inequality problem for joint activity-travel paths are also identified.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Economics
Kenju Kamei
Summary: This paper investigates the transfer paradox experimentally in a three-agent pure exchange economy and finds that the adjustment of endowments among agents affects market prices, leading to benefits for donors in line with competitive equilibrium theory.
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
Transportation Science & Technology
Qingyun Tian, Yun Hui Lin, David Z. W. Wang, Yang Liu
Summary: This paper studies the optimal planning of public transit services with modular vehicles and proposes two solution methods. A case study is conducted on the proposed Singapore DART line. The results show that modular-vehicle transit service can significantly reduce operating costs and passengers' travel time costs, providing a useful tool for determining optimal operation strategies for future transit service systems.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Transportation Science & Technology
Zhihong Guo, David Z. W. Wang, Danwei Wang
Summary: With the emergence of automated vehicles, the future traffic system is expected to consist of a mix of self-driving autonomous vehicles (AVs) and human-driven conventional vehicles. Therefore, it is crucial to propose new traffic management measures to handle this future traffic system. This study aims to utilize the controllable property of AVs' routing choices to develop a daily routing allocation scheme for a certain number of autonomous vehicles, in order to achieve the desired traffic state in the mixed traffic system.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Engineering, Electrical & Electronic
Wenbin Zhang, Zihao Tian, Lixin Tian, David Z. W. Wang, Yi Yao
IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE
(2022)
Article
Economics
Chang Zhou, Qiong Tian, David Z. W. Wang
Summary: This study proposes a novel control technique to mitigate bus bunching by providing passengers with real-time wait time information and degrees of in-vehicle congestion. The numerical results show that providing in-vehicle congestion information is as effective as the schedule-based and headway-based control methods in achieving mitigation of bus bunching.
Article
Environmental Studies
Roy Tan, Harilaos N. Psaraftis, David Z. W. Wang
Summary: This paper revisits speed optimization and speed reduction models for liner shipping in a multi/flexible fuel context, analyzing the influence of a maximum average speed limit on optimal speeds, carbon intensity and emissions for dual fuel Neopanamax container vessels utilizing liquefied natural gas.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2022)
Article
Economics
Qingyun Tian, David Z. W. Wang, Yun Hui Lin
Summary: This paper proposes a multi-stage mathematical modeling framework to optimize the deployment strategy of autonomous buses in public transit service operations. Passenger acceptance attitudes and the diffusion model are considered to forecast the passengers' adoption rate. The optimal deployment strategy that minimizes the total travel cost is determined through solving a mixed-integer nonlinear program.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Computer Science, Artificial Intelligence
Liang Du, Ruobin Gao, Ponnuthurai Nagaratnam Suganthan, David Z. W. Wang
Summary: Traffic forecasting is crucial for smart city development, and this study proposes a novel graph ensemble deep random vector functional link network (GEdRVFL) to achieve node-wise traffic forecasting, which outperforms state-of-the-art models in most cases.
APPLIED SOFT COMPUTING
(2022)
Article
Engineering, Civil
Zhen Di, David Z. W. Wang, Lixing Yang
Summary: The high-speed rail plays a pivotal role in intercity commuting, but there are issues with ticket pricing and seat allocation. This study proposes a new ticketing/exchanging scheme to address demand fluctuation and validates its effectiveness through numerical experiments.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Green & Sustainable Science & Technology
Jie Zhang, Meng Meng, David Z. W. Wang, Li Zhou, Linghui Han
Summary: This paper investigates the problem of bike allocation in a competitive bike sharing market. A continuum approximation (CA) approach is used to handle computational challenges by assuming that allocation points and user demand are continuously distributed in a two-dimensional region. Bike sharing companies bear allocation and bike depreciation costs while earning revenue from fare collection. User's choice of bike service depends on walking distance and bike quality preference. The demand elasticity is considered in relation to the density of allocation points. A leader-follower Stackelberg competition model is developed to derive the optimal allocation strategy for the market leader. Numerical studies are conducted for both hypothetical and real cases to examine the impact of parameters on model performance and demonstrate the application of the proposed model in decision making.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Transportation Science & Technology
Qingyun Tian, Yun Hui Lin, David Z. W. Wang
Summary: This paper focuses on the operation design of a future public transit service adopting modular vehicles. The unique feature of modular vehicles allows for assembling and disassembling operations along each trip to dynamically adjust the vehicle formation at stations. A mathematical model is proposed to determine the optimal scheduling and modular vehicle formation, considering time-dependent travel demand and module availability. The model is solved using exact reformulation techniques and a two-step heuristic approach, showing the validity and efficiency of the formulation and solution methods. It is found that modular transit services have remarkable advantages in reducing both operator's and passengers' costs.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Engineering, Electrical & Electronic
Wenbin Zhang, Zihao Tian, Lixin Tian, David Z. W. Wang
IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE
(2023)
Article
Transportation
Yuanyuan Wu, David Z. W. Wang, Feng Zhu
Summary: This study proposes a deep reinforcement learning approach to address the issue of optimizing traffic efficiency at congested major-minor intersections, which can negatively impact vehicle fairness. The proposed method optimizes both efficiency and fairness by measuring traffic fairness using the difference between the crossing order and the approaching order of vehicles, and measuring traffic efficiency using average travel time. The effectiveness of the method is evaluated in a simulated real-world intersection and compared with benchmark policies, and it shows outstanding performance in balancing traffic fairness and efficiency.
TRANSPORTMETRICA A-TRANSPORT SCIENCE
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Liang Du, Ruobin Gao, Ponnuthurai Nagaratnam Suganthan, David Z. W. Wang
Summary: This paper proposes a novel online performance-based ensemble deep random vector functional link neural network model for time series forecasting tasks. The model supports non-iterative online learning and dynamic ensemble method, and outperforms existing statistical, machine learning-based, and deep learning-based models in extensive experiments.
2022 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN)
(2022)
Article
Green & Sustainable Science & Technology
J. Zhang, M. Meng, David Z. W. Wang, B. Du
Summary: This study develops a methodology to determine the optimal allocation position to deploy bikes in a competitive dockless bike sharing market. Two different scenarios are considered, one with a potential competitor and one without. The study proposes two different heuristics to handle these scenarios based on different design objectives.
INTERNATIONAL JOURNAL OF SUSTAINABLE TRANSPORTATION
(2022)