Article
Multidisciplinary Sciences
Simone Loreti, Enrico Ser-Giacomi, Andreas Zischg, Margreth Keiler, Marc Barthelemy
Summary: Research shows that floods have affected over 2 billion people globally from 1998 to 2017, with the occurrence expected to increase as a result of climate warming, population growth, and rapid urbanization. Previous studies on the resilience of transportation networks during floods have mainly used the framework of percolation, but this study demonstrates its inadequacy through a realistic high-resolution flood simulation. Instead, a new approach is proposed to partition the road network based on the accessibility of local towns and define new measures to characterize the impact of flooding. This analysis helps to identify key cities that provide critical services to a large number of individuals during floods, aiding practical risk management and resource allocation decisions.
SCIENTIFIC REPORTS
(2022)
Article
Physics, Multidisciplinary
Christina Iliopoulou, Michail A. Makridis
Summary: Public transportation networks are susceptible to uncertainty, which can lead to disruptions and passenger dissatisfaction. Strategic planning should include identifying critical disruption scenarios that may result in the loss of network functionality and increased travel times for users. This study presents a multi-objective algorithm to identify critical disruption scenarios using a transit assignment model, demonstrating the effectiveness of optimization-based attacks in identifying significant impacts on passenger connectivity and travel costs.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2023)
Article
Geosciences, Multidisciplinary
Chiara Arrighi, Maria Pregnolato, Fabio Castelli
Summary: This study presents a risk analysis of indirect flood impacts on water distribution and road network systems, highlighting the risks posed by systemic interdependency. The results demonstrate that timely repairs to water distribution station can significantly reduce risks in terms of population equivalent and pipe length. Further research on systemic risk analysis for multiple urban infrastructures could enhance resilience planning for indirect impacts.
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES
(2021)
Article
Engineering, Civil
Guangjian Ren
Summary: This paper proposes a topology potential relative entropy (TPRE) model to analyze the robustness of air route network (ARN), and validates its applicability and accuracy through attack strategies. The conclusion is of practical significance for optimizing ARN structure and improving airspace efficiency.
JOURNAL OF ADVANCED TRANSPORTATION
(2021)
Article
Environmental Studies
Andre Borgato Morelli, Andre Luiz Cunha
Summary: This paper introduces a convenient metric for assessing the vulnerability of road networks in small to medium-sized cities, focusing on how obstructions from disasters can increase path lengths. A case study in Sa?o Carlos, Brazil, demonstrates that walking and cycling are more robust modes of transportation compared to motorized individual transport, highlighting the importance of compact city planning to make cities more resilient to floods.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2021)
Review
Mathematics, Interdisciplinary Applications
Tang Zhixing, Huang Shan, Han Songchen
Summary: Flight delay research utilizes complex network theory, analyzing static networks and temporal evolution, and identifying topologically important nodes/edges. Additionally, the relationships among robustness, vulnerability, and resilience in air transportation networks are clarified.
Article
Geography
Wei Luo, Lingfeng He, Zihui Yang, Shirui Zhang, Yong Wang, Dianbo Liu, Sheng Hu, Li He, Jizhe Xia, Min Chen
Summary: The COVID-19 pandemic and subsequent lockdowns have severely impacted global trade, with different economies experiencing varying degrees of damage and recovery rates. This research evaluates the spatio-temporal vulnerabilities of international trade networks during the current crisis to understand global production resilience and prepare for future crises. Analysis of pre- and post-COVID-19 outbreak trade networks at various scales reveals that countries with effective COVID-19 containment, such as East Asia (particularly Mainland China), and high-income countries with rapid vaccine roll-out (e.g., the U.S.) exhibit greater resilience, while low-income countries (e.g., Africa) show higher vulnerability. The findings emphasize the need for a comprehensive strategy to enhance international trade resilience, including non-pharmaceutical measures, timely vaccine development and distribution, strong governance, robust healthcare systems, and international cooperation.
Review
Physics, Multidisciplinary
Shouzheng Pan, Hai Yan, Jia He, Zhengbing He
Summary: With the advancement of integrated and intelligent transportation systems, emphasis has been placed on the stability and security of system performance. Resilience and vulnerability are crucial indicators in performance analysis, with recent progress in related studies focusing on traditional topological and system structure analysis in the transportation field.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Transportation Science & Technology
Mohammad Ansari Esfeh, Lina Kattan, William H. K. Lam, Mostafa Salari, Reza Ansari Esfe
Summary: The paper proposes a new data-driven approach to analyze the vulnerability of impact areas, taking into account the probability and effects of incidents. The approach focuses on the spatial and temporal impacts of non-recurrent incidents, capturing the dynamic propagation of congestion patterns in the vicinity of the affected area. The developed vulnerability index improves the modeling of multi-dimensional travel delays caused by non-recurrent incidents in a road network.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Environmental Sciences
Breanne K. Langlois, Elizabeth Marsh, Tyler Stotland, Ryan B. Simpson, Katherine Berry, David A. Carroll, Aris Ismanto, Magaly Koch, Elena N. Naumova
Summary: We explored the link between the national disaster database maintained by the Indonesian National Board for Disaster Management and the global flood monitoring database of Dartmouth Flood Observatory to aid local vulnerability assessment in Indonesia. We calculated a vulnerability metric for physical damage from flooding using principal component analysis and identified the most vulnerable areas as well as nonhomogeneous spatiotemporal trends of flooding and vulnerability. This study demonstrates the potential usability of public climate data and provides directions for further research.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Economics
Bramka Arga Jafino
Summary: Transport network criticality analyses aim to identify important segments in a transport network. By using alternative moral principles, different criticality results can be obtained. It is important to carefully select a moral principle during analysis to prevent overlooking critical transport segments.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2021)
Article
Operations Research & Management Science
Aura Reggiani
Summary: This paper emphasizes the importance of connectivity and its architecture in network vulnerability, complexity, and resilience. It highlights connectivity as a key element for network vulnerability and shock propagation and emphasizes the primary role of connectivity in network analysis. The paper also discusses the need for a unified methodological framework that considers both vulnerability and resilience.
NETWORKS & SPATIAL ECONOMICS
(2022)
Article
Engineering, Multidisciplinary
Pau Esteve, Jose J. Ramasco, Massimiliano Zanin
Summary: This study analyzes a large dataset of European flights from 2015 to 2018 and finds that air route networks are highly dynamic, with major topological changes occurring at the end of 2017. The overall resilience of the network remains constant over time despite an increase in traffic. These findings emphasize the importance of considering the evolution of air route networks in the study of traffic flows.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Oceanography
Meizhi Jiang, Jing Lu, Zhuohua Qu, Zaili Yang
Summary: This study aims to develop a novel port vulnerability assessment framework to guide standardized vulnerability analysis processes for ports from different geographies, enabling better management of resources at a global network level for optimal supply chain resilience.
OCEAN & COASTAL MANAGEMENT
(2021)
Article
Energy & Fuels
Rouhollah Shahnazi, Najmeh Sajedianfard, Mark Melatos
Summary: This paper analyzes the structure of the global oil trade network and its resilience to shocks, introducing the effective share index and resilience measure. The results show that countries like China and the USA play significant but unstable roles, while Saudi Arabia and Russia reduce the export-side resilience of the global oil trade network.
Editorial Material
Transportation
Andy H. F. Chow, Yong-Hong Kuo, Panagiotis Angeloudis, Michael G. H. Bell
TRANSPORTMETRICA B-TRANSPORT DYNAMICS
(2022)
Editorial Material
Transportation
Renxin Zhong, Zhengbing He, Andy H. F. Chow, Victor Knoop
TRANSPORTMETRICA A-TRANSPORT SCIENCE
(2022)
Article
Transportation
Cheng Zhang, H. W. Ho, William H. K. Lam, Wei Ma, S. C. Wong, Andy H. F. Chow
Summary: This paper proposes a new method for estimating lane-based travel time distributions by vehicle type using low-resolution vehicle video images captured by conventional traffic surveillance cameras. The method utilizes deep learning and graph matching techniques, and performs well in vehicle type-specific traffic management schemes.
JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Economics
Yimo Yan, Andy H. F. Chow, Chin Pang Ho, Yong-Hong Kuo, Qihao Wu, Chengshuo Ying
Summary: This paper provides a comprehensive review of the development and applications of reinforcement learning techniques in logistics and supply chain management. The most popular approach, Q-learning, is adopted by many studies, and recent research in urban logistics has been growing rapidly. Potential directions for future research are also presented.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2022)
Article
Economics
R. C. P. Wong, W. Y. Szeto
Summary: The study demonstrates that under a fixed taxi fare structure, passenger demand for taxis varies over time and space, and implementing surcharges may be a better way to address supply shortages. Analyzing taxi customer travel decisions using various models can provide insights into influencing factors and offer solutions based on market segmentation.
Article
Engineering, Civil
Cheng Zhang, Bi Yu Chen, William H. K. Lam, H. W. Ho, Xiaomeng Shi, Xiaoguang Yang, Wei Ma, S. C. Wong, Andy H. F. Chow
Summary: The study proposes a new vehicle re-identification method to estimate lane-level travel time distributions by considering lane-level traffic conditions, vehicles' lane changing behaviors, and visual features. A comprehensive case study in Hong Kong demonstrates that the proposed method outperforms existing methods and provides accurate lane-level travel time distribution information on congested urban roads.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(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
Economics
Z. C. Su, Andy H. F. Chow, C. L. Fang, E. M. Liang, R. X. Zhong
Summary: This study proposes a hierarchical control framework to maximize the throughput of a road network driven by travel demand with uncertainties. The upper level uses a reinforcement learning algorithm to regulate the traffic influx into the core road network without the need for an underlying system model and macroscopic fundamental diagram. The lower level is a local signal control system that regulates the spatial distribution of traffic flow within the core network. The study contributes to the management of urban road networks with advanced computing technologies.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(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 Science & Technology
Hoa T. M. Nguyen, Andy H. F. Chow
Summary: This paper presents an adaptive optimization framework for dynamic rail transit network operations using a rollout surrogate-approximate dynamic programming method. The proposed framework reduces passengers' waiting times significantly with reasonable computational time. The results suggest the potential of the proposed optimizer for real-time applications in large-scale rail transit networks.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(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)
