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Experimental Studies on Bicycle Flow Dynamics of Cyclist Loading and Unloading Processes at Bottlenecks


Speaker

Dr. WONG Wai

Department of Civil and Natural Resources Engineering, University of Canterbury

 

Date:    January 4, 2024 (Thursday)

Time:   4:00 pm – 5:00 pm

Venue:  Room 632C, 6/F Haking Wong Building, The University of Hong Kong

 

Abstract

Cycling has emerged as one of the most important green transport modes in recent years, with cities increasingly prioritizing cycling in their sustainable policy agenda. However, the associated traffic dynamics, especially the evolution of bicycle flow at bottlenecks, have not been extensively studied. In this study, real-world experiments were conducted to investigate the dynamics of bicycle flow at bottlenecks under varying cycling demands generated by the cyclist unloading and loading processes. Upon the activation of the bottleneck, its capacity remained largely constant. For the same physical system, the bottleneck capacity of the cyclist loading process exceeded that of the unloading process, indicating the occurrence of capacity drop and hysteresis. Statistical analyses demonstrated that the capacity drop was attributable to the difference in speeds of the two processes for the same cycling demands after the bottleneck activation. These findings could potentially be explained by behavioral inertia. Further analysis revealed that compared with the unloading process, the cyclist loading process was associated with higher cycling speeds owing to the higher overtaking rates. The outcomes of this study can advance our understanding of the physics of bicycle flow dynamics and provide valuable insights for transport planning professionals involved in the facility planning and control of existing networks.

 

About the Speaker

Dr. Wai Wong is a lecturer in the Department of Civil and Natural Resources Engineering at the University of Canterbury, New Zealand. He earned his Ph.D. in transportation and traffic engineering and his bachelor's degree with first-class honours in Civil Engineering both from the Department of Civil Engineering at The University of Hong Kong. Following his graduation, Dr. Wong served as a postdoctoral research fellow at the Department of Civil and Environmental Engineering at the University of Michigan, USA. His research interests include smart city development, big data analytics, intelligent transport systems, cybersecurity and sustainable transport. Fueled by his passion and vision for creating smarter and more efficient transportation systems, Wai has dedicated his research to advancing smart cities through cutting-edge research. He has published in top-tier international journals, including Transportation Science, Transportation Research Part B, Transportation Research Part C, and IEEE Transactions on Intelligent Transportation Systems. He also contributes as a reviewer for these prestigious transportation journals.

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Ensuring the robustness of link flow observation systems in sensor failure events


Speaker:

Dr. Ning ZHU

College of Management and Economics, Tianjin University

Joint work with Xinyao Yu, Shoufeng Ma, William H.K. Lam, Hao Fu

 

Date:    January 4, 2024 (Thursday)

Time:   5:00 pm – 6:00 pm

Venue:  Room 632C, 6/F Haking Wong Building, The University of Hong Kong

 

Abstract

Network link flow data are an intuitive information for monitoring the traffic condition of the entire network, and can be used to enhance traffic management and control. Link flow observation systems are typically designed using flow conservation equations to obtain the information of flow on unobserved links by inference. The occurrence of sensor failures in such systems may lead to flow information loss on both observed and inferred links. Most studies on this issue have considered sensor deployment and failure evaluation as separate processes. In contrast, in this study, both processes are integrated to establish a link flow observation system that withstands sensor failures. First, we propose a novel model to solve the sensor location problem for full link flow observability. The proposed model is then modified to evaluate the link flow information loss in sensor failure event, and incorporated into a distributionally robust optimization (DRO) model for the sensor location problem concerned. The DRO model minimizes the worst-case expected information loss of the system during the planning horizon with different types of sensors. Moreover, we extend the DRO model to a target-based version, into which a convex risk measure named Observation fulfillment risk index is introduced to evaluate the risk of failing to meet the predetermined observation target for any sensor installation schemes. The devised models can be directly solved by commercial solvers for networks like Nguyen-Dupuis, and a matheuristic genetic algorithm is designed for large-scale example networks. Numerical experiments are performed for networks with different sizes. The DRO model generates robust sensor location schemes with worst-case performances that are superior to those achieved using benchmark methods, such as stochastic programming. The use of the Observation fulfillment risk index enhances the system stability and target fulfillment level and decreases the standard deviation of the link flow information loss. We also make use of numerical experiments to derive some insightful conclusions on installation budget, coverage ratio, failure risks, etc..

 

About the Speaker

Dr. Ning ZHU is a Professor in the College of Management and Economics at Tianjin University. His research interests encompass transportation and logistics system modeling, operation, and optimization. He focuses on various research problems including traffic sensor locations, transit system modeling (including bus stop modeling and related topics), vehicle routing problems, bike sharing system operations, disaster operations and management. Ning Zhu employs technical tools such as mixed-integer programming, stochastic programming, robust optimization, and stochastic processes to tackle these problems. He has published more than 40 academic papers in international journals such as Transportation Science, Transportation Research Part B/C/E, INFORMS Journal on Computing, Manufacturing & Service Operations Management and the European Journal of Operational Research. Additionally, he is the Principal Investigator for four national natural science foundation projects, including one National Science Fund for Excellent Young Scholars.


Hosts:

DEPARTMENT OF CIVIL ENGINEERING

SEMINAR

JOINTLY ORGANIZED WITH

HONG KONG SOCIETY FOR TRANSPORTATION STUDIES

INSTITUTE OF TRANSPORT STUDIES, HKU

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Getting from here to there - Strategic, tactical and operational issues related to deployment of ACES (Autonomous, Connected, Electric & Shared) mobility technologies






SPEAKER Prof. Hani S. Mahmassani 

Professor of Civil and Environmental and (by courtesy) Industrial Engineering and Management Sciences Engineering 

William A. Patterson Distinguished Chair in Transportation 

Northwestern University  DATE AND TIME 15 December 2023 (Friday) 19:00 – 20:00 (Hong Kong Time) 

VENUE

CPD 3.04, Run Run Shaw Tower, Centennial Campus, The University of Hong Kong ORGANISED BY Institute of Transport Studies, The University of Hong Kong ABSTRACT Various emerging technologies and supply business models are envisioned to bring potentially transformative changes to the urban mobility landscape. These technologies, ranging from Autonomous, Connected, Electric, Shared (ACES) technologies, to micromobility and urban air mobility using eVTOLS, create significant opportunities for improved and more equitable mobility. They also face challenges along their deployment pathway, and stress our existing modeling frameworks and methodologies. We discuss key challenges and pathways for addressing them.    SPEAKER’S BIO Dr. Hani S. Mahmassani holds the William A. Patterson Distinguished Chair in Transportation at Northwestern University, where he is Director of the Northwestern University Transportation Center.  Prior to Northwestern, he served on the faculties of the University of Maryland and the University of Texas at Austin. His research contributions include the areas of intelligent transportation systems, freight and logistics systems, multimodal systems modeling and optimization, pedestrian and crowd dynamics and management, traffic science, demand forecasting and travel behavior, and real-time operation of transportation and distribution systems. He is past editor-in-chief of Transportation Science, senior editor of IEEE Transactions on Intelligent Transportation Systems, founding (past) associate editor and current scientific board member of Transportation Research C: Emerging Technologies, Distinguished Advisory Board Member of Transportation Research Part A: Policy and Practice, and associate editor of Transportation Research Record. He is a past president of the Transportation Science Section of the Institute for Operations Research and the Management Sciences, a past President of the International Association for Travel Behavior Research, and the Convenor of the ISTTT International Advisory Committee. He serves on the Executive Committee of the Transportation Research Board, the Research and Technology Advisory Committee of the US Department of Transportation’s Federal Highway Administration, and the Panama Canal Authority’s International Advisory Board.  He was the recipient of a Distinguished Alumnus Award of the Faculty of Engineering and Architecture of the American University of Beirut in 2006, the Intelligent Transportation Systems Outstanding Application Award of the Institute of Electrical and Electronics Engineers in 2010, the Transportation Research Board (TRB)’s Thomas Deen Distinguished Lectureship in 2016, TRB’s Roy Crum Award for Distinguished Service in 2022, and a Distinguished Engineering Alum of Purdue in 2022. He was elected Emeritus member of TRB committees on Telecommunications and Travel Behavior (2006), Transportation Network Modeling (2007), and Traveler Behavior and Values (2008). He was elected to the National Academy of Engineering in 2021 “for contributions to modeling of intelligent transportation networks and to interdisciplinary collaboration in transportation engineering”. He received his PhD from the Massachusetts Institute of Technology in transportation systems and MS in transportation engineering from Purdue University.




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