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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.




Research Cases on the Applications of Data-Driven Methods in Smart Cities

 

Speaker:

Dr. WANG Hai

School of Computing and Information Systems, Singapore Management University

 

Date:    December 28, 2023 (Thursday)

Time:   3:00 pm – 4:00 pm

Venue:  Room 612B, 6/F Haking Wong Building, The University of Hong Kong

 

Abstract

The rapid development and widespread adoption of mobile devices, sensors, IoT, and communication technology have led to the generation of vast volumes of multi-source, high-dimensional data in various systems within the broader framework of smart cities, including transportation, logistics, e-commerce, healthcare, etc. Consequently, numerous data-driven methods have been developed and implemented to address research challenges related to the design and operations of these systems. In this talk, we will briefly discuss several research cases on the applications of data-driven methods in smart cities. These cases include: (1) Descriptive methods for mobile transaction digits distribution and crowd-sourcing food delivery operations; (2) Predictive methods for ICU patient condition evaluation and freelance platform service quality prediction; (3). Prescriptive method for shared transportation ride matching and feeder vessel transshipment routing and scheduling. Through these cases, we aim to showcase the diverse applications of data-driven methods in addressing some key challenges in smart cities.

 

About the Speaker

Dr. WANG Hai is an Associate Professor in the School of Computing and Information Systems at Singapore Management University and a visiting teaching faculty at the Heinz College of Information Systems and Public Policy at Carnegie Mellon University. He is the Singapore PI for the interdisciplinary AI research program at Singapore-MIT Alliance for Research and Technology. He received B.S. from Tsinghua University and Ph.D. in Operations Research from MIT. His research focuses on methodologies of analytics and optimization, data-driven decision-making models, machine learning algorithms, and their applications in smart cities, transportation, and logistics systems. He has published in leading journals such as Transportation Science, American Economic Review P&P, M&SOM, Fundamental Research, and Transportation Research Part B/C/E and has long term collaborations with leading companies such as Meituan, Tencent, DiDi, Grab, and Upwork. He serves as Associate Editor for Transportation Science and Service Science, Special Issue Editor for Transportation Research Part B/Part C, and Service Science, and Editorial Board Member for Transportation Research Part C/Part E. Dr. Wang was selected as Chan Wu & Yunying Rising Star Fellow in transportation and mobility, received Lee Kong Chian Research Excellence Award twice, was nominated for MIT’s top graduate teaching award, and won the Excellent Teaching award for junior faculty at SMU. During his Ph.D. studies at MIT, he also served as the co-President of the MIT Chinese Students & Scholars Association and as Chair of the MIT-China Innovation and Entrepreneurship Forum.


Hosts:

DEPARTMENT OF CIVIL ENGINEERING

JOINTLY ORGANIZED WITH 

HONG KONG SOCIETY FOR TRANSPORTATION STUDIES

And INSTITUTE OF TRANSPORT STUDIES, HKU



Markov Decision Processes in Shared Mobility Operation Problems


Speaker:

Dr. Zheng Zhu

Department of Civil Engineering, Zhejiang University, China

 

Date:    December 28, 2023 (Thursday)

Time:   2:00-3:00 pm

Venue:  Room 612B, 6/F Haking Wong Building, The University of Hong Kong

 

Abstract

The supply-demand imbalance of shared mobility (e.g., ride-sourcing and bike-sharing) is one critical factor that leads to passenger queueing and congestion, idle ride-sourcing vehicles, accumulation of shared bikes, low public transit ridership, and high-level travel costs, so that it restricts the mobility efficiency and social welfare of urban transportation systems. Designing spatial-temporal operation strategies (e.g., pricing, (e)bike rebalancing/recharging, ride-sourcing idle vehicle relocation) can be a feasible approach for mitigating the imbalance. However, concerning the coupling mechanism among supply, demand, and operational strategies, it is difficult to seek smart spatial-temporal strategies via conventional modeling and optimization approaches. Recently, with Markov decision processes (MDPs) and reinforcement learning (RL) have received increasing attention, which have the capability of formulating and solving dynamic optimization problems in complex environments. In this presentation, we show several MDPs the research team has developed for depicting and solving spatial-temporal operational problems in the shared mobility market. Aiming at developing smarter shared mobility systems, we would share our knowledge and experiences for a better understanding of similar problems.

 

About the Speaker

Zheng Zhu, “Hundred Talents Program” Professor, Assistant Head of Department of Civil Engineering at Zhejiang University. Research interests include the planning, design, simulation, management/control and optimization of multi-modal transportation systems. From 2008 to 2021, Zheng has been studying and working at Tsinghua University, University of Maryland, Hong Kong University of Science. He is the principal investigator of 1 Hong Kong Research Grants Committee General Research Fund (RGC-GRF), the participant of 1 Major Research Plan of China National Natural Science Foundation. Zheng has participated in research projects funded by many agencies, such as the US department of transportation (USDOT), the US department of energy (USDOE), US National Science Foundation (NSF), US Federal Highway Administration (FHWA), Aspiration Zealous Force Trustworthy (AZFT), Smart Urban Future (SURF) Laboratory, Zhejiang Province. He has published over 50 SCI papers in top transportation journals such as IEEE TITS, TR Part B, POM, TR Part C, and TR Part E. Zheng serves as the area editor in the annual meeting of the Chinese Overseas Transportation Association (COTA) and an editorial board member in Transportation Safety and Environment.


Hosts:

DEPARTMENT OF CIVIL ENGINEERING

JOINTLY ORGANIZED WITH 

HONG KONG SOCIETY FOR TRANSPORTATION STUDIES

And INSTITUTE OF TRANSPORT STUDIES, HKU

© 2023 by Institute of Transport Studies. The University of Hong Kong.
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