28 DEC 2023 (THUR) | 15:00-16:00

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

28 DEC 2023 (THUR) | 14:00-15:00

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

09 NOV 2023 (THUR) | 10:00-11:00

Integrated optimization of bus bridging service design and passenger assignment in response to urban rail transit disruptions

Associate Prof. Yu Zhou

School of Transportation Science and Engineering, Beihang University, China

Date: November 9, 2023 (Thursday)

Time: 10:00am – 11:00am

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

Abstract

As the urban rail transit (URT) system plays an increasingly important role in supporting large cities' mobility around the world, service disruptions have become more prevalent, potentially resulting in severe economic losses and passenger safety issues. It is imperative to investigate effective response strategies to mitigate the effects of such disruptions. In response to URT service disruptions, this paper systematically investigates the bus bridging service design (BBSD) problem, which concerns the integration of bus bridging route design, frequency determination, and passenger assignment in the integrated URT and bus network. The problem is formulated as a path-based integer linear programming (ILP) model with the goal of simultaneously minimizing operator-oriented and passenger-oriented costs. A column generation-based approach is proposed to solve this model efficiently, allowing nonintuitive bus routes to be freely generated on the network dynamically. Our method has been tested with two different case studies based on real data from the Hong Kong Mass Transit Railway (MTR). Experiments demonstrate that our proposed approach can assist public transit (PT) operators in developing efficient emergency response plans for various potential disruption situations in advance. Even in the face of unexpected disruptions that necessitate a quick response, our approach can generate high-quality solutions in a matter of minutes.

About the Speaker

Dr. Yu Zhou is about to join the School of Transportation Science and Engineering, Beihang University as an associate professor. Dr. Zhou’s research interests include (i) public transportation operations and management, (ii) future mobility and (iii) multimodal transportation. Dr. Zhou dedicated his research efforts to addressing fundamental and cutting-edge issues in the field of transportation. His rigorous studies have culminated in the publication of over 30 papers in internationally renowned SCI journals and academic conferences. Notably, Dr. Zhou has taken the lead role, as either the first or corresponding author, in publishing 14 papers in prestigious SCI-indexed journals, including Transportation Research Part B, Part C, Part D, European Journal of Operational Research and Applied Energy. Beyond his published work, Dr. Zhou has actively contributed to the discourse within the global transportation community. He serves as the editorial member of Digital Transportation and Safety. In addition, Dr. Zhou has also been invited to peer review for over ten international journals and top-tier transportation conferences. These include but are not limited to Transportation Science, Transportation Research Part B, Part C, Part D, Part E, Accident Analysis and Prevention, and Computers & Operations Research. He is also a reviewer for prestigious conferences in the transportation field, like the International Symposium on Transportation and Traffic Theory (ISTTT) and TRB meetings.

Hosts:

DEPARTMENT OF CIVIL ENGINEERING

JOINTLY ORGANIZED WITH

HONG KONG SOCIETY FOR TRANSPORTATION STUDIES

And INSTITUTE OF TRANSPORT STUDIES, HKU