HKSTS 2025 Pre-Conference Workshop: International Symposium on Smart Mobility Systems

2025 International Symposium on Smart Mobility Systems

Pre-Conference (HKSTS) Workshop

Jointly organized by

Department of Civil Engineering & Department of Data and Systems Engineering & Institute of

Transport Studies, The University of Hong Kong

The Hong Kong Society for Transportation Studies (HKSTS)

Engineering Management (originally named as Frontiers of Engineering Management), a Springer Nature journal supervised by the Chinese Academy of Engineering

Date: 6 December 2025 (Saturday)

Time: 13:00 – 18:00

Venue: CPD-3.04, Centennial Campus, Central Podium Levels - Three (CPD-3, Run Run Shaw

Tower), The University of Hong Kong

Aims and Scopes

This workshop centers on Smart Mobility, emphasizing the integration of advanced technologies

and intelligent systems to create efficient, sustainable, and user-centric transport solutions. With the rise of emerging modes such as urban air traffic and shared autonomous vehicles, new challenges are reshaping traffic operations and planning. The workshop aims to foster discussion on innovative approaches that enhance mobility accessibility and system resilience. We welcome both local and overseas scholars to attend the workshop for exchanging their ideas and insights!

Co-chairs

Dr. Jintao KE (kejintao@hku.hk), Department of Civil Engineering, The University of Hong Kong

Dr. Fangni ZHANG (fnzhang@hku.hk), Department of Data and Systems Engineering, The

University of Hong Kong

Dr. Ryan C. P. WONG (cpwryan@hku.hk), Department of Civil Engineering, The University of

Hong Kong

Secretary

Dr. Bin ZHOU (binchou@hku.hk), Department of Civil Engineering, The University of Hong Kong

Registration: free admission but registration is required (Click Here). All are welcome. When you enter HKU,

please show the registration confirmation page to the campus guard.

Registration QR Code

Tentative Workshop Programme on 6 December 2025

13:00-13:05 Opening Address by Dr. Jintao Ke

13:05 –13:45 Sensitivity of ITS Learning Models with Mobility Data- applications in transportation privacy and cybersecurity by Xuegang Ban, William and Marilyn Conner Endowed Professor, Department of Civil and Environmental Engineering, The University of Washington

13:45 –14:25 Exact Methods through Decomposition: Insights from Logic-Based Benders Decomposition by Roberto Baldacci, Professor, College of Science and Engineering, Hamad Bin Khalifa University

14:25 – 15:05 Physics-informed data analytics - exploiting domain knowledge with hard data in a transportation network by Yueyue Fan, Professor, Department of Civil and Environmental Engineering, University of California, Davis

15:05 – 15:45 From Self-Driving to Self-Organizing: Connected Vehicles as Catalysts for Smart Mobility by Lina Kattan, Professor, Schulich School of Engineering, University of Calgary

15:45 – 16:00 Break

16:00 – 16:40 Disturbance Mitigation Strategies for Scheduled Mobility Systems by Fang He, Tenured Associate Professor, Department of Industrial Engineering, Tsinghua University

16:40 – 17:20 Coordinated urban logistics: Combining public transit and drones for efficient distribution by Kai Wang, Associate Professor, School of Vehicle and Mobility, Tsinghua University

17:20 – 18:00 Joint Online Freight Allocation and Train Unit Scheduling with Reusable Resources for Emergency Logistics by Jiateng Yin, Professor, School of Systems Science, Beijing Jiaotong University

For abstracts and biographies of speakers and more details, please check the details here.

2025 HKSTS pre-conference workshop programme.pdf

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5 Dec 2025 (Fri) 17:00-18:00 | Seminar by Dr. Ghim Ping Raymond ONG

Advances in Micromobility, Fleet Electrification, and Autonomous Mobility: Insights from Singapore

Speaker:

Dr. Ghim Ping Raymond ONG

Department of Civil and Environmental Engineering

National University of Singapore

Date:    Dec 5, 2025 (Friday)

Time:   5:00 pm – 6:00 pm

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

Abstract

This seminar highlights recent advances in data-driven and intelligent approaches for enhancing multimodal urban transport systems. The discussion begins with micromobility and multimodal operations, where agent-based simulation, equity-centred network design, and graph neural network techniques are used to examine how individual travel behaviour, built-environment characteristics, and sparse sensor networks influence accessibility, demand patterns, and congestion propagation. The focus then shifts to the electrification of vehicle fleets, drawing on studies of electric bus operations that account for charging constraints, battery degradation, service reliability, and route-specific energy requirements. Trajectory-based analyses of electric taxi operations further reveal how spatial–temporal variations in driving patterns and energy consumption affect large-scale fleet electrification strategies. The seminar concludes with recent investigations into autonomous and intelligent mobility, including microscopic analyses of interactions between autonomous and human-driven vehicles that shed light on safety-critical behaviours and the infrastructure needed to support emerging vehicle technologies. Together, these studies demonstrate how data-centric, behaviourally informed, and operationally grounded approaches can contribute to the development of more resilient, efficient, and equitable multimodal transport systems.

About the speaker

Dr. Ghim Ping Raymond Ong is the Dean’s Chair Associate Professor and Deputy Head (Research & Enterprise) in the Department of Civil and Environmental Engineering at the National University of Singapore. His research focuses on sustainable pavement engineering, and multimodal transport infrastructure and operations, with recent work spanning micromobility systems, electrified vehicle fleets, land use-transport modelling, and autonomous mobility. He serves on Singapore’s Road Safety Council, the Land Transport Authority’s Panel of Expert Advisors, and national committees on pavement engineering, railway systems, and intelligent transportation standards. He also holds editorial appointments in several leading international journals, including Transportation Research Part E and International Journal of Transportation Science and Technology.

Student Seminar by Ms. Xinyi Zhu on Nov 26, 2025, 1PM

Title: Resource allocation for an air-rail-integrated co-modality platform considering both demand and supply uncertainties

Speaker: Ms. Xinyi Zhu (Department of Aeronautical and Aviation Engineering, Hong Kong Polytechnic University)

Date: Nov 26, 2025 (Wednesday)

Time: 1:00 pm - 2:00 pm

Venue: Room 8-28, Haking Wong Building, The University of Hong Kong

Registration Link: https://forms.office.com/r/1nLK1SMMHh 

ITS Student Committee will provide light refreshments and drinks for registered participants.

Abstract: The co-modal mode, i.e., passenger-and-freight mixed transportation, has received increasing interest, given the rapid growth of parcel volume and its potential to save transportation costs. This paper examines an air-rail-integrated co-modal mode that utilizes the excess capacity of passenger trains and flights considering uncertainties in both supply and demand. On the supply side, uncertainty arises from travel time delays of passenger trains and flights. On the demand side, while historical data on cargo orders are available, such as volume distribution between each origin and destination pair, the daily cargo orders/demands remain uncertain and will be revealed in real-time. We aim to dynamically allocate these resources (excess capacity of trains and flights) to serve cargo orders while effectively accommodating uncertainties. To address this problem, a two-stage stochastic programming model is developed to minimize the total costs associated with cargo transportation, holding, transshipment, delays, and ad-hoc service options (when the co-modal mode is unavailable). The sample average approximation solution approach, embedded with an adaptive large neighborhood search algorithm, is employed to solve the problem. The above model and algorithm are implemented in a rolling horizon framework to make time-dependent resource allocation decisions. The test instances are generated based on rail and air transportation data in Hong Kong (with Hong Kong West Kowloon Station and Hong Kong International Airport). Numerical studies and sensitivity analysis are conducted to evaluate (i) the benefits of the air-rail-integrated co-modality, (ii) the effectiveness of the proposed solution algorithm, and (iii) the impact of demand/supply characteristics on the air-rail-integrated co-modality operation.

Bios: Xinyi Zhu is a third-year Ph.D. candidate in the Hong Kong Polytechnic University. She had previously received her master's degree from Shanghai Jiao Tong University in 2023 and her bachelor's degree from Dalian Maritime University in 2020. Her research centers on transportation modeling, with a particular focus on multimodal transport network design under uncertainty. Her research has been published in transportation journal such as Transportation Research Part C, and has presented her work at major international conferences, including POMS International Conference in China (POMS China), the International Conference of the Hong Kong Society for Transportation Studies (HKSTS), and the Air Transport Research Society (ATRS) World Conference.