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Title: Tactical Operations of Service Region Dimensioning, Bundling, and Matching for On-Demand Food Delivery Services

Speaker: Mr. Kaihang Zhang (Department of Civil Engineering)

Date: Feb 27, 2025 (Thursday)

Time: 4:00 pm - 5:00 pm

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


About the talk: On-demand food delivery (OFD) services have experienced a significant surge in popularity in recent years, which poses various challenges for service operators. To address these challenges, we discuss an analytical model that captures the complex interplay of the OFD system by considering factors such as adjustable service region size and order bundling. We investigate how key decision variables, including maximum delivery distance and bundling ratio, affect the system's endogenous variables and two critical system performance metrics: customer total waiting time and order throughput. Our analysis yields several intriguing managerial insights. First, the maximum delivery distance has a non-monotonic impact on the customer accumulation time, delivery time, and total waiting time, and there is a “win-win” situation in which increasing the maximum delivery distance benefits both the customer total waiting time and order throughput. Second, order bundling is crucial under high customer demand to ensure adequate food delivery supply, but it is less desirable under low customer demand due to increased detour distances in delivery. We further explore strategies for minimizing customer total waiting time (by setting small service regions and bundling ratios) and order throughput (by establishing larger service regions). Recognizing the partial conflict between these two objectives, we identify the Pareto-efficient frontier that serves as a guideline for service operators in balancing these competing goals.


About the speaker: Kaihang Zhang is currently a PhD candidate at The University of Hong Kong supervised by Dr. Jintao Ke. He is a student member of INFORMS, ITS of HKU, and the recipient of Hong Kong PhD Fellowship and HKU Presidential Scholarship. He has been developing economic analytical models and network flow models throughout his PhD study at HKU on the operations for on-demand urban mobility systems. During his time at HKU, he worked as a visiting research student at LIMOS, University of Michigan, working on the development of data-driven analytical model for food delivery services. He has Bachelor’s Degrees from Zhejiang University and UIUC, and a Master’s Degree from UC Berkeley.






This seminar is jointly organized by MTR, the Department of Data and Systems Engineering, Department of Civil Engineering, Institute of Transport Studies, The Edge, and Inno Wing Two.


Smart Railway Transformation with Data & New Technologies


Speaker:

Benny Ng, Acting Chief Digital Development Manager (Smart Operating), MTR;

Jackson Wu, Acting Lead Design Manager – Smart Maintenance, MTR.

Date:    Mar 6, 2025 (Thursday)

Time:   10:30 am – 12:30 am

Venue:  Innovation Wing Two, The University of Hong Kong


Abstract

In this talk, the speakers will introduce the innovation and technology development framework for Hong Kong Transport Services. They will also introduce examples of applications and utilization of data and new technologies for smart railway transformation. Finally, they will share experience on the key challenges, opportunities and required skills for exploring, development and application of data and smart technologies.

 

Group Photo
Group Photo

Mr. Benny Ng and Mr. Jackson Wu
Mr. Benny Ng and Mr. Jackson Wu

Dr. Yong-Hong Kuo - Opening
Dr. Yong-Hong Kuo - Opening


Mr. Jackson Wu delivering talk
Mr. Jackson Wu delivering talk

Mr. Benny Ng delivering talk
Mr. Benny Ng delivering talk

Q&A Session
Q&A Session



Autonomous driving: Embracing the era of large-scale commercialization


Speaker:

Dr. Luyi Mo

Vice President of Pony.ai

Date:    Feb 13 (Thu), 2025

Time:   5:00pm – 6:00pm

Venue:  Tam Wing Fan Innovation Wing Two, G/F Run Run Shaw Building, HKU



Abstract

The popularization of autonomous driving technology has brought significant changes to people's modes of transportation and lifestyles, and has also introduced new growth points for the automotive industry. We are witnessing the rapid iteration of autonomous driving technology and the continuous expansion of its application scenarios, while also facing many challenges. Starting from 2023, several cities in United States and China allowed fully driverless Robotaxi operating to the general public and hence the commercialization of Robotaxi business is accelerating. This speech aims to explore how to continuously drive industrial transformation and achieve large-scale commercialization of autonomous driving, especially Robotaxi, based on the technology and commercial practice of Pony.ai.


Speaker's Bio

Dr. Luyi Mo is a Vice President of Pony.ai, a global leader in the large-scale commercialization of autonomous mobility. She is responsible for overseeing Pony.ai's Guangzhou and Shenzhen offices as well as its Robotaxi service and operation. She successfully led the team to deploy China's first Robotaxi service in 2018 and continuously drove the efforts to make Pony.ai as the first company to operate fully driverless Robotaxi service in all tier-1 cities in China. Prior to joining Pony.ai, Dr. Mo worked as a senior software engineer at NetEase, specializing in game engine development. Dr. Mo holds a bachelor’s degree in mathematics from Zhejiang University and a Ph.D. in computer science from the University of Hong Kong. During her time in university, Dr. Mo was the first female world champion from China since 1977 at the 35(th) Annual ACM International Collegiate Programming Contest World Finals in 2011.


ITS Director, Prof. W.Y. Szeto presenting Dr. Luyi Mo a souvenir for appreciation.
ITS Director, Prof. W.Y. Szeto presenting Dr. Luyi Mo a souvenir for appreciation.
Prof. Reynold Cheng introducing the speaker, Dr. Luyi Mo
Prof. Reynold Cheng introducing the speaker, Dr. Luyi Mo
Dr. Luyi Mo delivering seminar.
Dr. Luyi Mo delivering seminar.
Dr. Luyi Mo explaining the view of the Robotaxi.
Dr. Luyi Mo explaining the view of the Robotaxi.
Q&A Session
Q&A Session
Q&A Session
Q&A Session
Group photo with all participants
Group photo with all participants


 

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