MTR Corporation / The Hong Kong University of Science and Technology
| Items | Content |
|---|---|
| Year | 2024 |
| Awards |
|
| Name of Entry | Public transport ridership simulation in railway planning – MTR to Keep Cities Moving |
| Description |
The solution involves creating a large-scale dynamic simulation model of Hong Kong’s public transport to predict passenger flows and enhance railway planning.
|
Description
In railway operations, the knowledge to visualize passengers’ need and behaviours is imperative for station and traffic management, and effective deployment of resources to provide seamless customer journey.
HKUST had built and advanced a large-scale dynamic simulation model for Hong Kong’s public transportation system, including MTR, bus, mini-buses, trams and ferries. MTR provided over 6 million daily station entry-exit trips of more than 8000 station pairs within the network for calibration. This agent-based digital twin is currently the largest model of its type having been developed for Hong Kong, and able to simulate the daily trips of over 4 million active travellers within the city.
Use case: The digital twin was successfully applied to simulate the effects of a planned partial closure of Kwun Tong Line on 28th July 2024 (7-28), whereby MTR endeavoured to minimize impact to passengers with all stations remained in service. This agent-based model allowed us to configure changes to our network in simulation of 7-28 traffic, to generate actionable data and operational insights.
This ridership forecast confers MTR the intelligence that facilitates a systematic decision-making process for railway planning, it is also a powerful showcase of industrialization of the HKUST-MTR Joint Research Laboratory R&D endeavours, that empowers MTR to “Keep Cities Moving”.
(Information is provided by awardee)
Comments from Judging Panel
This solution excellently demonstrates how to combine open data with MTR passenger data to adjust simulation models, achieving better traffic management. This helps improve the efficiency of the transportation system, bringing benefits to society as a whole.