Public transport ridership simulation and railway planning - MTR to Keep Cities Moving
Summary
An AI- and big-data-driven ridership simulation and railway planning project from the HKUST-MTR Joint Research Laboratory, developed to predict travel-pattern changes and support effective resource deployment across Hong Kong's public transport network.
The dynamic simulation digital twin integrates operational data from MTR, bus routes, trams, and ferries to model disruption scenarios, forecast passenger flow, and guide crowd management at interchange stations.
Related Experience
Tech Stack
React.js
Nginx
Docker
Ubuntu
PostgreSQL
Redis
Description
Led through the HKUST-MTR Joint Research Laboratory at the GREAT Smart Cities Institute, this project uses artificial intelligence and big data to simulate and predict changes in citizens' travel patterns, giving operators and planners actionable insights for resource deployment and railway planning.
A dynamic simulation digital twin combines daily operational data from MTR, bus routes, trams, and ferries. By running varied operational scenarios, it forecasts passenger-flow shifts and supports crowd distribution analysis at interchange stations—helping teams implement measures such as deploying additional staff and improving passenger information systems.
Multi-modal digital twin integrating MTR and other public transport modes for end-to-end ridership simulation.
Scenario-based disruption and operations modeling to predict passenger flow impacts and strengthen response strategies.
Crowd management support for interchange stations, including staffing and passenger information decisions.
i) Built predictive modeling for failure scenarios, helping MTR to strengthen response strategies for service disruptions.
ii) Architected and deployed secure, high-performance server infrastructure at the MTR control center.
The project received major accolades at the Hong Kong ICT Awards 2024—including the Smart Mobility (Smart Transport) Gold Award, Best Use of AI Award, Smart Mobility Grand Award, and Award of the Year—plus Winner in Business Data Analytics and Second Runner-up in Transport and Manufacturing at the APICTA Awards 2024. Related work (Metro Maestro) also earned a Gold Medal with Congratulations of the Jury at the 50th International Exhibition of Inventions Geneva.