The Transit Analytics Lab (TAL) at Mobility Network hosted "Workshop on Rail Analytics and Simulation Research" on January 26, 2023.
Mobility Network is a leader in rail-related research on the use of analytics and simulation tools to enhance planning and operations. The free half-day online workshop provided an overview of recent research activity and a platform for thoughtful discussion.
The worskshop was divided into sessions looking at operations analytics to improve rail performance, other rail-related research, and future rail research needs.
Attendees provided positive feedback on the event, commenting that the workshop was well-organized; the research presented was very interesting and relevant work; and the discussions and Q & A generated useful insights.
You are invited to explore the presentation decks, resources, and references shared by presenters, and watch the event video recording below.
Introduction to the Transit Analytics Lab (TAL) and Rail Analytics Research at the University of Toronto
- Words of Welcome and Update on TAL Activities (Amer Shalaby)
Operations Analytics to Improve Rail Performance
- Nexus: An Agent-Based Simulation Platform for Planning and Management of Multi-modal Transit Systems (Siva Srikukenthiran)
- Nexus: Sample Use Cases (Amer Shalaby)
- SPUR: Modular, Data-Driven Mesoscopic Simulator to analyze Stochastic Railway Networks (Peter Lai)
- Using Delay Logs and Machine Learning to Support Passenger Railway Operations (Willem Klumpenhouwer)
Other Rail-Related Research
- Using Customer Facing Wi-Fi Data for the Analysis of Subway Service Performance and User Experience (Aidan Grenville)
- Modelling Origin-Destination Demand in Toronto's Subway Network using Wi-Fi and AFC Data (Diego Da Silva)
A Discussion of Future Rail Research Needs
- Comments and Thoughts (Kenny Ling)
- Open Discussion
Resources and references
Note: If you are unable to access the listed papers, please reach out to the authors for a copy.
- The codebase for Spur is open and available. If you're a GitHub user feel free to star or follow along with the development: https://github.com/transit-analytics-lab/spur.
- Pu, Y. & Srikukenthiran, Siva & Morrow, E. & Shalaby, Amer & Klumpenhouwer, Willem. (2022). Capacity Analysis of a Passenger Rail Hub Using Integrated Railway and Pedestrian Simulation. Urban Rail Transit. 8. 10.1007/s40864-021-00162-7.
- Klumpenhouwer, W., & Shalaby, A. (2022). Using Delay Logs and Machine Learning to Support Passenger Railway Operations. Transportation Research Record, 2676(9), 134–147. https://doi.org/10.1177/03611981221085561.
- Scoping Paper on Transit System Innovation and Research Efforts. March 2022. Prepared for the Advanced Public Transit Systems (APTS) Technical Committee of ITS Canada by Brendon Hemily, PhD, Chair, APTS Committee. Email: firstname.lastname@example.org.
- Aboudina, A., A. Itani, E. Diab, S. Srikukenthiran and A. Shalaby. (2021). Evaluation of Bus Bridging Scenarios for Railway Service Disruption Management: A Users’ Delay Modelling Tool. Public Transport, 13(3):457-481.
- Srikukenthiran, S., and A. Shalaby. (2017). Enabling Large-scale Transit Microsimulation for Disruption Response Support using the Nexus Platform, Journal of Public Transport, 9(1-2):411-435. https://doi.org/10.1007/s12469-017-0158-y.
- King, D., S. Srikukenthiran and A. Shalaby. (2014). Using Simulation to Analyze Crowd Congestion and Mitigation Measures at Canadian Subway Interchanges: Case of Bloor-Yonge Station, Toronto, Ontario. Transportation Research Record: Journal of the Transportation Research Board, 2417:27-36. https://doi.org/10.3141/2417-04.
Watch the video recording of "Workshop on Rail Analytics and Simulation Research at the University of Toronto Mobility Network"
About the Transit Analytics Lab (TAL)
The Transit Analytics Lab (TAL) of the University of Toronto was established in 2020 with University of Toronto funding from the Faculty of Applied Science & Engineering Dean’s Strategic Fund. It is headed by Professor Amer Shalaby, an expert in urban public transit.
TAL brings together:
- Transportation and technology researchers from across the University of Toronto;
- Transit systems in the Greater Toronto & Hamilton Area; and
- Private sector software providers.
TAL aims to undertake a wide range of activities including research and development, creation of a data analytics platform, workshops, an international symposium, education, and professional development training.