The Transit Analytics Lab hosted its second annual Research Day virtually on July 6, 2022.
The day’s program featured sessions on transit analytics related to planning and scheduling; operations analytics to improve rail performance; transit analytics applications from the field; and transit analytics to support policy and equity.
TAL’s Director, Professor Amer Shalaby, and Senior Advisor, Dr. Brendon Hemily, moderated the day’s sessions.
Featured guest speakers
Graham Cavanagh, Senior Planner, New Mobility Policy & Strategy, TransLink, gave the keynote presentation “TransLink Tomorrow; Promoting Innovation in Transit through Collaboration on Research.”
Eric Lind, Manager, Research & Analytics, Metro Transit, presented “Guests Using Data and Analytics at Metro Transit.”
Catherine Vanderwaart, Strategic Planning Advisor, Office of Planning, Washington Metropolitan Area Transit Authority (WMATA) presented “Applied Planning Intelligence at WMATA.”
U of T presentations
Over the course of the day, thirteen U of T students and postdoctoral fellows from the Department of Civil & Mineral Engineering and the Department of Geography & Planning presented their recent and/or ongoing research.
Transit Analytics Related to Planning and Scheduling
- Planning Integrated On-Demand and Scheduled Bus Transit Services: Guiding Principles (Alaa Itani)
- Incorporating Service Reliability in Multi-Depot Vehicle Scheduling: Stochastic Optimization Approach (Margarita Castro)
- Transfer Synchronization in Transit Networks: Stochastic Programming Approach (Zahra Ansarilari)
- Advanced Real-Time Transit Management Strategies in Mixed-Traffic Arterials (Kareem Othman)
- Coordinated and Bi-Objective Transit Signal Priority (TSP): Optimization Using a Deep Reinforcement Learning Approach (Wenxun Hu)
Operations Analytics to Improve Rail Performance
- Using Customer Facing WiFi Data for the Analysis of Subway Service Performance and User Experience (Aidan Grenville and Willem Klumpenhouwer)
- Modelling Origin-Destination Demand in Toronto’s Subway Network using Wi-Fi and AFC Data (Diego Da Silva and Feras Elsaid)
- Disruption Delays in Nanjing Urban Rail Transit Network: Analysis of Disruption Duration and Frequency (Jinyi Chen)
- Analyzing Stochastic Railway Networks Using Event-Based Mesoscopic Simulation (Willem Klumpenhouwer)
Transit Analytics to Support Policy and Equity
- Potential Policy Analyses Using the Equity Dashboard Platform (Willem Klumpenhouwer and Diego Da Silva)
- An Equity Evaluation of Bus Prioritization Measures within the Toronto Transit Commission’s 5-year Service Plan & 10-year Outlook (Alex Tabascio)
- Assessment of Toronto Transit Network Resilience and Effects on Social Equity (Rick Liu)
- Investigating the Impact of COVID-19 on Post-Pandemic Transit Demand (Sk. Md. Mashrur)
About the Transit Analytics Lab
The Transit Analytics Lab (TAL) of the University of Toronto brings together transportation and technology researchers from across the University of Toronto, transit systems in the Golden Horseshoe area, and private sector technology providers and consultants.
Among its objectives are to: foster innovation in transit data-driven tools (analytics) using advanced methods of data science, machine learning, artificial intelligence, simulation and statistics; expose the professional community through knowledge transfer activities to advanced analytics; build collaborations with public and private organizations; and establish U of T as a national and international leader in transit data analytics.
TAL was launched in 2020 with the International Symposium on Automated Transit Data. Since then, TAL has organized workshops and has been involved in a number of research pursuits, many of which have practical applications.