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Transit Analytics Lab (TAL) Research Day
July 6, 2021 @ 9:00 am - 4:00 pm
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 software providers.
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; 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 a Workshop in December and has been involved in a number of research pursuits, many of which have practical applications.
The time is appropriate to organize a TAL Research Day that will provide a high-level overview of the many research activities being pursued by the TAL team; please see the Draft Program below.
Register on Eventbrite.
Final program (Download program PDF)
09:00 Introduction to the Transit Analytics Lab (TAL)
- Words of Welcome and Introduction to UTTRI’s TAL (Amer Shalaby)
09:20 Transit Analytics Related to Planning, Scheduling, and Customer Behaviour (Moderator: Brendon Hemily)
- Surface Transit Bunching: Understanding the Determinants and Opportunities for Real-Time Prediction (Ehab Diab)
- Use of Smart Card Data to Model Transit Demand (Khandker Nurul Habib)
- Incorporating Service Reliability in Multi-Depot Vehicle Scheduling (Margarita Castro)
- Leveraging Twitter Data to support Transit Planning and Operations (Rami Al-Sahar)
- Navigating the Network: Understanding Transit Users’ Information-Seeking Behaviour using Trip Planning Data (Lisa Li)
10:35 Break
10:50 Operations Analytics to Improve Reliability (Moderator: Amer Shalaby)
- Data-Driven Analysis of Service Reliability and its Determinants: Machine Learning Approach (Diego Da Silva)
- Using Delay Logs and Machine Learning to Support Passenger Railway Operations (Willem Klumpenhouwer)
- DASH-Bus Planner: A Toolkit for Deployment and Assessment of Bus Bridging Strategies (Alaa Itani)
- Two-Way Transit Signal Priority Algorithm for Optimizing Transit Reliability and Speed: A Deep Reinforcement Learning Approach (Wenxun Hu)
12:00 Lunch Break
12:20 Lunch Activity – “History of Public Transit in Toronto” Video
12:45 Keynote Presentation: Transit Data and Beyond: Emerging Landscapes (Brendon Hemily, Senior Advisor, TAL)
1:30 Transit Analytics to Support Equity and Policy (Moderator: Amer Shalaby)
- A Comprehensive Transit Accessibility and Equity Dashboard (Willem Klumpenhouwer)
- Bus On Time Performance, Equity and Wellbeing: What We Know and What We Need To Find Out (Matthew Palm)
- Evaluating the Equity Implications of Ride-hailing Through a Multi-Modal Accessibility Framework (Steven Farber)