The Transit Analytics Lab (TAL) of the University of Toronto, established in 2020 with University of Toronto funding from the Faculty of Applied Science and Engineering Dean’s Strategic Fund, is headed by UTTRI associated faculty Professor Amer Shalaby, an expert in urban public transit.
The Transit Analytics Lab 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.
The Transit Analytics Lab builds on the strength of UTTRI, one of Canada’s largest transportation research institutes and a recognized world leader in developing analytical tools and models of transport demand and performance.
It will 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.
It will facilitate:
- Fostering innovation in transit data-driven tools (analytics) using advanced methods of data science, machine learning, artificial intelligence, simulation and statistics;
- Developing standards & integration methods to accelerate the advancement of transit analytics;
- Training of U of T students (across the university) in advanced data-driven methods and their application to public transit decision-making;
- Exposing the professional community through knowledge transfer activities to advanced analytics;
- Establishing U of T as a national and international leader in transit data analytics.
Transit agencies today are confronted with unprecedented levels and types of transit ITS data, which call for effective processes and methods to transform such data into useful information. The volume and complexity of transit ITS data and the need for innovative processes will become an even greater challenge as initiatives of smart cities and connected vehicles and infrastructure continue to gain momentum
Envisioned as a “live” lab for Big Data transit analytics, the Transit Analytics Lab will also serve as a collaborative research forum, with the aim of promoting data-driven decision-making and improvements to user experience.
Professor Amer Shalaby, Department of Civil and Mineral Engineering
Phone: (416) 978-5907