Graduate student Tara Saeidi participated in the TransitData 2026 Conference, held virtually by the University of Toronto’s Transit Analytics Lab from June 22–25, 2026. Tara presented our research, “AI‑Driven Zoning Optimization for Elderly‑Focused Demand‑Responsive Transit: A Reinforcement Learning–Guided Genetic Algorithm Applied to Winnipeg, Canada,” during Session 8C: On‑Demand Transit, moderated by Dr. Amer Shalaby. Delivered as a six‑minute lightning talk, her presentation introduced our RL‑guided GA framework for optimizing demand‑responsive transit service zones to better support elderly populations in Winnipeg.
The opening plenary highlighted the work of the Transit Analytics Lab and underscored the expanding role of data analytics in transit planning and operations. Subsequent plenary sessions—Transit Data and Applied Analytics, Transit Agencies Using Data, Transit Agency–Academic Collaboration, and AI in Transit—emphasized the growing integration of AI, data‑driven decision‑making, and collaborative approaches between academia and transit agencies.
Conference video features also offered an engaging overview of the history and evolution of public transit in Canada, showcasing major milestones in transit development and the increasing influence of data‑driven innovation.