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Toronto Subway Station Barriers Aren't Enough to Keep Riders Safe: Transit Group
The agency will also use artificial intelligence to predict track intrusions and expand visible staffing, as officials seek lower-cost safety upgrades before wider platform-door installation.
On Wednesday, Toronto Mayor Olivia Chow announced a pilot project to install steel barriers and AI-assisted track detection at TMU Station, aiming to reduce track intrusions at the high-traffic downtown location.
A TTC report acknowledges that platform edge doors offer the highest safety level but cost $50 million per station, whereas steel barriers and AI systems provide a lower-cost, faster-to-implement alternative at approximately $2 million per station.
TTC CEO Mandeep Lali explained the AI system uses data to build an algorithm predicting track intrusion probability in real-time, while waist-high steel guardrails similar to New York City's subway system physically deter access.
Commissioners will review the plan at a board meeting on June 3, and the transit agency intends to expand these safety measures to four additional stations next year, pending resource availability.
August Puranauth of advocacy group TTCriders praised the plan but argued it falls short of full platform doors riders demand, while mayoral candidate Brad Bradford criticized the announcement as "empty promises" during election season.