Optimal Deployment of Vision Zero Road Safety Strategies

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The research will investigate emerging and existing road safety strategies targeted at vulnerable road users (cyclists and pedestrians) at signalised intersections, with two partner organisations, the City of Toronto and MicroTraffic. Using data derived from videos provided by the City of Toronto and other cities and the technological strength of MicroTraffic in computer vision, the Ryerson team will develop and apply advanced analytical methods and tools to the video-derived data to assess the design and operational circumstances associated with the greatest benefits of the targeted road safety strategies such as the following:- bike lane designs for minimising conflicts with right turn vehicular movements;- fully protected vehicular left turns as a pedestrian and cyclist safety measure, as an alternative to leading pedestrian/bicycle intervals;- left turn calming that results in slower turning speeds and better visibility of pedestrians and cyclists;- raised intersections and crosswalks; and- right turn channel designs.Apart from training students in advanced modelling techniques in road safety analysis, the project outcomes will save lives and reduce injuries in contributing to safer roads in Canada's increasingly congested cities. It is expected that the City of Toronto will use the results to optimise their data-driven Vision Zero program as well as re-formulate their design guidance and standard practices for transportation projects. MicroTraffic will use their software to process the City's video feeds and provide data to the Ryerson research team on traffic conflicts and vehicle speeds, and use the developed models to adapt the way their platform measures surrogate safety data.