Optimal Deployment of Vision Zero Road Safety Strategies

这项研究将与多伦多市和微交通两个合作组织一起，调查新出现的和现有的道路安全战略，目标是信号交叉口的脆弱道路使用者(骑自行车的人和行人)。利用多伦多市和其他城市提供的视频数据和计算机视觉微交通的技术优势，赖尔森团队将开发和应用先进的分析方法和工具，以评估与以下目标道路安全策略的最大好处相关的设计和运营环境：-自行车道设计，将与右转车辆运动的冲突降至最低；-充分保护车辆左转作为行人和骑自行车者的一种安全措施；-左转平静，导致转弯速度较慢，行人和骑自行车者的能见度更高；-提高十字路口和人行横道；除了对学生进行道路安全分析方面的高级建模技术培训外，该项目成果还将拯救生命，减少伤害，为加拿大日益拥堵的城市提供更安全的道路。预计多伦多市政府将利用这些结果来优化他们的数据驱动的Vision Zero计划，并重新制定他们的设计指南和交通项目的标准实践。微交通公司将使用他们的软件来处理该市的视频馈送，并向莱尔森研究团队提供关于交通冲突和车辆速度的数据，并使用开发的模型来调整他们的平台测量代理安全数据的方式。

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.