Improving roadway operations and safety considering vulnerable road users and emerging technologies

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There is critical need to improve the safety and efficiency of the transport of goods and people. On average, in Canada, 16 people are admitted to hospital and 6 people are killed each day because of a traffic collision and the annual economic cost of collisions is estimated to exceed $40 billion annually. Furthermore, urban mobility patterns, needs, and options are profoundly changing because of three factors. First, travel patterns are changing with increasing adoption of remote work, declining public transit ridership, and changes in desired location of principle residence. These changes have been dramatically accelerated and amplified by the COVID-19 pandemic but are likely to persist. Second, technological developments are rapidly expanding transportation options and altering travel patterns. Personal mobility patterns are being transformed by autonomous/semi-autonomous vehicles (e.g. Tesla's "Full Self Driving" and Waymo's autonomous taxi service) and by a wide range of personal mobility vehicles/devices (e.g. electric bikes, skateboards, scooters, etc). Freight transportation and goods deliveries are also experiencing dramatic technological transformations including last mile delivery robotic vehicles (e.g. Amazon's Scout). Third, there has been a rapid growth in the variety and coverage of transportation system and mobility data (collectively called smart city data). Transportation system managers and elected decision makers are tasked with the responsibility to plan, construct, and manage our road and public transportation systems to provide safe, equitable and efficient transport of goods and services while minimizing negative environmental impacts. However, given the rapid changes in mobility options and technologies, travel patterns, and smart city data, there is a lack of knowledge and tools by which plans and policies can be evaluated and systems can be actively managed. This proposal describes a 5-year research program that builds on the applicant's previous research accomplishments and existing research strengths and focuses on advancing methods and knowledge for improving roadway operations and safety in the context of emerging mobility options and smart city data, with a particular emphasis on vulnerable road users (pedestrians and cyclists). The research program consists of three key objectives as follows: 1.Improve road safety network screening (NS) through the application of AI 2.Develop more accurate methods for estimating exposure of vulnerable road users for planning and safety modeling 3.Identify better urban roadway designs and traffic controls through the development and application of advanced simulation models This program will train 4 PhD and 4 Masters students in high demand areas of transportation engineering, road safety and data analytics, and will result in advanced techniques for use by researchers and practitioners to improve safety and efficiency of Canadian urban road networks.