Advanced models for improving road operations and safety

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Traffic congestion is reported to cause over 4 billion hours of delay, waste 10.6 billion litres of fuel, and create an economic cost of $87 billion annually in the USA. Comparable national data are not readily available for Canada, but congestion in the Toronto region is estimated to cost more than $6 billion annually and is expected to increase to $15 billion by 2031 in the absence of significant intervention. Twenty five percent of congestion is caused by incidents (such as collisions and spilled loads) and a further 15% is caused by adverse weather. Given the significant costs associated with expanding existing networks to increase capacity, and the staggering costs associated with road congestion, there are substantial economic benefits to better optimizing the use of existing network infrastructure. Existing and emerging technologies, such as crowd sourcing, Connected Vehicles, and Autonomous Vehicles, along with the new data streams these technologies are expected to supply, provide an opportunity to significantly improve traffic operations and safety. The emergence of these new technologies and data streams also presents significant challenges to road authorities in terms of determining the regulations, design guidelines, and practices that are required to maximize benefits in the most cost effective manner. This proposal describes a 5-year research program that builds on the applicant’s previous research accomplishments and existing research strengths, and focuses on developing and evaluating algorithms and methods required for proactive and integrated transportation management. The research program consists of four interconnected themes: 1. Improving traffic conditions monitoring and prediction. 2. Identifying how existing roadway design standards and traffic control guidelines could be changed to optimize the performance of autonomous vehicles. 3. Creating a method for evaluating transportation system improvements in terms of their impacts on travel time reliability. 4. Measuring and modelling the interactions between cyclists and motorized vehicles. The objectives of the proposed research program are to (1) develop and evaluate the above methods, measures, and strategies to improve network capacity, reduce congestion, increase system reliability, and increase safety; (2) transfer the developed knowledge and results to practitioners, road authorities, and the scientific community; and (3) train HQP in the latest methods and techniques so they can continue to foster innovation and advances within the public sector, the private sector, and the academic and scientific community in Canada and abroad.