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A resilient, fluid, and safe road freight transport system is essential for sustaining and growing the industry sectors that drive the economy of the Canadian Prairie and Northern Region. The region’s road network is expected to serve the demand for truck transportation through widely varying geographic and climatic conditions. Physically and operationally, the network is sparse, features low redundancy, is subject to seasonal changes, has low volumes, and contains high-speed roads and at-grade intersections. These features make it prone to risks and hazards (e.g., warming winters, periodic flooding, on-road incidents, extreme weather events), which can disrupt supply chain fluidity. The proposed research: (1) produces uniquely-Canadian logistics data sets through the development and deployment of a leading-edge mobile truck traffic and road-weather monitoring facility; and (2) develops and applies Artificial Intelligence (AI) based frameworks to assess regional freight network resilience, fluidity, and safety subject to different types of natural and man-made risks and hazards including warming winters, flooding, transportation of hazardous materials, adverse road-weather conditions.
