Les exposés écrits du congrès ont été publiés dans la langue dans laquelle ils ont été soumis à l’ATC.
Efficient planning and design of road freight networks require an understanding of their spatial characteristics and demand patterns. However, the large scale and dense interconnections of these networks pose challenges in accurately representing and analyzing freight movement while ensuring computational efficiency. Public agencies also face difficulties in traffic monitoring, safety analysis, and asset management on a broader scale. This study focuses on the Prairie region of Canada and leverages data from the Canadian Freight Analysis Framework (CFAF) to propose a methodology for network extraction. Using a multi-model traffic assignment approach, the method extracts a sub-network from the original while preserving essential functional features. Results indicate that the proposed approach significantly simplifies the network without compromising structural integrity, offering a robust foundation for practical applications.