Abstract

Commercial vehicle movements compose perhaps 15% of all urban vehicle trips and produce large impacts in key areas, such as congestion, emissions, road wear, and industrial area traffic. A system for modeling such movements was developed for Calgary, Alberta, Canada. It is a novel application of an agent-based microsimulation framework that uses a tour-based approach and emphasizes important elements of urban commercial movement, including the role of service delivery, light commercial vehicles, and trip chaining. The microsimulation uses Monte Carlo techniques to assign tour purpose, vehicle type, next-stop purpose, next-stop location, and next-stop duration. Tours are “grown” with a return-to-establishment alternative within the next-stop purpose allocation, which is consistent with the nature of tour making in urban commercial movements. The Monte Carlo probabilities are established with the use of a series of logit models, with coefficients estimated on the basis of observed behavior of different commercial movement segments. The estimation results in themselves provide insights into the revealed behavior that have not been available previously.

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