A time-dependent freight tour synthesis model

• Proposes a freight demand model to estimate tour flows from traffic counts.
• Incorporates the time-dependent tour behavior of freight vehicles.
• Proposes a multi-attribute value function to assess the tradeoffs among objective functions.
• Assesses the ability of the model to replicate actual values using Denver as a case study.

This paper introduces a model of urban freight demand that seeks to estimate tour flows from secondary data sources e.g., traffic counts, to bypass the need for expensive surveys. The model discussed in this paper, referred as Freight Tour Synthesis (FTS), enhances current techniques by incorporating the time-dependent tour-based behavior of freight vehicles, and the decision maker’s (e.g., metropolitan planning agency planner) preferences for different sources of information. The model, based on entropy maximization theory, estimates the most likely set of tour flows, given a set of freight trip generation estimates, a set of traffic counts per time interval, and total freight transportation cost in the network. The type of inputs used allows the assessment of changes in infrastructure, policy and land use. The ability of the model to replicate actual values is assessed using the Denver Region (CO) as a case study.