Behavior-Based Supply Chain and Freight Transportation Model

RS&H led a team in developing a supply chain and logistics freight model for the Phoenix and Tucson, Arizona metropolitan regions. The project was part of FHWA SHRP2 C20: Freight Demand Modeling and Data Improvement Strategic Plan for the Maricopa Association of Governments (MAG). The main purpose was to develop a cutting-edge regional behavior-based freight model based on the identified principles in the SHRP2 C20 plan to improve the understanding of decision-making by freight agents and their implications for network modeling.

The project covers the Arizona Sun Corridor, which is among the fastest growing megaregions in the country and a freight gateway to the international market; hence, it is of significant importance to the MAG region and will be consistent with the MAG freight flows forecasting needs.

In this framework, the team evaluated international and domestic commodity flows for individual shipments. This is an agent-based model that incorporates robust behavioral theoretic approaches to capture business response to infrastructure, operational, and other changes in freight and transportation system. The framework utilizes multimodal supply chain and logistics modeling components to capture a range of freight movements and supply chain related choices for different commodities, types and size of firms, transportation modes, and geographies along the chain. The team combined the resulting model with a truck touring model and then evaluated truck vehicle-miles traveled, air quality, congestion, and other critical freight movements’ measures.

The project was selected the “Best Data Fusion Application” from a pool of 20 other applications United States by the Transportation Research Board (TRB) planning committee for the Innovations in Freight Data Workshop.

Project Details

Description Transportation
Planning & Environmental
Transportation/Corridor Planning
Urban & Regional Planning
Location Phoenix, AZ
Client/Owner Maricopa Association of Governments


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