Movement of goods and trucks at the transportation system level

Medium and heavy duty vehicles are currently accounting for 21% of the US GHG emissions, a share that is expected to increase in the future. In order to quantify the impact of advanced technologies at the system level (e.g., metropolitan area, state…), Argonne has developed a predictive agent-based freight model framework that captures trade and transport decisions. The novel model (CRISTAL) is a high fidelity representation of fleet decisions, fleet operations and end-to-end shipment and vehicle movements.

Based on extensive datasets, the model represents the supply chain (from raw material suppliers to customers), firms characteristics (facility locations, vehicle fleet…), how goods are moved and the overall impact on operations (e.g., refueling, charging, docking…)

When integrated with POLARIS to include all transportation modes, the tool allows the simulation of all passenger and commercial trips over a 24h period. Autonomie and SVTrip are then used to estimate the energy impact and GREET the overall GHG emissions.

Agent-Based Freight Model Framework