Selecting Freight routes and modes that minimize environmental impacts.

Principal Investigator: Dr. Michael Robinson

Abstract:
The transportation sector is responsible for 30% of all greenhouse gas emissions in the United States.  Despite comprising only slightly more than 5% of all vehicles, commercial trucks contribute more than 20% of the transportation sector total.  This project integrates existing emission models and commercial transportation simulations (microscopic, mesoscopic, and macroscopic) to estimate emissions produced by FHWA vehicle class 9 trucks (i.e., large trucks). Assessments of emissions will be made using a microscopic transportation simulation of a small, representative urban transportation network at the city block level. Then the work will be expanded to the regional level using a mesoscopic or macroscopic simulation.   Forecasts will consider a variety of road characteristics, including signalized and non-signalized intersections, changes in gradient, varying speed limits, congestion, and acceleration/deceleration due to merging traffic. Information obtained from the microscopic simulation runs will be adapted for use in macroscopic/mesoscopic models, enabling estimates of emissions reductions possible by changes in route at a larger scale than possible with the microscopic model.  Emission magnitudes will be estimated by integrating a yet to be selected emissions model.  Results will show potential changes/reductions in emissions possible by differing routes, providing information that can be used by transportation authorities to mandate or incentivize specific truck routes. The project will use the simulated acceleration and deceleration rates, average travel speeds, and total distances traveled in conjunction with a vehicle emissions model to estimate the total emissions.  Both the small and large scale simulations will be based on the Hampton Roads, VA transportation system.  However, the real world system networks will be modified to allow consideration of greater elevation changes than actually exist. Initial work will assess the potential gains available by varying route choice strategies and directly compare alternatives.  Design will support integration of behavioral influences, potentially using survey results, in future work.  This extension will include the likelihood that drivers would divert to routes that result in lower total emissions in the model, providing better forecasts of suggested route changes on efficiency.