RSG is leading a project on the use of detailed simulation models to help regional and state agencies plan for the effects of connected and autonomous vehicle (CAV) technologies in long-range planning. The research integrates the DaySim activity-based travel demand model with the TransModeler dynamic traffic simulation model for Jacksonville, FL, for exploratory modeling & analysis (EMA).

The work adapts travel demand models to simulate households’ decisions whether to purchase autonomous vehicles instead of conventional vehicles, and to simulate travelers’ decisions whether to use CAV-based car-sharing and ride-sharing services. The dynamic network models simulate operating characteristics of CAVs—depending on network vehicle mix—and simulate the performance of CAV-only infrastructure under different demand scenarios.

In the second phase of the project, the models will simulate generators of zero-occupant CAV trips, including dispatching strategies for ride-sharing fleets, use of remote parking locations, and intrahousehold sharing of private CAVs. The models will simulate dozens of different scenario combinations to explore potential outcomes and find critical input assumptions while identifying future policy directions that are likely to be the most robust in the face of “deep uncertainty.”