RSG is part of a team developing guidelines for implementing travel forecasting models to address travel behavior and system performance changes associated with connected and autonomous vehicles (CAVs). The research will assess current travel forecast modeling frameworks for their applicability and potential for inclusion of CAVs in the transportation system. The research will include guidance for 4-step trip-based, disaggregate/dynamic and strategic modeling systems. This study will include identification of gaps in current modeling frameworks, prioritize critical elements required to model CAVs, develop a draft framework for modeling CAVs, vet the framework with peers in the modeling community, and develop guidelines for data collection and implementation of the framework. The framework will include focus on both system performance (supply side) variables and travel behavior variables.
On the supply side, the team will study the potential impact of CAV operating characteristics on network capacity, including freeways, toll roads, signalized intersections, dedicated/managed lanes, and parking systems. On the demand side, the research will study the impact of CAVs on vehicle ownership and sharing, multimodal tours, trip destination choice, and trip purpose and frequency, among other factors. The research will also discuss the value of time as it relates to travel choices, especially related to modeling public transportation systems.