Incorporating features of autonomous vehicles in activity-based travel demand model for Columbus, OH

Autonomous vehicles (AVs) could change travel patterns of the population significantly and with the rapid improvements in AV technology, transportation planners should address AV impacts in regional plans and project evaluations for the mid-term and long-term horizons (10–15 years and beyond). There are multiple travel model components from demand generation to network assignments that need to be modified, updated, or added to fully capture the potential impacts of AVs on regional travel patterns. This paper describes how the features of AVs were incorporated in the regional Activity-Based travel demand Model developed for Columbus, OH, metropolitan region. The model modifications included multiple adjustments to the travel demand sub-models, network assignments, as well as an addition of a new sub-model for vehicle routing and parking that addresses such new phenomenon as empty AV relocation trips. Due to many factors of uncertainty associated with AVs, a scenario-based approach was adopted for evaluation of the potential impacts of AVs on the travel patterns. The emphasis of the scenario analysis was on multiple dimensions of travel behavior in addition to such aggregate regional measures as VMT, etc. The paper presents an analysis of potential impacts of AVs on accessibility measures, activity participation, tour formation, and mode choice. The scenario analysis applied to the Columbus region showed overall logical potential impacts of AVs with many insights useful for transportation planning.