A framework for the impact of highly automated vehicles with limited operational design domains

Abstract

Abstract Highly automated vehicles (AV) are in the early stages of deployment and are likely to have significant impacts on the United States transportation system. In particular, a broad deployment of shared, on-demand AVs might significantly impact vehicle ownership and transportation energy consumption; projecting these impacts is essential for climate, infrastructure, and policy planning. However, it seems increasingly likely that AVs will be deployed gradually over a period of decades, in which case there may be geographic or functional variation in their availability. This might occur for a combination of technological, policy, and economic reasons. This manuscript seeks to advance a new framework for projecting AV impacts, with a particular focus on energy consumption impacts. Specifically, we introduce a framework for AV impacts that allows for AVs catering to specific operating environments or ride types. As a demonstration of this framework, we use the 2009 National Household Transportation Survey (NHTS) to segment US household travel demand based on built environment and ride length. Our framework allows us to specify AV “availability” for each population segment and ride type and use that information to predict the impact of AVs. We analyze a case scenario where shared, on-demand AVs are mostly suited for short trips in highly urbanized environments. We project the impact on household relocation, private vehicle ownership, induced travel demand, and fuel consumption. Utilization of this framework would help identify policy levers for sustainable deployment of AVs.