Simulating impacts of automated driving behavior and traffic conditions on vehicle emissions

Abstract

Automated vehicles (AV) will have an impact on the movement of people and goods. Assessing the effects of AVs on land use, congestion and the environment is of utmost importance in order to inform policy and planning decisions. This study explores the effects of AVs and vehicle electrification on greenhouse gas emissions using traffic microsimulation and emission modeling. The driving behavior modeling parameters most relevant to AVs are tested within ranges representing potential AV operations. The effects of AVs are evaluated under both uninterrupted and interrupted traffic flow conditions, representing highway driving and driving on arterial roads, under high and low traffic demand. The main findings indicate that AVs can bring positive changes in terms of emissions and traffic flow performance. The effects are more evident when AVs are tuned to more aggressive driving settings (i.e., drive closer together) and especially under high levels of traffic demand in an uninterrupted flow setting (highway). When AVs are programmed to operate more aggressively, the subsequent emission factors could be reduced by up to 26% on the expressway, while cautiously programmed AVs could deteriorate traffic performance and lead to a 35% increase in emissions.