Assessing Traffic-Flow Safety at Various Levels of Autonomous-Vehicle Market Penetration

Abstract

This study analyzes the impact of autonomous-vehicle (AV) market-penetration rates on traffic-flow safety using a genetic algorithm. We set up a microscopic traffic-simulation scenario on a 640 m section of the US I-101 freeway using VISSIM, a microscopic traffic-simulation software. The results of analyzing the number of conflicts according to the introduction rate of autonomous vehicles showed that the number of conflicts increased as the introduction rate increased up to 30%, and then decreased from 40% or more. In this study, it was assumed that autonomous vehicles can avoid dangerous situations, so it is judged that this is the result of an increase in the traffic volume of autonomous vehicles and a decrease in the traffic volume of conventional vehicles. When planning an exclusive lane for autonomous vehicles, it is judged that it is desirable to install two exclusive lanes on the left side until the introduction rate of autonomous vehicles reaches 30%. When the introduction rate of autonomous vehicles is 40–90%, the risk of accidents between autonomous vehicles and conventional vehicles decreases, and the traffic volume of autonomous vehicles is higher than that of conventional vehicles. Therefore, it is judged that it is desirable to operate a mixed road where autonomous vehicles and conventional vehicles can drive together rather than operating an exclusive lane for autonomous vehicles.