Driving Automation Systems Penetration and Traffic Safety: Implications for Infrastructure Design and Policy

Abstract

The increasing penetration of autonomous vehicles (AVs) presents new challenges and opportunities for road safety. This study aims to evaluate the impact of AV penetration rates on traffic safety through the use of microscopic simulation scenarios based on the Villaverde network in Madrid. Eleven scenarios were simulated with SAE Level 5 AV market penetration rates (MPRs) ranging from 0% to 100% in 10% increments. Vehicle conflicts, defined as instances where the time to collision was less than 1.5 s, were analyzed along with traffic composition and roadway characteristics. Multiple linear and multinomial logistic regression models were applied to examine the relationships between time-to-collision (TTC), conflict numbers, maximum conflict speed, and critical influencing factors such as vehicle type and road capacity. The results indicate that higher AV penetration rates generally improve traffic safety, although the coexistence of conventional vehicles and vehicles equipped with driving automation systems introduces traffic heterogeneity, potentially influencing safety outcomes. These findings suggest that while AVs have a positive effect on road safety, further analysis is needed to address the complexities introduced by mixed-traffic conditions.