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

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.

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Publication Details

Journal
Infrastructures
Published
2024-12-16
DOI
https://doi.org/10.3390/infrastructures9120234
Citations
2
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
0.53
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article

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

Thodoris Garefalakis, George Yannis, Maria G. Oikonomou, Antonia Antonakaki
2 citations
Infrastructures
Traffic Prediction and Management Techniques
0.53
article

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

Thodoris Garefalakis, George Yannis, Maria G. Oikonomou, Antonia Antonakaki
article en
2 citations

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.

InfrastructuresVol. 9(12)
National Technical University of Athens (GR)
Openalex Percentile: Top 33%
Traffic Prediction and Management Techniques
0.53
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