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Citation |
Das T, Shoaib Samandar M, Rouphail N. Accid. Anal. Prev. 2022; 177: e106822. |
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Copyright |
(Copyright © 2022, Elsevier Publishing) |
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DOI |
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PMID |
36103759 |
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Abstract |
Autonomous vehicles (AVs) have been introduced into the traffic stream alongside traditional vehicles (TVs) with the expectation of improved transportation safety, efficiency, and reliability. The majority of AV safety research has been done through simulation. The results of such research on the safety performances of AVs are heavily influenced by the methodological framework, algorithms, and assumptions about AV driving characteristics in a simulated environment. There is a need for AV safety research based on real-world settings before any wide-scale deployment of this technology. This paper investigates the impact of the presence of SAE level 2 AVs in the traffic stream in reducing longitudinal traffic conflicts using Surrogate Safety Measures on a real-world open-source database of mixed traffic trajectories. The analysis is conducted for both AV-exclusive and mixed AV-TV platoons. Furthermore, we explore whether the presence of AVs decreases longitudinal traffic conflicts in two-vehicle platoons comprising AV and TV mixed leaders and followers. We find that an exclusive AV platoon behaves similarly to an exclusive TV platoon and produces similar longitudinal conflicts. However, mixed platoons with both AVs and TVs result in a higher number of longitudinal conflicts. Maintaining near-identical leader-follower conditions, we find that the number of conflicts in mixed platoons when an AV follows a TV is higher than when a TV follows an AV. The increase in conflict numbers in a TV-AV mixed platoon can be attributed to AV's longer response time lag. In summary, analyses conducted in this paper indicate that exclusive platoons and pairs of vehicles exhibit fewer longitudinal conflicts than mixed platoons and pairs. Language: en |
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Keywords |
Adaptive Cruise Control; Autonomous Vehicles; AV Platoons; Mixed Platoons; Real-World Mixed Traffic Dataset; Surrogate Safety Measures |