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Studying Traffic Safety During the Transition Period Between Manual Driving and Autonomous Driving: A Simulation-Based Approach

Authors: Tasneem Miqdady; Rocío de Oña; Jordi Casas; Juan de Oña;

Studying Traffic Safety During the Transition Period Between Manual Driving and Autonomous Driving: A Simulation-Based Approach

Abstract

Connected and Autonomous Vehicles (CAVs) are becoming a reality and are progressively penetrating the markets level by level. CAVs are a promising solution for traffic safety and are expected to eliminate human driving errors. However, robust studies are needed to explore and assess the expected behavior. This study attempts to evaluate traffic safety resulting from the penetration of CAVs with different levels of automation (from Level 1 to Level 4) and the corresponding impact of the near-real introduction of CAVs into the traffic flow, considering that Level 4 vehicles will not be immediately introduced into the traffic. The investigation consisted of the modeling of different CAV levels using Gipps’ model calibration, followed by the simulation of nine mixed fleets of CAV levels at a modeled motorway segment. Subsequently, the Surrogate Safety Assessment Model was used for safety analysis using vehicle trajectories. According to the results obtained: (1) the gradual penetration of CAV levels led to a progressive reduction in traffic conflicts. This reduction ranges from 18.9% when the penetration of high levels of automation (Level 3 and Level 4 vehicles) is 5%, to 94.1% when all the vehicles on the traffic flow are Level 4. And (2) human-driven vehicles and vehicles with low levels of automation (Level 1 and Level 2 vehicles) are more frequently involved in conflicts (as possible inductors of risky situations; as follower vehicles) than vehicles with high automation levels (Level 3 and Level 4 vehicles). In fact, human- driven vehicles are involved in conflicts from 8% to 122% more than its sharing percentage on fleets, while vehicles with high automation levels are involved in conflicts from 80% to 18% less than its sharing percentage on fleets, depending on the combination of different types of vehicles in the traffic flow. In general, this study confirms the theory and the conclusions from previous literature that indicate a safety gain due to CA V penetration. Moreover, it provides a broader perspective and support for the introduction of CAVs levels.

Keywords

traffic safety, Connected and Autonomous Vehicles, V2X, levels of automation, simulation, surrogate safety assessment

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Average
Average
Green
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