Tactical-Level Explanation is Not Enough: Effect of Explaining AV’s Lane-Changing Decisions on Drivers’ Decision-Making, Trust, and Emotional Experience

Zhang, Yiwen; Wang, Wenjia; Zhou, Xinyan; Wang, Qi; Sun, Xiaohua

doi:10.1080/10447318.2022.2098965

Cited by 7 publications

(1 citation statement)

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“…Conversely, HDVs can adapt and modify their speed more seamlessly than AVs, highlighting the limitations of AVs in comparison to the adeptness of experienced drivers 64 . And AVs face difficulties with executing lane changes or turning in heavy traffic and lack psychological insight 65 , 66 . In addition, HDVs can predict pedestrian movements and exercise caution based on their driving experience, whereas AVs may struggle with recognizing pedestrians’ intentions, potentially leading to emergency braking or accidents due to a lack of understanding of social cues and psychological reasoning 65 , 67 , 68 .…”

Section: Resultsmentioning

confidence: 99%

A matched case-control analysis of autonomous vs human-driven vehicle accidents

Abdel-Aty,

Ding

2024

Nat Commun

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Despite the recent advancements that Autonomous Vehicles have shown in their potential to improve safety and operation, considering differences between Autonomous Vehicles and Human-Driven Vehicles in accidents remain unidentified due to the scarcity of real-world Autonomous Vehicles accident data. We investigated the difference in accident occurrence between Autonomous Vehicles’ levels and Human-Driven Vehicles by utilizing 2100 Advanced Driving Systems and Advanced Driver Assistance Systems and 35,113 Human-Driven Vehicles accident data. A matched case-control design was conducted to investigate the differential characteristics involving Autonomous’ versus Human-Driven Vehicles’ accidents. The analysis suggests that accidents of vehicles equipped with Advanced Driving Systems generally have a lower chance of occurring than Human-Driven Vehicles in most of the similar accident scenarios. However, accidents involving Advanced Driving Systems occur more frequently than Human-Driven Vehicle accidents under dawn/dusk or turning conditions, which is 5.25 and 1.98 times higher, respectively. Our research reveals the accident risk disparities between Autonomous Vehicles and Human-Driven Vehicles, informing future development in Autonomous technology and safety enhancements.

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