Analysis of pre-crash scenarios and contributing factors for autonomous vehicle crashes at intersections

Article Ergonomics

Mining patterns of autonomous vehicle crashes involving vulnerable road users to understand the associated factors

Boniphace Kutela et al.

Summary: Autonomous vehicles have the potential to improve traffic safety and their involvement with vulnerable road users is a key factor.

ACCIDENT ANALYSIS AND PREVENTION (2022)

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Article Ergonomics

Causation analysis of crashes and near crashes using naturalistic driving data

Xuesong Wang et al.

Summary: This study addresses the issue of insufficient crash data by utilizing crashes and near crashes, as well as naturalistic driving studies. It proposes a two-stage crash causation analysis method based on pre-crash scenarios, and identifies causation patterns for rear-end, lane change, and vehicle-pedalcyclist scenarios. Countermeasures for the identified causation patterns are suggested to support safety improvement projects and the development of advanced driver assistance systems.

ACCIDENT ANALYSIS AND PREVENTION (2022)

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Article Ergonomics

Crash comparison of autonomous and conventional vehicles using pre-crash scenario typology

Qian Liu et al.

Summary: The study identified differences in pre-crash scenarios between AVs and conventional vehicles, with rear-end collisions and lane change collisions being the most common pre-crash scenarios for AVs. The study also found that AVs were rear-ended by conventional vehicles at a frequency 1.6 times higher than conventional vehicles.

ACCIDENT ANALYSIS AND PREVENTION (2021)

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Article Ergonomics

Operational design domain of autonomous vehicles at skewed intersection

Xuesong Wang et al.

Summary: This study investigates and quantifies the relationships between intersection angle on skewed intersections, revealing the importance of considering the impact of AV and providing formulae for detecting angle, distance, and time gap. Results show that intersection design needs to adjust according to AV's approach speed for improved safety and efficiency at intersections.

ACCIDENT ANALYSIS AND PREVENTION (2021)

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Article Multidisciplinary Sciences

Crash and disengagement data of autonomous vehicles on public roads in California

Amolika Sinha et al.

Summary: Autonomous Vehicles (AVs) are being extensively tested on public roads in various countries, with California requiring AV manufacturers to submit reports on disengagements and crashes for transparent deployment. Researchers utilize processed data to expedite research, improve reporting protocols, and establish policies and laws for the smooth deployment of this disruptive technology.

SCIENTIFIC DATA (2021)

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Article Engineering, Civil

Extracting Rules from Autonomous-Vehicle-Involved Crashes by Applying Decision Tree and Association Rule Methods

Md Tanvir Ashraf et al.

Summary: Autonomous vehicles have the potential to reduce traffic accidents and fatalities by eliminating human errors. Rear-end crashes at intersections are the most common AV-related crashes, and manufacturers can make design changes to minimize these accidents. Transportation agencies can enhance road safety by considering separating AVs from non-AVs through designated lanes.

TRANSPORTATION RESEARCH RECORD (2021)

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Article Ergonomics

Automated vehicle crash sequences: Patterns and potential uses in safety testing

Yu Song et al.

Summary: The study analyzed event sequence data from California AV collision reports and found that the most common pattern in AV crashes is collision following an AV stop, with disengagement events showing a high transition probability to immediate collision. Through cluster analysis, AV crash sequences were categorized into seven groups with associations to crash outcomes and environmental conditions.

ACCIDENT ANALYSIS AND PREVENTION (2021)

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Article Transportation