Autonomous driving testing scenario generation based on in-depth vehicle-to-powered two-wheeler crash data in China

Wu, Xinghua; Peng, Yong; Xu, Tuo; Xu, Qian; Wu, Xianhui; Xiang, Guoliang; Yi, Shengen; Wang, Honggang

doi:10.1016/j.aap.2022.106812

Cited by 16 publications

(8 citation statements)

References 27 publications

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“…The DOW system is used to monitor the moving targets in the blind spot on the rear side of the vehicle through rear millimeter wave radar or side view camera when the passenger is about to open the door or has already opened the door when the vehicle is in a parked state (as shown in Figure 5). When the system determines that a collision hazard may occur due to the opening of the door, it provides a risk warning to the driver and passengers 7 . Similarly, warning information can indicate the direction of risk occurrence.…”

Section: Door Open Warningmentioning

confidence: 99%

Research on side-to-rear ADAS functional test and evaluation technology for two-wheeler target

Liu,

Li,

Zhai

et al. 2024

Third International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2023)

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Electric bicycles, motorcycles, bicycles and other two-wheelers have incomparable convenience in short trips, but as vulnerable road users, the probability of accidents in complex traffic environments is higher than that of other vehicles. Based on the analysis of CIDAS accident data, this paper calculates the types of traffic participants in traffic accidents in which the passenger car is the main vehicle, and analyzes the two common traffic accident scenarios that are easy to cause injury to the two-wheeled vehicle. The basic principle, test scenario, test method and evaluation method of two ADAS functions, rear traffic crossing warning and door opening warning, are introduced according to the new C-NCAP protocol of 2024 edition. And the validation test results of three vehicle models were selected for analysis, and the final conclusion was drawn.

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Section: Door Open Warningmentioning

confidence: 99%

Research on side-to-rear ADAS functional test and evaluation technology for two-wheeler target

Liu,

Li,

Zhai

et al. 2024

Third International Conference on Intelligent Traffic Systems and Smart City (ITSSC 2023)

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“…This study also found characteristics of the near-crash such as slow or stopped, rapid deceleration or stop of the leading vehicle. Wang et al (2022) [ 31 ] derived six clusters through k-medoid clustering using two-wheeled vehicle crash data in China. Based on this analysis, they presented functional, logical, and concrete scenarios specifically for AV test.…”

Section: Related Workmentioning

confidence: 99%

The typical AV accident scenarios in the urban area obtained by clustering and association rule mining of real-world accident reports

Lee,

Kang,

Hwang

et al. 2024

Heliyon

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“…Building on the China In-Depth Accident Study (CIDAS) dataset, Sui et al [11] applied the K-medoid clustering algorithm to cluster 672 accident cases involving cars and TWs, resulting in 6 common collision scenarios; these were then compared to the 4 typical scenarios obtained by Cao et al [12]. Wang et al [13] employed 239 crash cases from the China In-Depth Mobility Safety Study-Traffic Accident (CIMSS-TA). They summarized six functional scenarios using the K-medoids clustering based on seven collision characteristics; additionally, they established dynamic parameters for collision trajectory analysis during hazardous moments and generated testing scenarios suitable for autonomous driving.…”

Section: Introductionmentioning

confidence: 99%

Data Mining-Based Collision Scenarios of Vehicles and Two Wheelers for the Safety Assessment of Intelligent Driving Functions

Wang,

Qian,

Dong

et al. 2023

WEVJ

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The safety performance test of intelligent driving vehicles needs to rely on the collision scenarios in a real road traffic environment. In order to study the collision scenarios and accident characteristics of vehicles and two wheelers (TWs) in line with the complex traffic conditions in China, this paper proposes using clustering analysis to initially cluster traffic accident data to obtain the base scenarios and then applying the association rule algorithm to each base scenario to obtain the potential connection of its accident attributes and describe the collision scenarios in more detail. This study is based on data from 335 vehicle and two-wheeler crashes in the National Automobile Accident In-Depth Investigation System (NAIS). It used clustering analysis to cluster the crash data into different partitions to obtain eight clusters of vehicle and two-wheeler base scenarios and applied association rules to analyze the rest of the accident attributes, revealing common crash characteristics to describe the base scenarios in more detail. In the end, it constructed eleven types of detailed vehicle and two-wheeler collision scenarios covering straight roads, intersections, and T-junctions. The results provide richer and more suitable crash scenarios of vehicles and two wheelers in China’s complex traffic and is an important reference for the development of intelligent driving testing scenarios in the future.

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Autonomous driving testing scenario generation based on in-depth vehicle-to-powered two-wheeler crash data in China

Cited by 16 publications

References 27 publications

Research on side-to-rear ADAS functional test and evaluation technology for two-wheeler target

Research on side-to-rear ADAS functional test and evaluation technology for two-wheeler target

The typical AV accident scenarios in the urban area obtained by clustering and association rule mining of real-world accident reports

Data Mining-Based Collision Scenarios of Vehicles and Two Wheelers for the Safety Assessment of Intelligent Driving Functions

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