AEB effectiveness research methods based on reconstruction results of truth vehicle-to-TW accidents in China

Peng, Yong; Yu, Weifeng; Wu, Xinghua; Xu, Qian; Wang, Honggang; Wu, Wenguang

doi:10.1177/0954407020976741

Cited by 9 publications

(5 citation statements)

References 21 publications

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“…It is useful to study the effectiveness of AEB systems by reconstructing real-world vehicle-to-VRU accident cases. Accident data may be cases from an traditional in-depth accident databases 4,5,19,20,29 or accident videos collected by a driver recorder. 6,7 In this study, in-depth accident data with both video recordings and detailed accident investigation report were used for pre-crash scenario modeling.…”

Section: Discussionmentioning

confidence: 99%

Comparative analysis of AEB effectiveness based on typical and atypical scenarios of electric two-wheeler accidents in China

Pan

Han

Jin

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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Electric two-wheeler (ETW) accidents are one of the most important types of traffic accidents in China. Currently, the China New Car Assessment Program (C-NCAP) has proposed test scenarios to evaluate the effectiveness of autonomous emergency braking (AEB) for ETWs, including several common typical crash scenarios, but other atypical scenarios have not been considered. To determine the performance of AEB in real accidents, 16 in-depth accident cases with typical scenarios and 11 cases with atypical scenarios were selected based on a proposed C-NCAP typical scenario set and reconstructed using the virtual simulation tools MADYMO and PC-Crash. The crashes were re-simulated with a car equipped with an AEB system while varying the sensor field of view (FOV), time-to-collision (TTC), sensor delay time (SDT), and lateral trigger width ( W). The results show that for almost all combinations of AEB parameters, the crash avoidance rate was much higher in the typical scenario than that in the atypical scenario. When using an AEB with a FOV of 90° (±45°), all ETW accidents were avoided in typical scenarios, while even with the most efficient AEB system (FOV = ±60°, TTC trigger value = 1.5 s, SDT = 0.1 s), only 82% of crashes were avoided in atypical scenarios. Further considering the effect of lateral width, increasing the width from 2 to 5 m, the maximum avoidance rate of the AEB system increased by 43% in the typical scenarios and 18% in the atypical scenarios. The findings suggest that the typical AEB test scenarios proposed for C-NCAP were useful for other crash scenarios, but that including additional test scenarios may better reflect real world crash scenarios. It is recommended that atypical scenarios should be considered in C-NCAP, particularly perpendicular crash scenarios with the car or ETW turning, to better describe real accidents and improve vehicle safety.

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Section: Discussionmentioning

confidence: 99%

Comparative analysis of AEB effectiveness based on typical and atypical scenarios of electric two-wheeler accidents in China

Pan

Han

Jin

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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“…With the fast application of driver assistance driving system on vehicle, the risk of traffic accident decrease greatly, such as the rear end collision scenario [1] and side collision. The safety of ADAS system becomes a standard function on the vehicle which produced by the Chinese OEM or luxurious brand, such as tesla model.…”

Section: Introductionmentioning

confidence: 99%

Research on cut-in scenario identification algorithm based on risk assessment

Zeng,

Ding,

et al. 2024

Seventh International Conference on Traffic Engineering and Transportation System (ICTETS 2023)

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The boundaries of typical scenes need to be extracted from the original scene data occurring in real roads, but the manual scene labeling method is inefficient and costly. Therefore, it is important to study the acquisition of autonomous driving scenes in real roads for the testing of autonomous vehicles, and the cut-in scenes are typical hazard scenes. In this paper, a scenario acquisition system with multi-source heterogeneous sensors is modified based on a vehicle equipped with L2- level autonomous driving system for acquiring natural road driving scenario data. Subsequently, a cut-in scenario automatic recognition algorithm based on risk assessment is proposed, and a recognition algorithm evaluation test platform is constructed, and a large number of test case generation procedures are designed to simulate and test the algorithm. And a large amount of natural driving data is used to verify the proposed recognition algorithm. The results show that the algorithm proposed in this paper can effectively identify the cut-in scenes occurring in front of the collection vehicle and has high accuracy.

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“…Woo et al 13 authored “Design and simulation of a vehicle test bed based on Intelligent Transport Systems (ITS).” Specifically, ITS-based intelligent vehicle test bed was constructed, satisfying the requirements of ISO/TC204 standards, to meet the growing demand of testing and verification for ADAS and ITS systems. Peng et al 14 authored “AEB effectiveness research methods based on reconstruction results of truth vehicle-to-two wheel (TW) accidents in China,” Zeng et al 15 authored “Improved AEB algorithm combined with estimating the adhesion coefficient of road ahead and considering the performance of electro-hydraulic brake,” Kinosada et al 16 authored “Trusting other vehicles’ automatic emergency braking decreases self-protective driving,” and Ahmad et al 17 authored “Simulation and experimental investigation of vehicle braking system employing a fixed caliper based electronic wedge brake.” Finally, Soule et al 18 authored “Testing an automated collision avoidance and emergency braking system for buses.”…”

Section: Introductionmentioning

confidence: 99%

Evaluation of autonomous emergency braking by using a theoretical formula and dual cameras

Kim

Lee

2023

Proceedings of the Institution of Mechanical Engineers, Part D:

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According to data gathered by the Korean National Police Agency, 1,028,777 vehicle-to-vehicle traffic accidents and 125,597 vehicle-to-pedestrian traffic accidents occurred in 2020. To decrease the occurrence possibility of traffic accidents, advanced driver-assistance system (ADAS), which provides assistance in regions that drivers do not recognize, have attracted increasing interest. Among the representative functions of ADAS, autonomous emergency braking (AEB) is a valuable system for accident prevention and mitigation. In this study, to evaluate AEB by using dual cameras, actual vehicle tests were conducted. In addition, the theoretically calculated values, results obtained using dual cameras, and results obtained using measuring instruments were compared and analyzed. The result values using the proposed theoretical formula and those of the actual vehicle test using the measurement instruments were compared and analyzed. The minimum and maximum error rates were 0.11% and 4.45%, respectively. For results obtained using dual cameras and measurement instruments, the minimum and maximum error rates were 1.80% and 8.89%, respectively. In the development stage of ADAS especially when developing AEB system, the use of the theoretical formula and dual cameras can decrease the cost burden compared to that associated with testing.

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AEB effectiveness research methods based on reconstruction results of truth vehicle-to-TW accidents in China

Cited by 9 publications

References 21 publications

Comparative analysis of AEB effectiveness based on typical and atypical scenarios of electric two-wheeler accidents in China

Comparative analysis of AEB effectiveness based on typical and atypical scenarios of electric two-wheeler accidents in China

Research on cut-in scenario identification algorithm based on risk assessment

Evaluation of autonomous emergency braking by using a theoretical formula and dual cameras

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