Citation

Seyedi MR, Koloushani MR, Jung S, Vanli A, Shriniwas A. J. Adv. Transp. 2021; 2021: e4430730.

Copyright

(Copyright © 2021, Institute for Transportation, Publisher John Wiley and Sons)

DOI

10.1155/2021/4430730

PMID

unavailable

Abstract

In this study, we selected four real-world rear-end crash scenarios with different crash characteristics. The vehicles involved in those crashes were not equipped with any crash avoidance systems. We then used the accident reconstruction method to build those crash scenarios in PC-Crash software. Then, different FCW/AEB safety algorithms have been defined for a subject vehicle model in each crash scenario and each scenario was simulated for a set of input parameters such as vehicle speed, brake intensity, and driver reaction time. The range and distribution of input parameters were extracted from the related field crash data and available literature. A total number of 16000 simulations have been conducted which produced input-output datasets for further investigations. Finally, the effects of input parameters on simulation outcomes including crash occurrence, AEB activation, injury risk, and vehicle damage have been quantified using the Boruta algorithm. The results indicated that the overall effectiveness of the AEB system was a 57% reduction of rear-end crashes, a 52% reduction of injury severity (striking vehicle’s passengers), and a 47% reduction of damages for striking vehicles. The results also showed that the available AEB algorithms were more effective for the average speed equal to or less than 80 kmph. The speed of the subject vehicle, type of AEB algorithm, sensor detection range, and driver reaction time were the most important parameters on crash outcomes. In addition, the results indicated that the performance of FCW had a direct impact on the effectiveness of the AEB system for the integrated FCW + AEB system.

Language: en