Xiamen University Reports Findings in Risk Management (Study of typical electric two-wheelers pre-crash scenarios using K-medoids clustering methodology based on video recordings in China)

Insurance Daily News

2021 AUG 19 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- New research on Risk Management is the subject of a report. According to news reporting originating from Xiamen, People’s Republic of China, by NewsRx correspondents, research stated, “Crash safety of electric two-wheelers (ETWs) has been one of the most important safety issues in China due to their high proportion of involvement in traffic accidents. Automated Emergency Braking (AEB) systems have proven to be effective in reducing the number of fatalities and injuries in traffic accidents.”

Our news editors obtained a quote from the research from Xiamen University, “Providing test scenarios is one of the fundamental tasks required for establishing a set of AEB test programs for ETWs. Compared to traditional in-depth accident data, accident data accompanied with video recordings provide more accurate accident information prior to a crash as both the traffic environment and the crash process can be observed from the video. In this study, a set of typical AEB test scenarios for ETWs was developed using accident data with video information. Video recordings of 630 car-to-ETW crashes in China from 2010 to 2021 were selected from the VRU Traffic Accident database with Video (VRU-TRAVi). A K-medoids cluster analysis was carried out based on variables including the collision time, visual obstruction, motion of the car and ETW before the collision, relative motion direction between the car and ETW, and the ETW type. The velocity information of cars and ETWs was also accounted for in each clustering scenario. Seven typical pre-crash scenarios were obtained, including five electric-scooter (E-scooter) scenarios (representing two scenarios where the ETWs are approaching the car from the left side, two scenarios where the ETWs are approaching the car in the same direction and another scenario where the ETWs are approaching the car in the opposite direction) and two electric-bike (E-bike) scenarios where the E-bikes are approaching the car in the perpendicular direction. Both E-bike scenarios are consistent with the E-scooter scenario except for the ETW type and velocity range; therefore, by combining the E-bike and E-scooter scenarios, five ETW scenarios were finally recommended as AEB test scenarios.”

According to the news editors, the research concluded: “By comparing with typical scenarios extracted based on the China In-Depth Accident Study (CIDAS) data and the China New Car Assessment Program (C-NCAP) test scenarios, the results show that future AEB test scenarios for ETWs should focus on scenarios with visual obstructions and scenarios where either the car or the ETW is turning, with a velocity range of 15-30 km/h for ETWs.”

This research has been peer-reviewed.

For more information on this research see: Study of typical electric two-wheelers pre-crash scenarios using K-medoids clustering methodology based on video recordings in China. Accident Analysis & Prevention, 2021;160:106320. Accident Analysis & Prevention can be contacted at: Pergamon-elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, England. (Elsevier - www.elsevier.com; Accident Analysis & Prevention - http://www.journals.elsevier.com/accident-analysis-and-prevention/)

The news editors report that additional information may be obtained by contacting Di Pan, School of Aerospace Engineering, Xiamen University, Xiamen, People’s Republic of China. Additional authors for this research include Yong Han, Qianqian Jin, He Wu and Hongwu Huang.

The direct object identifier (DOI) for that additional information is: https://doi.org/10.1016/j.aap.2021.106320. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.

Publisher contact information for the journal Accident Analysis & Prevention is: Pergamon-elsevier Science Ltd, The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, England.

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