Identifying major accident scenarios in intersection and evaluation of collision warning system

Yeeun Kim, Sehyun Tak, Jeongyun Kim, Hwasoo Yeo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

To improve the safety performance of the vehicle, various Advanced Driver Assistance Systems (ADAS) have been developed and apply to the vehicle. Among various ADASs, the collision warning system is one of the representative technology and contributed to prevent the accident and mitigate the severity of the accident. However, existing collision warning systems are designed to prevent the forward collision in an uninterrupted flow, so the safety performance in the interrupted flow near intersection have not been intensively studied. In this paper, the safety performance of Camera-Based collision warning system (CBS) and Radar-Based collision warning system (RBS) are evaluated near the intersection. For this, we newly derived the sixteen vehicle-to-vehicle accident scenarios near the intersection with a crash and near-crash data according to the movements of the subject vehicle and the opponent vehicle. Scenarios derived in this paper differs from the derived scenarios in the previous researches by dealing with more various movements of the subject vehicle such as turning movement. With the derived sixteen vehicle-to-vehicle accident scenarios, we evaluate how effectively CBS and RBS work in the intersection accident scenarios. The results show that CBS and RBS cannot prevent the all accident scenarios due to the limited field-of-view. With the 0.7 accident prevention rate, CBS can prevent the accident in five scenarios, and RBS can prevent the accident in four accident scenarios. To prevent all accident scenarios, another system that can detect the vehicle movement with longer range than CBS and RBS is needed. In the future study, communication-based collision warning system will be developed to further improve the safety performance of collision warning system.

Original languageEnglish
Title of host publication2017 IEEE 20th International Conference on Intelligent Transportation Systems, ITSC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781538615256
DOIs
StatePublished - 2 Jul 2017
Event20th IEEE International Conference on Intelligent Transportation Systems, ITSC 2017 - Yokohama, Kanagawa, Japan
Duration: 16 Oct 201719 Oct 2017

Publication series

NameIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
Volume2018-March

Conference

Conference20th IEEE International Conference on Intelligent Transportation Systems, ITSC 2017
Country/TerritoryJapan
CityYokohama, Kanagawa
Period16/10/1719/10/17

Keywords

  • accident scenario
  • collision warning system
  • CWS
  • intersection accident

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