TY - GEN
T1 - Identifying major accident scenarios in intersection and evaluation of collision warning system
AU - Kim, Yeeun
AU - Tak, Sehyun
AU - Kim, Jeongyun
AU - Yeo, Hwasoo
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - 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.
AB - 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.
KW - accident scenario
KW - collision warning system
KW - CWS
KW - intersection accident
UR - https://www.scopus.com/pages/publications/85046283288
U2 - 10.1109/ITSC.2017.8317660
DO - 10.1109/ITSC.2017.8317660
M3 - Conference contribution
AN - SCOPUS:85046283288
T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
SP - 1
EP - 6
BT - 2017 IEEE 20th International Conference on Intelligent Transportation Systems, ITSC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 20th IEEE International Conference on Intelligent Transportation Systems, ITSC 2017
Y2 - 16 October 2017 through 19 October 2017
ER -