Hang Junyu, Yan Xuedong, Li Xiaomeng, Duan Ke, Yang Jingsi, Xue Qingwan
MOT Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, PR China.
Queensland University of Technology (QUT), Centre for Accident Research and Road Safety-Queensland (CARRS-Q), Institute of Health and Biomedical Innovation (IHBI), Kelvin Grove, Queensland 4059, Australia.
J Safety Res. 2022 Feb;80:416-427. doi: 10.1016/j.jsr.2021.12.023. Epub 2021 Dec 29.
To assist drivers in avoiding rear-end collisions, many early warning systems have been developed up to date. Autonomous braking technology is also used as the last defense to ensure driver's safety.
By taking the accuracy and timeliness of automatic system control into account, this paper proposes a rear-end Real-Time Autonomous Emergency Braking (RTAEB) system. The system inserts brake intervention based on drivers' real-time conflict identification and collision avoidance performance. A driving simulator-based experiment under different traffic conditions and deceleration scenarios were conducted to test the different thresholds to trigger intervention and the intervention outcomes. The system effectiveness is verified by four evaluation indexes, including collision avoidance rate, accuracy rate, sensitivity rate, and precision rate.
The results showed that the system could help avoid all collision events successfully and enlarge the final headway distance, and a TTC threshold of 1.5 s and a maximum deceleration threshold of -7.5 m/s could achieve the best collision avoidance effect. The paper demonstrates the situations that are more inclined to trigger the RTAEB (i.e., a sudden brake of the leading vehicle and a small car-following distance). Moreover, the study shows that driver characteristics (i.e., gender and profession) have no significant association with system trigger. Practical Applications: The study suggests that development of collision avoidance systems design should pay attention to both the real-time traffic situation and drivers' collision avoidance capability under the present situation.
为帮助驾驶员避免追尾碰撞,迄今为止已开发了许多早期预警系统。自动制动技术也被用作确保驾驶员安全的最后一道防线。
考虑到自动系统控制的准确性和及时性,本文提出了一种追尾实时自动紧急制动(RTAEB)系统。该系统基于驾驶员的实时冲突识别和碰撞避免性能插入制动干预。在不同交通条件和减速场景下进行了基于驾驶模拟器的实验,以测试触发干预的不同阈值和干预结果。通过碰撞避免率、准确率、灵敏度率和精确率这四个评估指标验证了系统的有效性。
结果表明,该系统能够成功帮助避免所有碰撞事件并扩大最终车头间距,1.5秒的碰撞时间(TTC)阈值和-7.5米/秒的最大减速度阈值可实现最佳的碰撞避免效果。本文展示了更倾向于触发RTAEB的情况(即前车突然制动和较小的跟车距离)。此外,研究表明驾驶员特征(即性别和职业)与系统触发没有显著关联。实际应用:该研究表明,防撞系统设计的开发应同时关注实时交通状况和当前情况下驾驶员的防撞能力。