TY - GEN
T1 - A Safety Margin-Based Automatic Emergency Braking Model
AU - Ji, Xin
AU - Lu, Guangquan
AU - Wang, Jinghua
AU - Liang, Jinhao
AU - Tang, Renjing
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - The Automatic Emergency Braking (AEB) system is capable of assessing driving risks, alerting the driver to potential collision hazards, and, in the absence of driver response to the collision risk, autonomously activating braking to mitigate the occurrence of collision accidents. Most existing Automatic Emergency Braking (AEB) systems rely on Time to Collision (TTC) for risk assessment and decision-making. However, TTC fails to account for the impact of absolute velocity on driving safety when assessing risk, leading to inaccurate risk descriptions, particularly in high-speed scenarios with minor speed differences. The Safety Margin (SM) takes into account key factors affecting driving risk, such as relative velocity and distance, and is capable of accurately quantifying driving risks. Based on the SM, this study proposes a full-speed range single-threshold Automatic Emergency Braking (AEB) model. The model comprises two components: traffic environment risk quantification and road surface friction coefficient estimation. It is applicable to automatic emergency braking tasks under varying speeds and road surface conditions. Simulation experiments were conducted by constructing three typical scenarios: stationary lead vehicle, slow-moving lead vehicle, and braking lead vehicle, to determine the braking threshold as 0.2. The safety performance of the proposed safety margin-based AEB model is evaluated by comparing it with the traditional TTC-based AEB model across the specified scenarios. The results demonstrate that the safety margin-based AEB model proposed in this study achieves 100% safe braking in all scenarios, successfully performing emergency braking and outperforming the TTC-based AEB model.
AB - The Automatic Emergency Braking (AEB) system is capable of assessing driving risks, alerting the driver to potential collision hazards, and, in the absence of driver response to the collision risk, autonomously activating braking to mitigate the occurrence of collision accidents. Most existing Automatic Emergency Braking (AEB) systems rely on Time to Collision (TTC) for risk assessment and decision-making. However, TTC fails to account for the impact of absolute velocity on driving safety when assessing risk, leading to inaccurate risk descriptions, particularly in high-speed scenarios with minor speed differences. The Safety Margin (SM) takes into account key factors affecting driving risk, such as relative velocity and distance, and is capable of accurately quantifying driving risks. Based on the SM, this study proposes a full-speed range single-threshold Automatic Emergency Braking (AEB) model. The model comprises two components: traffic environment risk quantification and road surface friction coefficient estimation. It is applicable to automatic emergency braking tasks under varying speeds and road surface conditions. Simulation experiments were conducted by constructing three typical scenarios: stationary lead vehicle, slow-moving lead vehicle, and braking lead vehicle, to determine the braking threshold as 0.2. The safety performance of the proposed safety margin-based AEB model is evaluated by comparing it with the traditional TTC-based AEB model across the specified scenarios. The results demonstrate that the safety margin-based AEB model proposed in this study achieves 100% safe braking in all scenarios, successfully performing emergency braking and outperforming the TTC-based AEB model.
UR - https://www.scopus.com/pages/publications/105014240739
U2 - 10.1109/IV64158.2025.11097726
DO - 10.1109/IV64158.2025.11097726
M3 - 会议稿件
AN - SCOPUS:105014240739
T3 - IEEE Intelligent Vehicles Symposium, Proceedings
SP - 710
EP - 715
BT - IV 2025 - 36th IEEE Intelligent Vehicles Symposium
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 36th IEEE Intelligent Vehicles Symposium, IV 2025
Y2 - 22 June 2025 through 25 June 2025
ER -