Browse Publications Technical Papers 2017-01-0112

Method to Optimize Key Parameters and Effectiveness Evaluation of the AEB System Based on Rear-End Collision Accidents 2017-01-0112

Rear-end accident is one of the most important collision modes in China, which often leads to severe accident consequences due to the high collision velocity. Autonomous Emergency Braking (AEB) system could perform emergency brake automatically in dangerous situation and mitigate the consequence. This study focused on the analysis of the rear-end accidents in China in order to discuss about the parameters of Time–to-Collision (TTC) and the comprehensive evaluation of typical AEB. A sample of 84 accidents was in-depth investigated and reconstructed, providing a comprehensive set of data describing the pre-crash matrix. Each accident in this sample is modeled numerically by the simulation tool PC-Crash. In parallel, a model representing the function of an AEB system has been established. This AEB system applies partial braking when the TTC ≤ TTC1 and full braking when the TTC ≤ TTC2. Lastly, the AEB system’s model is coupled to the kinematic of the vehicle in simulation for virtual trajectories preceding the collision point to evaluate the potential effectiveness of different combinations of TTC according to the collision velocity reduction effectiveness and the excessive avoidance performance. After the simulations of 4284 run with 51 combination of the parameters based on 84 accidents, the results show that among the four desirable combinations, TTC1 = 1.0 s and TTC2 = 0.6 s is suitable for collision avoidance while TTC1 = 0.9 s and TTC2 = 0.5 s has satisfactory excessive collision avoidance.


Subscribers can view annotate, and download all of SAE's content. Learn More »


Members save up to 17% off list price.
Login to see discount.
We also recommend:

Assessment of Similarity of a Set of Impact Response Time Histories


View Details


Safety Benefits Estimation of an Intelligent Cruise Control System Using Field Operational Test Data


View Details


Modeling Ascending and Descending Stairs Using the Human Motion Simulation Framework


View Details