Analyzing the performance of a V2X-enhanced braking system in real-world crash situations

By using an automated braking system, such as the Automatic Emergency Brake (AEB), crashes can be avoided in situations where the driver is unaware of an imminent collision. However, conventional AEB systems detect potential collision adversaries with onboard sensor systems, such as radars and cameras, that may fail in non-line-of-sight situations. By lever-aging vehicle-to-everything (V2X) communication, information regarding an approaching vehicle can be received by the ego vehicle at an early point in time, even if the opponent vehicle is occluded by a view obstruction. In this work, we consider a 2-stage braking cascade, consisting of a partial brake, triggered based on V2X information, and a sensor-triggered AEB. We evaluate its crash avoidance performance in real-world crash situations extracted from the German In-Depth Accident Study (GIDAS) database using an accident simulation framework. The results are compared against a sensor-triggered AEB system and a purely V2X-triggered partial brake. To further analyze the results, we identify the crash cause for each situation in which the brake function under test could not prevent the crash. The simulation results show a high added benefit of the V2X-enhanced braking systems compared to the exclusive use of visual-based sensor systems for automated collision prevention.