LAUSR

Crashes between cars and powered two‐wheelers (PTWs: motorcycles, scooters, and e‐bikes) are a safety concern; as a result, developing car safety systems that protect PTW riders is essential. While the pre‐crash protection system automated emergency braking (AEB) has been shown to avoid and mitigate injuries for car‐to‐car, car‐to‐cyclist, and car‐to‐pedestrian crashes, much is still unknown about its effectiveness in car‐to‐PTW crashes. Further, the characteristics of the crashes that remain after the introduction of such systems in traffic are also largely unknown. This study estimates the crash avoidance and injury risk reduction performance of six different PTW‐AEB algorithms that were virtually applied to reconstructed car‐to‐PTW pre‐crash kinematics extracted from a Chinese in‐depth crash database. Five of the algorithms include combinations of drivers’ and PTW riders’ comfort zone boundaries for braking and steering, while the sixth is a traditional AEB. Results show that the average safety performance of the algorithms using only the driver's comfort zone boundaries is higher than that of the traditional AEB algorithm. All algorithms resulted in similar distributions of impact speed and impact locations, which means that in‐crash protection systems likely can be made less complex, not having to consider differences in AEB algorithm design among car manufacturers.