Evaluating the Effects of Cooperative Perception on Avoiding Pedestrian Crashes for Connected and Automated Vehicles

At an intersection, a crash between a pedestrian and a vehicle may occur under the occluded condition. An automated emergency braking (AEB) system could be utilized to actively detect pedestrians and react to avoid potential conflicts. This study contribution is evaluating the effectiveness of the AEB system under occlusion conditions. The braking algorithm was developed in the virtual simulator CARLA to control the ego vehicle. Three occlusion scenarios in which the sensor of the AEB system could not detect the pedestrian if the pedestrian is occluded by a stopping vehicle. The evaluation experiments were conducted at a typical 4-leg intersection considering different motion statuses of the ego vehicle and pedestrian. The effects of field of view (FoV) of the sensor and activation threshold of the AEB system were also explored. The study indicated that the effectiveness of the AEB system could be reduced by the occlusion time. A longer activation threshold is recommended if the pedestrian is potentially occluded for a long time. The effects of other factors such as the speed of the ego vehicle and pedestrian and scenarios were also identified.