TY - JOUR
T1 - Pedestrian Collision Avoidance System for Autonomous Vehicles
AU - Schratter, Markus
AU - Watzenig, Daniel
AU - Hartmann, Michael
PY - 2019
Y1 - 2019
N2 - Advanced driver assistance systems (ADAS) are state of the art in modern vehicles (SAE level 1-2). They support the driver and improve thereby the vehicle safety during manual driving. In critical situations, collision avoidance systems warn the driver or trigger an autonomous emergency braking maneuver to mitigate or avoid a collision. Also, automated driving vehicles (SAE level 3+) must be able to avoid critical situations and must be more capable than currently available systems. During automated driving, the vehicle is responsible for the driving task instead of the driver. Therefore, safe automated driving requires robust algorithms to avoid collisions with other traffic participants in every situation, especially in critical situations with pedestrians and a limited perception ability. In this work, we investigate how automated driving vehicles can handle critical situations with pedestrians on multilane roads with an emergency braking or evasion maneuver. We focus in detail on very critical situations, where pedestrians are crossing behind an occluded area, e.g. from behind a parked car on the side of the road. In these critical situations, a collision avoidance system is not enough anymore because of the limited time-to-react. It is not acceptable that an automated driving vehicle passes obstacles very slowly. Therefore, a collision avoidance system is combined with a situation awareness planner to optimize the driving velocity. The situation awareness planner considers the sensor’s visibility and the capability of the collision avoidance system to provide a set of collision-free trajectories. This combination has the advantage that the vehicle does not need to pass objects on the side very conservative. We evaluate the approach rigorously on a set of well-defined scenarios from the Euro NCAP test protocol.
AB - Advanced driver assistance systems (ADAS) are state of the art in modern vehicles (SAE level 1-2). They support the driver and improve thereby the vehicle safety during manual driving. In critical situations, collision avoidance systems warn the driver or trigger an autonomous emergency braking maneuver to mitigate or avoid a collision. Also, automated driving vehicles (SAE level 3+) must be able to avoid critical situations and must be more capable than currently available systems. During automated driving, the vehicle is responsible for the driving task instead of the driver. Therefore, safe automated driving requires robust algorithms to avoid collisions with other traffic participants in every situation, especially in critical situations with pedestrians and a limited perception ability. In this work, we investigate how automated driving vehicles can handle critical situations with pedestrians on multilane roads with an emergency braking or evasion maneuver. We focus in detail on very critical situations, where pedestrians are crossing behind an occluded area, e.g. from behind a parked car on the side of the road. In these critical situations, a collision avoidance system is not enough anymore because of the limited time-to-react. It is not acceptable that an automated driving vehicle passes obstacles very slowly. Therefore, a collision avoidance system is combined with a situation awareness planner to optimize the driving velocity. The situation awareness planner considers the sensor’s visibility and the capability of the collision avoidance system to provide a set of collision-free trajectories. This combination has the advantage that the vehicle does not need to pass objects on the side very conservative. We evaluate the approach rigorously on a set of well-defined scenarios from the Euro NCAP test protocol.
U2 - 10.4271/12-02-04-0021
DO - 10.4271/12-02-04-0021
M3 - Article
SN - 2574-0741
VL - 2
SP - 279
EP - 293
JO - SAE International Journal of Connected and Automated Vehicles
JF - SAE International Journal of Connected and Automated Vehicles
IS - 4
ER -