This paper presents a novel collision mitigation method for traffic scenarios in which accidents are inevitable. When a predicted accident is imminent, the suggested software agent changes the trajectory of the ego vehicle to optimize the predicted crash configuration. The target function results from the degree of crash severity, based on the deformation of the safety cage in the occupant area. We have performed numerous crash simulations with detailed FEM models to determine the crash severity for possible crash configurations. Since inevitable crash scenarios are inherently time-critical, the focus is on fast optimization. The proposed heuristic search algorithm computes a collision trajectory from a given initial state by searching for the maneuver leading to the lowest crash severity in the reachable crash configuration set. We rely on a previously developed approach to trajectory modeling that guarantees a minimum execution time for trajectory generation and collision detection and respects the limits of vehicle dynamics. Simulations prove the applicability of the proposed algorithm.
Motion Planning for Collision Mitigation via FEM–Based Crash Severity Maps
2019 IEEE Intelligent Vehicles Symposium (IV) ; 2187-2194
2019-06-01
3968282 byte
Conference paper
Electronic Resource
English
MOTION PLANNING FOR COLLISION MITIGATION VIA FEM—BASED CRASH SEVERITY MAPS
British Library Conference Proceedings | 2019
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