Active pedestrian safety by automatic braking and evasive steering

• Verfasst von: Keller, Christoph Gustav [VerfasserIn]
• Verfasst von: Dang, Thao [VerfasserIn]
• Verfasst von: Fritz, Hans [VerfasserIn]
• Verfasst von: Joos, Armin [VerfasserIn]
• Verfasst von: Rabe, Clemens [VerfasserIn]
• Verfasst von: Gavrila, Dariu M. [VerfasserIn]
• Titel: Active pedestrian safety by automatic braking and evasive steering
• Verf.angabe: Christoph G. Keller, Thao Dang, Hans Fritz, Armin Joos, Clemens Rabe, Dariu M. Gavrila
• E-Jahr: 2011
• Jahr: 30 June 2011
• Umfang: 13 S.
• Fussnoten: Gesehen am 28.07.2022
• Titel Quelle: Enthalten in: Institute of Electrical and Electronics EngineersIEEE transactions on intelligent transportation systems
• Ort Quelle: New York, NY : Inst. of Electrical and Electronics Engineers, 2000
• Jahr Quelle: 2011
• Band/Heft Quelle: 12(2011), 4, Seite 1292-1304
• DOI: doi:10.1109/TITS.2011.2158424
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Active safety intelligent transport system (ITS)
• Sach-SW: Collision avoidance
• Sach-SW: computer vision
• Sach-SW: Driver circuits
• Sach-SW: Estimation
• Sach-SW: pedestrian detection
• Sach-SW: Safety
• Sach-SW: Sensors
• Sach-SW: Trajectory
• Sach-SW: vehicle control
• Sach-SW: Vehicles
• K10plus-PPN: 1811891446

Abstract

Active safety systems hold great potential for reducing accident frequency and severity by warning the driver and/or exerting automatic vehicle control ahead of crashes. This paper presents a novel active pedestrian safety system that combines sensing, situation analysis, decision making, and vehicle control. The sensing component is based on stereo vision, and it fuses the following two complementary approaches for added robustness: 1) motion-based object detection and 2) pedestrian recognition. The highlight of the system is its ability to decide, within a split second, whether it will perform automatic braking or evasive steering and reliably execute this maneuver at relatively high vehicle speed (up to 50 km/h). We performed extensive precrash experiments with the system on the test track (22 scenarios with real pedestrians and a dummy). We obtained a significant benefit in detection performance and improved lateral velocity estimation by the fusion of motion-based object detection and pedestrian recognition. On a fully reproducible scenario subset, involving the dummy that laterally enters into the vehicle path from behind an occlusion, the system executed, in more than 40 trials, the intended vehicle action, i.e., automatic braking (if a full stop is still possible) or automatic evasive steering.