Christoph Keller, Thao Dang, Hans Fritz, Armin Joos, Clemens Rabe, Dariu GavrilaAbstractActive 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. [Download] [View] [BibTeX] |
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