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• W2941499360 abstract "Safe autonomous driving in urban areas requires robust algorithms to avoid collisions with other traffic participants with limited perception ability. Current deployed approaches relying on Autonomous Emergency Braking (AEB) systems are often overly conservative. In this work, we formulate the problem as a partially observable Markov decision process (POMDP), to derive a policy robust to uncertainty in the pedestrian location. We investigate how to integrate such a policy with an AEB system that operates only when a collision is unavoidable. In addition, we propose a rigorous evaluation methodology on a set of well defined scenarios. We show that combining the two approaches provides a robust autonomous braking system that reduces unnecessary braking caused by using the AEB system on its own." @default.
• W2941499360 created "2019-05-03" @default.
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• W2941499360 date "2019-04-25" @default.
• W2941499360 modified "2023-09-23" @default.
• W2941499360 title "Pedestrian Collision Avoidance System for Scenarios with Occlusions" @default.
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• W2941499360 hasPublicationYear "2019" @default.
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