Motion Planning via Optimization of Risk Quantified by Collision Velocity Accompanied with AEB Activation

Tsukasa Shimizu1, Pongsathorn Raksincharoensak2

  • 1Toyota Central R&D Labs., INC.
  • 2Tokyo University of Agriculture and Technology

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Regular Paper

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10:48 - 12:36 | Tue 27 Jun | | TuBPl

Trajectory Planning for Autonomous Vehicles

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Abstract

Risk predictive driving is essential to maintain safety while passing a parked vehicle, which is one of typical high risk traffic situations because a pedestrian might suddenly dart out from behind the parked vehicle. Aiming at generating a vehicle motion for risk predictive driving, first, a novel risk quantification method based on collision velocity accompanied with AEB (Automatic Emergency Braking) is presented via a simulated pedestrian darting out from behind the parked vehicle. Next, a preliminary investigation is conducted to show the effectiveness of the presented risk quantification on motion planning for risk predictive driving. The generated motion shows good consistency with actual safe driving data measured in same situations.

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