Highly automated road vehicles need the capabilityof stopping safely in a situation that disrupts continued normaloperation, e.g. due to internal system faults. Motion planningfor safe stop differs from nominal motion planning, since thereis not a specific goal location. Rather, the desired behavior isthat the vehicle should reach a stopped state, preferably outsideof active lanes. Also, the functionality to stop safely needs tobe of high integrity. The first contribution of this paper isto formulate the safe stop problem as a benchmark optimalcontrol problem, which can be solved by dynamic programming.However, this solution method cannot be used in real-time. Thesecond contribution is to develop a real-time safe stop trajectoryplanning algorithm, based on selection from a precomputedset of trajectories. By exploiting the particular properties ofthe safe stop problem, the cardinality of the set is decreased,making the algorithm computationally efficient. Furthermore, amonitoring based architecture concept is proposed, that ensuresdependability of the safe stop function. Finally, a proof of conceptsimulation using the proposed architecture and the safe stoptrajectory planner is presented. ; QC 20180806
Safe Stop Trajectory Planning for Highly Automated Vehicles:An Optimal Control Problem Formulation
2018-01-01
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
DDC: | 629 |
SAFE STOP TRAJECTORY PLANNING FOR HIGHLY AUTOMATED VEHICLES: AN OPTIMAL CONTROL PROBLEM FORMULATION
British Library Conference Proceedings | 2018
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Safe trajectory planning of autonomous vehicles.
Safe trajectory planning of AV
DSpace@MIT | 2006
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