Optimization-based motion primitive automata for autonomous driving

at - Automatisierungstechnik, vol. 71, pp. 294–300

Abstract

Abstract Trajectory planning for autonomous cars can be addressed by primitive-based methods, which encode nonlinear dynamical system behavior into automata. In this paper, we focus on optimal trajectory planning. Since, typically, multiple criteria have to be taken into account, multiobjective optimization problems have to be solved. For the resulting Pareto-optimal motion primitives, we introduce a universal automaton, which can be reduced or reconfigured according to prioritized criteria during planning. We evaluate a corresponding multi-vehicle planning scenario with both simulations and laboratory experiments.

Authors 4

1. Matheus V. A. Pedrosa corresponding

   Saarland University

   Affiliation as printed

   Chair of Systems Modeling and Simulation, Systems Engineering , Saarland University , Saarbrücken , Germany

2. Patrick Scheffe Aachen Chair for Embedded Software

   RWTH Aachen University

   Affiliation as printed

   Chair for Embedded Software , RWTH Aachen University , Aachen , Germany

3. Bassam Alrifaee Aachen Chair for Embedded Software

   RWTH Aachen University

   Affiliation as printed

   Chair for Embedded Software , RWTH Aachen University , Aachen , Germany

4. Kathrin Flaßkamp

   Saarland University

   Affiliation as printed

   Chair of Systems Modeling and Simulation, Systems Engineering , Saarland University , Saarbrücken , Germany