Prioritized Trajectory Planning for Networked Vehicles Using Motion Primitives

Springer eBooks, pp. 253–275

Abstract

Abstract The computation time required to solve nonconvex, nonlinear optimization problems increases rapidly with their size. This poses a challenge in trajectory planning for multiple networked vehicles with collision avoidance. In the centralized formulation, the optimization problem size increases with the number of vehicles in the networked control system (NCS), rendering the formulation unusable for experiments. We investigate two methods to decrease the complexity of networked trajectory planning. First, we approximate the optimization problem by discretizing the vehicle dynamics with an automaton, which turns it into a graph-search problem. Our search-based trajectory planning algorithm has a limited horizon to further decrease computation complexity. We achieve recursive feasibility by design of the automaton which models the vehicle dynamics. Second, we distribute the optimization problem to the vehicles with prioritized distributed model predictive control (P-DMPC), which reduces the problem size. To counter the incompleteness of P-DMPC, we propose a framework for time-variant priority assignment. The framework expands recursive feasibility to every vehicle in the NCS. We present two time-variant priority assignment algorithms for road vehicles, one to improve vehicle progress and one to improve computation time of the NCS. We evaluate our approach for online trajectory planning of multiple networked vehicles in simulations and experiments.

Authors 4

1. Patrick Scheffe corresponding Aachen Chair of Embedded Software

   RWTH Aachen University

   Affiliation as printed

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

2. Matheus V. A. Pedrosa

   Saarland University

   Affiliation as printed

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

3. Kathrin Flaßkamp

   Saarland University

   Affiliation as printed

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

4. Bassam Alrifaee

   Universität der Bundeswehr München

   Affiliation as printed

   Department of Aerospace Engineering, University of the Bundeswehr Munich, Neubiberg, Germany