Citation

Salzmann F, Gadi S, Gundlach I. Int. J. Veh. Perform. 2022; 8(1): 46-73.

Copyright

(Copyright © 2022, Inderscience Publishers)

DOI

10.1504/IJVP.2022.119437

PMID

unavailable

Abstract

This paper deals with an accurate, robust and efficient optimisation method for time optimal path planning on circular tracks. Starting with a general description of the problem, suitable method domains for time-optimal path planning are qualified. In terms of reproducibility and accuracy, we propose an algorithm combining a model- and a policy-based method which takes car, track and driving data gathered from connected cars into account. Hence, it can provide a consistently learning as well as a sufficient constant time-optimal racing line on worldwide race tracks for different driver assistance purposes. We evaluated the calculated racing lines with respect to heuristic criteria like curve cutting behaviour and by comparing them to ones driven by professional race drivers.

Keywords: advanced driver assistance; connected car; reinforcement learning; trajectory optimisation; vehicle dynamics.

Language: en