A personalized path generation for an autonomous vehicle overtaking maneuver

Benoit Vigne (1, 2) , Rodolfo Orjuela (2, 1) , Jean-Philippe Lauffenburger (2, 1) , Michel Basset (2, 1)

1 IRIMAS - Institut de Recherche en Informatique Mathématiques Automatique Signal
2 Université de Haute-Alsace (UHA) - Université de Haute-Alsace (UHA) Mulhouse - Colmar

The acceptability by a population for new technology is conditioned by its benefits and its adaptability. While an autonomous vehicle could be a nice solution as an intelligent transportation system to decrease road crashes, traffic jams, etc., the choice of a driving style (relaxed/sporty) could be a good factor of adaptability. This study presents a method to optimize a local overtaking trajectory defined as a sigmoid function integrating constraints of comfort, safety, and path continuity. An only one driving style parameter allows obtaining different paths from smooth to tight shapes respecting previous constraints. Simulations of use cases show good performance of the developed algorithm.

Mots clés: autonomous vehicle; driving style; parameter optimization; overtaking maneuver

Domaines: Sciences de l'ingénieur [physics]

Benoit Vigne, Rodolfo Orjuela, Jean-Philippe Lauffenburger, Michel Basset. A personalized path generation for an autonomous vehicle overtaking maneuver. 11th IFAC Symposium on Intelligent Autonomous Vehicles - IAV2022, Jul 2022, Prague, Czech Republic. ⟨hal-03720989⟩