@ARTICLE{10.21494/ISTE.OP.2018.0282, 

TITLE={Path planning with fractional potential fields for autonomous vehicles}, 
  
AUTHOR={Pierre Melchior, Stéphane Victor, Julien Moreau, Mathieu Moze, François Aioun, Franck Guillemard, }, 
	
JOURNAL={Control}, 
	
VOLUME={2}, 

NUMBER={Issue 1}, 
	
YEAR={2018}, 

URL={https://openscience.fr/Path-planning-with-fractional-potential-fields-for-autonomous-vehicles}, 
	
DOI={10.21494/ISTE.OP.2018.0282}, 
	
ISSN={2631-4924}, 
	
ABSTRACT={Path planning is an essential stage for mobile robot control. It is more newsworthy than ever in the automotive context and especially for autonomous vehicle. Also, path planning methods need to be adaptive regarding life situations, traffic and obstacle crossing. In this paper, potential field methods are proposed to cope with these constraints and autonomous vehicles are considered equipped with all necessary sensors for obstacle detection. In this way, Ge&Cui’s attractive potential field and fractional attractive potential field have been adapted to the context of autonomous vehicles.
In this way, this latter method ensures better stability degree robustness with controlled vehicle acceleration.}}