Reactive Path Planning for Autonomous Vehicle Using Bézier Curve Optimization

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 reactive and adaptive regarding life situations, traffic and obstacle crossing. In this paper, a Bézler curve optimization method is proposed to cope with these constraints and autonomous vehicles are considered equipped with all necessary sensors for obstacle detection. In this way, the obstacle avoidance problem is transformed into an optimization problem under equality constraints. This optimization problem is solved by combining Quadratic Programming (QP) and Hildreth's algorithm.

[1]  Benedetto Allotta,et al.  Generic Path Planning Algorithm for Mobile Robots Based on Bézier Curves , 2016 .

[2]  Thomas Gustafsson,et al.  Online Dynamic Smooth Path Planning for an Articulated Vehicle , 2013, ICINCO.

[3]  A. Oustaloup,et al.  Weyl fractional potential in path planning , 2001, 2001 European Control Conference (ECC).

[4]  Shuzhi Sam Ge,et al.  Dynamic Motion Planning for Mobile Robots Using Potential Field Method , 2002, Auton. Robots.

[5]  Eid H. Doha,et al.  Integrals of Bernstein polynomials: An application for the solution of high even-order differential equations , 2011, Appl. Math. Lett..

[6]  Purnima Parida,et al.  Estimation of Delay and Fuel Loss during Idling of Vehicles at Signalised Intersection in Ahmedabad , 2013 .

[7]  Ali Charara,et al.  Local Trajectory Planning and Tracking For Autonomous Vehicle Navigation Using Clothoid Tentacles Method , 2015 .

[8]  Nengcheng Chen,et al.  Efficient UAV Path Planning with Multiconstraints in a 3D Large Battlefield Environment , 2014 .

[9]  Daniel Delahaye,et al.  Potential Odor Intensity Grid Based UAV Path Planning Algorithm with Particle Swarm Optimization Approach , 2016 .

[10]  Stéphanie Lefèvre,et al.  Estimation du risque aux intersections pour applications sécuritaires avec véhicules communicants. (Risk estimation at road intersections for connected vehicle safety applications) , 2012 .

[11]  Franck Guillemard,et al.  TRAJECTORY PLANNING FOR AUTONOMOUS VEHICLE IN UNCERTAIN ENVIRONMENT USING EVIDENTIAL GRID , 2017 .

[12]  R. A. Fields Continuous Control Artificial Potential Function Methods and Optimal Control , 2014 .

[13]  François Aioun,et al.  Path planning with fractional potential fields for autonomous vehicles , 2017 .

[14]  A. Oustaloup,et al.  Robust path planning for dynamic environment based on fractional attractive force , 2009, 2009 6th International Multi-Conference on Systems, Signals and Devices.

[15]  Denis Gillet,et al.  Decentralized Coordination of Autonomous Vehicles at intersections , 2011 .

[16]  Xavier Moreau,et al.  CRONE Cruise Control System , 2016, IEEE Transactions on Vehicular Technology.

[17]  Naoki Shibata,et al.  Collision avoidance control with steering using velocity potential field , 2014, 2014 IEEE Intelligent Vehicles Symposium Proceedings.

[18]  David González Bautista,et al.  Functional architecture for automated vehicles trajectory planning in complex environments , 2017 .

[19]  Huijing Zhao,et al.  A Human-like Trajectory Planning Method by Learning from Naturalistic Driving Data , 2018, 2018 IEEE Intelligent Vehicles Symposium (IV).

[20]  Olivier Lavialle,et al.  Consideration of obstacle danger level in path planning using A* and Fast-Marching optimisation: comparative study , 2003, Signal Process..