An Improved Local Dynamic Path Planning Algorithm for Autonomous Driving

In this paper, an improved autonomous driving local dynamic path planning algorithm is proposed. Based on the predefined road center points, a set of path control points is constructed, and a one-dimensional cubic equation is used to fit the path and construct a center line. A new curved coordinate system is provided using the center line, and the path candidates are generated by arc length and lateral offset. The overall path is selected in consideration of the total cost of path safety and comfort. The results showed that under different scenarios, the proposed local path planning algorithm can plan an optimal path that does not collide with static obstacles, and can ensure the comfort of autonomous driving vehicles and the real-time path planning.

[1]  Jason Jianjun Gu,et al.  Artificial Immune Network-Based Multi-robot Formation Path Planning with obstacle avoidance , 2016, Int. J. Robotics Autom..

[2]  Myoungho Sunwoo,et al.  Local Path Planning for Off-Road Autonomous Driving With Avoidance of Static Obstacles , 2012, IEEE Transactions on Intelligent Transportation Systems.

[3]  Sébastien Campocasso,et al.  Automatic multi-axis path planning for thinwall tubing through robotized wire deposition , 2019, Procedia CIRP.

[4]  Jason Jianjun Gu,et al.  Fast Weighted Total Variation Regularization Algorithm for Blur Identification and Image Restoration , 2016, IEEE Access.

[5]  Jean-Yves Fourquet,et al.  Multi-layer path planning control for the simulation of manipulation tasks: Involving semantics and topology , 2019, Robotics and Computer-Integrated Manufacturing.

[6]  Juan Cort Sampling-Based Path Planning on Configuration-Space Costmaps , 2010 .

[7]  Fuad E. Alsaadi,et al.  A new approach to smooth global path planning of mobile robots with kinematic constraints , 2019, Int. J. Mach. Learn. Cybern..

[8]  Long Chen,et al.  Dynamic path planning for autonomous driving on various roads with avoidance of static and moving obstacles , 2018 .

[9]  Wang Juan Mobile Robot Path Planning Algorithm Based on Particle Swarm Optimization of Cubic Splines , 2009 .

[10]  Jason Jianjun Gu,et al.  An Efficient Method for Traffic Sign Recognition Based on Extreme Learning Machine , 2017, IEEE Transactions on Cybernetics.