A Global Optimal Path Planning and Controller Design Algorithm for Intelligent Vehicles

Autonomous vehicle guidance and trajectory planning is one of the key technologies in the autonomous control system for intelligent vehicles. Firstly, the target pursuit model for intelligent vehicles was established and described in this text. Then, the research work for global motion planning was carried out based on Stackelberg Differential Game Theory, and the global optimal solution was obtained by using the survival type differential game. Finally, to overcome errors, we use a polynomial method to achieve the smooth motion planning. So, based on Terminal Sliding Mode method, the Active Front Steering controller design was used to calculate the desired active wheel angle for intelligent vehicle path tracking. The simulation and experiment results demonstrate the feasibility and effectiveness of this method for intelligent vehicles’ path planning and tracking.

[1]  Michaël Soulignac,et al.  Feasible and Optimal Path Planning in Strong Current Fields , 2011, IEEE Transactions on Robotics.

[2]  Xudong Zhang.  Adjacent Scatter Point Cloud Registration Technology Research Based on Three-dimensional Camera of Time of Flight , 2013 .

[3]  Marco Dorigo,et al.  Path formation in a robot swarm , 2008, Swarm Intelligence.

[4]  A. Gasparetto,et al.  A technique for time-jerk optimal planning of robot trajectories , 2008 .

[5]  Sterling J. Anderson,et al.  An optimal-control-based framework for trajectory planning, threat assessment, and semi-autonomous control of passenger vehicles in hazard avoidance scenarios , 2010 .

[6]  Zeng Wen-xia.  Transmission of wireless sensor networks based on distributed multi-staging area check method , 2014 .

[7]  Thierry Siméon,et al.  Sampling-Based Path Planning on Configuration-Space Costmaps , 2010, IEEE Transactions on Robotics.

[8]  Sebastian Thrun,et al.  Path Planning for Autonomous Vehicles in Unknown Semi-structured Environments , 2010, Int. J. Robotics Res..

[9]  Alessandro Gasparetto,et al.  Experimental validation and comparative analysis of optimal time-jerk algorithms for trajectory planning , 2012 .

[10]  Lie Guo,et al.  Trajectory planning and tracking control for autonomous lane change maneuver based on the cooperative vehicle infrastructure system , 2015, Expert Syst. Appl..

[11]  Oscar Castillo,et al.  Path planning for autonomous mobile robot navigation with ant colony optimization and fuzzy cost function evaluation , 2009, Appl. Soft Comput..

[12]  Vincent Roberge,et al.  Comparison of Parallel Genetic Algorithm and Particle Swarm Optimization for Real-Time UAV Path Planning , 2013, IEEE Transactions on Industrial Informatics.

[13]  Maxim Likhachev,et al.  Planning Long Dynamically Feasible Maneuvers for Autonomous Vehicles , 2008, Int. J. Robotics Res..

[14]  T. Siméon,et al.  An NMA‐guided path planning approach for computing large‐amplitude conformational changes in proteins , 2007, Proteins.

[15]  Emilio Frazzoli,et al.  Sampling-based algorithms for optimal motion planning , 2011, Int. J. Robotics Res..

[16]  Yudong Zhang,et al.  A Novel Kinematic Coupling-Based Trajectory Planning Method for Overhead Cranes , 2012, IEEE/ASME Transactions on Mechatronics.

[17]  Fang Liu,et al.  Chaotic artificial bee colony approach to Uninhabited Combat Air Vehicle (UCAV) path planning , 2010 .

[18]  Jonathan P. How,et al.  Real-Time Motion Planning With Applications to Autonomous Urban Driving , 2009, IEEE Transactions on Control Systems Technology.

[19]  Carlos Silvestre,et al.  Coordinated Path-Following in the Presence of Communication Losses and Time Delays , 2009, SIAM J. Control. Optim..

[20]  Antonella Ferrara,et al.  Trajectory Planning and Second-Order Sliding Mode Motion/Interaction Control for Robot Manipulators in Unknown Environments , 2012, IEEE Transactions on Industrial Electronics.

[21]  Tonghai Jiang,et al.  An Method for Vehicle-Flow Detection and Tracking in Real-Time Based on Gaussian Mixture Distribution , 2013 .

[22]  Benoit Vanholme,et al.  Maneuver-Based Trajectory Planning for Highly Autonomous Vehicles on Real Road With Traffic and Driver Interaction , 2010, IEEE Transactions on Intelligent Transportation Systems.

[23]  Dong Sun,et al.  Coordinated Motion Planning for Multiple Mobile Robots Along Designed Paths With Formation Requirement , 2011, IEEE/ASME Transactions on Mechatronics.

[24]  Ching-Chih Tsai,et al.  Parallel Elite Genetic Algorithm and Its Application to Global Path Planning for Autonomous Robot Navigation , 2011, IEEE Transactions on Industrial Electronics.

[25]  N.M. Patrikalakis,et al.  Path Planning of Autonomous Underwater Vehicles for Adaptive Sampling Using Mixed Integer Linear Programming , 2008, IEEE Journal of Oceanic Engineering.

[26]  Jiang Wu,et al.  Novel intelligent water drops optimization approach to single UCAV smooth trajectory planning , 2009 .

[27]  N. Mahmoudian,et al.  Approximate Analytical Turning Conditions for Underwater Gliders: Implications for Motion Control and Path Planning , 2010, IEEE Journal of Oceanic Engineering.

[28]  Dinesh Manocha,et al.  Real-Time Path Planning in Dynamic Virtual Environments Using Multiagent Navigation Graphs , 2008, IEEE Transactions on Visualization and Computer Graphics.

[29]  Hadas Kress-Gazit,et al.  Temporal-Logic-Based Reactive Mission and Motion Planning , 2009, IEEE Transactions on Robotics.