A Behavior-Based Path Planning for Autonomous Vehicle

The path planning is one of the key issues of autonomous vehicle. In this paper, a behavior-based method is used for path planning. This method can manage complexity environment and is easy to design and test behaviors. An autonomous electric vehicle is tested in a driving course including the behaviors of road following, turning, obstacle avoidance and emergency braking. The test results show that the path planning algorithm can run in a real-time, while the unknown obstacles can be avoided and the autonomous vehicle can be driven toward the destination in a smooth path and continuous motion.

[1]  A. El Hajjaji,et al.  Modeling Human Vehicle Driving by fuzzy logic for standardized ISO double lane change maneuver , 2001, Proceedings 10th IEEE International Workshop on Robot and Human Interactive Communication. ROMAN 2001 (Cat. No.01TH8591).

[2]  Guan Xin,et al.  Driver Directional Control Model and the Application in the Research of Intelligent Vehicle , 2000 .

[3]  R. Dillmann,et al.  Design of the planner of team AnnieWAY’s autonomous vehicle used in the DARPA Urban Challenge 2007 , 2008, 2008 IEEE Intelligent Vehicles Symposium.

[4]  David C. Conner.  Sensor Fusion, Navigation, and Control of Autonomous Vehicles , 2000 .

[5]  Martial Hebert,et al.  A behavior-based system for off-road navigation , 1994, IEEE Trans. Robotics Autom..

[6]  Winston Nelson,et al.  Continuous-curvature paths for autonomous vehicles , 1989, Proceedings, 1989 International Conference on Robotics and Automation.

[7]  Tan Yuegang.  A Method Solving the Local Minimization Problem of Artificial Potential Field , 2005 .

[8]  A. Ramirez-Serrano,et al.  Navigation of unmanned vehicles using a swarm of intelligent dynamic landmarks , 2005, IEEE International Safety, Security and Rescue Rototics, Workshop, 2005..

[9]  Zhang Zeng-fang.  Study of local path planning of mobile robot based on improved artificial potential field method , 2008 .

[10]  Gabor Horvath,et al.  Artificial neural network based mobile robot navigation , 2009, 2009 IEEE International Symposium on Intelligent Signal Processing.

[11]  Li Long-shu.  A Method for Solving Local Minimization Problem of Artificial Potential Field , 2007 .

[12]  Y Zhang.  Study of Local Path Planning of Mobile Robot based on Improved Artificial Potential Field Method , 2006 .

[13]  Mohamed B. Trabia,et al.  Steering fuzzy logic controller for an autonomous vehicle , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[14]  G.K. Venayagamoorthy,et al.  Unmanned vehicle navigation using swarm intelligence , 2004, International Conference on Intelligent Sensing and Information Processing, 2004. Proceedings of.

[15]  Alain Liégeois,et al.  Generalized polar polynomials for vehicle path generation with dynamic constraints , 1996, Proceedings of IEEE International Conference on Robotics and Automation.