On-line reference trajectory generation for manually convoying a platoon of automatic urban vehicles

Various #x201C;Urban Transportation Systems#x201D; are currently in developing, in order to put forward solutions to congestion and pollution in dense areas. Autonomous electric vehicles in free-access can be seen as an attractive approach, in view of the large flexibility that can be expected. One instrumental functionality linked to this solution is platoon motion: several autonomous vehicles accurately follow the trajectory of a manually driven first vehicle, with pre-specified inter-distances. A global decentralized platoon control strategy, supported by inter-vehicle communications and relying on nonlinear control techniques is here proposed. Each vehicle is controlled with respect to the same smooth reference trajectory, inferred on-line from the motion of the first vehicle via B-spline optimization. Experimental results, carried out with four urban vehicles, demonstrate the capabilities of the proposed approach.

[1]  Steven M. LaValle,et al.  Current Issues in Sampling-Based Motion Planning , 2005, ISRR.

[2]  Patrick Rives,et al.  Vision-based Control for Car Platooning using Homography Decomposition , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[3]  Philippe Martinet,et al.  Nonlinear Control for Urban Vehicles Platooning, Relying upon a Unique Kinematic GPS , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[4]  Philippe Martinet,et al.  Accurate automatic guidance of an urban electric vehicle relying on a kinematic GPS sensor , 2004 .

[5]  Aurelio Piazzi,et al.  Quintic G2-splines for the iterative steering ofvision-based autonomous vehicles , 2002, IEEE Trans. Intell. Transp. Syst..

[6]  Jean-Paul Laumond,et al.  Dynamic path modification for car-like nonholonomic mobile robots , 1997, Proceedings of International Conference on Robotics and Automation.

[7]  Yi Guo,et al.  Formation Control of Nonholonomic Mobile Robots Using Graph Theoretical Methods , 2007 .

[8]  Zhihua Qu,et al.  A new analytical solution to mobile robot trajectory generation in the presence of moving obstacles , 2004, IEEE Transactions on Robotics.

[9]  Kazuo Tanie,et al.  Trajectory Design and Control of a Wheel-type Mobile Robot Using B-spline Curve , 1989, Proceedings. IEEE/RSJ International Workshop on Intelligent Robots and Systems '. (IROS '89) 'The Autonomous Mobile Robots and Its Applications.

[10]  Danwei Wang,et al.  Unified Control Design for Autonomous Car-Like Vehicle Tracking Maneuvers , 2006 .

[11]  Micha Sharir,et al.  A Survey of Motion Planning and Related Geometric Algorithms , 1988, Artificial Intelligence.

[12]  Jean-Claude Latombe,et al.  Motion Planning: Recent Developments , 2018, Autonomous Mobile Robots.

[13]  Juan Humberto Sossa Azuela,et al.  Auto Guided Vehicle Control using Expanded Time B- Splines , 1994 .

[14]  Chun Che Fung,et al.  Implementation of the spline method for mobile robot path control , 1999, IMTC/99. Proceedings of the 16th IEEE Instrumentation and Measurement Technology Conference (Cat. No.99CH36309).

[15]  C. Samson.  Control of chained systems application to path following and time-varying point-stabilization of mobile robots , 1995, IEEE Trans. Autom. Control..

[16]  John Valasek,et al.  Preliminary results of one-dimensional vehicle formation control using a structural analogy , 2003, Proceedings of the 2003 American Control Conference, 2003..

[17]  Domenico Prattichizzo,et al.  Discussion of paper by , 2003 .

[18]  Soo-Yeong Yi,et al.  Impedance control for a vehicle platoon system , 2005 .

[19]  Dong-Soo Kwon,et al.  Mobile robots at your fingertip: Bezier curve on-line trajectory generation for supervisory control , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).