Low Level Control Layer Definition for Autonomous Vehicles Based on Fuzzy Logic

Abstract The intelligent control of autonomous vehicles is one of the most important challenges that intelligent transport systems face today. The application of artificial intelligence techniques to the automatic management of vehicle actuators enables the different Advanced Driver Assistance Systems (ADAS) or even autonomous driving systems, to perform a low level management in a very similar way to that of human drivers by improving safety and comfort. In this paper, we present a control schema to manage these low level vehicle actuators (steering throttle and brake) based on fuzzy logic, an artificial intelligence technique that is able to mimic human procedural behavior, in this case, when performing the driving task. This automatic low level control system has been defined, implemented and tested in a Citroen C3 testbed vehicle, whose actuators have been automated and can receive control signals from an onboard computer where the soft computing-based control system is running.

[1]  Fredrik Gustafsson,et al.  Toward Autonomous Collision Avoidance by Steering , 2007, IEEE Transactions on Intelligent Transportation Systems.

[2]  S. Cetinkunt,et al.  Modeling, control, and validation of an electro-hydraulic steer-by-wire system for articulated vehicle applications , 2005, IEEE/ASME Transactions on Mechatronics.

[3]  Eam Khwang Teoh,et al.  Fuzzy speed and steering control of an AGV , 2002, IEEE Trans. Control. Syst. Technol..

[4]  John A. Michon,et al.  A critical view of driver behavior models: What do we know , 1985 .

[5]  Shirong Liu,et al.  Real-Time Trajectory Tracking Of Mobile Robots Based On Sliding Mode Control Using Irbfnns , 2009, Intell. Autom. Soft Comput..

[6]  Michio Sugeno,et al.  On stability of fuzzy systems expressed by fuzzy rules with singleton consequents , 1999, IEEE Trans. Fuzzy Syst..

[7]  Wai-Kai Chen,et al.  Linear Networks and Systems , 1983 .

[8]  K Yi,et al.  An investigation of intelligent cruise control laws for passenger vehicles , 2001 .

[9]  Bing-Fei Wu,et al.  The Heterogeneous Systems Integration Design and Implementation for Lane Keeping on a Vehicle , 2008, IEEE Transactions on Intelligent Transportation Systems.

[10]  José Eugenio Naranjo,et al.  ACC+Stop&go maneuvers with throttle and brake fuzzy control , 2006, IEEE Transactions on Intelligent Transportation Systems.

[11]  Ebrahim Mamdani,et al.  Applications of fuzzy algorithms for control of a simple dynamic plant , 1974 .

[12]  Miguel Ángel Sotelo,et al.  Interoperable Control Architecture for Cybercars and Dual-Mode Cars , 2009, IEEE Transactions on Intelligent Transportation Systems.

[13]  L. D. Brock,et al.  Reliability/safety analysis of a fly-by-wire system , 1980 .

[14]  Manuel Haro Casado,et al.  Thruster Control Based On The Shunt Dc Motors For A Precise Positioning Of The Marine Vehicles , 2009, Intell. Autom. Soft Comput..

[15]  M. Sugeno,et al.  Fuzzy Control of Model Car , 1985 .

[16]  Willibald Prestl,et al.  The BMW Active Cruise Control ACC , 2000 .

[17]  Michio Sugeno,et al.  Industrial Applications of Fuzzy Control , 1985 .

[18]  T. Endo.  Development of reverse parking. assist with automatic steering , 2003 .

[19]  Miguel Angel Sotelo Vázquez.  Sistema de navegación global aplicado al guiado de un vehículo autónomo terrestre en entornos exteriores parcialmente conocidos , 2001 .

[20]  Rodolfo E. Haber,et al.  Power-steering control architecture for automatic driving , 2005, IEEE Transactions on Intelligent Transportation Systems.

[21]  Yeqiong Song,et al.  Evaluating quality of service and behavioral reliability of steer-by-wire systems , 2003, EFTA 2003. 2003 IEEE Conference on Emerging Technologies and Factory Automation. Proceedings (Cat. No.03TH8696).

[22]  J. Mendel.  Fuzzy logic systems for engineering: a tutorial , 1995, Proc. IEEE.

[23]  Peter Andreas,et al.  From adaptive cruise control to active safety systems , 2001 .

[24]  William Travis,et al.  SciAutonics-Auburn Engineering's low-cost high-speed ATV for the 2005 DARPA grand challenge , 2006 .

[25]  M. Sugeno,et al.  Fuzzy algorithmic control of a model car by oral instructions , 1989 .

[26]  Yong-Woon Park,et al.  Real-time collision avoidance method for unmanned ground vehicle , 2008, 2008 International Conference on Control, Automation and Systems.

[27]  Masayoshi Tomizuka,et al.  Fuzzy Logic Control for Lane Change Maneuvers in Lateral Vehicle Guidance , 1995 .

[28]  María Cristina Riff,et al.  An Evolutionary Navigator for Autonomous Agents on Unknown Large-Scale Environments , 2008, Intell. Autom. Soft Comput..

[29]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[30]  Cris Koutsougeras,et al.  KAT‐5: Robust systems for autonomous vehicle navigation in challenging and unknown terrain , 2006 .