The Heterogeneous Systems Integration Design and Implementation for Lane Keeping on a Vehicle

In this paper, an intelligent automated lane-keeping system is proposed and implemented on our vehicle platform, i.e., TAIWAN i TS-1. This system challenges the online integrating heterogeneous systems such as a real-time vision system, a lateral controller, in-vehicle sensors, and a steering wheel actuating motor. The implemented vision system detects the lane markings ahead of the vehicle, regardless of the varieties in road appearance, and determines the desired trajectory based on the relative positions of the vehicle with respect to the center of the road. To achieve more humanlike driving behavior such as smooth turning, particularly at high levels of speed, a fuzzy gain scheduling (FGS) strategy is introduced to compensate for the feedback controller for appropriately adapting to the SW command. Instead of manual tuning by trial and error, the methodology of FGS is designed to ensure that the closed-loop system can satisfy the crossover model principle. The proposed integrated system is examined on the standard testing road at the Automotive Research and Testing Center (ARTC)1 and extra-urban highways.

[1]  Jürgen Ackermann,et al.  Robust control prevents car skidding , 1997 .

[2]  A. Modjtahedzadeh,et al.  A control theoretic model of driver steering behavior , 1990, IEEE Control Systems Magazine.

[3]  Romuald Aufrère,et al.  Accurate road following and reconstruction by computer vision , 2002, IEEE Trans. Intell. Transp. Syst..

[4]  Se-Young Oh,et al.  Three-feature based automatic lane detection algorithm (TFALDA) for autonomous driving , 2003, IEEE Trans. Intell. Transp. Syst..

[5]  Massimo Bertozzi,et al.  Vision-based intelligent vehicles: State of the art and perspectives , 2000, Robotics Auton. Syst..

[6]  Martial Hebert,et al.  Intelligent Unmanned Ground Vehicles: Autonomous Navigation Research at Carnegie Mellon , 1997 .

[7]  Bing-Fei Wu,et al.  A real-time robust lane detection approach for autonomous vehicle environment , 2004 .

[8]  Andrea Giachetti,et al.  The use of optical flow for road navigation , 1998, IEEE Trans. Robotics Autom..

[9]  Gianni Conte,et al.  Automatic Vehicle Guidance: the Experience of the ARGO Autonomous Vehicle , 1999 .

[10]  Wei-Bin Zhang,et al.  Demonstration of integrated longitudinal and lateral control for the operation of automated vehicles in platoons , 2000, IEEE Trans. Control. Syst. Technol..

[11]  Chao-Jung Chen,et al.  The automated lane-keeping design for an intelligent vehicle , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[12]  Michael Lützeler,et al.  ROAD RECOGNITION WITH MARVEYE , 1998 .

[13]  Gene F. Franklin,et al.  Feedback Control of Dynamic Systems , 1986 .

[14]  Keith Redmill,et al.  Automated lane change controller design , 2003, IEEE Trans. Intell. Transp. Syst..

[15]  Massimo Bertozzi,et al.  GOLD: a parallel real-time stereo vision system for generic obstacle and lane detection , 1998, IEEE Trans. Image Process..

[16]  Jerome Douret,et al.  A multi-model lane detector that handles road singularities , 2006, 2006 IEEE Intelligent Transportation Systems Conference.

[17]  Zu Kim.  Realtime lane tracking of curved local road , 2006, 2006 IEEE Intelligent Transportation Systems Conference.

[18]  Jitendra Malik,et al.  A Comparative Study of Vision-Based Lateral Control Strategies for Autonomous Highway Driving , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[19]  Ernst D. Dickmanns,et al.  Recursive 3-D Road and Relative Ego-State Recognition , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Azim Eskandarian,et al.  Research advances in intelligent collision avoidance and adaptive cruise control , 2003, IEEE Trans. Intell. Transp. Syst..

[21]  Dean A. Pomerleau,et al.  Visibility estimation from a moving vehicle using the RALPH vision system , 1997, Proceedings of Conference on Intelligent Transportation Systems.

[22]  Der-Cherng Liaw,et al.  Elucidating Vehicle Lateral Dynamics Using a Bifurcation Analysis , 2007, IEEE Transactions on Intelligent Transportation Systems.

[23]  M. Tomizuka,et al.  Fuzzy logic control for lateral vehicle guidance , 1993, IEEE Control Systems.

[24]  Martial Hebert,et al.  Intelligent Unmanned Ground Vehicles , 1997 .

[25]  Wei Ren,et al.  Design and performance evaluation of mixed manual and automated control traffic , 2000, IEEE Trans. Syst. Man Cybern. Part A.

[26]  Dean A. Pomerleau,et al.  RALPH: rapidly adapting lateral position handler , 1995, Proceedings of the Intelligent Vehicles '95. Symposium.

[27]  Luis Magdalena,et al.  VIRTUOUS: vision-based road transportation for unmanned operation on urban-like scenarios , 2004, IEEE Transactions on Intelligent Transportation Systems.

[28]  Aurelio Piazzi,et al.  Visual perception of obstacles and vehicles for platooning , 2000, IEEE Trans. Intell. Transp. Syst..

[29]  L. Giubbolini.  A multistatic microwave radar sensor for short range anticollision warning , 2000, IEEE Trans. Veh. Technol..

[30]  Sadayuki Tsugawa,et al.  Vision-based vehicles in Japan: machine vision systems and driving control systems , 1994, IEEE Trans. Ind. Electron..

[31]  Frédéric Jurie,et al.  Real time road mark following , 1991, Signal Process..

[32]  Jitendra Malik,et al.  A real-time approach to stereopsis and lane-finding , 1996, Proceedings of Conference on Intelligent Vehicles.