IMMPDAF Approach for Road-Boundary Tracking

Robust road-boundary extraction/tracking is one of the main problems in autonomous roadway navigation. Although the road boundary can be defined by various means including lane markings, curbs, and borders of vegetation, this paper focuses on road-boundary tracking using curbs. A vehicle-mounted (downward tilted) 2-D laser-measurement system is utilized to detect the curbs. The tracking problem is difficult because both the vehicle is moving and the target is disappearing, reappearing, and maneuvering in clutter. The interacting-multiple-model probabilistic-data-association filter (IMMPDAF) is proposed to solve the problems after detailed analysis. Track initiation, confirmation, and deletion are performed using the sequential-probability-ratio test. Extensive simulations followed by experiments in a campus environment show that the road-boundary tracking utilizing curbs is possible and robust through IMMPDAF

[1]  Hugh F. Durrant-Whyte,et al.  A new method for the nonlinear transformation of means and covariances in filters and estimators , 2000, IEEE Trans. Autom. Control..

[2]  Petros A. Ioannou,et al.  New Potential Functions for Mobile Robot Path Planning , 2000 .

[3]  Robin J. Evans,et al.  Integrated probabilistic data association , 1994, IEEE Trans. Autom. Control..

[4]  Ronald E. Helmick,et al.  Interacting multiple model integrated probabilistic data association filters (IMM-IPDAF) for track formation on maneuvering targets in cluttered environments , 1994, Defense, Security, and Sensing.

[5]  Yakov Bar-Shalom,et al.  Multitarget-Multisensor Tracking: Principles and Techniques , 1995 .

[6]  Shuzhi Sam Ge,et al.  Autonomous vehicle positioning with GPS in urban canyon environments , 2001, IEEE Trans. Robotics Autom..

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

[8]  M. Nikolova,et al.  Segmentation of a road from a vehicle-mounted radar and accuracy of the estimation , 2000, Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511).

[9]  W. S. Wijesoma,et al.  LASER-CAMERA COMPOSITE SENSING FOR ROAD DETECTION AND TRACKING , 2004 .

[10]  Todd Jochem,et al.  Rapidly Adapting Machine Vision for Automated Vehicle Steering , 1996, IEEE Expert.

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

[12]  Ruediger Lamm,et al.  Highway Design and Traffic Safety Engineering Handbook , 1999 .

[13]  W. Sardha Wijesoma,et al.  Road-boundary detection and tracking using ladar sensing , 2004, IEEE Transactions on Robotics and Automation.

[14]  Yaakov Bar-Shalom,et al.  Estimation and Tracking: Principles, Techniques, and Software , 1993 .

[15]  Klaus Dietmayer,et al.  Lane detection and street type classification using laser range images , 2001, ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585).

[16]  Shuzhi Sam Ge,et al.  Dynamic Motion Planning for Mobile Robots Using Potential Field Method , 2002, Auton. Robots.

[17]  W. Sardha Wijesoma,et al.  Laser-camera Compositite Sensing for Road Detection and Tracking , 2005, Int. J. Robotics Autom..

[18]  Alfred O. Hero,et al.  Simultaneous detection of lane and pavement boundaries using model-based multisensor fusion , 2000, IEEE Trans. Intell. Transp. Syst..

[19]  M. Mariton,et al.  Tracking a 3D maneuvering target with passive sensors , 1991 .

[20]  Y. Bar-Shalom,et al.  Multisensor tracking of a maneuvering target in clutter , 1989 .

[21]  Bing Chen,et al.  Multisensor tracking of a maneuvering target in clutter using IMMPDA fixed-lag smoothing , 2000, IEEE Trans. Aerosp. Electron. Syst..

[22]  T. Kirubarajan,et al.  Adaptive beam pointing control of a phased array radar in the presence of ECM and false alarms using IMMPDAF , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[23]  A Kirchner,et al.  MODEL BASED DETECTION OF ROAD BOUNDARIES WITH A LASER SCANNER , 1998 .