Simultaneous registration and fusion of multiple dissimilar sensors for cooperative driving

The fusion of multiple sensory information plays a key role in cooperative driving for flexible platooning of automated vehicles over a couple of lanes within a short intervehicle distance. In this paper, the problem of online sensor fusion with spatially and temporally misaligned dissimilar sensors is considered. A spatial-temporal registration model for the popular intelligent vehicular sensors including radar, global positioning system, inertial navigation system, and camera is first developed for sensor alignment. An unscented Kalman filter (UKF) is proposed here to fuse and register these sensors that are installed on a platoon of vehicles simultaneously. When the road geometry information is available from a digital map database, a constrained UKF is further developed to improve the fusion accuracy. The effect of spatial-temporal sensor misalignment upon the vehicle-state estimation is also analyzed theoretically. Simulations show that the proposed UKF method not only can align the dissimilar vehicular sensors properly with both spatial and temporal biases, but can also obtain accurate fused tracks of vehicles in a platoon.

[1]  S Kato,et al.  An architecture for cooperative driving of automated vehicles , 2000, ITSC2000. 2000 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.00TH8493).

[2]  Christopher O Nwagboso.  Advanced vehicles and infrastructure systems : computer applications, control and automation , 1997 .

[3]  D. Simon,et al.  Kalman filtering with state equality constraints , 2002 .

[4]  Lisa M. Brown,et al.  A survey of image registration techniques , 1992, CSUR.

[5]  Eloi Bosse,et al.  Registration of mobile sensors using the parallelized extended Kalman filter , 1997 .

[6]  Fan-Ren Chang,et al.  Constrained filtering method for attitude determination using GPS and gyro , 2002 .

[7]  K. Mehrotra,et al.  A jerk model for tracking highly maneuvering targets , 1997, IEEE Transactions on Aerospace and Electronic Systems.

[8]  D. Gruyer,et al.  Multi-sensors fusion approach for driver assistance systems , 2001, Proceedings 10th IEEE International Workshop on Robot and Human Interactive Communication. ROMAN 2001 (Cat. No.01TH8591).

[9]  Jae Weon Choi,et al.  Carrier phase GPS/millimeter-wave radar for vehicle platooning , 2001, ISIE 2001. 2001 IEEE International Symposium on Industrial Electronics Proceedings (Cat. No.01TH8570).

[10]  Gary E. Christensen,et al.  Consistent landmark and intensity-based image registration , 2002, IEEE Transactions on Medical Imaging.

[11]  Lawrence A. Klein,et al.  Sensor Technologies and Data Requirements for Its , 2001 .

[12]  Massimo Bertozzi,et al.  Self-calibration of a stereo vision system for automotive applications , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[13]  Jan Becker,et al.  Sensor and navigation data fusion for an autonomous vehicle , 2000, Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511).

[14]  AVCS Platooning,et al.  Vehicle-to-Vehicle Communications For AVCS Platooning , 1996 .

[15]  Yifeng Zhou,et al.  Sensor alignment with Earth-centered Earth-fixed (ECEF) coordinate system , 1999 .

[16]  Srdjan S. Stankovic,et al.  Decentralized overlapping control of a platoon of vehicles , 2000, IEEE Trans. Control. Syst. Technol..

[17]  Qiang Ji,et al.  Camera calibration with genetic algorithms , 2001, IEEE Trans. Syst. Man Cybern. Part A.

[18]  Kiyohito Tokuda,et al.  Vehicle control algorithms for cooperative driving with automated vehicles and intervehicle communications , 2002, IEEE Trans. Intell. Transp. Syst..

[19]  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..

[20]  Gideon P. Stein,et al.  Tracking from multiple view points: Self-calibration of space and time , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[21]  Henry Leung,et al.  An exact maximum likelihood registration algorithm for data fusion , 1997, IEEE Trans. Signal Process..

[22]  Jay A. Farrell,et al.  Real-time differential carrier phase GPS-aided INS , 2000, IEEE Trans. Control. Syst. Technol..

[23]  Giovanni Ulivi,et al.  An outdoor navigation system using GPS and inertial platform , 2001, 2001 IEEE/ASME International Conference on Advanced Intelligent Mechatronics. Proceedings (Cat. No.01TH8556).

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

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

[26]  M. Irani,et al.  Spatio-Temporal Alignment of Sequences , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[27]  Hugh F. Durrant-Whyte,et al.  The aiding of a low-cost strapdown inertial measurement unit using vehicle model constraints for land vehicle applications , 2001, IEEE Trans. Robotics Autom..