NDLI: A relative information metric for vehicle following systems

Content Provider	IEEE Xplore Digital Library
Author	Teck Chew Ng Adams, M. Ibanez-Guzman, J.
Copyright Year	2008
Description	Author affiliation: Singapore Inst. of Manuf. Technol., Singapore (Teck Chew Ng)
Abstract	Vehicle following can be achieved by minimizing the relative information (Kullback-Leibler or K-L distance), between the estimated poses of leader and follower vehicles by formulating the vehicle following system as an optimization problem. The aim is to search for an optimal control action for the follower vehicle in the admissible control command space. Relative information is used as a metric in the search space and for evaluating the expected performance of vehicle following. With this metric, and based on the assumption that both vehicle pose (position and orientation) distributions are Gaussian functions, the K-L distance of the vehicle following system can be computed. With a series of admissible actions, such as steering and velocity commands, for the follower vehicle at each pose prediction step, and by minimizing the K-L distance, an optimized action for the follower vehicle can be obtained. The proposed vehicle following algorithm has been tested and the performance of the follower vehicle when the leader undergoes various kinds of maneuvers has been analyzed. Results using this new method, as compared to classical methods, have shown the advantages of this method.
Starting Page	1811
Ending Page	1816
File Size	621923
Page Count	6
File Format	PDF
ISBN	9781424420575
DOI	10.1109/IROS.2008.4650858
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-09-22
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vehicles Lead Distance measurement Trajectory Uncertainty Equations Prediction algorithms
Content Type	Text
Resource Type	Article

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