DocumentCode :
47146
Title :
A Tracking System of Multiple LiDAR Sensors Using Scan Point Matching
Author :
Shuqing Zeng
Author_Institution :
Electr. & Control Syst. Res. Lab., Gen. Motors Co., Warren, MI, USA
Volume :
62
Issue :
6
fYear :
2013
fDate :
Jul-13
Firstpage :
2413
Lastpage :
2420
Abstract :
We address a tracking system of 360° field of view using Light Detection And Ranging (LiDAR) sensors, which are a key module for detecting surrounding traffic and infrastructure for vehicular safety applications. We propose a joint algorithm for estimating motion and a nonparametric contour model whose complexity is O(N), with N being the number of scan points. Particularly, the proposed nonparametric model has the potential to track objects with arbitrary shape (e.g., car, pedestrian, and bicycle). A comparison of the proposed approach with other methods using parametric models shows the robustness and the quality of the proposed system. Quantitative performance evaluation against ground truth is presented in tracking a car, a pedestrian, and a bicycle. Experiments demonstrate that the proposed system substantially improves performance. Road test results show the effectiveness and efficiency of the implemented system. A lane-change alert (LCA) demonstration system is built based on the detection system, and the LCA performance is analyzed using ground truth.
Keywords :
computational complexity; image matching; motion estimation; nonparametric statistics; object detection; object tracking; optical radar; pedestrians; road safety; sensor fusion; traffic engineering computing; video surveillance; LCA demonstration system; bicycle tracking; car tracking; field of view; lane change alert; light detection and ranging; motion estimation; multiLiDAR sensor; nonparametric contour model estimation; object tracking; pedestrian tracking; quantitative performance evaluation; scan point matching; tracking system; traffic detection; vehicular safety application; Clustering algorithms; Complexity theory; Laser radar; Sensors; Shape; Target tracking; Vehicles; Expectation maximization; intelligent vehicles; lane change warning; laser rangefinder; object detection; scan registration; tracking;
fLanguage :
English
Journal_Title :
Vehicular Technology, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9545
Type :
jour
DOI :
10.1109/TVT.2013.2245694
Filename :
6451303
Link To Document :
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