World Academy of Science, Engineering and Technology
Published May 3, 2016 | Version 10004678
Journal article Open

LiDAR Based Real Time Multiple Vehicle Detection and Tracking

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Description

Self-driving vehicle require a high level of situational
awareness in order to maneuver safely when driving in real world
condition. This paper presents a LiDAR based real time perception
system that is able to process sensor raw data for multiple target
detection and tracking in dynamic environment. The proposed
algorithm is nonparametric and deterministic that is no assumptions
and priori knowledge are needed from the input data and no
initializations are required. Additionally, the proposed method is
working on the three-dimensional data directly generated by LiDAR
while not scarifying the rich information contained in the domain of
3D. Moreover, a fast and efficient for real time clustering algorithm
is applied based on a radially bounded nearest neighbor (RBNN).
Hungarian algorithm procedure and adaptive Kalman filtering are
used for data association and tracking algorithm. The proposed
algorithm is able to run in real time with average run time of 70ms
per frame.

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References

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