A Vehicle Detection and Tracking Approach Using Probe Vehicle LIDAR Data

Bin Gao and Benjamin Coifman
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Bin Gao: The Ohio State University, Department of Electrical and Computer Engineering
Benjamin Coifman: The Ohio State University, Department of Electrical and Computer Engineering

A chapter in Traffic and Granular Flow’05, 2007, pp 675-685 from Springer

Abstract: Summary Detection, identification and tracking of multiple moving targets have important applications in transportation and vehicle control areas. In this paper we present our approach to detect, recognize and track the vehicles within the detection region of a moving probe vehicle, based on the data collected by multiple sensors, including LIDAR and GPS. This paper develops a methodology to group the LIDAR measurements into targets, classify the targets as vehicles or fixed objects, and track the vehicular targets within lanes using a Kalman-filter. One important feature of this approach is that we track all of the observations in world coordinates, allowing us to average over many samples and ideally many runs to differentiate between the fixed objects (road boundaries) and moving objects (vehicles).

Keywords: Lidar Data; Density Image; Tracking Process; Lidar Measurement; Vehicle Detection (search for similar items in EconPapers)
Date: 2007
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-540-47641-2_66

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DOI: 10.1007/978-3-540-47641-2_66

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