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ISPRS Int. J. Geo-Inf. 2018, 7(8), 317; https://doi.org/10.3390/ijgi7080317

Method Based on Floating Car Data and Gradient-Boosted Decision Tree Classification for the Detection of Auxiliary Through Lanes at Intersections

1
Faculty of Geomatics, East China University of Technology, Nanchang 330013, China
2
Key Laboratory of Watershed Ecology and Geographical Environment Monitoring, NASG, Nanchang 330013, China
*
Authors to whom correspondence should be addressed.
Received: 25 May 2018 / Revised: 6 July 2018 / Accepted: 19 July 2018 / Published: 5 August 2018
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Abstract

The rapid detection of information on continuously changing intersection auxiliary through lane is a major task of lane-level navigation data updates. However, existing lane number detection methods possess long update cycles and high computational costs. Therefore, this study proposes a novel method based on floating car data (FCD) for the detection of auxiliary through lane changes at road intersections. First, roads near intersections are divided into three sections and the spatial distribution characteristics of the FCD of each section are analyzed. Second, the FCD is preprocessed to obtain a standardized FCD dataset by removing redundant data through an improved amplitude-limiting average filtering method. Third, a basic classifier for the number of lanes is constructed. Fourth, the final number of lanes of the road section is determined by combining the basic classifier and the gradient-boosted decision tree model. Finally, the presence of an auxiliary through lane at the intersection is determined in accordance with the change in the number of intersection lanes. The method was tested using data for a road in Wuchang District, Wuhan City. Experimental results show that this method can rapidly obtain auxiliary through lane information from the FCD and is superior to other classification methods. View Full-Text
Keywords: floating car data; gradient-boosted decision tree; intersection lane; lane number; auxiliary through lane floating car data; gradient-boosted decision tree; intersection lane; lane number; auxiliary through lane
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Li, X.; Wu, Y.; Tan, Y.; Cheng, P.; Wu, J.; Wang, Y. Method Based on Floating Car Data and Gradient-Boosted Decision Tree Classification for the Detection of Auxiliary Through Lanes at Intersections. ISPRS Int. J. Geo-Inf. 2018, 7, 317.

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