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Remote Sens. 2019, 11(3), 305;

Combined Lane Mapping Using a Mobile Mapping System

School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
Center for Data Science, Peking University, Beijing 100871, China
Author to whom correspondence should be addressed.
Received: 27 December 2018 / Revised: 26 January 2019 / Accepted: 30 January 2019 / Published: 2 February 2019
(This article belongs to the Section Urban Remote Sensing)
Full-Text   |   PDF [26104 KB, uploaded 2 February 2019]   |  


High-definition mapping of 3D lane lines has been widely needed for the highway documentation and intelligent navigation of autonomous systems. A mobile mapping system (MMS) captures both accurate 3D LiDAR point clouds and high-resolution images of lane markings at highway driving speeds, providing an abundant data source for combined lane mapping. This paper aims to map lanes with an MMS. The main contributions of this paper include the following: (1) an intensity correction method was introduced to eliminate the reflectivity inconsistency of road-surface LiDAR points; (2) a self-adaptive thresholding method was developed to extract lane markings from their complicated surroundings; and (3) a LiDAR-guided textural saliency analysis of MMS images was proposed to improve the robustness of lane mapping. The proposed method was tested with a dataset acquired in Wuhan, Hubei, China, which contained straight roads, curved roads, and a roundabout with various pavement markings and a complex roadside environment. The experimental results achieved a recall of 96.4%, a precision of 97.6%, and an F-score of 97.0%, demonstrating that the proposed method has strong mapping ability for various urban roads. View Full-Text
Keywords: mobile mapping system(MMS); point cloud; lane marking; lane mapping mobile mapping system(MMS); point cloud; lane marking; lane mapping

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Wan, R.; Huang, Y.; Xie, R.; Ma, P. Combined Lane Mapping Using a Mobile Mapping System. Remote Sens. 2019, 11, 305.

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