GPS trajectory-based segmentation and multi-filter-based extraction of expressway curbs and markings from mobile laser scanning data. Issue 1 (1st January 2018)

• Record Type: Journal Article
• Authors: Wang, Jin; Zhao, Hongrui; Wang, Duo; Chen, Yanyan; Zhang, Zhiqing; Liu, Hao
• Is Part Of: European journal of remote sensing. Volume 51:Issue 1(2018)
• Page Start: 1022
• Page End: 1035
• Publication Date: 2018-01-01
• Subjects: Mobile laser scanning -- expressway -- road curb -- road marking -- point clouds -- transportation; Remote sensing -- Periodicals; Remote sensing; Electronic journals; Periodicals; 621.3678
• DOI: 10.1080/22797254.2018.1533388
• Languages: English
• ISSNs: 2279-7254

Abstract

ABSTRACT: Mobile laser scanning (MLS) technology directly collects dense 3D coordinate information at expressway and satisfied with the demands of transportation-related road surveying. This paper aims to extract road curbs and road markings from MLS point clouds. The proposed method is based on the following approaches: 1) extracting and segmenting road surfaces and subsidiary facility point clouds from raw point clouds based on the GPS trajectory; 2) dynamically shifting the point clouds from the global coordinate system to block-based local coordinate systems; 3) estimating the curbs and centre points based on the block profiles and re-sampled point clouds; and 4) extracting road markings based on the passthrough-statistical-radius-filter. An application for an expressway and its interchange road is performed to test the proposed method. The mean deviation in the estimated road centres was 5.30 cm, which satisfies the demand for centimetre-scale road precision in expressway applications. The results illustrate that the proposed method is a precise alternative for expressway curb and marking extraction, and can be performed for horizontal analysis and lane navigation in intelligent transportation systems.