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Lane marking detection algorithm based on high-precision map and multisensor fusion

journal contribution
posted on 2020-01-01, 00:00 authored by H Yao, C Chen, S Liu, K Li, Y Ji, Guangyan HuangGuangyan Huang, R Wang
In case of sharp road illumination changes, bad weather such as rain, snow or fog, wear or missing of the lane marking, the reflective water stain on the road surface, the shadow obstruction of the tree, and mixed lane markings and other signs, missing detection or wrong detection will occur for the traditional lane marking detection algorithm. In this manuscript, a lane marking detection algorithm based on high-precision map and multisensor fusion is proposed. The basic principle of the algorithm is to use the centimeter-level high-precision positioning combined with high-precision map data to complete the detection of lane markings. In the process of generating high-precision maps or in the uncovered areas of high-precision maps, LIDAR (LIght Detection And Ranging) is used to estimate the curvature of the road to assist in lane marking detection. The experimental results show that the algorithm has lower false detection rate in case of bad road conditions, and the algorithm is robust.

History

Journal

Concurrency and Computation: Practice and Experience

Volume

34

Pagination

1 - 11

Location

Ningbo, China

Start date

2019-05-15

End date

2019-05-20

ISSN

1532-0626

eISSN

1532-0634

Language

English

Publication classification

C1 Refereed article in a scholarly journal

Copyright notice

2020, John Wiley & Sons, Ltd.

Issue

8

Publisher

WILEY

Place of publication

Hoboken, N.J.