Lane centerline extraction based on surveyed boundaries: an efficient approach using maximal disks

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dc.contributor.authorYin, Chenhui
dc.contributor.authorCecotti, Marco
dc.contributor.authorAuger, Daniel J.
dc.contributor.authorFotouhi, Abbas
dc.contributor.authorJiang, Haobin
dc.date.accessioned2025-04-22T13:48:17Z
dc.date.available2025-04-22T13:48:17Z
dc.date.freetoread2025-04-22
dc.date.issued2025-04-18
dc.date.pubOnline2025-04-18
dc.description.abstractMaps of road layouts play an essential role in autonomous driving, and it is often advantageous to represent them in a compact form, using a sparse set of surveyed points of the lane boundaries. While lane centerlines are valuable references in the prediction and planning of trajectories, most centerline extraction methods only achieve satisfactory accuracy with high computational cost and limited performance in sparsely described scenarios. This paper explores the problem of centerline extraction based on a sparse set of border points, evaluating the performance of different approaches on both a self-created and a public dataset, and proposing a novel method to extract the lane centerline by searching and linking the internal maximal circles along the lane. Compared with other centerline extraction methods producing similar numbers of center points, the proposed approach is significantly more accurate: in our experiments, based on a self-created dataset of road layouts, it achieves a max deviation below 0.15 m and an overall RMSE less than 0.01 m, against the respective values of 1.7 m and 0.35 m for a popular approach based on Voronoi tessellation, and 1 m and 0.25 m for an alternative approach based on distance transform.
dc.description.journalNameSensors
dc.description.sponsorshipThis work was supported in part by the China Scholarship Council under Grant No. 202108690001 and the Graduate Research and Innovation Projects of Jiangsu Province under Grant KYCX21_3334.
dc.identifier.citationYin C, Cecotti M, Auger DJ, et al., (2025) Lane centerline extraction based on surveyed boundaries: an efficient approach using maximal disks. Sensors, Volume 25, Issue 8, April 2025, Article number 2571
dc.identifier.eissn1424-8220
dc.identifier.elementsID672857
dc.identifier.issueNo8
dc.identifier.paperNo2571
dc.identifier.urihttps://doi.org/10.3390/s25082571
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/23824
dc.identifier.volumeNo25
dc.languageEnglish
dc.language.isoen
dc.publisherMDPI
dc.publisher.urihttps://www.mdpi.com/1424-8220/25/8/2571
dc.relation.isreferencedbyhttps://doi.org/10.57996/cran.ceres-2734
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectAnalytical Chemistry
dc.subject3103 Ecology
dc.subject4008 Electrical engineering
dc.subject4009 Electronics, sensors and digital hardware
dc.subject4104 Environmental management
dc.subject4606 Distributed computing and systems software
dc.subjectmaximal disk
dc.subjectdistance transform
dc.subjectvoronoi tessellation
dc.subjectcenterline extraction
dc.titleLane centerline extraction based on surveyed boundaries: an efficient approach using maximal disks
dc.typeArticle
dcterms.dateAccepted2025-04-17

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