Show simple item record

dc.creatorKošanin, Ivan
dc.creatorGnjatović, Milan
dc.creatorMaček, Nemanja
dc.creatorJoksimović, Dušan
dc.date.accessioned2023-12-05T13:26:58Z
dc.date.available2023-12-05T13:26:58Z
dc.date.issued2023
dc.identifier.issn2075-1680
dc.identifier.urihttp://jakov.kpu.edu.rs/handle/123456789/1513
dc.description.abstractThis paper introduces a parameter-free clustering-based approach to detecting critical traffic road segments in urban areas, i.e., road segments of spatially prolonged and high traffic accident risk. In addition, it proposes a novel domain-specific criterion for evaluating the clustering results, which promotes the stability of the clustering results through time and inter-period accident spatial collocation, and penalizes the size of the selected clusters. To illustrate the proposed approach, it is applied to data on traffic accidents with injuries or death that occurred in three of the largest cities of Serbia over the three-year period.sr
dc.language.isoensr
dc.publisherBasel, Switzerland : MDPIsr
dc.rightsrestrictedAccesssr
dc.sourceAxiomssr
dc.subjecttraffic accidentsr
dc.subjectclusteringsr
dc.subjectcritical road segmentssr
dc.subjectknee detectionsr
dc.subjectopen datasr
dc.titleA Clustering-Based Approach to Detecting Critical Traffic Road Segments in Urban Areassr
dc.typearticlesr
dc.rights.licenseARRsr
dc.citation.volume12
dc.citation.issue6
dc.citation.spage509
dc.identifier.doi10.3390/axioms12060509
dc.type.versionpublishedVersionsr


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record