Automated Road Defect and Anomaly Detection for Traffic Safety: A Systematic Review

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aut.relation.articlenumber5656
aut.relation.endpage5656
aut.relation.issue12
aut.relation.journalSensors
aut.relation.startpage5656
aut.relation.volume23
dc.contributor.authorRathee, Munish
dc.contributor.authorBačić, Boris
dc.contributor.authorDoborjeh, Maryam
dc.date.accessioned2023-07-10T02:19:43Z
dc.date.available2023-07-10T02:19:43Z
dc.date.issued2023-06-16
dc.description.abstractRecently, there has been a substantial increase in the development of sensor technology. As enabling factors, computer vision (CV) combined with sensor technology have made progress in applications intended to mitigate high rates of fatalities and the costs of traffic-related injuries. Although past surveys and applications of CV have focused on subareas of road hazards, there is yet to be one comprehensive and evidence-based systematic review that investigates CV applications for Automated Road Defect and Anomaly Detection (ARDAD). To present ARDAD’s state-of-the-art, this systematic review is focused on determining the research gaps, challenges, and future implications from selected papers (N = 116) between 2000 and 2023, relying primarily on Scopus and Litmaps services. The survey presents a selection of artefacts, including the most popular open-access datasets (D = 18), research and technology trends that with reported performance can help accelerate the application of rapidly advancing sensor technology in ARDAD and CV. The produced survey artefacts can assist the scientific community in further improving traffic conditions and safety.
dc.identifier.citationSensors, ISSN: 1424-8220 (Print); 1424-8220 (Online), MDPI AG, 23(12), 5656-5656. doi: 10.3390/s23125656
dc.identifier.doi10.3390/s23125656
dc.identifier.issn1424-8220
dc.identifier.issn1424-8220
dc.identifier.urihttp://hdl.handle.net/10292/16397
dc.languageen
dc.publisherMDPI AG
dc.relation.urihttps://www.mdpi.com/1424-8220/23/12/5656
dc.rights.accessrightsOpenAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject4605 Data Management and Data Science
dc.subject46 Information and Computing Sciences
dc.subject3 Good Health and Well Being
dc.subject0301 Analytical Chemistry
dc.subject0502 Environmental Science and Management
dc.subject0602 Ecology
dc.subject0805 Distributed Computing
dc.subject0906 Electrical and Electronic Engineering
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.titleAutomated Road Defect and Anomaly Detection for Traffic Safety: A Systematic Review
dc.typeJournal Article
pubs.elements-id510608
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