{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T15:21:31Z","timestamp":1783783291012,"version":"3.55.0"},"reference-count":30,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2022,8,31]],"date-time":"2022-08-31T00:00:00Z","timestamp":1661904000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Intact Financial Corporation and the Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["RDCPJ-515901-17"],"award-info":[{"award-number":["RDCPJ-515901-17"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000038","name":"Intact Financial Corporation and the Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["RGPIN-2019-04190"],"award-info":[{"award-number":["RGPIN-2019-04190"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000038","name":"Intact Financial Corporation and the Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","award":["RGPIN-2019-06788"],"award-info":[{"award-number":["RGPIN-2019-06788"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>GPS trajectories collected from automotive telematics for insurance purposes go beyond being a collection of points on the map. They are in fact a powerful data source that we can use to extract map and road network properties. While the location of road junctions is readily available, the information about the traffic control element regulating the intersection is typically unknown. However, this information would be helpful, e.g., for contextualizing a driver\u2019s behavior. Our focus is to use a map-matched GPS OBD-dongle dataset provided by a Canadian insurance company to classify intersections into three classes according to the type of traffic control element present: traffic light, stop sign, or no sign. We design a convolutional neural network (CNN) for classifying intersections. The network takes as entries, for a defined number of trips, the speed and the acceleration profiles over each segment of one meter on a window around the intersection. Our method outperforms two other competing approaches, achieving 99% overall accuracy. Furthermore, our CNN model can infer the three classes even with as few as 25 trips.<\/jats:p>","DOI":"10.3390\/ijgi11090475","type":"journal-article","created":{"date-parts":[[2022,8,31]],"date-time":"2022-08-31T23:53:21Z","timestamp":1661990001000},"page":"475","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Identification of Road Network Intersection Types from Vehicle Telemetry Data Using a Convolutional Neural Network"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8892-9126","authenticated-orcid":false,"given":"Abdelmajid","family":"Erramaline","sequence":"first","affiliation":[{"name":"Centre for Research in Geospatial Data and Intelligence, Universit\u00e9 Laval, Qu\u00e9bec, QC G1V 0A6, Canada"},{"name":"Big Data Research Center, Universit\u00e9 Laval, Qu\u00e9bec, QC G1V 0A6, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9984-1843","authenticated-orcid":false,"given":"Thierry","family":"Badard","sequence":"additional","affiliation":[{"name":"Centre for Research in Geospatial Data and Intelligence, Universit\u00e9 Laval, Qu\u00e9bec, QC G1V 0A6, Canada"},{"name":"Big Data Research Center, Universit\u00e9 Laval, Qu\u00e9bec, QC G1V 0A6, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0383-1689","authenticated-orcid":false,"given":"Marie-Pier","family":"C\u00f4t\u00e9","sequence":"additional","affiliation":[{"name":"Big Data Research Center, Universit\u00e9 Laval, Qu\u00e9bec, QC G1V 0A6, Canada"},{"name":"School of Actuarial Science, Universit\u00e9 Laval, Qu\u00e9bec, QC G1V 0A6, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9893-604X","authenticated-orcid":false,"given":"Thierry","family":"Duchesne","sequence":"additional","affiliation":[{"name":"Big Data Research Center, Universit\u00e9 Laval, Qu\u00e9bec, QC G1V 0A6, Canada"},{"name":"Department of Mathematics and Statistics, Universit\u00e9 Laval, Qu\u00e9bec, QC G1V 0A6, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0092-6914","authenticated-orcid":false,"given":"Olivier","family":"Mercier","sequence":"additional","affiliation":[{"name":"Big Data Research Center, Universit\u00e9 Laval, Qu\u00e9bec, QC G1V 0A6, Canada"},{"name":"School of Actuarial Science, Universit\u00e9 Laval, Qu\u00e9bec, QC G1V 0A6, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.aap.2016.10.006","article-title":"Innovative motor insurance schemes: A review of current practices and emerging challenges","volume":"98","author":"Tselentis","year":"2017","journal-title":"Accid. 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