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Determining the road traffic accident hotspots using GIS-based temporal-spatial statistical analytic techniques in Hanoi, Vietnam / Khanh Giang Le in Geo-spatial Information Science, vol 23 n° 2 (June 2020)
[article]
Titre : Determining the road traffic accident hotspots using GIS-based temporal-spatial statistical analytic techniques in Hanoi, Vietnam Type de document : Article/Communication Auteurs : Khanh Giang Le, Auteur ; Pei Liu, Auteur ; Liang-Tay Lin, Auteur Année de publication : 2020 Article en page(s) : pp 153 - 164 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] accident de la route
[Termes IGN] base de données spatiotemporelles
[Termes IGN] données météorologiques
[Termes IGN] estimation par noyau
[Termes IGN] Hanoï
[Termes IGN] indice de risque
[Termes IGN] nuit
[Termes IGN] système d'information géographique
[Termes IGN] variation diurne
[Termes IGN] variation saisonnièreRésumé : (auteur) This study applied GIS-based statistical analytic techniques to investigate the influence of accident Severity Index (SI) on temporal-spatial patterns of accident hotspots related to the specific time intervals of day and seasons. Road Traffic Accident (RTA) data in 3 years (2015 − 2017) in Hanoi, Vietnam were used to analyze and test this approach. Firstly, the RTA data were divided into four seasons in accordance with Hanoi’s weather conditions and the time intervals such as the daytime, nighttime, or peak hours. Then, the Kernel Density Estimation (KDE) method was applied to analyze hotspots according to the time intervals and seasons. Finally, the results were presented by using the comap technique. This study considered both analyses with and without SI. The accident SI measures the seriousness of an accident. The approach method is to give higher weights to the more serious accidents, but not with the extremely high values calculated on a direct rate to the accident expenditures. The results showed that both analyses determined the relatively similar hotspots, but the rankings of some hotspots were quite different due to the integration of SI. It is better to take into account SI in determining RTA hotspots because the gained results are more precise and the rankings of hotspots are more accurate. From there, the traffic authorities can easily understand the causes behind each accident and provide reasonable solutions to solve the most dangerous hotspots in case of limited budget and resources appropriately. This is also the first study about this issue in Vietnam, so the contribution of the article will help the traffic authorities easily solve this problem not only in Hanoi but also in other cities. Numéro de notice : A2020-317 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/10095020.2019.1683437 Date de publication en ligne : 02/12/2019 En ligne : https://doi.org/10.1080/10095020.2019.1683437 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95176
in Geo-spatial Information Science > vol 23 n° 2 (June 2020) . - pp 153 - 164[article]