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Conference Paper: The Spatiotemporal Traffic Accident Risk Analysis in Urban Traffic Network

TitleThe Spatiotemporal Traffic Accident Risk Analysis in Urban Traffic Network
Authors
Zhang, Chijunjin, JingHuang, QiuyangDu, ZhanweiYuan, ZhiluTang, ShengjunLiu, Yang
KeywordsRisk analysis
Urban traffic network
Traffic accident
Issue Date2020
PublisherSpringer.
Citation
9th EAI International Conference (MOBILWARE 2020), Hohhot, China, 11 July 2020. In Mobile Wireless Middleware, Operating Systems and Applications: 9th EAI International Conference, MOBILWARE 2020, Hohhot, China, July 11, 2020, Proceedings, 2020, p. 92-97 How to Cite?
DOI: http://dx.doi.org/10.1007/978-3-030-62205-3_8
Abstract© 2020, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Traffic accidents seriously threaten people’s lives and property all over the world. Therefore, it is of great significance to human society to have a long-term traffic accidents data with detail temporal and geographic information in a specific space, which can be used for traffic accident hotspots identification to reduce the incidence of traffic accidents. Here, we obtain a one-year dataset of traffic accidents of the city center in Changchun, Northeast China, in 2017. In this paper, we analyze the risk of traffic accident in urban area, and then discover the characteristics of traffic accidents at the temporal and spatial aspect. We construct a traffic network, which takes crossings as nodes and road sections as edges and weighted by the total number of traffic accidents. In addition, we integrate road structure data and meteorological data to explore the characteristics of the traffic network.
Persistent Identifierhttp://hdl.handle.net/10722/296229
ISBN
9783030622046
ISSN
1867-8211
2020 SCImago Journal Rankings: 0.142
Series/Report no.Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ; 331

 

DC FieldValueLanguage
dc.contributor.authorZhang, Chijun-
dc.contributor.authorjin, Jing-
dc.contributor.authorHuang, Qiuyang-
dc.contributor.authorDu, Zhanwei-
dc.contributor.authorYuan, Zhilu-
dc.contributor.authorTang, Shengjun-
dc.contributor.authorLiu, Yang-
dc.date.accessioned2021-02-11T04:53:07Z-
dc.date.available2021-02-11T04:53:07Z-
dc.date.issued2020-
dc.identifier.citation9th EAI International Conference (MOBILWARE 2020), Hohhot, China, 11 July 2020. In Mobile Wireless Middleware, Operating Systems and Applications: 9th EAI International Conference, MOBILWARE 2020, Hohhot, China, July 11, 2020, Proceedings, 2020, p. 92-97-
dc.identifier.isbn9783030622046-
dc.identifier.issn1867-8211-
dc.identifier.urihttp://hdl.handle.net/10722/296229-
dc.description.abstract© 2020, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Traffic accidents seriously threaten people’s lives and property all over the world. Therefore, it is of great significance to human society to have a long-term traffic accidents data with detail temporal and geographic information in a specific space, which can be used for traffic accident hotspots identification to reduce the incidence of traffic accidents. Here, we obtain a one-year dataset of traffic accidents of the city center in Changchun, Northeast China, in 2017. In this paper, we analyze the risk of traffic accident in urban area, and then discover the characteristics of traffic accidents at the temporal and spatial aspect. We construct a traffic network, which takes crossings as nodes and road sections as edges and weighted by the total number of traffic accidents. In addition, we integrate road structure data and meteorological data to explore the characteristics of the traffic network.-
dc.languageeng-
dc.publisherSpringer.-
dc.relation.ispartofMobile Wireless Middleware, Operating Systems and Applications: 9th EAI International Conference, MOBILWARE 2020, Hohhot, China, July 11, 2020, Proceedings-
dc.relation.ispartofseriesLecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ; 331-
dc.subjectRisk analysis-
dc.subjectUrban traffic network-
dc.subjectTraffic accident-
dc.titleThe Spatiotemporal Traffic Accident Risk Analysis in Urban Traffic Network-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/978-3-030-62205-3_8-
dc.identifier.scopuseid_2-s2.0-85097429023-
dc.identifier.spage92-
dc.identifier.epage97-
dc.publisher.placeCham, Switzerland-
dc.identifier.issnl1867-8211-

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