Identification of motorcycle accidents hotspots in the Czech Republic and their conditional factors: The use of KDE+ and two‐step cluster analysis.
In recent decades, there has been a significant increase in the number of newly registered motorcycles worldwide. However, there is not only an increase in the number of motorcycles in traffic but also an increase in the number of conflicts between motorcyclists and the surrounding environment. A re...
| Published in: | Geographical Journal Vol. 188; no. 3; pp. 444 - 459 |
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| Main Authors: | , , , , |
| Format: | Article |
| Published: |
Wiley-Blackwell
Sep2022
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=158412162&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 158412162 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00167398 GEO jtl: Geographical Journal issn: 00167398 maglogo: Y pubinfo: dt: Sep2022 vid: 188 iid: 3 pid: 480 pub: Wiley-Blackwell artinfo: ui: 158412162 10.1111/geoj.12446 ppf: 444 ppct: 15 formats: fmt: – @attributes: type: T db: hlh ui: 158412162 – @attributes: type: C db: hlh ui: 158412162 – @attributes: type: P db: hlh ui: 158412162 tig: atl: Identification of motorcycle accidents hotspots in the Czech Republic and their conditional factors: The use of KDE+ and two‐step cluster analysis. aug: au: Kraft, Stanislav Marada, Miroslav Petříček, Jakub Blažek, Vojtěch Mrkvička, Tomáš affil: Department of Geography, Faculty of Education, University of South Bohemia in České Budějovice, České Budějovice, Czech Republic Department of Social Geography and Regional Development, Faculty of Science, Charles University, Praha, Czech Republic Department of Applied Mathematics and Informatics, Faculty of Economics, University of South Bohemia in České Budějovice, České Budějovice, Czech Republic su: Czech Republic City traffic Motorcycling accidents Cluster analysis (Statistics) Probability density function Traffic density sug: subj: City traffic Czech Republic Motorcycling accidents Cluster analysis (Statistics) Probability density function Traffic density ab: In recent decades, there has been a significant increase in the number of newly registered motorcycles worldwide. However, there is not only an increase in the number of motorcycles in traffic but also an increase in the number of conflicts between motorcyclists and the surrounding environment. A relatively significant research gap can be identified in the relationship between spatial factors and motorcycle accident rates. This paper analyses the spatiotemporal patterns of motorcycle accidents and studies their underlying factors. The KDE+ method (an extension of the kernel density estimation method) is used to identify concentrations of motorcycle accident key hotspots. To study the underlying traffic accident determinants, a two‐step cluster analysis is used. The analysis is based on the database of motorcycle accidents in the Czech Republic from 1 January 2016 to 31 December 2020. The paper achieves a few main findings. By applying the KDE+ method, the most dangerous sections of the road network in the Czech Republic were identified, where a significant accumulation of motorcycle accidents occur. Motorcycle accidents are highly seasonal. Motorcycle accidents tend to accumulate in the afternoon, especially during the summer months. Concerning the frequency of accidents and the collective risk index, urban traffic, that is the traffic density, is an important cause of motorcycle accidents, along with the winter period with rather unfavourable weather conditions, and especially the directional conditions—curves and intersections—are among the hazardous sections. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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