A MODEL SUGGESTION FOR THE DETERMINATION OF THE TRAFFIC ACCIDENT HOTSPOTS ON THE TURKISH HIGHWAY ROAD NETWORK: A PILOT STUDY
Autor(a) principal: | |
---|---|
Data de Publicação: | 2015 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Boletim de Ciências Geodésicas |
Texto Completo: | https://revistas.ufpr.br/bcg/article/view/40463 |
Resumo: | Traffic accidents are very serious problems for human life and the environment. In road safety, it is crucial to identify the high risk locations to apply proper counter measures. This paper aims at introducing outcomes of a pilot project whose main goal is to develop a GIS based crash analysis system integrated with the quantitative methods for identification of high risk locations on road networks in Turkey. In this concept, traditional hotspot detection methods used in Turkey(crash frequency, rate, and severity) are compared with the spatial statistical methods including Moran‟s I, GetisOrd G and planar and network kernel density estimation in terms of their sensitivity to spatial characteristics of crash clusters. Many countries use traditional hotspot detection approaches such as crash frequency, crash rate, and crash severity as well as Turkey. In this project, we aimed at obtaining a model including different hotspot identification methods for the safety program of Turkey. In order to obtain the model, many hotspot detection methods will be used and compare stage by stage. In the first stage, the seven methods mentioned above are used and examined. Although some of these methods are compared in couple, there is no study using all these methods together extensively in the literature. Methods validated with a different spatial vantage points. Repetitiveness of hotspots in a seven years period are used to compare the methods. Meanwhile advantages and disadvantages of the methods according to location of hotspots are examined additionally. Results show that using planar KDE with Gi in the junction locations and using planar KDE with Moran‟s I in the straight road locations could improve the model while determining hotspots |
id |
UFPR-2_123b85a1bec2f7cc818cdede3a1f32ba |
---|---|
oai_identifier_str |
oai:revistas.ufpr.br:article/40463 |
network_acronym_str |
UFPR-2 |
network_name_str |
Boletim de Ciências Geodésicas |
repository_id_str |
|
spelling |
A MODEL SUGGESTION FOR THE DETERMINATION OF THE TRAFFIC ACCIDENT HOTSPOTS ON THE TURKISH HIGHWAY ROAD NETWORK: A PILOT STUDYA MODEL SUGGESTION FOR THE DETERMINATION OF THE TRAFFIC ACCIDENT HOTSPOTS ON THE TURKISH HIGHWAY ROAD NETWORK: A PILOT STUDYGeociências; GeodésiaTraffic Accidents; Hotspot; Spatial Statistical Methods; GIS.Geociências; GeodésiaTraffic Accidents; Hotspot; Spatial Statistical Methods; GIS.Traffic accidents are very serious problems for human life and the environment. In road safety, it is crucial to identify the high risk locations to apply proper counter measures. This paper aims at introducing outcomes of a pilot project whose main goal is to develop a GIS based crash analysis system integrated with the quantitative methods for identification of high risk locations on road networks in Turkey. In this concept, traditional hotspot detection methods used in Turkey(crash frequency, rate, and severity) are compared with the spatial statistical methods including Moran‟s I, GetisOrd G and planar and network kernel density estimation in terms of their sensitivity to spatial characteristics of crash clusters. Many countries use traditional hotspot detection approaches such as crash frequency, crash rate, and crash severity as well as Turkey. In this project, we aimed at obtaining a model including different hotspot identification methods for the safety program of Turkey. In order to obtain the model, many hotspot detection methods will be used and compare stage by stage. In the first stage, the seven methods mentioned above are used and examined. Although some of these methods are compared in couple, there is no study using all these methods together extensively in the literature. Methods validated with a different spatial vantage points. Repetitiveness of hotspots in a seven years period are used to compare the methods. Meanwhile advantages and disadvantages of the methods according to location of hotspots are examined additionally. Results show that using planar KDE with Gi in the junction locations and using planar KDE with Moran‟s I in the straight road locations could improve the model while determining hotspotsTraffic accidents are very serious problems for human life and the environment. In road safety, it is crucial to identify the high risk locations to apply proper counter measures. This paper aims at introducing outcomes of a pilot project whose main goal is to develop a GIS based crash analysis system integrated with the quantitative methods for identification of high risk locations on road networks in Turkey. In this concept, traditional hotspot detection methods used in Turkey(crash frequency, rate, and severity) are compared with the spatial statistical methods including Moran‟s I, GetisOrd G and planar and network kernel density estimation in terms of their sensitivity to spatial characteristics of crash clusters. Many countries use traditional hotspot detection approaches such as crash frequency, crash rate, and crash severity as well as Turkey. In this project, we aimed at obtaining a model including different hotspot identification methods for the safety program of Turkey. In order to obtain the model, many hotspot detection methods will be used and compare stage by stage. In the first stage, the seven methods mentioned above are used and examined. Although some of these methods are compared in couple, there is no study using all these methods together extensively in the literature. Methods validated with a different spatial vantage points. Repetitiveness of hotspots in a seven years period are used to compare the methods. Meanwhile advantages and disadvantages of the methods according to location of hotspots are examined additionally. Results show that using planar KDE with Gi in the junction locations and using planar KDE with Moran‟s I in the straight road locations could improve the model while determining hotspots.Boletim de Ciências GeodésicasBulletin of Geodetic SciencesErdogan, SaffetIlçi, VeliSaysal, OmerKorkmaz, Aysegul2015-03-30info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistas.ufpr.br/bcg/article/view/40463Boletim de Ciências Geodésicas; Vol 21, No 1 (2015)Bulletin of Geodetic Sciences; Vol 21, No 1 (2015)1982-21701413-4853reponame:Boletim de Ciências Geodésicasinstname:Universidade Federal do Paraná (UFPR)instacron:UFPRporhttps://revistas.ufpr.br/bcg/article/view/40463/24695info:eu-repo/semantics/openAccess2015-05-26T14:02:15Zoai:revistas.ufpr.br:article/40463Revistahttps://revistas.ufpr.br/bcgPUBhttps://revistas.ufpr.br/bcg/oaiqdalmolin@ufpr.br|| danielsantos@ufpr.br||qdalmolin@ufpr.br|| danielsantos@ufpr.br1982-21701413-4853opendoar:2015-05-26T14:02:15Boletim de Ciências Geodésicas - Universidade Federal do Paraná (UFPR)false |
dc.title.none.fl_str_mv |
A MODEL SUGGESTION FOR THE DETERMINATION OF THE TRAFFIC ACCIDENT HOTSPOTS ON THE TURKISH HIGHWAY ROAD NETWORK: A PILOT STUDY A MODEL SUGGESTION FOR THE DETERMINATION OF THE TRAFFIC ACCIDENT HOTSPOTS ON THE TURKISH HIGHWAY ROAD NETWORK: A PILOT STUDY |
title |
A MODEL SUGGESTION FOR THE DETERMINATION OF THE TRAFFIC ACCIDENT HOTSPOTS ON THE TURKISH HIGHWAY ROAD NETWORK: A PILOT STUDY |
spellingShingle |
A MODEL SUGGESTION FOR THE DETERMINATION OF THE TRAFFIC ACCIDENT HOTSPOTS ON THE TURKISH HIGHWAY ROAD NETWORK: A PILOT STUDY Erdogan, Saffet Geociências; Geodésia Traffic Accidents; Hotspot; Spatial Statistical Methods; GIS. Geociências; Geodésia Traffic Accidents; Hotspot; Spatial Statistical Methods; GIS. |
title_short |
A MODEL SUGGESTION FOR THE DETERMINATION OF THE TRAFFIC ACCIDENT HOTSPOTS ON THE TURKISH HIGHWAY ROAD NETWORK: A PILOT STUDY |
title_full |
A MODEL SUGGESTION FOR THE DETERMINATION OF THE TRAFFIC ACCIDENT HOTSPOTS ON THE TURKISH HIGHWAY ROAD NETWORK: A PILOT STUDY |
title_fullStr |
A MODEL SUGGESTION FOR THE DETERMINATION OF THE TRAFFIC ACCIDENT HOTSPOTS ON THE TURKISH HIGHWAY ROAD NETWORK: A PILOT STUDY |
title_full_unstemmed |
A MODEL SUGGESTION FOR THE DETERMINATION OF THE TRAFFIC ACCIDENT HOTSPOTS ON THE TURKISH HIGHWAY ROAD NETWORK: A PILOT STUDY |
title_sort |
A MODEL SUGGESTION FOR THE DETERMINATION OF THE TRAFFIC ACCIDENT HOTSPOTS ON THE TURKISH HIGHWAY ROAD NETWORK: A PILOT STUDY |
author |
Erdogan, Saffet |
author_facet |
Erdogan, Saffet Ilçi, Veli Saysal, Omer Korkmaz, Aysegul |
author_role |
author |
author2 |
Ilçi, Veli Saysal, Omer Korkmaz, Aysegul |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
|
dc.contributor.author.fl_str_mv |
Erdogan, Saffet Ilçi, Veli Saysal, Omer Korkmaz, Aysegul |
dc.subject.por.fl_str_mv |
Geociências; Geodésia Traffic Accidents; Hotspot; Spatial Statistical Methods; GIS. Geociências; Geodésia Traffic Accidents; Hotspot; Spatial Statistical Methods; GIS. |
topic |
Geociências; Geodésia Traffic Accidents; Hotspot; Spatial Statistical Methods; GIS. Geociências; Geodésia Traffic Accidents; Hotspot; Spatial Statistical Methods; GIS. |
description |
Traffic accidents are very serious problems for human life and the environment. In road safety, it is crucial to identify the high risk locations to apply proper counter measures. This paper aims at introducing outcomes of a pilot project whose main goal is to develop a GIS based crash analysis system integrated with the quantitative methods for identification of high risk locations on road networks in Turkey. In this concept, traditional hotspot detection methods used in Turkey(crash frequency, rate, and severity) are compared with the spatial statistical methods including Moran‟s I, GetisOrd G and planar and network kernel density estimation in terms of their sensitivity to spatial characteristics of crash clusters. Many countries use traditional hotspot detection approaches such as crash frequency, crash rate, and crash severity as well as Turkey. In this project, we aimed at obtaining a model including different hotspot identification methods for the safety program of Turkey. In order to obtain the model, many hotspot detection methods will be used and compare stage by stage. In the first stage, the seven methods mentioned above are used and examined. Although some of these methods are compared in couple, there is no study using all these methods together extensively in the literature. Methods validated with a different spatial vantage points. Repetitiveness of hotspots in a seven years period are used to compare the methods. Meanwhile advantages and disadvantages of the methods according to location of hotspots are examined additionally. Results show that using planar KDE with Gi in the junction locations and using planar KDE with Moran‟s I in the straight road locations could improve the model while determining hotspots |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-03-30 |
dc.type.none.fl_str_mv |
|
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://revistas.ufpr.br/bcg/article/view/40463 |
url |
https://revistas.ufpr.br/bcg/article/view/40463 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://revistas.ufpr.br/bcg/article/view/40463/24695 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Boletim de Ciências Geodésicas Bulletin of Geodetic Sciences |
publisher.none.fl_str_mv |
Boletim de Ciências Geodésicas Bulletin of Geodetic Sciences |
dc.source.none.fl_str_mv |
Boletim de Ciências Geodésicas; Vol 21, No 1 (2015) Bulletin of Geodetic Sciences; Vol 21, No 1 (2015) 1982-2170 1413-4853 reponame:Boletim de Ciências Geodésicas instname:Universidade Federal do Paraná (UFPR) instacron:UFPR |
instname_str |
Universidade Federal do Paraná (UFPR) |
instacron_str |
UFPR |
institution |
UFPR |
reponame_str |
Boletim de Ciências Geodésicas |
collection |
Boletim de Ciências Geodésicas |
repository.name.fl_str_mv |
Boletim de Ciências Geodésicas - Universidade Federal do Paraná (UFPR) |
repository.mail.fl_str_mv |
qdalmolin@ufpr.br|| danielsantos@ufpr.br||qdalmolin@ufpr.br|| danielsantos@ufpr.br |
_version_ |
1799771718234931200 |