Weather Conditions, Weather Information and Car Crashes

Road traffic safety is the result of a complex interaction of factors, and causes behind road vehicle crashes require different measures to reduce their impacts. This study assesses how strongly the variation in daily winter crash rates associates with weather conditions in Finland. This is done by...

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Main Authors: Adriaan Perrels, Athanasios Votsis, Väinö Nurmi, Karoliina Pilli-Sihvola
Format: Article
Language:English
Published: MDPI AG 2015-11-01
Series:ISPRS International Journal of Geo-Information
Subjects:
Online Access:http://www.mdpi.com/2220-9964/4/4/2681
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spelling doaj-8918adaa7fb3484093d9691a8b3727802020-11-24T23:20:09ZengMDPI AGISPRS International Journal of Geo-Information2220-99642015-11-01442681270310.3390/ijgi4042681ijgi4042681Weather Conditions, Weather Information and Car CrashesAdriaan Perrels0Athanasios Votsis1Väinö Nurmi2Karoliina Pilli-Sihvola3Finnish Meteorological Institute, P.O: Box 503, Helsinki 00101, FinlandFinnish Meteorological Institute, P.O: Box 503, Helsinki 00101, FinlandFinnish Meteorological Institute, P.O: Box 503, Helsinki 00101, FinlandFinnish Meteorological Institute, P.O: Box 503, Helsinki 00101, FinlandRoad traffic safety is the result of a complex interaction of factors, and causes behind road vehicle crashes require different measures to reduce their impacts. This study assesses how strongly the variation in daily winter crash rates associates with weather conditions in Finland. This is done by illustrating trends and spatiotemporal variation in the crash rates, by showing how a GIS application can evidence the association between temporary rises in regional crash rates and the occurrence of bad weather, and with a regression model on crash rate sensitivity to adverse weather conditions. The analysis indicates that a base rate of crashes depending on non-weather factors exists, and some combinations of extreme weather conditions are able to substantially push up crash rates on days with bad weather. Some spatial causation factors, such as variation of geophysical characteristics causing systematic differences in the distributions of weather variables, exist. Yet, even in winter, non-spatial factors are normally more significant. GIS data can support optimal deployment of rescue services and enhance in-depth quantitative analysis by helping to identify the most appropriate spatial and temporal resolutions. However, the supportive role of GIS should not be inferred as existence of highly significant spatial causation.http://www.mdpi.com/2220-9964/4/4/2681responsivenessroad vehicle crashestraffic safetyearly warningweather conditions
collection DOAJ
language English
format Article
sources DOAJ
author Adriaan Perrels
Athanasios Votsis
Väinö Nurmi
Karoliina Pilli-Sihvola
spellingShingle Adriaan Perrels
Athanasios Votsis
Väinö Nurmi
Karoliina Pilli-Sihvola
Weather Conditions, Weather Information and Car Crashes
ISPRS International Journal of Geo-Information
responsiveness
road vehicle crashes
traffic safety
early warning
weather conditions
author_facet Adriaan Perrels
Athanasios Votsis
Väinö Nurmi
Karoliina Pilli-Sihvola
author_sort Adriaan Perrels
title Weather Conditions, Weather Information and Car Crashes
title_short Weather Conditions, Weather Information and Car Crashes
title_full Weather Conditions, Weather Information and Car Crashes
title_fullStr Weather Conditions, Weather Information and Car Crashes
title_full_unstemmed Weather Conditions, Weather Information and Car Crashes
title_sort weather conditions, weather information and car crashes
publisher MDPI AG
series ISPRS International Journal of Geo-Information
issn 2220-9964
publishDate 2015-11-01
description Road traffic safety is the result of a complex interaction of factors, and causes behind road vehicle crashes require different measures to reduce their impacts. This study assesses how strongly the variation in daily winter crash rates associates with weather conditions in Finland. This is done by illustrating trends and spatiotemporal variation in the crash rates, by showing how a GIS application can evidence the association between temporary rises in regional crash rates and the occurrence of bad weather, and with a regression model on crash rate sensitivity to adverse weather conditions. The analysis indicates that a base rate of crashes depending on non-weather factors exists, and some combinations of extreme weather conditions are able to substantially push up crash rates on days with bad weather. Some spatial causation factors, such as variation of geophysical characteristics causing systematic differences in the distributions of weather variables, exist. Yet, even in winter, non-spatial factors are normally more significant. GIS data can support optimal deployment of rescue services and enhance in-depth quantitative analysis by helping to identify the most appropriate spatial and temporal resolutions. However, the supportive role of GIS should not be inferred as existence of highly significant spatial causation.
topic responsiveness
road vehicle crashes
traffic safety
early warning
weather conditions
url http://www.mdpi.com/2220-9964/4/4/2681
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AT athanasiosvotsis weatherconditionsweatherinformationandcarcrashes
AT vainonurmi weatherconditionsweatherinformationandcarcrashes
AT karoliinapillisihvola weatherconditionsweatherinformationandcarcrashes
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