Prediction of pedal cyclists and pedestrian fatalities from total monthly accidents and registered private car numbers

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dc.contributor.authorGhasemlou K.
dc.contributor.authorAydin M.M.
dc.contributor.authorYildirim M.S.
dc.date.accessioned2024-07-22T08:14:01Z
dc.date.available2024-07-22T08:14:01Z
dc.date.issued2015
dc.description.abstractAccident prevention is relatively a complex issue considering the effectiveness of the injury prevention technologies as well as more detailed assessment of the complex interactions between the road condition, vehicle and human factor. For many years, highway agencies and vehicle manufacturers showed great efforts to reduce the injuries resulting from the vehicle crashes. Many researchers used a broad range of methods to evaluate the impact of several factors on traffic accidents and injuries. Recent developments lead up to capable for determining the effects of these factors. According to World Health Organization (WHO), cyclists and pedestrians comprise respectively 1.6% and 16.3% in traffic crash fatalities in 2013. Also in Turkey crash fatalities for pedestrian and cyclists are respectively 20.6% and 3% according to Turkish Statistical Institute data in 2013. The relationship between cycling and pedestrian rates and injury rates over time is also unknown. This paper aims to predict the crash severity with the traffic injury data of the Konya City in Turkey by implementing the Artificial Neural Networks (ANN), Regression Trees (RT) and Multiple Linear Regression modelling (MLRM) method.
dc.identifier.DOI-ID10.5604/08669546.1169209
dc.identifier.issn08669546
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/16468
dc.language.isoEnglish
dc.publisherWarsaw University of Technology
dc.rightsAll Open Access; Gold Open Access
dc.subjectAccidents
dc.subjectAutomobile manufacture
dc.subjectComplex networks
dc.subjectCrashworthiness
dc.subjectForestry
dc.subjectHighway accidents
dc.subjectLinear regression
dc.subjectNeural networks
dc.subjectRegression analysis
dc.subjectTrees (mathematics)
dc.subjectVehicles
dc.subjectCyclist
dc.subjectInjury prevention
dc.subjectMultiple linear regressions
dc.subjectPedestrian fatalities
dc.subjectPedestrians
dc.subjectRegression trees
dc.subjectVehicle manufacturers
dc.subjectWorld Health Organization
dc.subjectPedestrian safety
dc.titlePrediction of pedal cyclists and pedestrian fatalities from total monthly accidents and registered private car numbers
dc.typeArticle

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