Crash Prediction Models and Methodological Issues

Journal Article (2022)
Author(s)

Anteneh Afework Mekonnen (Budapest University of Technology and Economics)

Tibor Sipos (Budapest University of Technology and Economics)

Affiliation
External organisation
DOI related publication
https://doi.org/10.3311/PPtr.16295 Final published version
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Publication Year
2022
Language
English
Affiliation
External organisation
Journal title
Periodica Polytechnica Transportation Engineering
Issue number
3
Volume number
50
Pages (from-to)
267-272
Downloads counter
5

Abstract

The conducted literature review aimed to provide an overall perspective on the significant findings of past research works related to vehicle crashes and prediction models. The literature review also provided information concerning past road safety research methodology and viable statistical analysis and computing tools. Though the selection of a specific model hinges on the objective of the research and nature of the response, when compared to statistical modeling techniques, Artificial Neural Networks (ANNs), which can model complex nonlinear relationships among dependent and independent parameters, have been witnessed to be very powerful.