Crash Prediction Models and Methodological Issues
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.
Keywords:
crash prediction models, Artificial Neural Network, statistical methods, road safety, soft computing tools, methodological issuesPublished Online
2022-05-09
How to Cite
Mekonnen, A. A., Sipos, T. (2022) “Crash Prediction Models and Methodological Issues”, Periodica Polytechnica Transportation Engineering, 50(3), pp. 267–272. https://doi.org/10.3311/PPtr.16295
Issue
Section
Articles