Open AccessAccident‐related cost analysis and decision‐making support through econometric modelling
Author(s) -
Catalano Mario,
Galatioto Fabio,
Shaikh Nabeel
Publication year - 2020
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2020.0093
Subject(s) - transport engineering , work (physics) , econometric model , government (linguistics) , principal (computer security) , accident analysis , scale (ratio) , decision support system , engineering , accident (philosophy) , predictive modelling , computer science , operations research , geography , computer security , cartography , data mining , mechanical engineering , linguistics , philosophy , epistemology , machine learning
This study illustrates the early results of on‐going research started under a recent project sponsored by the United Kingdom Government Transport Department to investigate the principal factors influencing road accidents as well as develop an internet application for the prediction of road accident‐related effects at different scales. In particular, accident modelling, analysis of socio–economic, land use, infrastructural and contextual factors of road safety, as well as decision‐making support are the focus of this work. In particular, an application in the United Kingdom of a model framework potentially transferable to other contexts is described. This application resulted in an extensive analysis of road safety factors as well as the development of a simulation web‐based platform that uses microeconometric models to estimate the frequency of road accident along with the number and severity of injuries. These models proved considerable accuracy at the national level. In the end, the potential benefit of the simulation platform for road safety decision‐making is showcased on a micro‐scale with an application to a medium‐sized town in South East England.