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Erschienen in: International Journal of Intelligent Transportation Systems Research 1/2021

14.11.2020

Bayesian Network-Based Framework for Cost-Implication Assessment of Road Traffic Collisions

verfasst von: Tebogo Makaba, Wesley Doorsamy, Babu Sena Paul

Erschienen in: International Journal of Intelligent Transportation Systems Research | Ausgabe 1/2021

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Abstract

Investigating the cost-implications of road traffic collision factors is an important endeavour that has a direct impact on the economy, transport policies, cities and nations around the world. A Bayesian network framework model was developed using real-life road traffic collision data and expert knowledge to assess the cost of road traffic collisions. Findings of this study suggest that the framework is a promising approach for assessing the cost-implications associated with road traffic collisions. Moreover, adopting this framework with other computational intelligence approaches would have a positive impact towards achieving the Sustainable Development Goals in terms of road safety.

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Metadaten
Titel
Bayesian Network-Based Framework for Cost-Implication Assessment of Road Traffic Collisions
verfasst von
Tebogo Makaba
Wesley Doorsamy
Babu Sena Paul
Publikationsdatum
14.11.2020
Verlag
Springer US
Erschienen in
International Journal of Intelligent Transportation Systems Research / Ausgabe 1/2021
Print ISSN: 1348-8503
Elektronische ISSN: 1868-8659
DOI
https://doi.org/10.1007/s13177-020-00242-1

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