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.
Bayesian Network-Based Framework for Cost-Implication Assessment of Road Traffic Collisions
Int. J. ITS Res.
International Journal of Intelligent Transportation Systems Research ; 19 , 1 ; 240-253
2021-04-01
14 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Bayesian network , Cost-implication , Framework , Road traffic collisions , Sensitivity analysis Engineering , Electrical Engineering , Automotive Engineering , Robotics and Automation , Computer Imaging, Vision, Pattern Recognition and Graphics , Civil Engineering , User Interfaces and Human Computer Interaction
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