Literature DB >> 27183516

Alternative method of highway traffic safety analysis for developing countries using delphi technique and Bayesian network.

Anthony C Mbakwe1, Anthony A Saka2, Keechoo Choi3, Young-Jae Lee4.   

Abstract

Highway traffic accidents all over the world result in more than 1.3 million fatalities annually. An alarming number of these fatalities occurs in developing countries. There are many risk factors that are associated with frequent accidents, heavy loss of lives, and property damage in developing countries. Unfortunately, poor record keeping practices are very difficult obstacle to overcome in striving to obtain a near accurate casualty and safety data. In light of the fact that there are numerous accident causes, any attempts to curb the escalating death and injury rates in developing countries must include the identification of the primary accident causes. This paper, therefore, seeks to show that the Delphi Technique is a suitable alternative method that can be exploited in generating highway traffic accident data through which the major accident causes can be identified. In order to authenticate the technique used, Korea, a country that underwent similar problems when it was in its early stages of development in addition to the availability of excellent highway safety records in its database, is chosen and utilized for this purpose. Validation of the methodology confirms the technique is suitable for application in developing countries. Furthermore, the Delphi Technique, in combination with the Bayesian Network Model, is utilized in modeling highway traffic accidents and forecasting accident rates in the countries of research.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Bayesian network; Delphi technique; Developing countries; Forecasting accident rate; Korea; Traffic safety

Mesh:

Year:  2016        PMID: 27183516     DOI: 10.1016/j.aap.2016.04.020

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  4 in total

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Journal:  PLoS One       Date:  2018-01-03       Impact factor: 3.240

2.  Developing an Organ Donation Curriculum for Medical Undergraduates in China Based on Theory of Planned Behavior: A Delphi Method Study.

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Journal:  Ann Transplant       Date:  2020-05-15       Impact factor: 1.530

3.  Evaluating the Safety Risk of Rural Roadsides Using a Bayesian Network Method.

Authors:  Tianpei Tang; Senlai Zhu; Yuntao Guo; Xizhao Zhou; Yang Cao
Journal:  Int J Environ Res Public Health       Date:  2019-04-01       Impact factor: 3.390

4.  Decision Tree Ensemble Method for Analyzing Traffic Accidents of Novice Drivers in Urban Areas.

Authors:  Serafín Moral-García; Javier G Castellano; Carlos J Mantas; Alfonso Montella; Joaquín Abellán
Journal:  Entropy (Basel)       Date:  2019-04-03       Impact factor: 2.524

  4 in total

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