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Analyzing accident severity of motorcyclists using a Bayesian network |
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| รหัสดีโอไอ | |
| Creator | 1. Pada Lumba 2. Sigit Priyanto 3. Imam Muthohar |
| Title | Analyzing accident severity of motorcyclists using a Bayesian network |
| Publisher | Research and Development Office, Prince of Songkla University |
| Publication Year | 2561 |
| Journal Title | Songklanakarin Journal of Science and Technology |
| Journal Vol. | 40 |
| Journal No. | 6 |
| Page no. | 1464-1472 |
| Keyword | accident severity, Bayesian network, Bekasi, motorcycle |
| URL Website | http://rdo.psu.ac.th/sjstweb/index.php |
| ISSN | 0125-3395 |
| Abstract | This paper focuses on the probability of crashes with severe and mild injuries in motorcyclists. The probability of crashes took human, road and environment, and vehicle factors into consideration. From July to December, 2015, 70.93% of the crashes that occurred in Indonesia involved motorcycles. The research took place in Bekasi City, Indonesia. The samples consisted of 184 respondents who had experienced crashes. The results indicated that the probability of severe injuries from the crashes was 13% and the probability of mild injuries was 87%. The mean absolute deviation of the model was 20.20%. Female drivers were more likely to be severely injured than males. Driving on roads which have road side variability and driving on curvy roads would be able to decrease the level of monotonous driving from 41% to 21%. Motorcycles which have engine capacity above 125 cm3 were 14% more likely to experience crashes with severely injuries. |
