Analyzing accident severity of motorcyclists using a Bayesian network

Lumba, Pada and Priyanto, Sigit and Muthohar, Imam (2018) Analyzing accident severity of motorcyclists using a Bayesian network. Songklanakarin Journal of Science and Technology, 40 (6). pp. 1464-1472. ISSN 01253395

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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.

Item Type:	Article
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Fakultas Teknik > Teknik Sipil
Depositing User:	Dr Pada Lumba
Date Deposited:	01 Sep 2022 06:40
Last Modified:	02 Sep 2022 04:56
URI:	http://repository.upp.ac.id/id/eprint/1276

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