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马来西亚联邦道路上道路状况对事故严重程度的影响。

The impact of roadway conditions towards accident severity on federal roads in Malaysia.

作者信息

Musa Mohad Fedder, Hassan Sitti Asmah, Mashros Nordiana

机构信息

Public Work Department, JKR, Kuala Lumpur, Malaysia.

School of Civil Engineering, Faculty of Engineering, Universiti Teknologi Malaysia, Skudai, Johor, Malaysia.

出版信息

PLoS One. 2020 Jul 6;15(7):e0235564. doi: 10.1371/journal.pone.0235564. eCollection 2020.

Abstract

The fatal accidents on the roads remain a global concern. Daily, approximately 18 traffic accidents occur in the Peninsular Malaysia that cause on an average one death in every hour, a situation that needs preventive measures. The development of the effective strategies to reduce such fatal accidents requires the identification of various risk factors including the road condition. We identified such accident severity issues using the public work and police department databases that consisted of 1067 cases of various severity levels occurred on the Malaysian federal roads during 2008 to 2015. These records were used to develop ordered logistic regression model for the accident severity and nine variables were analyzed. The results revealed that the presence of poor horizontal alignment affected the model outcomes. The likelihood of the more serious accident severity due to the poor horizontal alignment was correspondingly about 0.4 times less compared to the absence of such factors. It is established that the present findings may assist the local authorities to take proactive actions to prevent serious road accidents on the road segments possessing the standard horizontal alignment.

摘要

道路上的致命事故仍然是一个全球关注的问题。在马来西亚半岛,每天大约发生18起交通事故,平均每小时造成1人死亡,这种情况需要采取预防措施。制定有效的策略来减少此类致命事故需要识别各种风险因素,包括道路状况。我们使用公共工程和警察部门的数据库识别了此类事故严重程度问题,该数据库包含2008年至2015年期间在马来西亚联邦道路上发生的1067起不同严重程度的案件。这些记录被用于建立事故严重程度的有序逻辑回归模型,并对九个变量进行了分析。结果表明,水平线形不佳会影响模型结果。与不存在此类因素相比,由于水平线形不佳导致更严重事故严重程度的可能性相应降低约0.4倍。已确定本研究结果可能有助于地方当局采取积极行动,防止在具有标准水平线形的路段发生严重道路事故。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b909/7337329/af42fe2fc4ca/pone.0235564.g001.jpg

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