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城市快速路交通事故严重程度调查:来自北京的案例研究。

Investigation of injury severity in urban expressway crashes: A case study from Beijing.

机构信息

State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing, China.

School of Civil Engineering and Mechanics, Huazhong University of Science and Technology Wuhan, China.

出版信息

PLoS One. 2020 Jan 13;15(1):e0227869. doi: 10.1371/journal.pone.0227869. eCollection 2020.

Abstract

Urban expressway is the main artery of traffic network, and an in-depth analysis of the crashes is crucial for improving the traffic safety level of expressways. This study intended to address the injury severity of expressways in Beijing by proposing Bayesian ordered logistic regression model. Crash data were collected from urban express rings and expressways in 2015 and 2016. The results showed that crash location, time and crash season are significant variables influencing injury severity. The findings revealed that the proposed model can address the ordinal feature of injury severity, while accommodating the data with small sample sizes that may not adequately represent population characteristics. The conclusions can provide the management departments with valuable suggestions for the injury prevention and safety improvement on the urban expressways.

摘要

城市快速路是交通网络的主要干线,深入分析事故情况对提高快速路交通安全水平至关重要。本研究旨在通过提出贝叶斯有序逻辑回归模型来解决北京快速路的伤害严重程度问题。事故数据收集于 2015 年和 2016 年的城市快速环和快速路上。结果表明,事故位置、时间和事故季节是影响伤害严重程度的显著变量。研究结果表明,所提出的模型可以解决伤害严重程度的有序特征,同时适用于可能不能充分代表总体特征的小样本量数据。研究结论可为城市快速路的伤害预防和安全改善提供管理部门有价值的建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c2d/6957292/9fd80b62db72/pone.0227869.g001.jpg

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