Berhanu Girma
Department of Civil Engineering, Addis Ababa University, P.O. Box 30026, Addis Ababa, Ethiopia.
Accid Anal Prev. 2004 Sep;36(5):697-704. doi: 10.1016/j.aap.2003.05.002.
This paper presents the study carried out to develop accident predictive models based on the data collected on arterial roads in Addis Ababa. Poisson and negative binomial regression methods were used to relate the discrete accident data with the road and traffic flow explanatory variables. Significant accident predictive models were found with a number of significant explanatory variables. The results show that the existing inadequate road infrastructure and poor road traffic operations are the potential contributors of this ever-growing challenge of the road transport in Addis Ababa. The results also indicate that improvements in roadway width, pedestrian facilities, and access management are effective in reducing road traffic accidents.
本文介绍了一项基于在亚的斯亚贝巴主干道收集的数据开展的研究,旨在开发事故预测模型。采用泊松回归和负二项回归方法,将离散事故数据与道路和交通流解释变量相关联。发现了具有若干显著解释变量的重要事故预测模型。结果表明,现有的道路基础设施不足和道路交通运营不佳是亚的斯亚贝巴道路运输这一日益严峻挑战的潜在成因。结果还表明,改善道路宽度、行人设施和通道管理对减少道路交通事故有效。