Literature DB >> 14642870

Traffic safety assessment and development of predictive models for accidents on rural roads in Egypt.

Khaled A Abbas1.   

Abstract

This paper starts by presenting a conceptualization of indicators, criteria and accidents' causes that can be used to describe traffic safety. The paper provides an assessment of traffic safety conditions for rural roads in Egypt. This is done through a three-step procedure. First, deaths per million vehicle kilometers are obtained and compared for Egypt, three other Arab countries and six of the G-7 countries. Egypt stands as having a significantly high rate of deaths per 100 million vehicle kilometers. This is followed by compiling available traffic and accident data for five main rural roads in Egypt over a 10-year period (1990-1999). These are used to compute and compare 13 traffic safety indicators for these roads. The third step for assessing traffic safety for rural roads in Egypt is concerned with presenting a detailed analysis of accident causes. The paper moves on to develop a number of statistical models that can be used in the prediction of the expected number of accidents, injuries, fatalities and casualties on the rural roads in Egypt. Time series data of traffic and accidents, over a 10 years period for the considered roads, is utilized in the calibration of these predictive models. Several functional forms are explored and tested in the calibration process. Before proceeding to the development of these models three ANOVA statistical tests are conducted to establish whether there are any significant differences in the data used for models' calibration as a result of differences among the considered five roads.

Mesh:

Year:  2004        PMID: 14642870     DOI: 10.1016/s0001-4575(02)00145-8

Source DB:  PubMed          Journal:  Accid Anal Prev        ISSN: 0001-4575


  1 in total

1.  Will higher traffic flow lead to more traffic conflicts? A crash surrogate metric based analysis.

Authors:  Yan Kuang; Xiaobo Qu; Yadan Yan
Journal:  PLoS One       Date:  2017-08-07       Impact factor: 3.240

  1 in total

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