A Survey-Based Probabilistic Statistical Approach for Characterizing Drivers’ Negative Behaviors

This paper aims at characterizing the behavioral issues of road users of relevance to traffic safety in the United Arab Emirates (UAE). A stated preference driver survey was used for data collection. Statistical analyses were conducted to identify the most common types of violations particularly associated with negative behavioral forms, and associate these behavioral forms to probable causes. A probabilistic analysis approach was adopted based on the results of statistical cross classification to identify the probabilities (penetration rate among the overall driver population) of the frequent violators and the most common negative behavior forms. A step further was accomplished by estimating the joint probabilities combining more than one behavioral form. This is particularly important in identifying the joint negative forms of significant threat to society, and quantifying their magnitudes. Results identified speeding, use of mobile phones, not using seat belts, and not giving priority to pedestrians as most alarming violations. The joint probabilities were used to estimate particular threatening behaviors such as speeding combined with drugs and alcohol, or combined with use of mobile phones while driving, etc. Statistical Chi-square tests were also conducted to estimate the strength of relation among the violations and their causes. Results indicated a strong association between speeding and being in a hurry on good roadway conditions. Cross relationships were thoroughly investigated allowing for violation-cause studies as well as behavioral form-violations studies. The probabilistic approach together with the statistical Chi-square tests were used to identify critical behavioral issues of immediate intervention need, to quantify their penetration levels (magnitude) in society, and as such were used to develop a coherent set of recommendations to remedy such critical behavioral forms.


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  • Accession Number: 01490490
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jul 9 2013 9:10AM