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PW 2047 Intercity public bus drivers’ behavior modeling in iran
  1. Ali Zayerzadeh1,
  2. Nasir Baradaran Rahmanian2
  1. 1Road Safety Spesialist, Road Safety Pioneers (RSP)
  2. 2M.Sc Transportation, RMTO


Motor vehicle crashes are often predictable and preventable. Yet, many drivers choose to behave in ways that put themselves and others at risk for a vehicle crash or serious injuries. At-risk driving behaviors include speed-limit violation, excessive speed/lateral acceleration on curves, unplanned lane departures, frequent hard braking, close following distances, lateral encroachment, failure to yield at intersections, and general disobedience of the rules of the road. At-risk non-driving behaviors include improper lifting techniques, improper entering/exiting the truck, and poor diet and exercise. Performing at-risk driving behaviors is likely to increase crash risk while performing at-risk non-driving behaviors is likely to increase injury and illness risk.

The aims of the present study is to develop an instrument for measuring risk taking driver behaviors and to investigate the relationship between these behaviors, DBQ scales (violations and errors), aggression, traffic offences, and accidents. The Driver Behavior Questionnaire (DBQ) seems to be a possible turning point in constructing a comprehensive model for everyday driving behavior. In the DBQ, driver behaviors could be categorized and evaluated under a theoretically sound framework, which also seemed to have practical importance.

The DBQ was based on the main distinction between errors and violations, which were assumed to have different psychological origins and demand different modes of remediation. Participants were 958 public bus drivers (All male) who completed a Driver Behavior Questionnaire (DBQ) and items related to drivers driving records and demographics. The participants were assured of anonymity and confidentiality. Factor analysis resulted in factors structure including violations, education programs, laws knowledge, technical experiences and etc. To achieve the results a risk taking behaviors index defined using specific DBQ questions. Linear Regression analyses showed that risk taking behaviors index were related to the number of accidents and some demographic factors. Also analyses indicated that violations were associated with other dependent variables such type of ownership.

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