Modeling Drivers’ Natural Behavior When Overtaking on Undivided Rural Roads (Case Study: Mazandaran Province)

Document Type : Research Note

Authors

1 D‌e‌p‌t. o‌f C‌i‌v‌i‌l E‌n‌g‌i‌n‌e‌e‌r‌i‌n‌g S‌c‌i‌e‌n‌c‌e a‌n‌d R‌e‌s‌e‌a‌r‌c‌h B‌r‌a‌n‌c‌h I‌s‌l‌a‌m‌i‌c A‌z‌a‌d U‌n‌i‌v‌e‌r‌s‌i‌t‌y

2 T‌r‌a‌n‌s‌p‌o‌r‌t‌a‌t‌i‌o‌n R‌e‌s‌e‌a‌r‌c‌h I‌n‌s‌t‌i‌t‌u‌t‌e, R‌o‌a‌d H‌o‌u‌s‌i‌n‌g a‌n‌d U‌r‌b‌a‌n D‌e‌v‌e‌l‌o‌p‌m‌e‌n‌t R‌e‌s‌e‌a‌

Abstract

Traffic accidents between two cars when overtaking on undivided rural roads are considered as one of the unpredictable events. They reduce road safety and cause severe head-to-head accidents or deviations. It can be overwhelming with appropriate suggestions and solutions to reduce the interaction between the two cars and decrease the number of drivers’ accidents and fatalities. This study tried to identify the effective factors, especially those associated with the natural behavior of drivers, in the overtaking process. In order to collect the required information, 6 undivided rural roads in the northern province of Iran (Mazandaran province) were selected as the study sites; thirty participants were considered for driving and their performance and behaviors were studied using three in-car cameras .Finally, by examining 34 factors in the driving behavior of participants from video X-ray and data extraction from camera films, 327 inter-vehicle interactions were recorded. By analyzing the recorded videos, the data for each variable were recorded as numeric codes in Excel software. After data collection, the dual logit model in SPSS software was used because of the bi-directionality of the target variable (Overtaking or not overtaking). Prior to data modeling, dependent variables were examined and the related variables were removed from the modeling process. Next, the data were modeled in three simultaneous, forward, and backward methods and by evaluating the models, the concurrent model was selected as the best model for the obtained data. Accuracy of 89% in this study showed that male gender, driving distance, and listening to music increased the chance of overtaking drivers. Also, distance to front vehicle, driver-talk time, vehicle speed, poor pavement surface, and lack of knowledge of safety in overtaking time reduced the likelihood of overtaking.

Keywords


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