Journal of Transportation Research

Journal of Transportation Research

Modeling the Factors Affecting the Probability of an Accident and Predicting the Number of Taxi Drivers' Accidents

Document Type : Original Article

Authors
Ghasem Dermanakifarahani 1
Morteza Asadamraji 2
Babak Ebrahimian 3
1 M.Sc., Student of Transportation, Faculty of Civil Engineering, Water and Environment, Shahid Beheshti University, Tehran.
2 Assistant Professor, Department of Geotechnics and Transportation, Faculty of Civil Engineering, Water and Environment, Shahid Beheshti University, Tehran.
3 Assistant Professor, Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University (SBU), East Vafadar Blvd., Tehran, Iran.1658953571, Tehran, Iran
10.22034/tri.2023.416931.3193
Abstract
One of the vehicles on the city streets is a taxi, which is a supplement to public transportation and a part of an active transportation. Due to the fact that taxi drivers spend a longer time on the roads compared to other drivers, they have a higher probability of an accident; Therefore, safety and proper driving are important for taxi drivers. in this research, the influence of driver's behavior and characteristics on the probability of being involved in an accident and the rate of taxi accidents and presenting quantitative models for predicting the number of accidents and the probability of being involved in an accident have been investigated. For this purpose and by reviewing the literature on demographic characteristics, driving history and accidents of the last three years, driving behaviors and impulsivity characteristics were considered as independent variables, and to collect them, standard questionnaires were distributed to the target population, which were taxi drivers in Arak metropolis. In this regard, 330 random samples of taxi drivers completed the questionnaires. In the following, the reliability and validity of the questionnaires were verified and the logistic regression model was estimated to predict the probability of involvement in an accident and generalized Poisson models to predict the number of accidents as the best models using SPSS 24 software. The significant independent variables of the accident involvement equation include: age, number of violations, driver's hours of work, errors and slips, and interest in driving were significant. The influential variables in the model for predicting the number of accidents also included: age, error and slip, Disregarding the Regulation, interest in driving and history of driving a taxi. The results of this study can be used in designing training courses, evaluating taxi drivers' qualifications, and making cultural packages for these drivers.
Keywords
Accident Probability
Accident Number
Taxi Drivers
Logistic Regression
Generalized Poisson
Subjects
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