Predicting traffic accidents using regional spatial modeling (Case Study: Big Tehran, 2016)

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Karami Hamidreza

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Journal: Scientific Quarterly of Rahvar Year:2020 | Volume:8 | Issue:31 Page(s): 165-190

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Information Journal Paper

Title

Predicting traffic accidents using regional spatial modeling (Case Study: Big Tehran, 2016)

Author(s)

Karami Hamidreza | Issue Writer Certificate

Keywords

traffic accidentsQ1

Accidents PredictionQ1

regional spatial regression modelQ1

total causeQ1

Abstract

traffic accidents are a social problem in the country that annually kills a largenumber of people and brings huge economic costs to society. In recent years, in Traffic Management Discussion, there has been a lot of attention toAccidents Prediction methods. Accident prediction has a great impact onreducing the number of casualties, injuries and financial losses resulting fromaccidents. The main purpose of this study is to predict traffic accidents usingthe regional spatial model of Big Tehran in 2016. This research is descriptivecrosssectional in terms of data collection method. The statistical population ofthis study is accident statistics and data in 22 districts of Tehran in 2016 whichis registered in the database of traffic police station. In this study, whileanalyzing the factors affecting traffic accidents, regional spatial regressionmodel was used for data analysis and presenting prediction models. Thefindings of this study show that the three factors of human, road and vehicleswere the factors affecting traffic accidents in Tehran; In such a way that theauxiliary variables of the number of trips absorbed and trips produced areinfluenced by the severity of traffic accidents (total accidents involving suddenchange of direction, disregard forwards, disregard of right of way anddisregard of long distance); So that a one percent increase in absorbed andproduced travels leads to a 21. 7 percent and a 23. 2 percent increase in drivingviolations, respectively. The results also showed that by considering thecorrelation structure of the counting data, one can deal with traffic accidentprediction models in the coming years and dentified and controlled the factorsaffecting them.

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APA: Copy

Karami, Hamidreza. (2020). Predicting traffic accidents using regional spatial modeling (Case Study: Big Tehran, 2016). RAHVAR SCIENTIFIC QUARTERLY, 8(31 ), 165-190. SID. https://sid.ir/paper/231557/en

Vancouver: Copy

Karami Hamidreza. Predicting traffic accidents using regional spatial modeling (Case Study: Big Tehran, 2016). RAHVAR SCIENTIFIC QUARTERLY[Internet]. 2020;8(31 ):165-190. Available from: https://sid.ir/paper/231557/en

IEEE: Copy

Hamidreza Karami, “Predicting traffic accidents using regional spatial modeling (Case Study: Big Tehran, 2016),” RAHVAR SCIENTIFIC QUARTERLY, vol. 8, no. 31 , pp. 165–190, 2020, [Online]. Available: https://sid.ir/paper/231557/en

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