چکیده:
Nowadays, road accidents and the resulting high economic and social losses and costs are among the most fundamental problems that have challenged transportation and traffic specialists and officials. The aim of this research is to analyze accident severity and determine the factors affecting it on two-lane, two-way intercity roads using geographic information systems and decision tree and regression data mining models. This study, while creating a database of accident and road facility data, uses decision tree and regression data mining models to estimate accident severity and examine the role of spatial factors and other factors affecting accident severity. The proposed method is investigated and evaluated on a set of accident records on the Qazvin - Rasht (Iran) axis that occurred over a four-year period. The results of this study indicate the high efficiency and interpretability of the proposed method in analyzing accident severity. Examining the relative importance of factors in the proposed model shows that spatial factors, especially proximity to curves and urban development around the road, along with technical vehicle defects, failure to use seat belts, and visibility obstacles, are among the most important factors influencing the increase in accident severity.
خلاصه ماشینی:
The aim of this research is to analyze accident severity and determine the factors affecting it in two-lane - two-way intercity roads using Geographic Information Systems (GIS) and data mining models, specifically decision tree and regression.
Investigating the relative importance of factors in the proposed model shows that spatial factors, especially proximity to curves and urban development around the road, along with vehicle technical defects, failure to use seat belts, and visual obstructions, are among the most important factors influencing the increase in accident severity.
Siddiqui The goal of this research is to present a spatial method based on data mining using the Classification and Regression Tree model 1 to analyze accident severity on extra-urban roads.
This study also attempts to investigate the role of spatial factors on accident severity by integrating the capabilities of Geospatial Information Systems 3 with the Classification and Regression Tree model.
The main objective of this research is to analyze accident severity and determine the influential factors on it in two-lane two-way roads based on Geospatial Information Systems and the Classification and Regression Tree model.
Research Methodology The main approach of the research is based on the integration of spatial analyses and the classification tree and regression data mining model to analyze accident severity and determine the factors affecting it.
This is carried out using a spatial method based on the classification tree and regression model, and the result is an analysis of the role of spatial factors on accident severity alongside other influential factors investigated in previous studies.
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