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Development of Accident Prediction Model under Mixed Traffic Conditions: A Case Study
Ashish Dhamaniya
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DOI:10.17265/2328-2142/2024.04.003
Civil Engineering Department, Indian Institute of Technology (IIT) Roorkee, Uttarakhand 247667, India
Accident prediction models are developed under mixed traffic conditions. Two models have been developed. The first model is a city based traffic accident prediction model. City population and vehicle ownership are the two parameters used to develop the model. A case study of Surat city in Gujarat is taken up. Total accident occurred in the city are regressed with population and vehicle ownership. Second model is the urban arterial based accident prediction model. Past accident record of ring road of Surat city shows that there are eight different locations on a ten kilometer stretch of ring road where the accidents took place consistently. These locations are picked up as accident spots. As there are many contributing factors and causes to road accidents. A comprehensive study of road safety found that human error was the sole cause in 57% of all accidents and was a contributing factor in over 90%. Keeping this in view a new term driver-pedestrian index is used to develop this model. Regression function of Microsoft excel is used for model development. Both the models are checked with R-statistics and t-statistics further the models are validated by using statistical goodness of fit (chi square test). Hence these models can be used to predict number of accidents in future subjected to the same geometric standards. Keeping this in mind improvement measures can be taken up by the district authorities.
Traffic, accidents, regression, population and vehicle ownership, driver-pedestrian index.
Journal of Traffic and Transportation Engineering 12 (2024) 187-195 doi: 10.17265/2328-2142/2024.04.003
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