Accident prediction modelling for expressways: a review. Issue 1 (1st April 2022)

• Record Type: Journal Article
• Authors: Kumar, P; Jain, J K; Singh, G
• Is Part Of: IOP conference series. Volume 1236:Issue 1(2022)
• Publication Date: 2022-04-01
• Subjects: Accident Frequency Models -- Explanatory Variables -- Review -- Expressway; Materials science -- Periodicals; 620.1105
• DOI: 10.1088/1757-899X/1236/1/012011
• Languages: English
• ISSNs: 1757-8981

Abstract

Abstract: Expressways are the need for fast movement of goods and human being for long distances in current scenario for every country, but at the same time these facilities have the highest severity rate among all the road categories. Various researchers around the world have tried to find out the effect of traffic volume, road geometry and environmental factors on frequency of accident on expressway by using different accident prediction modeling methods during last three decades. The purpose of this review paper is to find out the appropriate modeling method which can be used to predict accident frequency on the expressways in the developing country like India where traffic conditions, vehicular characteristics, and the driver behaviour are very different from the developing countries and to find out the research areas where the findings are inconclusive. Literature review suggests that among various models used so far, correlated random parameter model found to be the most advanced model to simultaneously account for both the heterogeneous effects of explanatory factors across the road segments and the cross correlations among the random parameter estimates. Findings related to variables like percentage of heavy vehicles, vertical gradient and lane width are not conclusive. However, safety effect of variables like speed limit, roadway lighting, pavement type and fog are less studied on expressway. The effect of allowing two wheelers on the expressways safety has not been studied yet, and the accidents related to fatigue or drowsiness also need examination.