Faculty Publications
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Item Accident Prediction Modelling and Crash Scene Investigation(Springer Science and Business Media Deutschland GmbH, 2023) Sumayya Naznin, P.H.; Panackel, L.S.; Zaviar, S.; Babu, S.In recent years, traffic incidents have been a major cause of deaths, injuries, and property damage in India. By definition, an accident is “an unforeseen and unplanned incident that causes harm or injury†; nevertheless, in most circumstances, accidents can be avoided by taking specific precautions. Understanding the primary and contributing factors may combat road traffic accident severity. This research uncovered new information as well as the most important target-specific contributing elements to the severity of road accidents. The goal of this study was to analyse accident data from Koratty and Angamaly towns in Kerala's Ernakulam district, and to identify and classify black spots into first, second, third, fourth, and fifth orders based on the ASI value and the crash scenes were investigated in order to analyze the causes. An attempt was made to design collision and condition diagrams, as well as develop an accident prediction model for these dangerous areas, using the information acquired thus far. The collision diagrams for various places also revealed the pattern of road accidents that occurred over a two-year period, while the condition diagrams revealed the precise site of the accident. Using this knowledge, certain short-term corrective measures/solutions for the crash studied sites were offered. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.Item Accident Prediction Model for Horizontal Curves on State Highways Using Spatial Variation(Springer Science and Business Media Deutschland GmbH, 2025) Pandey, S.K.; Mulangi, R.H.; Sanganaikar, R.S.; Babu, K.R.N.N.Accidents have become one of the primary cause of fatalities on highways. Road accidents are one of the significant issue around the globe, but in context of India, the severity is more due to immense growth in road networks and traffic capacity. Curve are at higher range of potential risks of accidents because of inadequate sight distance and speed measures. This study aims to develop accident prediction model using regression analysis. Location selected for study was State Highway-1 in Udupi district, Karnataka. Ten curves are selected on the road and comparative study of model prepared is checked to verify the model reliability. Datasets used for model calibration and development is Highway Geometric data, past accidents records, and spot speed of vehicles. Geometric data for the road sections are obtained from satellite imageries, and GIS data and speed data are collected using speed camera. Model generation was done using statistical computing by using multi-linear regression. The model showed that curve details and speed reduction between successive features were strongly related to accident frequency. Sharper curves are more tend to accidents, and speed reduction is higher at curves with smaller radius. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.