Analysis of road accidents due to obstruction in sight distance caused by foggy weather using Geographic Information System (GIS) and Artificial Neural Network (ANN) at Jumja along Thimphu-Phuentsholing Highway (Asian Highway 48)

Abstract

Road accident analysis is a crucial technique for determining what elements contribute to collisions and can help lower the accident rate. The consideration of sight distance is a crucial component of highway geometric design in order to guarantee effective traffic operations with the highest level of safety at an affordable price. Road accidents frequently result from reduced visibility caused by foggy weather, hence there is increased interest in studying this issue. This study aims to determine and correlate sight distance, fog blockage, and their effects on traffic accidents at Jumja along Thimphu-Phuentsholing Highway (Asian Highway 48). Data gathering and prediction was aided by the usage of Geographic Information Systems and Artificial Neural Network technologies. Temperature, relative humidity and wind speed for seven years from 2017 to 2023 were considered for fog occurrence to train Artificial Neural Network. Visibility was trained and predicted for summer and winter seasons since the occurrence of fog is prevalent during these seasons. As a result, a correlation value R of 0.998 was found, proving the findings to be almost accurate. This study offers a thorough investigation of how sight distance contributes to traffic accidents at Jumja region. A conclusive finding addressing the significance of sight distance as a contributing factor to traffic accidents due to fog invisibility along Jumja region was made after completion of this study.