Due to urbanization, population growth, and the proliferation of vehicles (motorized and non-motorized), the complexity of traffic accident situations has increased. The purpose of this research is to examine NH-40 highway traffic accidents using a multi-method approach. Using the Quantum of Accident approach and the Accident-Prone Index approach, the study identifies high-risk sites, collects accident data, analyzes preliminary data, and selects highway segments. Corrective actions are suggested to lessen the likelihood of accidents after site inspections. To forecast the likelihood of accidents given certain traffic and road variables, sophisticated modeling approaches including Poisson Regression, Multiple Linear Regression, and Simple Linear Regression are used. On top of that, we poll people to find out how they feel about road safety and what they do while driving. A prototype accident-avoidance system that makes use of current technology like sensors and microcontrollers is also investigated in the research. The results high-light the significance of combining accurate data gathering, advanced modeling, and technology advancements to improve road safety and decrease accident rates.