Analysis of Traffic Accidents in Terms of Cost and Complexity Depending on the Number of Vehicles
AbstractTraffic accidents are a critical problem that causes significant economic losses on a global scale and threatens human life. Increasing vehicle density is one of the main factors that directly affects the frequency and severity of accidents. Therefore, it is important to examine the effect of the number of vehicles on traffic accidents in detail and to develop strategies to increase traffic safety. In this study, the dynamics of accident occurrence depending on the number of vehicles were analyzed using data from past accidents and the cost and complexity of accidents were modeled. Statistical analyses and machine learning algorithms were used in the modeling process. In line with the findings obtained, a risk analysis model that estimates the probability of traffic accidents was developed and proactive measures were presented for traffic management systems. In addition, drivers and relevant public authorities were informed with risk maps created depending on traffic density, and especially the areas where accidents occur most were determined and possible measures were optimized. Thus, a safer and more sustainable transportation infrastructure was contributed to for urban and intercity roads.