Prevention and Safety Strategies for Road Accidents by using Evolutionary Algorithms

The advancement of vehicle-integrated networking technology allows for the creation of new protocols and applications to enhance the effectiveness of Road Traffic Accident (RTA) support. When this technology is combined with smart applications, most of the judgments required to develop suitable sanitary resource sets may be automated, reducing the time between the accident and the stabilization and hospitalization of the injured passengers. However, establishing the ideal sanitary resource allocation is difficult since various purposes are mutually incompatible, such as improving assistance, keeping costs down, and balancing resource utilization. This study presents a method for allocating sanitary resources in traffic accidents. Our method is based on the implementation of Evolutionary Algorithms (EA), and it can provide a list of ideal solutions that consider the most important criteria. The proposed method is pushed to the limits in various vehicular contexts. The results indicate that a memetic variant of the Group Counseling Optimizer (GCO) algorithm is the most efficient way of selecting the optimal resource set. The proposed method reduces the death ratio with the penalty of resource overuse and service cost and increases assistance quality in Punjab, Pakistan.