A Survey on Implementation of Swarm Evolutionary Algorithms to Vehicular Communication

Rapid metropolitan city development and population growth have resulted in an exponential increase in the number of cars used by commuters. The already overwhelming issue of traffic congestion is being made worse by this. Highway construction additions are no longer appropriate short-term, expensive, or short-sighted solutions. Concentrating on the frequently utilized controlling traffic signals and fewer time schedules is one efficient approach to allocating road resources. It may not be the simplest or practical approach to find a suitable or optimum plan for the prior by using brute force. Adapti ve and swarm intelligence methods are two examples of algorithms that were influenced by nature. Numerous of these methods have been applied during the past two decades to various smart city applications, such as controlling traffic signals (CTS). The use of swarm and adaptive intelligence methods to CTS is thoroughly reviewed in this work. The collection of objective(s), issue modeling, choice variables, optimization, and the encoding solution is used to classify the work that was surveyed. The study suggests interesting future directions for research and examines where research is headed is heading based on Genetic Algorithm (GA) discovered by the performed review.