Adaptive Genetic Algorithm for Reducing Average Waiting Time for Road Traffic Signals

Addressing the important need to reduce average waiting times at road traffic signals is crucial, this research offers an optimal strategy targeted at improving the traffic flow efficiency. However, despite its success in lowering wait times, the suggested system has difficulties in dealing with unanticipated traffic spikes. The work proposes an Adaptive Genetic Algorithm (AGA) to reduce traffic waiting time and incorporates complex algorithms and modules along with heuristic algorithms and various sorts of crossovers to achieve notable outcomes to minimize traffic congestion. The performance of AGA was evaluated using the Simulation for Urban MObility (SUMO). The simulation included a four-way junction in which a network with default traffic signal information was simulated and their modified phase time using AGA in network waiting time was also simulated and analysed. The analysis revealed improved results in optimization, with considerable gains produced by combining either of the crossover approaches that have been utilized.