Traffic Signal Timings optimization Based on Genetic Algorithm and Gradient Descent

Traffic congestions are a recurring problem that results in significant losses both financially and environmentally. optimizing traffic signal timings is one of the most cost-effective ways to mitigate such effects. optimization of traffic signal timings capable of minimizing congestion is, however, computationally expensive. Research needs to be conducted to develop algorithms capable of better optimization using fewer computational resources. This paper presents a novel approach to traffic signal optimization that combines genetic algorithms and a gradient descent like algorithm to obtain optimized traffic signal timings. The genetic algorithm is used to arrive at a starting point for gradient descent; gradient descent is then used to obtain further improvement.