In everyday routines, there are multiple situations of high traffic congestion, especially in large cities. Traffic light timed regulated intersections are one of the solutions used to improve traffic flow without the need for large-scale and costly infrastructure changes. A specific situation where traffic lights are used is on single-lane roads, often found on roads under maintenance, narrow roads or bridges where it is impossible to have two lanes. In this paper, a simulation-optimization strategy is tested for this scenario. A Particle Swarm Optimization algorithm is used to find the optimal solution to the traffic light timing problem in order to reduce the waiting times for crossing the lane in a simulated vehicle system. To assess vehicle waiting times, a network is implemented using the Simulation of Urban MObility software. The performance of the PSO is analyzed by testing different parameters of the algorithm in solving the optimization problem. The results of the traffic light time optimization show that the proposed methodology is able to obtain a decrease of almost 26% in the average waiting times.

Smart cities aim to rise strategies that reduce issues caused by the urban population growth and fast urbanization. Thus, traffic light optimization emerges as an important option for urban traffic management. The main goal of this study is to improve traffic light management at a specific intersection, in the City of Guimarães (Portugal), where high-intensity traffic and an active pedestrian area were observed, generating traffic queues. To achieve the goals, a simulation-based optimization strategy using the Particle Swarm Optimization combined with the Simulation of Urban Mobility software was used to minimize the average waiting time of the vehicles by determining the optimal value of the traffic light cycle. The computational results showed it is possible to decrease by 78.2% the average value of the waiting time. In conclusion, by better managing the traffic light cycle time, traffic flow without congestion or queues can be achieved.

The significant increase in the number of vehicles in urban areas emerges the challenge of urban mobility. Researchers in this area suggest that most daily delays in urban travel times are caused by intersections, which could be reduced if the traffic lights at these intersections were more efficient. The use of simulation for real intersections can be effective in optimizing the cycle times and improving the traffic light timing to coordinate vehicles passing through intersections. From these themes emerge the research questions: How are the existing approaches (optimization techniques and simulation) to managing traffic lights smartly? What kind of data (offline and online) are used for traffic lights optimization? How beneficial is it to propose an optimization approach to the traffic system? This paper aims to answer these questions, carried out through a bibliometric literature review. In total, 93 articles were analyzed. The main findings revealed that the United States and China are the countries with the most studies published in the last ten years. Moreover, Particle Swarm Optimization is a frequently used approach, and there is a tendency for studies to perform optimization of real cases by real-time data, showing that the praxis of smart cities has resorted to smart traffic lights.