**2. Methodology**

The relevant literature on TSC was searched (in May 2021) using a detailed systematic review (SR). SR is a formal and standard protocol for performing a review study. To ensure that findings were reached in a valid and reliable manner, the study adopted a three-staged approach, i.e., i) planning, ii) execution, and iii) analysis. The planning stage involved defining the research scope and aims, setting the inclusion and exclusion criteria, and developing the review protocols. The execution stage involved a systematic search using relevant search strings. The relevant publications were meticulously selected by browsing through different electronic databases such as "Google Scholar," Science Direct," Wiley Online Library," "Scopus," "Web of Science," and "IEEE Xplore." To explore these databases, the following "Keywords" were used: "signalized intersections," "traffic congestion," "traffic signal control," "traffic signal timing optimization," "traffic control

### *Metaheuristics for Traffic Control and Optimization: Current Challenges and Prospects DOI: http://dx.doi.org/10.5772/intechopen.99395*

through metaheuristics," "intelligent traffic control," "dynamic traffic management," "traffic simulation and optimization," "multi-objective traffic control," etc. Titles, keywords, and abstracts of all the downloaded documents were reviewed to determine the appropriate selection of articles for the current study. Additional appropriate publications were added to the list by looking at the references selected

**Figure 1.** *Chronological distribution of indexed publications on traffic signal optimization using swarm intelligence and evolutionary computation techniques (period 2000–2021).*

publications. Publications were searched irrespective of publication year and the number of citations to have the maximum number for initial consideration. Duplicate articles found in various databases were also identified and removed. Non-academic publications, such as magazine articles, company reports, newspapers, presentations, and interview transcripts, were excluded. Finally, the analysis stage involved the classification, categorization, and summarization of the main theme of selected articles.

**Figure 1** presents the chronological distributions of shortlisted publications in which metaheuristics are used for solving traffic signal control optimization. It may be observed from the publications reporting in **Figure 1** that is there is a growing trend in the application of metaheuristics in the subject domain. **Figure 2** shows the percentage distribution of published studies in the area of traffic control optimization based on the type of metaheuristic applied. It may be observed from the Figure that the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Ant Colony Optimization (ACO) have been widely used for signal optimization.
