As the world becomes increasingly urbanized, cities are facing a growing challenge of managing traffic congestion. Traffic jams not only cause frustration and delays for commuters, but also result in increased air pollution and carbon emissions. In order to address this issue, smart cities are turning to advanced technologies such as artificial intelligence (AI) and quantum computing to optimize traffic signal timings and reduce congestion.
Traditional traffic signal optimization methods rely on fixed timing plans that are based on historical traffic patterns. However, these plans are often not flexible enough to adapt to changing traffic conditions in real-time.