Intelligent Traffic Signal System Market Size

Intelligent Traffic Signal System Market Size

The global intelligent traffic signal system market size was valued at USD 5 billion in 2024 and is projected to grow at a CAGR of 10.2% between 2025 and 2034. Technological advancements are driving the growth of the market by improving the efficiency and adaptability of traffic systems. The use of AI and ML enables traffic signal systems to process real-time data, predict traffic patterns, and adjust signal timings based on current conditions. This helps reduce congestion, cut delays, and enhance traffic flow.

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Additionally, IoT devices, such as connected sensors, cameras, and traffic lights, allow continuous traffic monitoring. Through Vehicle-to-Infrastructure (V2I) technologies, these devices enable communication between vehicles and traffic signals, allowing signals to prioritize emergency vehicles, public transport, or congested areas, thereby improving traffic management.
 

For instance, in October 2024, SRL Traffic Systems announced of launching its new TOPAS-compliant portable traffic signal, named UltraLight, at the Highways UK event. This innovative product has achieved compliance with the TOPAS 2540A standard, which is increasingly required in Intelligent Transport System (ITS) contracts. UltraLight is compatible with SRL's Solar Plus technology, enabling users to harness solar energy and reduce their carbon footprint
 

Urbanization and increasing traffic congestion is another major driving factor of this market. As cities worldwide face rapid population growth and urban expansion, the number of vehicles on the road continues to rise, leading to more congestion, longer commutes, and inefficient traffic flow.
 

Traditional traffic management system often fails to address these challenges, resulting in traffic jams, higher emissions, and safety risks. Intelligent traffic signal system, which use real-time data and adaptive signal control, provide solutions by optimizing traffic flow. These systems adjust signal timings based on factors like traffic volume, weather conditions, and accidents, helping to reduce delays and improve road safety.