Why congestion happens
Traffic in big cities tends to cluster around core activity hubs. In many places, the morning rush from suburbs into the center and the evening return trip create a peak that far exceeds road capacity. This pattern is common in major metros and is reinforced by a mix of structural limits, vehicle volume, and recurring events like weather-related lane reductions or road repairs. Other factors include driver behavior and gaps in driving culture, which can worsen congestion even when infrastructure is adequate.
Additional contributors include limited road capacity, mismatched vehicle numbers, and seasonal or temporary disruptions. Understanding these dynamics is essential for any plan to improve flow, as real-time data and coordinated response can dramatically reduce delays when used effectively.
What is it
Intelligent transport systems (ITS) roll out in two main phases: creating a digital backbone and gathering and interpreting traffic data. First, high-precision cameras, radars, and lidar devices are deployed along roadways. They measure speeds on segments, following distances, routes, intersections, delays, and lane usage.
With data collected and organized, specialists gain a broader view of the city’s traffic health. Decisions follow from this picture: traffic signals can be re-timed, speed limits adjusted, or lanes reopened to improve flow. The goal is to compute the actual impact of any regulation change before it is implemented, something humans alone cannot reliably predict at scale.
How ITS helps unload cities
ITS adoption has grown beyond its early focus on central districts. In large capitals, these systems cut congestion, optimize public transport routes, and provide timely alerts to drivers and riders. The urban experience is informing other cities as well, with real-time monitoring and adaptive signal control becoming more common.
One illustrative example is a city where ITS began with a data center and a traffic control center in 2021–2022. Real-time traffic monitoring enabled adaptive signal operations and continuous road status updates around the clock. Implementations on main corridors used a directional “green wave” approach, aligning signal timings to expected flows so morning trips to the center move smoothly and evening trips return with minimal stops.
Early results showed measurable gains: traffic capacity on key streets increased, jam times shortened, and overall congestion declined on central corridors. Similar progress is being reported in nearby urban regions, where ITS efforts focus on shortening travel times and improving reliability for commuters and freight alike.
In other districts, ITS maturity has progressed to broader regional rollouts. Local authorities partner with technology groups to prepare road networks in multiple towns, then expand to neighboring communities. The impact is consistently a reduction in average travel time, fewer hours stuck in traffic per day, and a notable rise in network capacity across the broader street grid.
Why ITS is not a panacea, but the best tool
Experts emphasize that ITS has technical boundaries. It does not erase the root causes of congestion, nor does it overhaul city designs overnight. Even with advanced analytics and artificial intelligence to predict and advise, ITS cannot change daily commuting patterns, city layouts, or driving culture by itself.
Expert opinion
Analysts stress that solving transport challenges requires a holistic approach. Data collection, analysis, planning, and careful implementation must be followed by ongoing evaluations of effectiveness. ITS is a powerful tool for improving safety and comfort on the road, but its success depends on human coordination and continuous optimization. The future of urban mobility increasingly leans on digital solutions as part of a broader strategy.