Euichul Kim, Vice President of Intelligent Transportation Systems at bitsensing makes the case for AI-powered radar technology in transforming traffic management
Despite technological innovation happening at breakneck speed across pretty much every sector imaginable, cities continue to struggle with one of the biggest urban challenges: traffic congestion. Balancing traffic congestion, road safety, and environmental impact on our roadways is no easy feat, yet failing to address these issues comes at a high cost for both cities and residents alike.
While legacy traffic management systems are struggling to meet the challenge, radar, powered by artificial intelligence (AI), is proving to be the solution that with revolutionise urban mobility. This all-weather, high-precision sensor enables real-time traffic patten analysis, predictive congestion modeling, and automated incident detection, to usher in the kind of smart traffic management that will not only get the buy-in of city leaders, but also everyday commuters.
What congestion and pollution are doing to us
Before diving into the technology, it’s important to set the stage for why it’s so important that we focus on smart traffic management – not just for the sake of our cities, but for public health and the well-being of those who inhabit them. First off, it’s critical to note that the world is rapidly urbanising. According to the United Nations, over 55% of the global population lives in urban areas, a number expected to rise to 68% by 2050. More people moving to cities undoubtedly means more traffic. But what exactly is all this road congestion doing to us?
The effects are not just relegated to being late to work every once in a while, but far-reaching into our physical and mental health. The World Health Organization (WHO) reports that air pollution from traffic contributes to 4.2 million premature deaths globally each year. On top of the loss of life from dirty air, we are also losing precious time while stuck in the car. According to the INRIX Global Traffic Scorecard for 2024, London drivers lost an astonishing 156 hours each year due to traffic, while New Yorkers were not that far behind with 117 hours.
Once we pull into our driveway, the impact of driving isn’t over either. According to the American Psychological Association, prolonged traffic exposure is linked to increased stress levels – with regular commuters experiencing a 20% rise in cortisol levels, which can lead to long-term mental health effects. The longer we are in the car, idling and waiting to get to our destination, the more anxious, annoyed, and generally uneasy we feel.
All this points to one solution: we need to drive and guide traffic smarter, so that we spend less time behind the wheel and more time enjoying our lives.
How AI-powered radar is filling the gaps in legacy smart traffic solutions
Why haven’t legacy smart traffic solutions been able to solve for the massive, cultural problems surrounding traffic congestion? The problems are spread across the way the collect data all the way to how they use it to understand the nature of traffic.
Lacking real-time insights and the ability to predict traffic flow
The first thing to note here is that legacy systems rely on static collection methods, such as capturing vehicle counts and traffic flow after the fact. Beyond this, there’s a lack of integrated AI-driven analytics, meaning that traffic signals are rendered reactive rather than predictive.
Radar solutions, combined with Edge computing, empower solutions to have real-time data processing, which enables instant traffic pattern analysis and automated congestion management.
When thinking about this from a logistical perspective, it’s the only approach that makes sense, as the success of a traffic management solution is tethered to its ability to solve problems before they happen. For example, a smart solution should be able to identify emerging bottlenecks and bumper-to-bumper traffic points before they get out of hand and adjust the traffic signals in the surrounding areas to optimise traffic flow.
Older monitoring systems have a “weather problem”
Cameras and inductive loops have long been the trusted technologies supporting traffic monitoring systems. However, both struggle with accuracy – especially in bad weather and lighting conditions. This means that unreliable traffic data is being funneled into the traffic control system whenever there’s rain, fog, or snow. Similarly, inductive loop sensors that are typically installed under the roadway surface, are easily damaged overtime with regular road repair and can become quite costly for cities.
AI-powered radar, on the other hand, offers all-weather detection, and precision tracking across multiple lanes of traffic without any of the vulnerabilities of cameras or inductive loops.
Another major challenge with traditional traffic monitoring systems is data fragmentation, resulting from different sensors and control centers fail to communicate effectively with one another. Without this, it’s difficult to make the solution work city-wide and effectively manage traffic flow. AI-powered radar systems, however, are specifically designed to integrate with existing infrastructure, consolidate data from various different sources, and funnel that information into a traffic management solution. This allows city planners to utilise all their technology investments in smart traffic to the best of their ability, justifying use of budget and solving the issues they set out to in the first place.
Traffic management is a public health issue
From economic cost to the degradation of our mental and physical health, traffic should be considered a public health crisis. AI-powered radar is poised to change the face of traditional traffic management, solving for the pain points of yesterday’s systems while providing a much clearer, real-time, and predictive analysis of the roadway. It’s this approach that not only brings to fruition next-generation traffic management, but also can eradicate the negative consequences on our health and wellbeing simply from getting in our cars and heading from point A to point B.
Euichul Kim is the Vice President of Intelligent Transportation Systems (ITS) at bitsensing, where he drives innovation and spearheads the company’s global expansion in smart mobility solutions. With over 15 years of experience in operations, business development, and project management, Euichul has played a pivotal role in the successful deployment of bitsensing’s TraXight solution in cities worldwide, helping to revolutionise urban traffic management.
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