Smart traffic management is a sector projected to grow, as a combination of tools such as AI, machine learning (ML), vision systems and cameras are ostensibly paving the way for a future where traffic flows smoothly and congestion is a thing of the past.
According to information provided by the European Automobile Manufacturers’ Association (ACEA) in 2023, in 2022 85.4 million cars were produced, marking an increase of 5.7% compared with 2021 figures. And the same association reports that the average car in the EU emits 110g Co2 per km. In short, smart traffic management is necessitated by a growing number of cars on the road and growing population numbers to manage flow and assist with reducing emissions.
Smart traffic management does more than this, though. It adopts a data-driven approach where cities and transport planners are provided with detailed information on anything from times of heavy congestion to detecting poor driving behaviours. Being provided with this kind of information facilitates better decision-making and an understanding of how to address an environment – for instance, a busy junction – to reduce congestion.
A study by Juniper Research from November 2023 anticipated spend on smart traffic management to increase by 75% by 2028; a total of $10.6 billion. It also found that deploying traffic analysis and systems is becoming crucial to avoid costs incurred further down the line from having to restructure.
“Cities need to avoid solutions that will likely become obsolete quickly, or result in vendor lock-in. By opening their process to a wide pool of vendors and developers, cities will encourage innovation and interest from a variety of stakeholders and partners,” explained Cara Malone, Research Author.
Use cases for smart traffic management
Around the globe, smart traffic management systems are being implemented for a range of reasons, including tackling heavy traffic and the subsequent emissions, monitoring poor driving behaviours and improving responses to accidents. As previously reported by IoT Insider on IoT innovations driving sustainability, the application of IoT systems to smart traffic management is helping with improving traffic flow and subsequently cutting down on fuel consumption and pollution.
From Graz in Austria, to Amsterdam in the Netherlands and beyond, device manufacturers, OEMs and cities are all envisioning what smart traffic management looks like.
Over in Graz, Austria, a smart traffic monitoring platform (TMP) powered by LMT sought to gather real-time data on an intersection that experienced heavy traffic, using a video system equipped with Edge computing and AI algorithms capable of differentiating between different vehicles like cars, motorbikes and lorries, and individuals. Data provided was on traffic volume and traveller types as well as illegal and poor driving.
At the time of the announcement, Gints Jakovels, Computer Vision & Solutions Manager at LMT said: “Having access to accurate data is key to driving any meaningful change.”
This approach to smart traffic management can be seen replicated elsewhere. The introduction of a FLIR camera system for traffic monitoring a couple of months ago uses AI models trained on FLIR-captured images collected around the world, in order to ensure reliable data collection. Using 30 years worth of imagery for its AI algorithm was “unmatched,” according to Gil Marques, President of Tacel.
The cameras can predict vehicle speed and trajectory alongside poor driving behaviours such as tailgating, sudden lane changes or wrong-way drivers, and are housed in stainless steel casing to protect the camera against a range of weather conditions.
Conclusion
Forecasts, predictions and use cases: all point to the view that investing in smart traffic management systems is becoming a must-have, rather than a nice-to-have. Not only does investing in these systems improve flow, reduce congestion and subsequent emissions, but it avoids incurring costs later down the line when a city may have to redo a junction to address traffic.
