Everything is getting smarter these days including traffic signals. Virtually unchanged for more than 100 years, today’s American traffic signals have entered the era of machine learning. The result is an efficient, safer, and more sustainable transportation system. Technology for preventing traffic signals for instance can assist drivers in avoiding an injury-causing collision with pedestrians. And a system that integrates traffic lights and e-bike/scooter sensors will automatically time stops to align with commuters’ travel plans.
IoT sensors and connectivity technologies enable smarter traffic control systems to maximize energy efficiency by optimizing signal timings based on real-time conditions. The data from sensors and cameras can either be pre-processed in the device itself or transmitted to a hub for traffic management and then integrated into AI algorithms. The results are more precise analysis and predictive models to avoid congestion, set the schedules of public transportation and reduce carbon emissions.
These smart technologies could transform urban transport systems. Smart sensors for e-bikes and scooters for instance, could detect and transmit the location of shared vehicles to make ride-sharing more practical. Micromobility payment systems on the other hand allow on-street parking and road tolls, without the need for a change in the right amount.
Smart traffic technology that is based on IoT can also improve the efficiency of public transit by allowing commuters to track buses and trams in real time by using live tracking apps. Intelligent intersection technology can help prioritize emergency vehicles so they can get to their destination more quickly which has already reduced crash rate in certain cities.