Traffic lights aren’t the only exception. For the most part, unchanged for over 100 years, the current American traffic signals have entered the era of machine learning. The result is an efficient, safer, and more eco-friendly transportation system. Traffic signal preemption technology for instance will help drivers avoid a life-threatening collision with pedestrians. A system that combines traffic lights and e-bike/scooter sensors can automatically time stops so that they align with commuters’ travel schedules.
IoT sensor and connectivity technologies enable intelligent traffic control systems that maximize energy efficiency by optimizing signal timings based upon real-time conditions. The data gathered from sensors and cameras can either be processed within the device or sent to an infrastructure for traffic management and then integrated into AI algorithms. The results are more precise analysis and predictive models to reduce congestion, align public transit schedules and reduce carbon emissions.
These advanced technologies can revolutionize urban transportation systems. Smart sensors for e-bikes and scooters for instance, can identify and transmit the location of shared vehicles to make ride sharing more practical. Micromobility payment systems however, enable on-street parking or road tolls without the requirement for changing the correct amount.
IoT smart traffic technology could also increase the efficiency of public transport making it easier for commuters to track buses and trams in real-time by using live tracking apps. Intelligent intersection technology can prioritize emergency vehicles, allowing them to get to their destination quicker – an innovation that has already dramatically reduced the rate of crashes in a few cities.