technologytraffic.com/2021/12/29/generated-post-4/
Traffic lights aren’t an exception. Virtually unchanged for more than 100 years, the current American traffic lights have entered the era of machine learning. The result is an efficient more sustainable, safer and greener transport world. Preemption of traffic signals, for example can assist drivers in avoiding a potentially life-threatening collision. A system that incorporates traffic light and e-bike/scooter sensors can automatically time stops to align with commuters’ schedules.
IoT sensors and connectivity technologies allow more intelligent traffic control systems to maximize energy efficiency by improving signal timings according to the current conditions. The data that cameras and sensors can be pre-processed on the device or transmitted to an infrastructure for traffic management, where it is integrated into AI-based algorithms. The results are more precise analysis and predictive modeling to avoid congestion, coordinate the schedules of public transportation and reduce carbon emissions.
These advanced technologies are able to transform urban transport systems. Smart e-bike and scooter sensors, for instance, can identify and transmit the location of shared personal vehicles to facilitate more convenient ride-sharing micromobility payment systems can facilitate street parking and road-toll payments without the need for a changes.
Smart traffic technology that is based on IoT can also boost the efficiency of public transit and allow commuters to track buses and trams in real-time by using live tracking apps. And intelligent intersection technology can prioritize emergency vehicles to assist them reach their destination more quickly – an innovation that has already dramatically decreased crash rates in certain cities.
