Traffic lights aren’t an exception. Virtually unchanged for more than 100 years, modern American traffic signals have entered the age of machine learning. The result is a faster safer, safer, and green transportation system. Technology to prevent traffic signals, for example can assist drivers in avoiding an injury-causing collision with pedestrians. A system that combines traffic lights and e-bike/scooter sensor can automatically time stoppages so that they align with commuters’ daily schedules.
IoT sensors and connectivity technologies enable smarter traffic control systems that maximize energy efficiency by optimizing signal timings based on actual conditions. The data collected by sensors and cameras can be pre-processed on the device or transmitted to an infrastructure for traffic management, where it is integrated into AI-based algorithms. The result is more precise model and predictive analysis that could help avoid congestion, create schedules that align with public transit and reduce carbon emission.
These innovative technologies could transform urban transport systems. Smart sensors for e-bikes and scooters for instance, can detect and communicate the location of shared personal vehicles to make ride sharing more efficient. Micromobility payment systems however allow on-street parking and road toll payments with no requirement for changing the correct amount.
Smart traffic technology that is based on IoT can also improve the efficiency of public transit by allowing commuters to track trams and buses in real-time through live tracking apps. Intelligent intersection technology can prioritize emergency vehicles to help them reach their destination more quickly – an innovation that has already dramatically reduced crash rates in some cities.
technologytraffic.com/2020/05/21/the-benefits-of-using-modern-traffic-technologies-by-data-room