Everything’s getting smarter these days including traffic signals. Almost unchanged for more than 100 years, the current American traffic signals are now undergoing machine learning. The result is a more efficient, safer, and more environmentally friendly transportation world. Technology for preemption of traffic signals, for example can assist drivers in avoiding a life-threatening collision with pedestrians. A system that incorporates traffic lights and e-bike/scooter sensors will automatically time stoppages so that they align with commuters’ schedules of travel.
IoT sensor and connectivity technology enables more intelligent traffic control systems that maximize energy efficiency by optimizing signal timings in real time. The data from cameras and sensors can be processed in the device or sent to an infrastructure for traffic management and then integrated into AI algorithms. The result is a more precise model and predictive analysis that will help prevent congestion, create schedules that align with public transportation and reduce carbon emissions.
These advanced technologies could transform the urban transport system. Smart sensors for e-bikes and scooters for instance, could detect and communicate the location of shared personal vehicles to make ride sharing more efficient. Micromobility payment systems, on the other hand allow on-street parking and road tolls, without the requirement for accurate change.
Smart traffic technology that is based on IoT could also increase the efficiency of public transit which allows commuters to follow trams and buses in real-time through live tracking apps. Intelligent intersection technology can assist prioritize emergency vehicles to ensure they arrive at their destination quicker – a breakthrough that has already reduced the number of crashes in certain cities.