Traffic lights are not an exception. The American traffic lights, which have remained virtually unchanged for over a century now are now dependent on machine learning. The result is a more efficient safe and environmentally friendly transportation world. Traffic signal preemption technology for instance will help drivers avoid the possibility of a fatal collision with pedestrians. A system that incorporates traffic lights and e-bike/scooter sensors can automatically click this time stops so that they align with commuters’ travel schedules.
IoT sensor and connectivity technology helps to build smarter 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 the traffic management hub which will then be integrated into AI algorithms. The result is a more precise modeling and a predictive analysis that can help to avoid congestion, create schedules that align with public transportation and reduce carbon emissions.
These smart technologies can transform urban transport systems. Smart e-bike/scooter sensors, for instance, can identify and transmit the locations of personal vehicles that are shared to make it easier to share rides, micromobility payment systems can facilitate street parking and road toll payment without the need to change.
Smart traffic technology that is based on IoT can also boost the efficiency of public transportation which allows commuters to follow buses and trams in real time via live tracking apps. Intelligent intersection technology can assist prioritize emergency vehicles so that they get to their destination faster which has already reduced the number of crashes in some cities.