Traffic lights aren’t an exception. The American traffic lights which have remained virtually unchanged for over 100 years are now being controlled by machine learning. The result is a more efficient more sustainable, safer and greener transport world. Technology for preemption of traffic signals for instance can help drivers avoid the possibility of a fatal collision with pedestrians. A system that integrates traffic signals and an e-bike/scooter sensor will automatically time stoppages so that they align with commuters’ daily schedules.
IoT sensor and connectivity technologies enable smarter traffic control systems to maximize energy efficiency by improving signal timings according to the current conditions. The data collected by sensors and cameras can be pre-processed by the device, or sent to a traffic management hub, which is then integrated into AI-based algorithms. The result is a more precise modeling and predictive analysis that will help prevent congestion, create schedules that align with public transit and reduce carbon emission.
These smart technologies are able to transform urban transport systems. Smart sensors for e-bikes and scooters for instance, can identify and share the location of shared vehicles to make ride-sharing more efficient. Micromobility payment systems, on the other hand allow on-street parking and road tolls with no requirement for accurate change.
Smart traffic technology based on IoT can also enhance the efficiency of public transit, allowing commuters to track buses and trams in real time by using live tracking apps. Intelligent intersection technology can assist prioritize emergency vehicles so that they get to their destination faster – a breakthrough that has already reduced crash rates in certain cities.
