Next Chapter for Smart Cities Is Practical, Equitable

Source: Gov Tech Published: June, 2020

Like so many American cities these days, Pittsburgh finds itself suffering from significant growth in traffic and road congestion. By 2017, drivers were spending an extra 81 hours commuting to work each year. To ease the problem, the city worked with Carnegie Mellon University to build a traffic signal system that ran on artificial intelligence instead of relying on pre-programmed signal cycles.

The results were soon apparent. For the initial 50-intersection project, the system reduced travel time by 25 percent, braking by 30 percent and idling by more than 40 percent. The AI software detects traffic and creates a predictive model that generates a signal timing plan in real time.

While drivers were happy, pedestrians let the project team know that they felt left out of the picture. So, the researchers responded by tweaking the system to minimize wait time for pedestrians at lights. Meanwhile, researchers and students at Carnegie Mellon set to work on a side project to make a mobile phone app to communicate with the lights for people with disabilities who need more time to cross the street.