Urban congestion is a pressing challenge, driving up emissions and compromising transport efficiency. Advances in big-data collection and processing now enable adaptive traffic signals, offering a promising strategy for congestion mitigation. In our study of China’s 100 most congested cities, big-data empowered adaptive traffic signals reduced peak-hour trip times by 11% and off-peak by 8%, yielding an estimated annual CO₂ reduction of 31.73 million tonnes. Despite an annual implementation cost of US$1.48 billion, societal benefits—including CO₂ reduction, time savings, and fuel efficiency—amount to US$31.82 billion. Widespread adoption will require enhanced data collection and processing systems, underscoring the need for policy and technological development. Our findings highlight the transformative potential of big-data-driven adaptive systems to alleviate congestion and promote urban sustainability. Big-data empowered traffic signal control in China can reduce vehicle trip times, creating potential reduction of 31.73 million tonnes (Mt) of CO2 emissions annually and US$31.8 billion benefits per year.
Did you read the article? Standard traffic cameras or sensors are all you need to implement this. And yes, most places have the technology already in place to do most of it. You just need to add the part to network them and control the lights.
But they already have sensors. That‘s not what China differentiates from the rest here.
Did you read the article? Standard traffic cameras or sensors are all you need to implement this. And yes, most places have the technology already in place to do most of it. You just need to add the part to network them and control the lights.