Using Machine Learning to Predict City Traffic Activity
A Complexity Science Hub researcher has successfully used a new machine learning model to predict traffic activity in different zones of cities. The model was tested using data from a main car-sharing company in Italy as a proxy for overall city traffic.
Understanding how different urban zones interact and how that influences traffic activity can help avoid traffic jams, and enable more targeted responses from policy makers—such as local expansion of public transportation.
The researcher hopes that this approach to predicting traffic activity can be applied in other cities and regions, and further their understanding of traffic activity in urban zones.
https://www.lifetechnology.com/blogs/life-technology-technology-news/predicting-city-traffic-using-a-machine-learning-model
Buy SuperforceX™
