How a city increased public transport reliability by 30%

By GovInsider

Steps on using location data to plan ahead.

A city has increased the reliability of its public bus services by 30% using data analytics.


This case study shows how the city monitors the position of every bus in the city, predicting when they will arrive at stops and which routes will need more buses. The predictions are automatically verified, providing commuters with accurate information on bus arrival times. The city’s bus operator is also sharing transport data with other city departments to improve public safety, and road conditions and parking plan.


If you would like to know more about how this city provided more reliable buses, download the case study from Microsoft: