Case studies

Oxford Bus Company uses CitySwift to identify and implement high impact bus priority measures


  • Reduced vehicle requirement by 1 bus
  • 10% - 29% reduction in bus journey time
  • £140k in cost savings per operator

Oxford Bus Company is an award-winning bus operator regularly commended for its achievements in enhancing customer experience and community development. In 2019 the operator was named the UK Large Bus Operator of the Year. The Oxford Bus Company runs the BROOKESbus service in partnership with Oxford Brookes University, and the popular park&ride service which connects four car parks to the city centre.

Driving Modern Public Transport Networks

In March 2021, the National Bus Strategy for England was launched by the Government, aiming to improve the bus network quality and efficiency by creating “a virtuous circle: increasing usage, but also reducing operating costs so better services can be sustained without permanently higher subsidy”.

The key to achieving this goal was more ambitious bus priority measures. Partnering with CitySwift, Oxford Bus Company addressed this challenge through accurately identifying where the largest impact could be made.

CitySwift’s Decision Intelligence platform offers bus network providers the precise data and insights they need to digitally transform and grow their networks through productivity gains, improved service performance, and passenger experience. CitySwift's team blends real-world bus industry experience with a deep knowledge of data science to give bus networks the best of both worlds.

This partnership enabled Oxford Bus Company to pinpoint bus priority measures that would result in a more efficient service and significant cost savings that could be reinvested into improving other areas of the network.

Creating a More Efficient Urban Future

Using CitySwift Evolve Oxford Bus Company analysed free flowing traffic conditions during February 2021's lockdown, and demand levels prior to the Covid-19 pandemic, to generate a scenario data model. This model predicted the likely impact of bus priority measures being introduced on a specific corridor, providing "free flow" traffic conditions. With this data, Oxford Bus Company produced new timetables with optimised journey times, achieving improved efficiency, cost savings and service enhancements.