Global Public Transit Index
Comparing On-Time Performance around the world.
The Mosaiq Global Public Transit (PT) Index uses publicly available data to build referenceable insights and benchmarks for public transit authorities and operators around the world. It will continue to build on its On-Time Performance base to become a trusted reference to make public transport more efficient, more effective and more sustainable.
Latest edition of the Global PT Index
In this first release of the Global PT Index we review data from eight locations around the world and map them to six different scenarios as to how they define early, on-time and late performance.
There are some significant differences between the best in On-Time Performance including those that leave too early or too late. It also gives insight into the wide variance of what is ‘on-time’ around the world - which will be of as much interest to those travelling on the buses, as those who run them.
The data covers a four week period and it is our intention to provide quarterly updates to the locations we currently track as well as adding additional locations and insights over time.
Learn more about the data source
For this first report we put the spotlight on eight locations and what they considered to fall within the 'on-time threshold', before a bus is determined to be early or late. This created six ‘Scenarios’ that we could then apply across the various locations.
The Index is based on publicly available data feeds and was focused on first-stop performance. We ran the data for a four week period (16 August to 13 September) in all locations except Tokyo for which we have three weeks data. We then applied that data against the thresholds defined across the six scenarios representing OTP for the represented locations.
We only used data from trips where we were able to match real time data to the schedule. We then classified as ’not detected’ those trips for which we could identify the vehicle later in the journey but could not observe its first stop performance.
The locations were selected as being geographically disperse, having publicly available data feeds and a relatively comparable number of trips tracked over the period.
We are looking to add more locations and/or insights to our Index - please tell us where or what else to include next time.
