In this paper we use large-scale mass transit data to improve the journey time performance
measurement of urban bus systems. For low frequency bus services, the application of ontime performance (OTP) metrics, particularly the location and number of stops to sample,
varies greatly across operators, which can lead to biased estimates. In this paper, we aim to
address sampling disparity, and propose a new statistically robust sampling scheme to ensure
representative, non-biased, and comparable measurement of route level on time performance
(OTP) which enables the inclusion of operators with sparse data in benchmarking activities.
We use automated vehicle location data and analyse 59 unique low frequency route-direction
data sets from 9 international bus operators. Across all route-direction data sets, an average
of 28% of stops are required to be sampled under the defined sampling scheme to achieve a
95% confidence level of sampling the route-level mean within a ± 5% range of accuracy. By
including data on additional routes, the analysis can be further refined and generalised to
enable progressive improvement of inter-operator comparability and benchmarking.