2016/132 - Measuring perceived impact of schedule deviation in public transport
Frédéric Roulland, Luis Ulloa, John Handley
TRB, Washington, USA, 08 - 12 January 2017
This paper illustrates new opportunities offered by using massive user data in transportation applications through an example of analytics for quality of service of public transit. In this method we propose new metrics for understanding the real impact of public transit service schedule deviation on traveler’s perception of the quality of service. These metrics are computed at a user centric level and use different sources of passengers’ data instead of traditional vehicle location tracking systems data. We describe the method used to compute the metric and how it can be put into practice in order to give new insights for analysts. We show experimental results on real transit data from Nancy, France.