Customer Journey Time Metrics for New York City Bus Service using Big Data

Abstract

As data collection for public transportation improves and customers’ appetite for information grows, there has been a growing interest in performance measurement systems that better reflect customer experience and quantify the impacts of service while accounting for ridership. A fair amount of research has been dedicated to developing and refining these kinds of metrics, with a particular focus on comparing customers’ expected and actual waiting time on train platforms or at bus stops. Despite this, only a limited number of transit agencies have implemented such measures. This paper presents a set of metrics developed by the Metropolitan Transportation Authority (MTA) that calculates the additional time customers spend waiting for and riding buses in excess of the schedule, termed additional bus stop time (ABST) and additional travel time (ATT) respectively. Trip time performance, termed customer journey time performance (CJTP), is also computed. The methodology leverages MTA’s origin–destination (OD) ridership model and bus location data to calculate these values for each individual passenger. Measuring at the passenger level means that impacts of service delays or changes can be weighted by the number of passengers affected, unlike past bus-level measures. This enables the design of service management techniques that benefit the most riders possible. The form of the metrics, which puts service impacts in easy-to-understand terms that reflect actual customer experience, likewise provides the opportunity to better engage with customers. MTA is among the first to make these metrics regularly available to the public, and the first to publicly report them for buses.

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