It matters how transit agencies measure their own performance, not only internally but also for their riders. These measurements help agencies form the basic understanding of how reliable their services are and help them identify what needs to be improved.
In a post today, transit advocacy and research organization TransitCenter notes how New York’s MTA could change how it measures its subway performance in order to provide more clarity. Zak Accuardi writes that the MTA currently tracks several metrics that focus on train headways and schedules:
But those measurements might not actually indicate whether the agency is delivering good service to riders. For example, regarding subway delay, the MTA relies heavily on a performance metric known as “wait assessment,” defined as the percentage of train arrivals that cause passengers to wait at least 25 percent longer than expected.
Wait assessment has two major problems. First, it is not obvious what it means to have a “good” wait assessment score. If the A train has a wait assessment score of 85 percent, what does that mean for riders? Second, wait assessment is indifferent to how late a train is or how many riders are affected by its lateness. On a line with service every four minutes, a gap of six minutes between trains in the Bronx at 6 a.m. is equally as “bad” as a gap of 15 minutes between trains passing through Grand Central at rush hour.
Instead, Accuardi suggests the MTA look into a different metric, “excess wait time,” which focuses on how much time riders actually spend waiting for a train rather than how much they should be waiting against the real schedule.
For starters, EWT records delay in minutes rather than as a percentage, which captures the problem of delay for riders much more accurately and intuitively. As a result, long gaps in service that cause big rider delays are weighted more heavily than small delays. Additionally, EWT weights delay by the number of people affected, so a service problem during rush hour counts as a bigger negative than an equivalent service delay on Sunday morning.
In the D.C. region, WMATA recently began pilot-testing a slightly different method of measuring its rail performance. While past reports have documented what percent of trains adhere to scheduled arrival times and headways, called “rail on-time performance,” the new pilot metric “rail customer on-time performance” focuses more on how riders move through the system.
Customer on-time performance – measured by the time between entry and exit SmarTrip card taps – calculates the percentage of trips made on-time, integrating factors such as walking times and faregate availability into train delays. Ultimately this could mean a more realistic reading of how people are experiencing the Metrorail system; however, it doesn’t have the rider-facing benefits of translating into an easy-to-understand idea of “minutes of waiting.”
As agencies work to establish goals and quantify the effects of maintenance and repair programs, adopting easy-to-understand metrics that reflect the true experiences of riding, and costs of delays, can help to communicate reliability to riders.
Read TransitCenter’s full analysis – which also discusses how Boston’s MBTA is using EWT and open data, as well as TransitCenter’s New York-based bus EWT application – here.
Photo: Riders on the New York subway (David Barkan, Flickr, Creative Commons).