Reliability of service

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An out-of-service bus in New York City. Source: Mtattrain

Introduction

A common theme among articles within TransitWiki is strategies to improve reliability of transit service (see Off-vehicle fare payment, Transit signal priority, and Internet communications, for example). To understand how to improve reliability of service, transit planners should understand the perception of unreliability among passengers and common responses to such factors. Many people may consider transit were it not for fear of perceived or true unreliability. Reliability can be an objective, performance-based measure, but what is most important for passengers making a decision about how to travel is the subjective perception of reliability <ref>Prashker, J.N. "Direct Analysis of the Perceived Importance of Attributes of Reliability of Travel Modes in Urban Travel." Transportation 8, pp 329-346. 1979.</ref>. Users do not typically consider the reported statistical performance of a roadway when making a trip; they rely on their personal recollection of typical circumstance or from reputation and other subjective information sources. Therefore, it is in the best interest of transit planners to consider passenger perceptions of the travel experience and, to the extent possible, plan to mitigate factors of unreliability.

Research

In 2013, student researchers from the University of California at Berkeley (UCB) conducted a survey of current and former users of the San Francisco area public transportation system<ref>Carrel, Andre, Anne Halvorsen and Joan Walker. Transportation Research Board: Transit 2013, Volume 2. "Passengers' Perception of and Behavioral Adaptation to Unreliability in Public Transportation." pp 153-162. 2013. http://trid.trb.org/view/1243072</ref>. Survey respondents rated the importance of reliability factors, including the time waiting at a transfer and possibility of waiting for less than 10 minutes for a bus after walking to a stop.

The researchers also gathered information on how passengers handled anticipated unreliability. Real-time information is a tool for mitigating unreliability, for example, but planners should remember that not all riders have access to real-time information. Most important in considering passenger response is that negative experiences can actually reduce transit use by individuals; regaining those lost customers could be more challenging than simply addressing problems of reliability.

Factors of Unreliability

Reliability may seem like an intuitive concept: can I depend on the transit service to be there on schedule and arrive at my destination on time? However there are many other factors that passengers may consider. The availability of seats on a bus, or bike rack space at certain stops could be one factor. The UCB report contrasts two riders: one typically travels every day at peak-hours and experiences longer, but predictable travel times. This rider might consider their trips reliable even in congestion, because it is expected. Another rider might typically take the bus during the off-peak time with shorter travel times; they may consider an experience riding during peak-period to be highly unreliable. Therefore, reliability can be affected by predictable circumstances such as congestion, and unpredictable, non-recurring circumstances.

According to passengers surveyed in San Francisco, 10 minutes is the maximum amount of time between buses and trains still considered frequent. In other words, a headway longer than 10 minutes is considered infrequent, and by association, unreliable.

Reliability aspects for work and non-work trips were measured by survey respondents in terms of importance. Reliability is more important for work trips, intuitively. Many reliability factors in choosing transit are the same for work and non-work trips:

  • Making connections that are possible according to the published schedule
  • Ability to walk to a stop and leave within 10 minutes
  • Waiting 10 minutes or less for transfers
  • Actual trip time matches published schedule
  • Each trip takes the same amount of time
  • Checking real-time information shows departure within 10 minutes of desired time
  • Service leaves at the time on the published schedule
  • Service departs at the same time daily
  • Availability of seating and space on the vehicle

Below is a selection of experiences reported by riders in order of frequency of occurrence on MUNI:

  1. Waited at least twice as long as scheduled for vehicles on a frequent route (in other words, a scheduled bus fails to arrive)
  2. Real-time information showed a bus arriving that never did
  3. Bus unexpectedly arrived that was not on real-time info
  4. Service delayed by traffic
  5. Service delayed by unknown issue further ahead on the route
  6. Passenger missed bus because the real-time info was incorrect
  7. Delayed by other agency [MUNI] vehicles blocking bus passenger is riding
  8. Bus pulls away from stop as passenger is running to it
  9. Vehicle delayed by mechanical problem or other on-board emergency
  10. Waited 20 or more minutes past the scheduled time for an infrequent route (>10 minute headways)
  11. Bus was too crowded to board or did not stop because of crowding
  12. Bus turned around before reaching passenger's destination
  13. Waiting for long periods when transferring to an infrequent route
  14. Bus did not stop at passenger's requested stop
  15. Bus did not see passenger waiting at stop
  16. Bus switched routes or made a route diversion and didn't serve intended destination
  17. Missed last bus because it wasn't following schedule
  18. No available space on bus bike rack

Passenger Behavior in Response to Unreliability

Passengers facing unreliable service can either employ their own strategy for absorbing the consequence (such as leaving earlier or perhaps walking to a different route), or they can choose to reduce their use of public transit. People reducing their use of transit are more likely to be shifting travel modes than simply giving up a trip they would have made.

Measuring Reliability

There are various approaches to measuring reliability. See:

References

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