Estimating Passenger Miles, Origin–Destination Patterns, and Loads with Location-Stamped Farebox Data

Abstract

Integrating an electronic farebox with a location system can provide location-stamped records of passenger boardings, a valuable source of information on passenger travel patterns. However, this information is of small value unless the pattern of passenger alightings can also be determined, since most relevant measures of interest—passenger loads, passenger miles, and origin–destination (O-D) patterns—require a knowledge or at least estimate of passenger alightings by stop. The assumption of symmetry—that the pattern of passenger alightings in one direction mirrors the daily boardings pattern in the opposite direction—is explored. Estimation methods using this assumption are tested at the trip, route, and system levels using a full-day’s set of on–off counts on five Los Angeles area routes. Tests at the route level indicate that although perfect symmetry does not exist, patterns are substantially similar on many routes. Based on the Los Angeles data, it can be found that systemwide estimates of passenger miles made using this method satisfy U.S. National Transit Database precision requirements; however, this finding should be confirmed using data from other cities. Proposed and tested, with a small amount of success, is a method for estimating trip-level O-D patterns using location-stamped farebox data based on the symmetry principle and a gravity model. Location-stamped farebox data can also be used to estimate passenger loads in real time to support control measures such as conditional priority at traffic signals without requiring automatic passenger counters.

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