Constructing a Transit Origin–Destination Table Using the Uncertainty Maximization Concept

Abstract

An origin–destination (O-D) table contains information essential for making decisions about the operation and management of a transit system, such as determining the schedule, train composition, and fare structure. The table needs to be updated frequently. However, the collection of O-D data is time-consuming, costly, and cumbersome. This paper proposes a method that produces an O-D table on the basis of generally available data: passenger boarding and alighting counts at individual stations and the analyst's knowledge, either qualitative or quantitative, about the values for some station pairs; for example, the number of trips ( i, j) is approximately 100 or the number of trips ( i, j) is much greater than the number of trips ( m, n) (where i, j, m, and n are stops). The method applies the entropy maximization principle, in which the values for the O-D pairs whose information is not available are maximally unbiased and the available information is used as a constraint in the optimization problem. The uniqueness of the proposed approach is its ability to deal with qualitative and often language-based information, which the analyst often possesses. An example from a real transit line is presented to show the usefulness of the method and also to show how the additional information about select O-D pairs affects the quality of the solution.