The planning and analysis implications of automated data collection systems : rail transit OD matrix inference and path choice modeling examples

(cont.) by presenting two case studies both in the context of the Chicago Transit Authority. One study proposes an enhanced method of inferring the rail trip OD matrix from an origin-only AFC system to replace the routine passenger survey. The proposed algorithm takes advantage of the pattern of a person's consecutive transit trip segments. In particular the study examines the rail-to-bus case (which is ignored by prior studies) by integrating AFC and AVL data and utilizing GIS and DBMS technologies. A software tool is developed to facilitate the implementation of the algorithm. The other study is of rail path choice, which employs the Logit and Mixed Logit models to examine revealed public transit riders' travel behavior based on the inferred OD matrix and the transit network attributes. This study is based on two data sources: the rail trip OD matrix inferred in the first case study and the attributes of alternative paths calculated from a network representation in Trans CAD. This study demonstrates that a rigorous traveler behavior analysis can be performed based on the data source from ADC systems. Both cases illustrate the potential as well as the difficulty of utilizing these systems and more importantly demonstrate that at relatively low marginal cost, ADC systems can provide transit agencies with a rich information source to support decision making. The impact of a new data collection strategy ...