摘要: |
Route-level Origin-Destination (OD) flow matrices provide useful information for ridership forecasting, service planning (e.g., extending routes, splitting or combining routes, and introducing new routes), and control strategies development (e.g., short turning, expressing, and holding). Since directly observing OD flows via on-board surveys is time consuming and costly, many methodologies have been proposed to estimate route-level OD matrices from boarding and alighting counts (Ben-Akiva et al., 1985; Ben-Akiva, 1987; Kikuchi and Perincherry, 1992; Li and Cassidy, 2007; Li, 2009; Hazelton, 2010; Ji et al., 2014; Ji et al., 2015). Passenger boarding and alighting counts are relatively easier and less costly to collect than OD flow data. Moreover, many transit agencies are now collecting large quantities of boarding and alighting counts on a routine basis via Automatic Passenger Count (APC) technologies, thus, providing the opportunity to estimate up-to-date OD flows on an ongoing basis. Transit agencies have also been adopting Automatic Fare Collection (AFC) technologies. Transit passenger OD flows could be derived from AFC data. However, many AFC systems, notably those for bus transit, are access-based (i.e., swipe-on or tap on) only and, thus, only record the stops where passengers board and do not record the stops where passenger alight. As a result, assumptions, some of which are difficult to verify, need to be made for inferring individual passenger OD flows (Chan, 2007; Wang el al., 2011) from such AFC data. The focus of this study is on the use of large quantities of APC data to estimate OD flows for transit bus routes. Since most OD flow estimation methodologies based on boarding and alighting counts were developed before the prevalence of APC technologies, the value of large quantities of APC boarding and alighting data are not effectively utilized in previously developed estimation methodologies (Ji et al., 2014; Ji et al., 2015). More specifically, many OD estimation methodologies – such as the well-known and extensively used Iterative Proportional Fitting (IPF) procedure (Ben-Akiva et al., 1985; Bacharach, 1970) in its most commonly implemented form – predominantly rely on aggregated boarding and alighting counts to determine a time-of-day period OD flow matrix, where the aggregation is performed by stop across bus trips. |