In order to obtain more credible estimation of time-dependent travel demands, various data sources should be jointly exploited to improve the observability of the transportation system. This paper carries out a comprehensive case study using a real freeway network to reveal how different data coverage affects the quality of estimated origin-destination (O-D) tables.The dynamic O-D estimation (DoDE) problem is formulated as a variational inequality (VI) which provides a flexible framework to incorporate different data sources and to encapsulate realistic traffic flow dynamics. Traffic surveillance data considered include: traffic counts from vehicle detectors, historical O-D tables (static or dynamic), and travel time measurements on sub-paths. A novel method is employed to evaluate marginal path travel times, which is a key procedure to properly incorporate travel time measurements in the VI formulation. Our numerical experiments generate a number of guidelines to the proper selection of data coverage for obtaining improved O-D estimates.
Abstract