Author: Pei-Wei Lin
Type: PhD Dissertation
Abstract: The purpose of this study is to develop an effective model and algorithm for estimating dynamic Origin-Destination demands for freeways. The primary challenge for this research subject lies in the fact that the number of unknown parameters is always more than the number of observable data, especially for a large network. Hence, the estimated O-D patterns may result in a large variance and insufficient reliability for use in practice. Besides, most existing approaches are grounded on the assumptions that a reliable initial O-D set is available and traffic volume data from detectors are accurate. However, in most highway network systems, both types of critical information are either unavailable or subjected to a significant level of measurement errors. To deal with those critical issues, this study has developed a set of dynamic models and solution algorithms for estimating freeway dynamic O-D matrices. The first extended model formulations can capture the speed discrepancy among drivers with an embedded travel time distribution function and the derivable interrelations between time varying ramp and mainline flows. These formulations also feature their best use of the available mainline information and travel time function, and hence substantially increase the system observability with fewer parameters.