A data fusion framework is proposed to predict vehicle trajectories in urban signalized arterials. Recent advancements in data collection techniques and availability of traffic data from fixed and probe sensors suggest data fusion-based models as an alternative approach for traffic prediction....

Traffic assignment is a set of criteria through which the demand for mobility is distributed over the links of a transport network. Over the last 30 years, Dynamic Traffic Assignment (DTA) models have been developed to support time-dependent analyses in nascent fields that need to take into...

This research discusses the formulation and solution algorithm of the reactive dynamic traffic assignment with the link travel time explicitly taking into account the effects of queues under the point queue concept. In the reactive assignment, vehicles are assumed to choose their routes based on...

The purpose of this study is to develop a valid and efficient method for estimating origin-destination tables from roadside survey data. Roadside surveys, whether conducted by interviews or postcard mailback methods, typically have in common the sampling of trip origin and destination...

This research extends the dynamic user optimal assignment under the point queue concept so as to deal with physical queues. Given time-dependent many-to-many OD volumes, this paper first shows the formulation of the assignment subject to the flow conservation and the first-in-first-out (FIFO)...