Modeling the effects of traveler information on freeway origin-destination demand prediction

摘要

The primary focus of this research is to develop an approach tocapture the effect of travel time information on travelers's routeswitching behavior in real-time, based on on-line trafficsurveillance data. It also presents a freeway Origin-Destinationdemand prediction algorithm using an adaptive Kalman Fil- teringtechnique, where the effect of travel time information on users'route diversion behavior has been explicitly modeled using a dynamic,aggregate, route diversion model. The inherent dynamic nature of thetraffic flow characteristics is captured using a Kalman Filtermodeling framework.