id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_pndbidtl7beexdfp7a3oexhkly	Steven Chien	Predicting Travel Times for the South Jersey Real-Time Motorist Information System	2003	9	.pdf	application/pdf	5659	928	75	A dynamic travel-time prediction model was developed for the South Jersey (southern New Jersey) motorist real-time information system. the sensors, and this was applied to emulate traffic operations and evaluate the proposed prediction model under time-varying traffic conditions. With emulated real-time information (travel times) generated by the simulation model, an algorithm based on Kalman filtering was developed and Results show that the developed travel-time predictive model In previous studies, probe vehicles (1) and geographic information system (GIS) technology (2) were applied to estimate travel time. Some prediction models were developed by using historic traffic data that travel-time prediction is a point process, and they use purely statistical techniques to identify the stochastic nature in the observed data. used to perform travel-time prediction based on the traffic data generated by a microscopic traffic simulation, which is calibrated with applied to predict the travel time with the simulated data.	./cache/work_pndbidtl7beexdfp7a3oexhkly.pdf	./txt/work_pndbidtl7beexdfp7a3oexhkly.txt