Travel time forecasting and dynamic origin-destination estimation for freeways based on bluetooth traffic monitoring

Traditional technologies, such as inductive loop detectors, do not usually produce measurements of the quality required by real-time applications. Therefore, one wonders what could be expected from newer information and communication technologies, such as automatic vehicle location, license plate recognition, and detection of mobile devices. The main objectives of this paper are to explore the quality of the data produced by Bluetooth detection of mobile devices that equip vehicles for travel time forecasting and its use in estimating time-dependent origin-destination matrices. Ad hoc procedures based on Kalman filtering have been designed and implemented successfully, and the numerical results of the computational experiments are presented and discussed.

https://doi.org/10.3141/2175-03

Cite as:

@article{Barcel__2010,
	doi = {10.3141/2175-03},
	url = {https://doi.org/10.3141%2F2175-03},
	year = 2010,
	month = {jan},
	publisher = {{SAGE} Publications},
	volume = {2175},
	number = {1},
	pages = {19--27},
	author = {Jaume Barcelö and Lidin Montero and Laura Marqu{'{e}}s and Carlos Carmona},
	title = {Travel Time Forecasting and Dynamic Origin-Destination Estimation for Freeways Based on Bluetooth Traffic Monitoring},
	journal = {Transportation Research Record: Journal of the Transportation Research Board}
}