@conference {
	title = {Filtering Techniques For Urban Traffic Data},
	author = {Baras, John S., Levine, William S.},
	year = {1976},
	month = {12/1976},
	abstract = {There is evidence that the algorithms for estimating traffic flows from sensor data need to be improved before computer controlled traffic responsive urban traffic control systems can reach their full potential effectiveness . A large part of the problem appears to be that the data - from traffic sensors is, in the statistical jargon, a marked point process. It is only very recently that the theoretical techniques for estimation based on point process data have reached the sophistication needed for traffic problems. In this paper, these techniques are used to derive several recursive algorithms for filtering traffic sensor data and predicting urban traffic flows. These filters and predictors are then evaluated and compared using simulated traffic data .},
	address = {Clearwater, Florida},
	booktitle = {1976 Conference on Decision and Control (CDC)},
	pages = {pp. 1297-1298}
}
@conference {
	title = {Filtering and Prediction Algorithms for Urban Traffic Control Systems},
	author = {Baras, John S., Levine, William S.},
	year = {1976},
	month = {07/1976},
	abstract = {There is evidence that the algorithms for estimating traffic flows from~sensor data need to be improved before computer controlled traffic responsive~urban traffic control systems can reach their full potential effectiveness. A~large part of the problem appears to be that the data from traffic sensors is,in the statistical jargon, a marked point process. It is only very recently that the theoretical techniques for estimation based on point process data have reached the sophistication needed for traffic problems. Thus, this paper~describes and illustrates the way in which these techniques are being applied~to the design of algorithms for filtering and prediction of urban traffic flows.},
	address = {Los Angeles, California},
	booktitle = {4th Intersociety Conference on Transportation},
	pages = {pp. 1-17}
}
