%0 Conference Paper %1 948660 %A Rice, J. %A van Zwet, E. %B Intelligent Transportation Systems, 2001. Proceedings. 2001 IEEE %D 2001 %K analysiscurrent coefficients freeway linear prediction regression road statistical status theory time traffic traffic-forecast-2009 travel varying %P 227-232 %R 10.1109/ITSC.2001.948660 %T A simple and effective method for predicting travel times on freeways %X We present a method to predict the time that will be needed to traverse a certain stretch of freeway when departure is at a certain time in the future. The prediction is done on the basis of the current traffic situation in combination with historical data. We argue that, for our purpose, the current situation of a stretch of freeway is well summarized by the 'current status travel time'. This is the travel time that would result if one were to depart immediately and no significant changes in the traffic would occur. This current status travel time can be estimated from single or double loop detectors, video data, probe vehicles or by any other means. Our prediction method arises from the empirical fact that there exists a linear relationship between any future travel time and the current status travel time. The slope and intercept of this relationship is observed to change subject to the time of day and the time until departure. This naturally leads to a prediction scheme by means of linear regression with time varying coefficients

@inproceedings{948660, abstract = {We present a method to predict the time that will be needed to traverse a certain stretch of freeway when departure is at a certain time in the future. The prediction is done on the basis of the current traffic situation in combination with historical data. We argue that, for our purpose, the current situation of a stretch of freeway is well summarized by the 'current status travel time'. This is the travel time that would result if one were to depart immediately and no significant changes in the traffic would occur. This current status travel time can be estimated from single or double loop detectors, video data, probe vehicles or by any other means. Our prediction method arises from the empirical fact that there exists a linear relationship between any future travel time and the current status travel time. The slope and intercept of this relationship is observed to change subject to the time of day and the time until departure. This naturally leads to a prediction scheme by means of linear regression with time varying coefficients}, added-at = {2009-07-03T15:41:04.000+0200}, author = {Rice, J. and van Zwet, E.}, biburl = {https://www.bibsonomy.org/bibtex/25a00d723fa86b33a5e60a442cb28540f/naufraghi}, booktitle = {Intelligent Transportation Systems, 2001. Proceedings. 2001 IEEE}, description = {Welcome to IEEE Xplore 2.0: A simple and effective method for predicting travel times onfreeways}, doi = {10.1109/ITSC.2001.948660}, interhash = {09a5d52968a20cfb2eb1f449ec4cb2ee}, intrahash = {5a00d723fa86b33a5e60a442cb28540f}, keywords = {analysiscurrent coefficients freeway linear prediction regression road statistical status theory time traffic traffic-forecast-2009 travel varying}, pages = {227-232}, timestamp = {2009-07-03T15:43:17.000+0200}, title = {A simple and effective method for predicting travel times on freeways}, year = 2001 }