Automatic speed-bias correction with flow-density relationships

Accurate and reliable speeds measured with local traffic sensors are critically important for many applications, such as travel time estimation, state estimation and prediction and dynamic traffic control. Many local sensors (e.g. the dual induction loops used in The Netherlands, UK and in Germany) calculate average speed by arithmetic time averaging, which leads to strongly biased estimates. This paper proposes a speed-bias correction algorithm based on notions from first order traffic flow theory and empirical flow-density relationships, using only a limited number of parameters. On the basis of a microscopic simulation study, it is demonstrated that this algorithm is able to correct the speed bias due to time averaging considerably. A more extensive version of this paper can be found at http://dux.ict.tbm.tudelft.nl/Research/SpeedCorr.pdf.