This study proposes a missing data recovery method based on grey-relational nearest-neighbor substitution techniques for treating with missing data from dual-loop detectors in estimating travel time and evaluates the effects of the missing data on travel-time estimation performance. Field data from the Taiwan national freeway no.1 were used as a case study for testing the proposed model. Study results shown that the travel time estimation with missing data rate up to 33%. It is indicated that the proposed missing data treatment model can ensure the accuracy of travel time estimation with incomplete data sets.
關聯:
Proceedings of the 2003 IEEE International Conference on Systems, Man, and Cybernetics, p.p 102 - 107
