An Algorithm to Estimate Continuous-time Traffic Speed Using Multiple Regression Model

In this study we present a novel algorithm to estimate continuous-time traffic speed data using multiple regression based on the correlated speed and then compare its results to other baseline missing speed prediction methods with real freeway traffic speed data. Since this approach has greater generalization ability for given real speed data, it is believed that this model will also perform well for all time-series missing data estimation fields.