Making NGSIM Data Usable for Studies on Traffic Flow Theory Multistep Method for Vehicle Trajectory Reconstruction

Despite the importance of NGSIM data for research on traffic flow theory, these data proved to be massively affected by measurement errors in the vehicle's spatial coordinates, errors that were further amplified in the differentiation process when speed and acceleration values were calculated. If not properly accounted for, these errors would make NGSIM data unusable for any study on traffic flow theory. However, the techniques applied in the literature to correct vehicle trajectory data are not suitable for the scope; these techniques do not treat the cause of the bias appropriately and are limited to smoothing out the effects, which are the high-and medium-frequency disturbances in the data. Therefore, in this study the mechanism that was the root of the NGSIM data errors was illustrated, and the limits of available techniques were shown. Then, clarification that extremely high errors, the outliers, need special treatment to be fixed was provided. A multistep filtering procedure aimed at (a) eliminating outliers giving rise to unphysical values for acceleration by local reconstruction of the vehicle trajectory and (b) cutting off the residual random disturbances from the signal while still preserving the driving dynamics was proposed. Both operations were performed, with the requirement for internal consistency of the trajectory being taken into account. Results related to a single vehicle's trajectory from the NGSIM I-80 data set and results from the application to the complete set of trajectories from the same data set are presented. The results necessitated correction of NGSIM data before further processing.