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Title: A Critical Evaluation of the Next Generation Simulation (NGSIM) Vehicle Trajectory Dataset - Abridged
Accession Number: 01697829
Record Type: Component
Abstract: A clear understanding of car following behavior and microscopic relationships is critical for advancing traffic flow theory. Without empirical microscopic data, plausible but incorrect hypotheses perpetuate in the vacuum. The Next Generation Simulation (NGSIM) project was undertaken to collect such data and the NGSIM data set has become the de facto standard, underlying the vast majority of empirically based advances of the past decade. But there has been a growing minority of researchers who have found unrealistic relationships in the NGSIM data. To date, the critical findings have almost exclusively come from the existing NGSIM database itself. Unfortunately, as this paper shows, the NGSIM errors are beyond anything that could be corrected strictly through cleaning or interpolation of the reported NGSIM data. This paper takes the deepest evaluation yet of the NGSIM data. This research manually re-extracts the vehicle trajectories from a portion of the original NGSIM video to explicitly quantify NGSIM errors, e.g., piecewise constant speeds punctuated by brief periods of large acceleration exhibited by the NGSIM data were not evident in the newly extracted trajectories. This point is particularly troublesome for applications that rely on acceleration, e.g., most car following models. The magnitude of errors exhibit a dependency on speed, location and vehicle length. Examples are shown where a real vehicle stopped but the NGSIM trajectory does not and then overruns the location of the real leader. Needless to say, the re-extracted trajectories showed much cleaner speed-spacing relationships than the corresponding raw NGSIM trajectories.
Supplemental Notes: This paper was sponsored by TRB committee AHB45 Standing Committee on Traffic Flow Theory and Characteristics.
Report/Paper Numbers: 19-03752
Language: English
Corporate Authors: Transportation Research BoardAuthors: Coifman, BenjaminLi, LizhePagination: 7p
Publication Date: 2019
Conference:
Transportation Research Board 98th Annual Meeting
Location:
Washington DC, United States Media Type: Digital/other
Features: Figures; References
(10)
TRT Terms: Identifier Terms: Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Vehicles and Equipment
Source Data: Transportation Research Board Annual Meeting 2019 Paper #19-03752
Files: TRIS, TRB, ATRI
Created Date: Dec 7 2018 9:38AM
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