A spline-based bi-level optimization approach for extracting accurate vehicle trajectories

Wuping Xin, John Hourdos PhD

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a new approach for processing vehicle trajectories collected from the field. Unlike traditional approaches such as Finite Differencing or Locally Weighed Regression, the proposed approach combines bi-level optimization with spline interpolations, seeking to minimize not only measurement errors, but also internal inconsistency errors in positions, speeds and accelerations data. Real-life vehicle trajectories collected from I-94 WB were used to test the proposed approach. Results indicate the new approach is effective in eliminating both measurement and inconsistency errors. Moreover, the proposed approach is further compared to Locally Weighted Regression, an approach that has been commonly used in earlier studies, by conducting a sensitivity analysis where the magnitude of measurement errors is varied with different values. The comparison results show that the proposed approach is not only more robust with respect to varying measurement errors, but also more effective in removing data inconsistency from vehicle speed and acceleration profiles.

Original languageEnglish (US)
Title of host publication15th World Congress on Intelligent Transport Systems and ITS America Annual Meeting 2008
Pages389-400
Number of pages12
StatePublished - Dec 1 2008
Event15th World Congress on Intelligent Transport Systems and ITS America Annual Meeting 2008 - New York, NY, United States
Duration: Nov 16 2008Nov 20 2008

Publication series

Name15th World Congress on Intelligent Transport Systems and ITS America Annual Meeting 2008
Volume1

Other

Other15th World Congress on Intelligent Transport Systems and ITS America Annual Meeting 2008
CountryUnited States
CityNew York, NY
Period11/16/0811/20/08

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