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- W99209537 abstract "Accurate vehicle trajectories are an important component of microscopic traffic modeling. 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 approach proposed in this paper 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. The authors used real-life vehicle trajectories collected from Interstate Highway 94 Westbound in the Twin Cities (Minnesota) to test the proposed approach. Results indicate the new approach is effective in eliminating both measurement and inconsistency errors. When this approach is compared to Locally Weighted Regression, by conducting a sensitivity analysis where the magnitude of measurement errors is varied with different values, the 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." @default.
- W99209537 created "2016-06-24" @default.
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- W99209537 date "2008-12-01" @default.
- W99209537 modified "2023-09-23" @default.
- W99209537 title "A Spline-Based Bi-Level Optimization Approach for Extracting Accurate Vehicle Trajectories" @default.
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