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A Non-Gaussian Kalman Filter With Application to the Estimation of Vehicular Speed

Summary: [This abstract is based on the author’s abstract.] Rapid estimation and forecasting of vehicular speed using data collected from an inductive loop detector (ILD) are vital to online management of road traffic. In this study, the Gaussian Kalman filter is extended to a non-Gaussian scenario in which observations of statistical inference for vehicular speed have a reciprocal inverse Gaussian distribution, resulting in a non-Gaussian Kalman filter. By applying the non-Gaussian Kalman filter to analyze traffic data collected by an ILD, an alternative for estimating vehicular speed is provided at minimum computational cost.

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  • Topics: Product-Service Design
  • Keywords: Linear models, Gaussian curve, State space models, Estimation, Forecasting, Closed loop
  • Author: Li, Baibing
  • Journal: Technometrics