Extended Kalman Filter for the On-line Calibration of Traffic Simulation Models

Sadek, Adel W; Rizzo, Donna M.; University of Vermont. Department of Civil and Environmental Engineering; New England University Transportation Center; Massachusetts Institute of Technology

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Extended Kalman Filter for the On-line Calibration of Traffic Simulation Models

2009-04-09
By Sadek, Adel W ; Rizzo, Donna M.

[PDF-51.78 KB]

English

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Creators:

Sadek, Adel W ; Rizzo, Donna M.

Sadek, Adel W ; Rizzo, Donna M. Less -
Corporate Creators:

University of Vermont. Department of Civil and Environmental Engineering ; New England University Transportation Center ; Massachusetts Institute of Technology

University of Vermont. Department of Civil and Environmental Engineering ; New England University Transportation Center ; Massachusetts Institute of Technology Less -
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology Less -
Subject/TRT Terms:

[+]

Calibration Kalman Filtering Loop Detectors Neural Networks Traffic Data Traffic Simulation
Publication/ Report Number:

Project No. UVMR16-7
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

Final Report
Corporate Publisher:

New England University Transportation Center ; Massachusetts Institute of Technology

New England University Transportation Center ; Massachusetts Institute of Technology Less -
Abstract:

The main purpose of this research was to develop methods and procedures for using the on-line data collected by field traffic detectors in the calibration of simulation models, whether they are to be used for off-line analyses or on-line traffic state estimation. Initially, the study’s goal was to use an Extended Kalman Filter to achieve this objective. Later however, it was decided to use an Artificial Neural Network (ANN) to act as a post-processing algorithm that would bring the simulation model’s predictions closer to real-world observations.
Format:

PDF
Collection(s):

University Transportation Centers
Main Document Checksum:

[+]

urn:sha256:c9a78c5cbf701ecf2832d6f61a43e710083a84e25973166804ed099887aaa861
Download URL:

https://rosap.ntl.bts.gov/view/dot/65870/dot_65870_DS1.pdf
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Extended Kalman Filter for the On-line Calibration of Traffic Simulation Models

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