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Permanent link (DOI): https://doi.org/10.7939/R35Q4RX3T

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Implementing Model Predictive Control based Variable Speed Limit on Urban Freeways: Data Imputation, Model Modification and Field Test Analysis Open Access

Descriptions

Other title
Subject/Keyword
Transportation
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Bie, Yuwei
Supervisor and department
Tony Z. Qiu ( Civil and Environmental Engineering)
Examining committee member and department
Tony Z. Qiu ( Civil and Environmental Engineering)
Karim El-Basyouny ( Civil and Environmental Engineering)
John Doucette (Mechanical Engineering)
Department
Department of Civil and Environmental Engineering
Specialization
Transportation Engineering
Date accepted
2016-09-15T14:35:10Z
Graduation date
2016-06:Fall 2016
Degree
Master of Science
Degree level
Master's
Abstract
Among different freeway traffic control strategies, Variable Speed Limit (VSL) shows its excellence in terms of control scale, technical feasibility and the capability of improving driving environment and traffic throughput. The Model Predictive Control (MPC) based VSL method provides a close form control loop enabling optimized variable speed limit value. The MPC-VSL control system relies heavily on a stable real time data source, an accurate traffic state prediction model and timely feedback from field implementation. The Vehicle Detection Stations (VDS) system is responsible for providing real time traffic flow related data. Most of the time VDS system works well, however, there are occasions when one set of loop lost data due to hardware failure, and this thesis provides imputation algorithm for missing data. The macroscopic traffic state prediction model in MPC-VSL control scheme is the modified METANET model. The feasibility of modifying one critical term in the original METANET model, namely “desire speed”, is tested in this thesis with different weather conditions using real field weather and loop detector data. The last part of thesis will be evolutionary analysis of VSL field test that was conducted on Whitemud Drive, Edmonton from August 13 to September 4 of 2015, borrowing the concept of time domain analysis scheme and system robustness analytical tool.
Language
English
DOI
doi:10.7939/R35Q4RX3T
Rights
This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for the purpose of private, scholarly or scientific research. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
Citation for previous publication
Bie, Yuwei, Xu Wang, and Tony Z. Qiu. "Online Method to Impute Missing Loop Detector Data for Urban Freeway Traffic Control." Transportation Research Record: Journal of the Transportation Research Board 2593 (2016): 37-46.

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