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Theses and Dissertations

A Fuel-Saving Green Light Optimal Speed Advisory for Signalized Intersection Using V2I Communication Open Access


Other title
Connected Vehicle
Fuel consumption
Type of item
Degree grantor
University of Alberta
Author or creator
Supervisor and department
Tony Z. Qiu
Examining committee member and department
Di Niu (Department of Electrical and Computer Engineering)
Karim El-Basyouny (Karim El-Basyouny)
Tony Z. Qiu (Department of Civil & Environmental Engineering)
Department of Civil and Environmental Engineering
Transportation Engineering
Date accepted
Graduation date
Master of Science
Degree level
The research in this thesis introduces a connected vehicle environmental green light speed advisory which helps the vehicle to avoid unnecessary stops before intersections and improves the fuel consumption efficiency. Lots of works for Eco-driving on GLOSA (Green Light Optimal Speed Advisory) have been done by the previous researchers. Most of them focus on the macro level where the process of speed changes is ignored. Hesham Rakha, etc12 considered the acceleration process, but there is no simulation and field data to support his result and also the fuel consumption objective is the total consumption which did not consider the total distance. As the total fuel consumption will depend on the processing distance. This paper will formulate fuel consumption objective functions based on VT (Virginal Tech) Micro model to analyze the fuel consumption on vehicle’s different speed profiles. To avoid the unnecessary stops, different speed strategies will be provided by the system. Over 100,000 rounds of simulations have been conducted in MATLAB and the result shows that the average fuel saving for green light signal is 21% and for red signal scenarios is 56%. Also an android based app has been developed to collect the field data on connected vehicle environment. The result from the field shows 14% of fuel was saved for vehicle with GLOSA application compared to vehicle without GLOSA. However, the research on this paper only considered one vehicle and one intersection for ideal conditions. In the future, queues at intersection need to be considered as well as multi-intersections condition.
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
Citation for previous publication
Katsaros, K (2010), Performance study of a Green Light Optimal Speed Advisory (GLOSA) Application Using an Integrated Cooperative ITS Simulation Platform. Sciences New York, 918–923.

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