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

  • Author / Creator
  • 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.

  • Subjects / Keywords
  • Graduation date
    Fall 2015
  • Type of Item
  • Degree
    Master of Science
  • DOI
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. 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.
  • Language
  • Institution
    University of Alberta
  • Degree level
  • Department
  • Specialization
    • Transportation Engineering
  • Supervisor / co-supervisor and their department(s)
  • Examining committee members and their departments
    • Di Niu (Department of Electrical and Computer Engineering)
    • Karim El-Basyouny (Karim El-Basyouny)
    • Tony Z. Qiu (Department of Civil & Environmental Engineering)