Fuel-Optimal Centralized Control of a Cooperating Car Swarm

How should a group of cars cooperate in order to save the most fuel? To provide insight into the driving behavioral objectives and control possibilities of a cooperating vehicle group sharing the goal of overall fuel savings, a method for collaborative dynamic eco-driving is developed by applying fuel-optimal centralized control to a swarm-inspired model of two-dimensional (2D) vehicle interactions. In this article, a continuous time, nonlinear system model which describes both lateral and longitudinal dynamics is used for purposes of control design, with the objective to minimize the amount of fuel used by the whole group of cars. This is accomplished using the semi-analytical optimal control algorithm of the conditional gradient method. The result of this synthesis is a type of collaborative dynamic eco-driving that offers insight into the way collaborating vehicles ought to interact on the road in order to save collective fuel. It is shown that centralized, collaborative control lowers total cost for the group compared to decentralized control. Several application scenarios are investigated as a demonstration of the proposed control method.

• Record URL:
  https://doi.org/10.4271/12-03-01-0004
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/25740741
• Supplemental Notes:
  • Abstract reprinted with permission of SAE International.
• Authors:
  • Fredette, Danielle
  • Ozguner, Umit
• Publication Date: 2020-3-11

Language

• English

Media Info

• Media Type: Digital/other
• Features: References;
• Pagination: pp 39-52
• Serial:
  • SAE International Journal of Connected and Automated Vehicles
  • Volume: 3
  • Issue Number: 1
  • Publisher: SAE International
  • ISSN: 2574-0741
  • Serial URL: https://www.sae.org/publications/collections/content/E-JOURNAL-12/

Subject/Index Terms

• TRT Terms: Advanced vehicle control systems; Automobile driving; Ecodriving; Fuel consumption; Mathematical models; Multi-agent systems; Nonlinear systems; Optimization; Traffic platooning; Vehicle to vehicle communications
• Subject Areas: Data and Information Technology; Energy; Environment; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01740738
• Record Type: Publication
• Source Agency: SAE International
• Report/Paper Numbers: 12-03-01-0004
• Files: TRIS, SAE
• Created Date: May 26 2020 10:42AM