Application of game theory for adaptive energy conscious traffic control at isolated intersections and arterial corridors

Traffic congestion is a growing issue in many counties and cities in the United States and around the world. According to recent statistics [1], congestion costs the United States $74.1 billion every year, with $66.1 billion of this cost occurring in urban areas. This has led to a myriad of problems including environmental pollution, increased fuel consumption, increased crash probability, depression, and wasted work hours. Thanks to new technologies that have enabled data collection and processing, machine learning, and computer vision, new solutions can be proposed to tackle this multi-faceted challenge of congestion and rapidly improve the quality of life of urban dwellers. This thesis focuses on utilizing game theoretic concepts to develop algorithms that reduce overall fuel consumption and dangerous emissions at traffic intersections and corridors. The solutions proposed will assist city managers in improving the traffic control system and drastically reduce the Carbon footprints of our road networks.

Grantor dc:publisher

University of Tennessee at Chattanooga

Year dc:date.available

2023

Author dc:creator

• Babatunde, Jibril

Contributors dc:contributor

• Fomunung, Ignatius
• Sartipi, Mina; Wu, Weidong; Osman, Osama A.
• College of Engineering and Computer Science

• Game theory
• Electronic traffic controls

Licence

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language

English, eng

Repository record dc:identifier

https://scholar.utc.edu/theses/776

OAI identifier oai:identifier

oai:scholar.utc.edu:theses-1954