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Adaptive/Optimal Vehicle Infrastructure Integration With Intelligent Vehicles and Environmentally-Friendly Continuous Flow Network Design

Abstract

The American transportation system faces unprecedented challenges today and will face even more significant challenges in the near future. According to Texas A&M’s 2012 Urban Mobility Report, the combined effects of wasting 5.5 billion hours and 2.9 billion gallons of fuel annually, resulted in a total congestion cost of $121 billion in the United States. In addition, according to the National Highway Traffic Safety Administration (NHTSA), approximately 33,000 traffic fatalities occurred in 2014 with an additional estimated 53,000 annual deaths due to transportation-related emissions. Each of these challenges is compounded by the prospect of the U.S. population increasing 44% by 2050. The field of Intelligent Transportation Systems (ITS) can play a major role in meeting the aforementioned challenges and in creating a 21st century transportation system that is safer, more reliable, more efficient, and more sustainable than the existing transportation system, while remaining affordable. A total of three solutions are proposed in this dissertation with varying ability to improve the mobility and environmental sustainability of traffic. The first solution is the application of Eco-Cooperative Adaptive Cruise Control (Eco-CACC) and the associated lane-changing algorithms with Connected Vehicles (CVs) to freeway traffic systems. The second solution is the leveraging of CV technology to provide real-time adaptive signal control for arterial intersections. Finally, the third solution is the development of an eco-friendly city designed around a proposed novel continuous flow intersection.

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