Impacts of vehicle automation on traffic flow stability

This dissertation is motivated by the possibility of a small number of autonomous vehicles (AVs) or partially autonomous vehicles that may soon be present on our roadways. This automation may take the form of fully autonomous vehicles without human intervention (Society of Automotive Engineers, SAE Level 5) or, as is already the case in many modern vehicles, may take the form of driver assist features such as adaptive cruise control (ACC), or other SAE Level 1 features. Regardless of the extent of automation, changing the vehicle dynamics of a small number of vehicles in the bulk traffic flow may have substantial implications on the underlying traffic flow and may influence the development of emergent phenomena such as phantom traffic jams, or traffic stability. This dissertation has four main contributions: (i) experimental evidence to validate that human driving behavior alone is sufficient for the development of phantom jams, (ii) theoretical work as well as experimental work to demonstrate that current commercially-available ACC systems may be string unstable under certain circumstances, (iii) theoretical and experimental results that demonstrate the ability of autonomous vehicles to stabilize traffic flow and prevent phantom jams from arising even at low autonomous vehicle penetration rates (∼5%), and (iv) experimental evidence for the emissions impacts of phantom traffic jams, and the potential for AVs to substantially reduce these emissions