Date of Completion

Spring 5-6-2022

Degree Type


Degree Name

Master of Science in Construction Engineering


Construction Engineering


Transportation and Pavement Engineering

Thesis Advisor




The recent advances in information and communication technologies have enabled cooperative traffic control at signal-free intersections, which can significantly improve safety of the roads and performance of urban networks. The impacts of cooperative control of traffic on the battery life of communicant autonomous vehicles (CAVs), however, are not necessarily positive. This research develops an analytical model for the battery-capacity loss rate of CAV platoons coordinated to pass through signal-free smart intersections with no interruption. The main objective of the research is to demonstrate the importance of adjusting the macro-level setting of the cooperative control system for enhancing the battery life of CAVs. To achieve this goal, the average battery-capacity loss rate (percentage) is formulated for the expected length of coordination cycles. The proposed analytical model is then used to investigate the sensitivity of the battery-capacity loss rate to the preset platoon size, network speed, and the synchronization marginal gap length. These analytical results of the research indicate that the battery-capacity loss rate of CAVs is a strictly increasing function of the network speed, but a strictly decreasing function of both the platoon size and the marginal gap. However, at constant network speed, the effect of increasing the marginal gap and the platoon size on reducing the battery-capacity loss rate is more significant. To evaluate the analytical results of the research, the proposed model is used to solve a numerical example. The numerical results of the research show that adjusting the macro-level control variables can improve CAVs’ battery life by 20.9% at the cost of a 5.6% reduction from the maximum network capacity.