Date of Award


Document Type

Campus Access Dissertation

Degree Name

Doctor of Philosophy in Civil Engineering (PhD)

Administrative Home Department

Department of Civil, Environmental, and Geospatial Engineering

Advisor 1

Kuilin Zhang

Committee Member 1

Andrew Swartz

Committee Member 2

Wayne Weaver

Committee Member 3

Chee-Wooi Ten


Connected and Automated Vehicle (CAV) is an emerging technology that integrates vehicular communication and automated driving capabilities. It has the potential to improve driving safety and stability with enhanced perception (via vehicular communication) and real-time control (via automated driving). Moreover, vehicular communication enables CAVs to engage in various classes of cooperation that could potentially enhance the overall traffic performance. This dissertation studies Cooperative Driving Automation (CDA) on freeways and arterials, with a focus on real-time control and platoon formation.

One of the biggest challenges of CDA is the real-time control of CAVs subject to time delays and actuator lag. This dissertation proposes a real-time predictive distributed control framework that addresses time delays (due to sensing, communication, and computation) and actuator lag issues for a fixed platoon of CAVs in freeway driving scenarios. A Kalman Filter-based real-time current driving state prediction model is proposed to provide more accurate initial conditions for the controller by compensating time delays using data from multi-rate on-board sensors and vehicular communication. A real-time distributed Cooperative Adaptive Cruise Control (CACC) controller based on Model Predictive Control (MPC) considering actuator lag is proposed for the driving control of CAVs. Numerical analyses are conducted to demonstrate the benefits of intent-sharing-based distributed computing, delay compensation, and actuator lag consideration on string stability under various traffic conditions.

The platoon formation problem under interrupted traffic flow is also a challenge for CDA. This dissertation proposes a forest-based platoon formation model to construct the platoon-based cooperation topology for all CAVs driving on signalized arterials. Cooperation and communication frameworks and an automated driving system to achieve Class D Prescriptive Cooperation are designed. A predictive lane-changing planning model and a longitudinal-lateral coupled trajectory planning model are proposed, enabling the cooperation between CAVs and between CAVs and signal controllers. Co-simulations of traffic and wireless communication on a signalized arterial network are conducted. Numerical analyses are conducted to demonstrate the feasibility of the platoon formation model and the communication and traffic implications of various classes of CDA.

Available for download on Saturday, April 26, 2025