Leveraging Control Theory to Facilitate UAV Application for CAV Deployment

Leveraging Control Theory to Facilitate UAV Application for CAV Deployment

Headshot of Shaoshuai Mou. The link directs to their bio page on the CCAT website.
Shaoshuai Mou
Sikai Chen Headshot. The link directs to their bio page on the CCAT website.
Sikai Chen
Purdue University Logo. The link directs to the research page on the CCAT website.

Principal Investigator(s):

Shaoshuai Mou, Associate Professor of Aeronautics and Astronautics – Purdue University
Co-Director – Center for Innovation in Control, Optimization, and Networks (ICON)
Sikai Chen, Post-Doctoral Researcher – Center for Connected and Automated Transportation
Post-Doctoral Researcher – NEXTRANS Center at Purdue University
Visiting Research Fellow – Robotics Institute at the School of Computer Science at Carnegie Mellon University

Project Abstract:
Recent studies have espoused the benefits of connectivity among ground vehicles, which include proactive safety management, savings in fuel consumption, efficiency of traffic mobility, and reduction in emissions. Connectivity makes it possible to acquire data on the traffic streams (and any disruptions thereto), as well as threats and opportunities associated with the weather conditions, pedestrians, and the non-roadway environment. With such data, the ground vehicles can make more informed decisions that reduce delay and yield the attendant benefits associated with safety, mobility, emissions, and energy use. In quests to identify additional potential sources of data, researchers have identified the opportunity offered by Unmanned Aerial Vehicles (UAVs) in this regard. It has been found that UAVs can acquire and transit aerial data to ground vehicles and other end users quickly and cost-effectively. First, camera-equipped UAVs acquire visual information about the terrain they are monitoring. Secondly, UAVs provide greater efficiency and convenience compared to surveillance cameras with fixed camera angle, scale and view. Thirdly, if UAVs are equipped with Vehicle-to-Everything (V2X) communication technologies, they can lend another dimension of communication in the Connected and Autonomous vehicle (CAV) data environment. Previous studies have used microscopic traffic simulation to investigate and exploit the potential benefits and use cases of a CAV-UAV connected networks. In the proposed study, we intend to use real life (but, smaller scale) simulation of both UAV and CAVs. We intend to show how the traffic and roadway environment information can be collected by the connected UAVs and disseminated to the CAVs below. We will then assess the performance of the CAVs in fuel economy and traffic mobility vis-à-vis the baseline case of no UAV communication and the case where only connected UAVs were present. We shall do this for a number of scenarios involving traffic and roadway conditions, and we shall identify the conditions under which the UAV application is most beneficial to CAV deployment. In addition, recognizing that the benefits of UAVs are not just for information delivery to the ground CAVs, we shall show how control theory can be used by the UAV to help provide prescriptions for safe and efficient movement of the CAVSs. The proposed study will also demonstrate the efficacy of a DSRC based communication architecture between the connected UAV and the ground CAVs, and examine the issues related to package loss in the data transfer, reliability of the DSRC communication, and communication ranges, latency, and scalability to real life deployment. The practical benefits of the proposed products are numerous. A reliable UAV-CAV data domain can help the road agency carry out traffic safety risk assessment and vehicle trajectory monitoring. From the control perspective, it can also help establish optimal operational maneuvers for CAVs (including weaving and lane-change) and trajectory planning.

Institution(s): Purdue University

Award Year: 2022

Research Thrust(s): Control & Operations, Enabling Technology, Modeling & Implementation

Project Form(s):
Project Information Form