Many emerging cyber physical systems are composed of a large number of mobile intelligent agents. In these systems, each agent travels along a trajectory that is often not pre-determined. At any time interval, new agents might appear in the system, and some existing agents might disappear. Additionally, these agents are normally capable of communicating with each other or outside stations using wireless communications. We refer to these systems as Trajectory-Based Cyber-Physical Networks (TCN). Examples of such systems are abundant and range from future generations of Unmanned Aircraft Systems (UAS) to networks of human or robot agents that are deployed in an area to perform missions such as disaster recovery. The goal of this research is (1) to develop a unifying theory called "Trajectory Process Theory" for TCNs, and (2) to design, implement, and test two specific real-life TCNs based on the proposed theory.
This research has two main thrusts: Thrust 1 builds the foundations of Trajectory Process Theory. Thrust 2 applies the theory to UAS technologies, specifically aerial base stations and unmanned aircraft delivery systems. This research brings together concepts from probability theory, stochastic geometry, wireless networks, and transportation engineering. The proposed research can directly impact the design of important emerging real life systems such as UASs. Educational and outreach activities including workshops for underrepresented groups as well as creating open educational content are undertaken.
This work is supported by the National Science Foundation under Grant CPS-1932326. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.