ERI: Driving Risk-Initiated Vehicle-to-Everything Communications (DRIVEcomm)

Connected and autonomous vehicles are no longer a futuristic dream from science fiction, but they are already emerging as a reality in our everyday life. Throughout the short yet rich history of evolution of connected and autonomous vehicles, a salient paradigm is to accomplish the efficient data exchange among vehicles, which has made vehicle-to-everything (V2X) communications a household name. Despite the rapid evolution of V2X communications, successful exchange of safety messages still remains an ambitious task mainly due to the high mobility and dynamicity of vehicular systems. The bigger problem is that as more vehicles are connected and autonomously driven, the number of exchanged messages will explode, which will likely deteriorate the chance of successful message delivery. As an effort to address this problem, we propose to carefully define the priority of the transmitted information and prioritize channel access among vehicles accordingly. Predicated on the significance, this project will form a significant step towards the overarching vision of persistent and reliable operations of connected and autonomous vehicles in real-world conditions. The proposed research activities will go hand-in-hand with educational and outreach activities to train the next generation of engineers in multidisciplinary thinking. Specifically, the outcomes of this project (i.e., a testbed and further academic findings) will act as the research team's main resource in modernization of the courses, promotion of underrepresented minorities recruitment, community outreach, undergraduate research, and further collaboration with local/national stakeholders on resolving practical issues in deployment of connected and autonomous vehicles.

The key intellectual contributions of this project lie in the following innovative aspects: 1) Quantification of a 'metric' capturing the holistic impacts of multiple risk-determining features in concert; 2) Formulation of the metric computation mechanism as a 'combinatorial optimization' problem with a time constraint; 3) Proposition of a practical methodology of 'solving' the proposed combinatorial optimization problem; 4) Development of a 'testbed' implementing the proposed risk-based prioritization among safety message types defined in current V2X use cases. We will draw from these techniques to prove theoretical performance bounds for the proposed V2X communications framework and understand its practical performance limits. Consequently, the mathematical techniques and empirical observations made by this project will inform and enable future research in a broad class of problems on connected and autonomous vehicles and intelligent transportation systems.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.