Safety-Critical Traffic Control by Connected Automated Vehicles

Abstract

Connected automated vehicles (CAVs) have shown great potential in improving traffic throughput and stability. Although various longitudinal control strategies have been developed for CAVs to achieve string stability in mixed-autonomy traffic systems, the potential impact of these controllers on safety has not yet been fully addressed. This paper proposes safety-critical traffic control (STC) by CAVs-a strategy that allows a CAV to stabilize the traffic behind it, while maintaining safety relative to both the preceding vehicle and the following connected human-driven vehicles (HDVs). Specifically, we utilize control barrier functions (CBFs) to impart collision-free behavior with formal safety guarantees to the closed-loop system. The safety of both the CAV and HDVs is incorporated into the framework through a quadratic program-based controller, that minimizes deviation from a nominal stabilizing traffic controller subject to CBF-based safety constraints. Considering that some state information of the following HDVs may be unavailable to the CAV, we employ state observer-based CBFs for STC. Finally, we conduct extensive numerical simulations-that include vehicle trajectories from real data-to demonstrate the efficacy of the proposed approach in achieving string stable and, at the same time, provably safe traffic.

Unveiling the Hidden Effects of Automated Vehicles on “Do No Significant Harm’’ Components

“…The rapid growth of automated and connected vehicles (CAVs) has the potential to revolutionize urban transport systems [1], offering numerous benefits such as improved safety [2], reduced congestion [3], and increased mobility options [4]. Previous studies have examined specific aspects of AV impacts such as traffic flow optimization [5], energy consumption [6], safety improvements [7], and land use impacts [8].…”