Experimental testing of a control barrier function on an automated vehicle in live multi-lane traffic

Gunter, George; Nice, Matthew; Bunting, Matt; Sprinkle, Jonathan; Work, Daniel B.

doi:10.1109/di-cps56137.2022.00011

Cited by 4 publications

(2 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this work, we rely on the framework of CBFs to maintain safety, due to its ability to take advantage of existing nominal controllers such as those that stabilize traffic. Importantly, CBFs have been applied on a wide range of safety-critical systems, including adaptive cruise control [8] and its experimental implementation on heavy-duty trucks [5], automated vehicle experiments in multi-lane traffic [19], obstacle avoidance with automated vehicles [13], multi-agent systems representing automated vehicles [24], traffic merging [64], and roundabout crossing [1].…”

Section: Safety Of Mixed-autonomy Trafficmentioning

confidence: 99%

Safety-Critical Traffic Control by Connected Automated Vehicles

Yu¹,

Zhao²,

Molnár³

2023

Preprint

View full text Add to dashboard Cite

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.

show abstract

Section: Safety Of Mixed-autonomy Trafficmentioning

confidence: 99%

Safety-Critical Traffic Control by Connected Automated Vehicles

Yu¹,

Zhao²,

Molnár³

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…The CBF-Mode employs a low-level supervisory controller based on a control barrier function that overrides engaged controllers to avoid forward collisions. For a formal description of the design of this CBF, see [28]- [30]. The form of the controller is as follows:…”

Section: A Controllersmentioning

confidence: 99%

Middleware for a Heterogeneous CAV Fleet

Nice

Bunting

Work

et al. 2023

Proceedings of Cyber-Physical Systems and Internet of Things Week 2023

View full text Add to dashboard Cite

This paper introduces a novel approach that seeks a middle ground for traffic control in multi-lane congestion, where prevailing traffic speeds are too fast, and speed recommendations designed to dampen traffic waves are too slow. Advanced controllers that modify the speed of an automated car for wavedampening, eco-driving, or other goals, typically are designed with forward collision safety in mind. Our approach goes further, by considering how dangerous it can be for a controller to drive so slowly relative to prevailing traffic that it creates a significant issue for safety and comfort. This paper explores open-road scenarios where large gaps between prevailing speeds and desired speeds can exist, specifically when infrastructure-based variable speed limit systems are not strictly followed at all times by other drivers. Our designed, implemented, and deployed algorithm is able to follow variable speed limits when others also follow it, avoid collisions with vehicles ahead, and adapt to prevailing traffic when other motorists are traveling well above the posted speeds. The key is to reject unsafe speed recommendations from infrastructure-based traffic smoothing systems, based on realtime local traffic conditions observed by the vehicle under control. This solution is implemented and deployed on two control vehicles in heavy multi-lane highway congestion. The results include analysis from system design, and field tests that validate the system's performance using an existing Variable Speed Limit system as the external source for speed recommendations, and the on-board sensors of a stock Toyota Rav4 for inputs that estimate the prevailing speed of traffic around the vehicle under control.

show abstract