Decentralized optimal merging control for Connected and Automated Vehicles with safety constraint guarantees

Xiao, Wei; Cassandras, Christos G.

doi:10.1016/j.automatica.2020.109333

Cited by 53 publications

(34 citation statements)

References 25 publications

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“…2), such as the preceding vehicle k p . This merging problem can be solved analytically by optimal control methods (Xiao and Cassandras, 2021), but at the cost of extensive computation, and the solution becomes complicated when one or more constraints become active in an optimal trajectory, hence possibly prohibitive for real-time implementation.…”

Section: Traffic Merging Controlmentioning

confidence: 99%

BarrierNet: A Safety-Guaranteed Layer for Neural Networks

Xiao¹,

Hasani²,

Li³

et al. 2021

Preprint

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This paper introduces differentiable higher-order control barrier functions (CBF) that are end-toend trainable together with learning systems. CBFs are usually overly conservative, while guaranteeing safety. Here, we address their conservativeness by softening their definitions using environmental dependencies without loosing safety guarantees, and embed them into differentiable quadratic programs. These novel safety layers, termed a BarrierNet, can be used in conjunction with any neural network-based controller, and can be trained by gradient descent. BarrierNet allows the safety constraints of a neural controller be adaptable to changing environments. We evaluate them on a series of control problems such as traffic merging and robot navigations in 2D and 3D space, and demonstrate their effectiveness compared to state-of-the-art approaches.

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Section: Traffic Merging Controlmentioning

confidence: 99%

BarrierNet: A Safety-Guaranteed Layer for Neural Networks

Xiao¹,

Hasani²,

Li³

et al. 2021

Preprint

Self Cite

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“…After introducing the sub-coordinator queue tables, we also allow some resequencing for CAVs passing each MP and focus on the CZ associated with that MP. Thus, each such problem resembles the merging control problem in [17] which can be analytically solved. However, as pointed out in [17], when one or more constraints become active, this solution becomes computationally intensive.…”

Section: Joint Optimal Control and Control Barrier Function Controlle...mentioning

confidence: 99%

“…In this paper, we build on the use of optimal control and CBF-based methods in unsignalized intersections [16] and merging [17] to study roundabouts with all traffic consisting of CAVs. There are several similarities between merging, intersections and roundabouts problems.…”

Section: Introductionmentioning

confidence: 99%

“…There are several similarities between merging, intersections and roundabouts problems. The singlelane merging problem [17] contains a single Merging Point (MP) where safety constraints must be guaranteed, while CAVs follow the same moving direction in each lane. In intersection problems, CAVs have a number of possible paths which conflict at multiple MPs restricted to a small area.…”

Section: Introductionmentioning

confidence: 99%

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Decentralized Time and Energy-Optimal Control of Connected and Automated Vehicles in a Roundabout

Cassandras

Xiao

2021

Preprint

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The paper considers the problem of controlling Connected and Automated Vehicles (CAVs) traveling through a three-entry roundabout so as to jointly minimize both the travel time and the energy consumption while providing speeddependent safety guarantees, as well as satisfying velocity and acceleration constraints. We first design a systematic approach to dynamically determine the safety constraints and derive the unconstrained optimal control solution. A joint optimal control and barrier function (OCBF) method is then applied to efficiently obtain a controller that optimally track the unconstrained optimal solution while guaranteeing all the constraints. Simulation experiments are performed to compare the optimal controller to a baseline of human-driven vehicles showing effectiveness under symmetric and asymmetric roundabout configurations, balanced and imbalanced traffic rates and different sequencing rules for CAVs.

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“…Examples of that evolution are in almost every new house: Closed-Circuit Television (CCTV) cameras, smart lights, smart blinds, and doorbells. Even cars are becoming always connected to the cloud to provide owners with information such as their parking location and even perform automated tasks—Connected and Automated Vehicles (CAV) [ 7 ]. This globalization, combined with the small scale of the new devices, is also known as smart dust, that means that we are surrounded by many small particles with embedded intelligence [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

Distributed Architecture for Unmanned Vehicle Services

Ramos

Ribeiro

Safadinho

et al. 2021

Sensors

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The demand for online services is increasing. Services that would require a long time to understand, use and master are becoming as transparent as possible to the users, that tend to focus only on the final goals. Combined with the advantages of the unmanned vehicles (UV), from the unmanned factor to the reduced size and costs, we found an opportunity to bring to users a wide variety of services supported by UV, through the Internet of Unmanned Vehicles (IoUV). Current solutions were analyzed and we discussed scalability and genericity as the principal concerns. Then, we proposed a solution that combines several services and UVs, available from anywhere at any time, from a cloud platform. The solution considers a cloud distributed architecture, composed by users, services, vehicles and a platform, interconnected through the Internet. Each vehicle provides to the platform an abstract and generic interface for the essential commands. Therefore, this modular design makes easier the creation of new services and the reuse of the different vehicles. To confirm the feasibility of the solution we implemented a prototype considering a cloud-hosted platform and the integration of custom-built small-sized cars, a custom-built quadcopter, and a commercial Vertical Take-Off and Landing (VTOL) aircraft. To validate the prototype and the vehicles’ remote control, we created several services accessible via a web browser and controlled through a computer keyboard. We tested the solution in a local network, remote networks and mobile networks (i.e., 3G and Long-Term Evolution (LTE)) and proved the benefits of decentralizing the communications into multiple point-to-point links for the remote control. Consequently, the solution can provide scalable UV-based services, with low technical effort, for anyone at anytime and anywhere.

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Decentralized optimal merging control for Connected and Automated Vehicles with safety constraint guarantees

Cited by 53 publications

References 25 publications

BarrierNet: A Safety-Guaranteed Layer for Neural Networks

BarrierNet: A Safety-Guaranteed Layer for Neural Networks

Decentralized Time and Energy-Optimal Control of Connected and Automated Vehicles in a Roundabout

Distributed Architecture for Unmanned Vehicle Services

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