Infrastructure Support for Cooperative Maneuvers in Connected and Automated Driving

Correa, Alejandro; Alms, Robert; Gozálvez, Javier; Sepulcre, Miguel; Rondinone, Michele; Blokpoel, Robbin; Lücken, Leonhard; Thandavarayan, Gokulnath

doi:10.1109/ivs.2019.8814044

Cited by 54 publications

(33 citation statements)

References 10 publications

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“…There is a paucity of literature on resource allocation addressing cooperative driving. A first study is provided by Correa et al [58] that applies the statistical analysis of static and dynamic rules based on the Cooperative Awareness Message (CAM) to the generation of Maneuver Coordination Messages (MCMs). The authors show that dynamic rules are superior w. r. t. the CBR, particularly in high traffic densities.…”

Section: Discussionmentioning

confidence: 99%

Prioritizing Relevant Information: Decentralized V2X Resource Allocation for Cooperative Driving

Bischoff¹,

Schiegg

Schuller³

et al. 2021

IEEE Access

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Cooperative driving is a promising approach to increase traffic efficiency and safety. However, cooperative driving requires high communication performance from the application perspective when coordinating and executing a cooperative maneuver, especially in scenarios with high vehicle densities under congested channel conditions. Recent studies identified that content-agnostic congestion control mechanisms deployed in decentralized vehicular networks, e. g., from the European Telecommunications Standard Institute, maintain the radio communication performance under congested channel conditions but can severely degrade the communication performance from the application perspective. In this paper, we propose a collaborative resource allocation mechanism with content-aware congestion control for decentralized vehicular networks that prioritizes vehicles with relevant information under congested channel conditions. Our evaluation results show that our proposed approach maintains the radio communication performance and significantly increases the communication performance from the application perspective compared to content-agnostic congestion control mechanisms.

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Section: Discussionmentioning

confidence: 99%

Prioritizing Relevant Information: Decentralized V2X Resource Allocation for Cooperative Driving

Bischoff¹,

Schiegg

Schuller³

et al. 2021

IEEE Access

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“…To this aim, this study implements a second and more advanced infrastructure-assisted ToC management scheme aimed at preventing the negative effects of ToCs on the traffic flow and safety. This second scheme relies on the MCMs messages under definition in ETSI for cooperative maneuvering, and that [19] [20] extends to introduce the possibility for the infrastructure to support cooperative maneuvers. These extensions enable the road infrastructure to send individual advices to the CAVs on how to manage ToC and safe spots (among others) in order to increase the overall traffic safety and efficiency.…”

Section: Infrastructure-assisted Toc/mrm Managementmentioning

confidence: 99%

Prototyping and Evaluation of Infrastructure-Assisted Transition of Control for Cooperative Automated Vehicles

Coll-Perales

Schulte-Tigges

Rondinone

et al. 2022

IEEE Trans. Intell. Transport. Syst.

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Automated driving is now possible in diverse road and traffic conditions. However, there are still situations that automated vehicles cannot handle safely and efficiently. In this case, a Transition of Control (ToC) is necessary so that the driver takes control of the driving. Executing a ToC requires the driver to get full situation awareness of the driving environment. If the driver fails to get back the control in a limited time, a Minimum Risk Maneuver (MRM) is executed to bring the vehicle into a safe state (e.g., decelerating to full stop). The execution of ToCs requires some time and can cause traffic disruption and safety risks that increase if several vehicles execute ToCs/MRMs at similar times and in the same area. This study proposes to use novel C-ITS traffic management measures where the infrastructure exploits V2X communications to assist Connected and Automated Vehicles (CAVs) in the execution of ToCs. The infrastructure can suggest a spatial distribution of ToCs, and inform vehicles of the locations where they could execute a safe stop in case of MRM. This paper reports the first field operational tests that validate the feasibility and quantify the benefits of the proposed infrastructure-assisted ToC and MRM management. The paper also presents the CAV and roadside infrastructure prototypes implemented and used in the trials. The conducted field trials demonstrate that infrastructure-assisted traffic management solutions can reduce safety risks and traffic disruptions.

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“…To this end, cooperation among various agents appears to be a promising remedy for such problems. While some previous studies have demonstrated limited realisations of this concept for applications such as lane selection [9], maneuver coordination [10] and automated intersection crossing [11], this paper tackles the challenge of using the concept for cooperative perception in the form of 3D object detection, extending our previous work in [12]. For this purpose, information from single modality, spatially diverse sensors distributed around the environment is fused as a remedy to spatial sensor impairments as alluded above.…”

Section: Introductionmentioning

confidence: 95%

Cooperative Perception for 3D Object Detection in Driving Scenarios Using Infrastructure Sensors

Arnold

Dianati

Temple

et al. 2022

IEEE Trans. Intell. Transport. Syst.

167

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Infrastructure Support for Cooperative Maneuvers in Connected and Automated Driving

Cited by 54 publications

References 10 publications

Prioritizing Relevant Information: Decentralized V2X Resource Allocation for Cooperative Driving

Prioritizing Relevant Information: Decentralized V2X Resource Allocation for Cooperative Driving

Prototyping and Evaluation of Infrastructure-Assisted Transition of Control for Cooperative Automated Vehicles

Cooperative Perception for 3D Object Detection in Driving Scenarios Using Infrastructure Sensors

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