Data Fusion with Split Covariance Intersection for Cooperative Perception

Lima, Antoine; Cherfaoui, Véronique; Hage, Joelle Al

doi:10.1109/itsc48978.2021.9564963

Cited by 12 publications

(7 citation statements)

References 28 publications

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“…To validate our approach, it has been applied to real-world data using the same dataset as in [10]. In it, three vehicles v 1 , v 2 and v 3 were driven in an busy roundabout with v 1 stopped at one of the roundabout entrance while v 2 and v 3 followed each other inside of it.…”

Section: Resultsmentioning

confidence: 99%

Evidential Trustworthiness Estimation for Cooperative Perception

Lima

Cherfaoui

2022

Belief Functions: Theory and Applications

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Intelligent Vehicles can exchange their perception information using wireless technology in a cooperative and decentralized manner. This has the potential to extend the range of perception and thus improve anticipation for complex driving maneuvers and decision making. However, information received from other peers can be erroneous and has to be used carefully. In this paper, we present a method that allows each peer to assign a trust in the information received from other peers based on comparisons with its current knowledge of the world. We describe how this process is managed using the Dempster-Shafer theory. We also present how positive and negative evidence cues can be developed in this problem, in particular by using detectability grids. An experimental evaluation, carried out with real vehicles, is reported to show that this formalism behaves correctly.

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Section: Resultsmentioning

confidence: 99%

Evidential Trustworthiness Estimation for Cooperative Perception

Lima

Cherfaoui

2022

Belief Functions: Theory and Applications

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“…Therefore, raw sensor data must be effectively combined to save storage space and transmission resources. Previously, some strategies [36][37][38] were presented for handling and processing such raw sensor data. In this sense, data fusion approaches may integrate shared perceptual information provided by CP applications to increase the accuracy of discovered items.…”

Section: Data Selection and Fusion Aspectmentioning

confidence: 99%

“…Lima et al [37] studied the split covariance intersection filter, which is a method capable of handling both independent and arbitrarily correlated estimates and observa-tion errors. Various filtering solutions based on the covariance intersection filter or split covariance intersection filter were presented.…”

Section: Data Selection and Fusion Aspectmentioning

confidence: 99%

Redundancy Mitigation Mechanism for Collective Perception in Connected and Autonomous Vehicles

et al. 2023

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Due to poor local range of the perception and object recognition mechanisms used by autonomous vehicles, incorrect decisions can be made, which can jeopardize a fully autonomous operation. A connected and autonomous vehicle should be able to combine its local perception with the perceptions of other vehicles to improve its capability to detect and predict obstacles. Such a collective perception system aims to expand the field of view of autonomous vehicles, augmenting their decision-making process, and as a consequence, increasing driving safety. Regardless of the benefits of a collective perception system, autonomous vehicles must intelligently select which data should be shared with who and when in order to conserve network resources and maintain the overall perception accuracy and time usefulness. In this context, the operational impact and benefits of a redundancy reduction mechanism for collective perception among connected autonomous vehicles are analyzed in this article. Therefore, we propose a reliable redundancy mitigation mechanism for collective perception services to reduce the transmission of inefficient messages, which is called VILE. Knowledge, selection, and perception are the three phases of the cooperative perception process developed in VILE. The results have shown that VILE is able to reduce it the absolute number of redundant objects of 75% and generated packets by up to 55%. Finally, we discuss possible research challenges and trends.

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“…with ω ∈ (0, 1), where the last term is identical to the upper bound used in CI. Split CI has been applied in many practical problems, see, e.g., [89,91,104,105] and [42,111] for more recent studies.…”

Section: Split Covariance Intersectionmentioning

confidence: 99%

The Dark Side of Decentralized Target Tracking : Unknown Correlations and Communication Constraints

Forsling

2023

Linköping Studies in Science and Technology. Dissertations

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Cover illustration: Fusion of estimates with unknown correlations. The colored ellipses represent covariances of estimates to be fused. The white circles represent possible covariances of the fused result given different assumptions about the unknown correlations. The white ellipses are mainly there for show.Linköping studies in science and technology. Dissertations. No. 2359 The Dark Side of Decentralized Target Tracking: Unknown Correlations and Communication ConstraintsRobin Forsling

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Data Fusion with Split Covariance Intersection for Cooperative Perception

Cited by 12 publications

References 28 publications

Evidential Trustworthiness Estimation for Cooperative Perception

Evidential Trustworthiness Estimation for Cooperative Perception

Redundancy Mitigation Mechanism for Collective Perception in Connected and Autonomous Vehicles

The Dark Side of Decentralized Target Tracking : Unknown Correlations and Communication Constraints

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