Platooning merging maneuvers in the presence of parametric uncertainty

Baldi, Simone; Rosa, Muhammad Ridho; Frasca, Paolo; Kosmatopoulos, Elias B.

doi:10.1016/j.ifacol.2018.12.026

Cited by 11 publications

(6 citation statements)

References 23 publications

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“…The potential function is a real-valued nonnegative function Ψ A (e) : R m → R, where e ∈ R m is the error state of the system, e.g., lateral error as (7) or longitudinal error as (13). The function Ψ A can be thought as an artificial energy, which is zero at a desired location, small in desirable regions of the error space and tends to infinity if the error is approaching a restricted region.…”

Section: Potential Function Designmentioning

confidence: 99%

“…The vehicle merging problem in a vehicle platoon indeed involves lane-changing behavior and has also been researched recently. In [13], the merging maneuver is addressed in the presence of uncertain vehicle parameters and a platoon of three vehicles. In [14], an adaptive synchronization protocol with driveline uncertainty is used to describe merging maneuvers.…”

Section: Introductionmentioning

confidence: 99%

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A Cooperative Protocol for Vehicle Merging Using Bi-dimensional Artificial Potential Fields

Liu

et al. 2022

Lecture Notes in Networks and Systems

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In recent years, platooning solutions like cooperative adaptive cruise control (CACC) have been deeply studied. It is common in such platooning literature to assume that the vehicles drive on the same lane (longitudinal platooning). At the same time, lateral control during merging maneuvers is commonly addressed as a path planning problem, in which the ego vehicle changes the lane during merging without necessarily cooperating with its neighboring vehicles (i.e. without considering gap closing). The primary objective of this article is to develop a control strategy which involves both longitudinal and lateral vehicle dynamics, where the vehicles merge and form a platoon in a cooperative way without a priori path planning. Appropriately designed bi-dimensional artificial potential fields are used to achieve this goal and the proposed protocol is verified through simulations with CarSim.

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Section: Potential Function Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Cooperative Protocol for Vehicle Merging Using Bi-dimensional Artificial Potential Fields

Liu

et al. 2022

Lecture Notes in Networks and Systems

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“…1, where v i is the speed of the agents and d i is the distance between each vehicle. It is important to highlight four aspects of this methodology: the dynamics of the vehicles, the distributed controller, the information communicated through the network and its topology [13]. To validate the control law, a numerical simulation is performed.…”

Section: Numerical Examplementioning

confidence: 99%

Adaptive Control for Unknown Heterogeneous Vehicles Synchronization with Unstructured Uncertainty

Arévalo-Castiblanco

Tellez‐Castro

Sofrony

et al. 2019

2019 IEEE 4th Colombian Conference on Automatic Control (CCAC)

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The cooperative control applied to vehicles allows the optimization of traffic on the roads. There are many aspects to consider in the case of the operation of autonomous vehicles on highways since there are different external parameters that can be involved in the analysis of a network. In this paper, we present the design and simulation of adaptive control for a platoon with heterogeneous vehicles, taking into account that not all vehicles can communicate their control input, and in turn include structured nonlinear uncertainty input parameters.Index Terms-Multiagent systems, adaptive control, input estimation, neural network approximation n i=1 |x i | 2 . We describe A −⊤ = (A ⊤ ) −1 as the

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“…20,26 In these approaches, each agent tries to match the model of the leading vehicle or of their neighbors by using "feedback matching gains" or "coupling matching gains". [27][28][29] As compared with this literature, the main contribution of this work can be listed as follows:…”

Section: Introductionmentioning

confidence: 99%

A minimal sensing and communication control strategy for adaptive platooning

Yang

Liu

2021

Adaptive Control & Signal

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Several cooperative driving strategies proposed in literature, sometimes known as cooperative adaptive cruise control strategies, assume that both relative spacing and relative velocity with preceding vehicle are available from on-board sensors (laser or radar). Alternatively, these strategies assume communication of both velocity states and acceleration inputs from preceding vehicle. However, in practice, on-board sensors can only measure relative spacing with preceding vehicle (since getting relative velocity requires additional filtering algorithms); also, reducing the number of variables communicated from preceding vehicle is crucial to save bandwidth. In this work we show that, after framing the cooperative driving task as a distributed model reference adaptive control problem, the platooning task can be achieved in a minimal sensing and communication scenario, that is, by removing relative velocity measurements with preceding vehicle and by removing communication from preceding vehicle of velocity states. In the framework we propose, vehicle parametric uncertainty is taken into account by appropriately designed adaptive laws. The proposed framework is illustrated and shown to be flexible to several standard architectures used in cooperative driving (one-vehicle look-ahead topology, leader-to-all topology, multivehicle look-ahead topology).

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Platooning merging maneuvers in the presence of parametric uncertainty

Cited by 11 publications

References 23 publications

A Cooperative Protocol for Vehicle Merging Using Bi-dimensional Artificial Potential Fields

A Cooperative Protocol for Vehicle Merging Using Bi-dimensional Artificial Potential Fields

Adaptive Control for Unknown Heterogeneous Vehicles Synchronization with Unstructured Uncertainty

A minimal sensing and communication control strategy for adaptive platooning

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