Are Commercially Implemented Adaptive Cruise Control Systems String Stable?

Gunter, George; Gloudemans, Derek; Stern, Raphael; McQuade, Sean T.; Bhadani, Rahul; Bunting, Matt; Monache, Maria Laura Delle; Lysecky, Roman; Seibold, Benjamin; Sprinkle, Jonathan; Piccoli, Benedetto; Work, Daniel B.

doi:10.1109/tits.2020.3000682

Cited by 189 publications

(106 citation statements)

References 43 publications

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“…Recently, as the vehicle systems have transitioned from research to practical deployments on commercial vehicles, the traffic modeling community is now in need of good models for how these vehicles behave in practice. Surprisingly, all commercial systems that have been tested [9,15,18,19,21,33] are shown to be string unstable and with varying performance characteristics. Being able to characterize the behavior of the ACC system in real time has implications for traffic management, where an emerging area of research [6,9,38,41,44] aims to dampen phantom traffic jams caused by string unstable driving behavior [34].…”

Section: Motivation and Problem Statementmentioning

confidence: 99%

“…These findings highlight the need to accurately model the implications of deploying ACC vehicles at scale, and motivate our desire for fast and accurate methods to estimate the parameters of the ACC vehicles. In our prior works investigating the string stability of commercial ACC systems [9,10], ACC model parameters are estimated through an offline optimization procedure to best fit recorded data. While accurate and computationally efficient for small datasets, online methods are desirable for real-time applications and for computation on large (high frequency, long time duration) datasets.…”

Section: Motivation and Problem Statementmentioning

confidence: 99%

“…Punzo and Simonelli [29] estimated optimal parameters for several different car-following models on a four vehicle platoon equipped with GPS tracking units, and used a batch optimization method in which a gradient-based optimization technique was used starting from several different initial points, again in order to account for potential non-convexity. This method (along with ones in [9,10,15,18,21]) is in the same family of techniques used in this article as a benchmark to compare the newly presented methods. In general it should be noted that many of these techniques find parameters of non-linear models, and as such need to employ optimization techniques that account for this difficulty.…”

Section: Related Workmentioning

confidence: 99%

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Online Parameter Estimation Methods for Adaptive Cruise Control Systems

Wang

Gunter

Nice

et al. 2021

IEEE Trans. Intell. Veh.

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Modeling Adaptive Cruise Control (ACC) vehicles enables the understanding of the impact of these vehicles on traffic flow. In this work, two online methods are used to provide real time system identification of ACC enabled vehicles. The first technique is a recursive least squares (RLS) approach, while the second method solves a nonlinear joint state and parameter estimation problem via particle filtering (PF).We provide a parameter identifiability analysis for both methods to analytically show that the model parameters are not identifiable using equilibrium driving. The accuracy and computational runtime of the online methods are compared to a commonly used offline simulationbased optimization (i.e., batch optimization) approach. The methods are tested on synthetic data as well as on empirical data collected directly from a 2019 model year ACC vehicle using data from sensors that are part of the stock ACC system. The online methods are scalable and provide comparable accuracy to the batch method. RLS runs in real time and is two orders of magnitude faster than the batch method for modest sized (e.g., 15 min) datasets. The particle filter also runs in real-time, and is also suitable in streaming applications in which the datasets can grow arbitrarily large.

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Section: Motivation and Problem Statementmentioning

confidence: 99%

Section: Motivation and Problem Statementmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Online Parameter Estimation Methods for Adaptive Cruise Control Systems

Wang

Gunter

Nice

et al. 2021

IEEE Trans. Intell. Veh.

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“…Our analysis starts from the observation that the standard notion of string stability on a ring roadway is too demanding for a mixed traffic scenario, since human drivers are prone to string instability (and this drawback also affects current ACC systems [15], [18]). A new definition, named weak ring stability, is therefore proposed (Section 2).…”

Section: Introductionmentioning

confidence: 99%

“…Let us investigate numerically the stability and WRS of (20)-(21) for different pairs (a, b) and by varying the number of vehicles N on the ring. The parameters in(15) are as in Tab. 1.…”

mentioning

confidence: 99%

Traffic Flow on a Ring With a Single Autonomous Vehicle: An Interconnected Stability Perspective

Giammarino

Baldi

Frasca

et al. 2021

IEEE Trans. Intell. Transport. Syst.

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In recent years, field experiments have been performed on ring roadways with human-driven vehicles or with a mix of human-driven and autonomous vehicles. While these experiments demonstrate the potential for controlling traffic flows by a small number of autonomous vehicles, the theoretical framework about such a possibility is to a large extent incomplete. Indeed, most work on mixed traffic focused on classical asymptotical stability notions, neglecting that human drivers are prone to the interconnected instability known in the literature as string instability. This work aims to enhance the existing theories to meet the questions raised by the field experiments. It starts from the observation that the standard notion of string stability on a ring roadway is too demanding for a mixed traffic scenario: therefore, a new interconnected stability definition, named weak ring stability, is proposed. This new interconnected stability notion, in combination with classical stability, is able to explain phenomena observed in field experiments and to highlight possibilities and limitations of traffic control via sparse autonomous vehicle. Furthermore, it allows designing AV controllers with improved string stability specifications, at the price of reducing the sparsity of the autonomous vehicles.

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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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Are Commercially Implemented Adaptive Cruise Control Systems String Stable?

Cited by 189 publications

References 43 publications

Online Parameter Estimation Methods for Adaptive Cruise Control Systems

Online Parameter Estimation Methods for Adaptive Cruise Control Systems

Traffic Flow on a Ring With a Single Autonomous Vehicle: An Interconnected Stability Perspective

A minimal sensing and communication control strategy for adaptive platooning

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