Stabilizing traffic flow via a single autonomous vehicle: Possibilities and limitations

Cui, Shumo; Seibold, Benjamin; Stern, Raphael; Work, Daniel B.

doi:10.1109/ivs.2017.7995897

Cited by 124 publications

(129 citation statements)

References 18 publications

Supporting

Mentioning

117

Contrasting

Unclassified

Order By: Relevance

“…We consider a single-lane ring road of length L and with n vehicles. As discussed in Cui et al [18], the ring road setting has several theoretical advantages for modeling a traffic system, including 1) the existence of experiment results that can be used to calibrate model parameters [23], 2) perfect control of average traffic density, and 3) correspondence with an infinite straight road with periodic traffic dynamics.…”

Section: Resultsmentioning

confidence: 99%

“…More recently, Cui et al. first pointed out the potential of a single autonomous vehicle in stabilizing mixed traffic flow [18], and they also implemented simple control strategies to demonstrate the dissipation of stop-and-go waves via a single autonomous vehicle in real experiments [19]. The control principle is essentially a slow-in fast-out approach, which is an intuitive method to dampen traffic jams [20].…”

Section: Introductionmentioning

confidence: 99%

“…While the potential of autonomous vehicles has been recognized and demonstrated [18,19,21,22], a comprehensive theoretical understanding is lacking. In this paper, we provide a theoretical analysis on the potential of autonomous vehicles in smoothing mixed traffic flow from a complex system viewpoint.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Smoothing Traffic Flow via Control of Autonomous Vehicles

Zheng

Wang

2020

IEEE Internet Things J.

136

146

View full text Add to dashboard Cite

The emergence of autonomous vehicles is expected to revolutionize road transportation in the near future. Although large-scale numerical simulations and small-scale experiments have shown promising results, a comprehensive theoretical understanding to smooth traffic flow via autonomous vehicles is lacking. Here, from a control-theoretic perspective, we establish analytical results on the controllability, stabilizability, and reachability of a mixed traffic system consisting of human-driven vehicles and autonomous vehicles in a ring road. We show that the mixed traffic system is not completely controllable, but is stabilizable, indicating that autonomous vehicles can not only suppress unstable traffic waves but also guide the traffic flow to a higher speed. Accordingly, we establish the maximum traffic speed achievable via controlling autonomous vehicles. We also design an optimal control strategy for autonomous vehicles to actively dampen undesirable perturbations. These theoretic findings validate the high potential of autonomous vehicles to smooth traffic flow. * Electronic address: yang.zheng@eng.ox.ac.uk

show abstract

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Smoothing Traffic Flow via Control of Autonomous Vehicles

Zheng

Wang

2020

IEEE Internet Things J.

136

146

View full text Add to dashboard Cite

show abstract

“…The early experiments formed the basis of microscopic traffic flow modelling, an area of study with numerous popular models that followed such as the Gipps model [17], the intelligent driver model [18], and the optimal velocity model (OVM) [19]. Many of these models are able to reproduce the same type of instabilities seen in phantom jams [20], [21].…”

mentioning

confidence: 99%

Model-Based String Stability of Adaptive Cruise Control Systems Using Field Data

Gunter

Janssen

Barbour

et al. 2020

IEEE Trans. Intell. Veh.

Self Cite

107

View full text Add to dashboard Cite

This article is motivated by the lack of empirical data on the performance of commercially available Society of Automotive Engineers level one automated driving systems. To address this, a set of car following experiments are conducted to collect data from a 2015 luxury electric vehicle equipped with a commercial adaptive cruise control (ACC) system. Velocity, relative velocity, and spacing data collected during the experiments are used to calibrate an optimal velocity relative velocity car following model for both the minimum and maximum following settings. The string stability of both calibrated models is assessed, and it is determined that the best-fit models are string unstable, indicating they are not able to prevent all traffic disturbances from amplifying into phantom jams. Based on the calibrated models, we identify the consequences of the string unstable ACC system on synthetic and empirical lead vehicle disturbances, highlighting that some disturbances can be dampened even with string unstable commercial ACC platoons of moderate size.

show abstract

“…HV traffic is observed to be an unstable system in which a small perturbation (caused by driving errors or delays) to the uniform flow will grow up with time and develop traffic congestion [2]. Traffic instability leads to less efficient fuel consumption and longer waiting time for drivers [3].…”

Section: Introductionmentioning

confidence: 99%

Stabilizing Traffic via Autonomous Vehicles: A Continuum Mean Field Game Approach

Huang

et al. 2019

2019 IEEE Intelligent Transportation Systems Conference (ITSC)

View full text Add to dashboard Cite

This paper presents scalable traffic stability analysis for both pure autonomous vehicle (AV) traffic and mixed traffic based on continuum traffic flow models. Human vehicles are modeled by a non-equilibrium traffic flow model, i.e., Aw-Rascle-Zhang (ARZ), which is unstable. AVs are modeled by the mean field game which assumes AVs are rational agents with anticipation capacities. It is shown from linear stability analysis and numerical experiments that AVs help stabilize the traffic. Further, we quantify the impact of AV's penetration rate and controller design on the traffic stability. The results may provide insights for AV manufacturers and city planners.

show abstract

Stabilizing traffic flow via a single autonomous vehicle: Possibilities and limitations

Cited by 124 publications

References 18 publications

Smoothing Traffic Flow via Control of Autonomous Vehicles

Smoothing Traffic Flow via Control of Autonomous Vehicles

Model-Based String Stability of Adaptive Cruise Control Systems Using Field Data

Stabilizing Traffic via Autonomous Vehicles: A Continuum Mean Field Game Approach

Contact Info

Product

Resources

About