2000
DOI: 10.1007/s100510051176
|View full text |Cite
|
Sign up to set email alerts
|

Decentralized delayed-feedback control of an optimal velocity traffic model

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

2
53
0

Year Published

2014
2014
2018
2018

Publication Types

Select...
8
1

Relationship

0
9

Authors

Journals

citations
Cited by 127 publications
(55 citation statements)
references
References 0 publications
2
53
0
Order By: Relevance
“…They are considered as multi-agent and are defined by a system of differential equations, each of which captures a different state. Konishi et al (2000) proposed a coupled map (CM) car-following model to describe the dynamical behavior of an open flow. Ge et al (2014) proposed a control method to suppress two-lane traffic congestion.…”
Section: Overview Of Car-following Modelsmentioning
confidence: 99%
“…They are considered as multi-agent and are defined by a system of differential equations, each of which captures a different state. Konishi et al (2000) proposed a coupled map (CM) car-following model to describe the dynamical behavior of an open flow. Ge et al (2014) proposed a control method to suppress two-lane traffic congestion.…”
Section: Overview Of Car-following Modelsmentioning
confidence: 99%
“…The typical OVM is presented as Referring to previous study 14,15 , the velocity difference between the nth and its leading vehicle…”
Section: Improved Modelmentioning
confidence: 99%
“…According to stability analysis method [15][16][17] , the stable condition of the modified car-following model can be shown as …”
Section: Stability Analysismentioning
confidence: 99%
“…Zhang and Wang [10] proposed a mixed linear-nonlinear CML model for image encryption. Konishi et al [11] presented a car-following CML model for suppression of traffic congestion. Kohar et al [12] used a quadratic CML method to research the role of network topology in noise reduction.…”
Section: Introductionmentioning
confidence: 99%