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Traffic congestion reconstruction with Kerner's three-phase theory

About: Traffic congestion reconstruction with Kerner's three-phase theory is a(n) research topic. Over the lifetime, 5009 publication(s) have been published within this topic receiving 86817 citation(s).
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Journal Article
Abstract: This paper uses the method of kinematic waves, developed in part I, but may be read independently. A functional relationship between flow and concentration for traffic on crowded arterial roads has been postulated for some time, and has experimental backing (§2). From this a theory of the propagation of changes in traffic distribution along these roads may be deduced (§§2, 3). The theory is applied (§4) to the problem of estimating how a ‘hump’, or region of increased concentration, will move along a crowded main road. It is suggested that it will move slightly slower than the mean vehicle speed, and that vehicles passing through it will have to reduce speed rather suddenly (at a ‘shock wave’) on entering it, but can increase speed again only very gradually as they leave it. The hump gradually spreads out along the road, and the time scale of this process is estimated. The behaviour of such a hump on entering a bottleneck, which is too narrow to admit the increased flow, is studied (§5), and methods are obtained for estimating the extent and duration of the resulting hold-up. The theory is applicable principally to traffic behaviour over a long stretch of road, but the paper concludes (§6) with a discussion of its relevance to problems of flow near junctions, including a discussion of the starting flow at a controlled junction. In the introductory sections 1 and 2, we have included some elementary material on the quantitative study of traffic flow for the benefit of scientific readers unfamiliar with the subject.

3,983 citations


Journal ArticleDOI
Masako Bando1, Katsuya Hasebe1, Atsuko Nakayama, Akira Shibata2  +1 moreInstitutions (2)
01 Feb 1995-Physical Review E
TL;DR: In this model, the legal velocity function is introduced, which is a function of the headway of the preceding vehicle, and the evolution of traffic congestion is observed with the development of time.
Abstract: We present a dynamical model of traffic congestion based on the equation of motion of each vehicle. In this model, the legal velocity function is introduced, which is a function of the headway of the preceding vehicle. We investigate this model with both analytic and numerical methods. The stability of traffic flow is analyzed, and the evolution of traffic congestion is observed with the development of time.

2,163 citations


01 Jan 1952-

1,672 citations


Proceedings ArticleDOI
01 Oct 1993-
Abstract: We demonstrate that Ethernet local area network (LAN) traffic is statistically self-similar, that none of the commonly used traffic models is able to capture this fractal behavior, and that such behavior has serious implications for the design, control, and analysis of high-speed, cell-based networks. Intuitively, the critical characteristic of this self-similar traffic is that there is no natural length of a "burst": at every time scale ranging from a few milliseconds to minutes and hours, similar-looking traffic bursts are evident; we find that aggregating streams of such traffic typically intensifies the self-similarity ("burstiness") instead of smoothing it.Our conclusions are supported by a rigorous statistical analysis of hundreds of millions of high quality Ethernet traffic measurements collected between 1989 and 1992, coupled with a discussion of the underlying mathematical and statistical properties of self-similarity and their relationship with actual network behavior. We also consider some implications for congestion control in high-bandwidth networks and present traffic models based on self-similar stochastic processes that are simple, accurate, and realistic for aggregate traffic.

1,053 citations


01 Jan 1971-

1,014 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
201820
2017206
2016305
2015336
2014398
2013373