Empirical analysis of freeway flow-density relationships

Hall, Fred L.; Allen, Brian; Gunter, Margot A

doi:10.1016/0191-2607(86)90094-4

Cited by 182 publications

(106 citation statements)

References 3 publications

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“…Fig. 4 shows a collection of possible forms of averaged fundamental diagrams consistent with empirical data [40]. While the discontinuity of the fundamental diagram now seems to be well established [41] no clear answer can be given to the question on the form of the diagram in the free-flow or high-density regime.…”

Section: Fig 4 Schematic Representation Of Fundamental Diagrams Conmentioning

confidence: 90%

“…However, contrary to this naive expectation, in recent years some nontrivial variation of flux with density have been observed. The nature of the variation of the flux with the density is still not clearly understood [40] since the details of the complex experimental setup can strongly influence the empirical results. [40].…”

Section: Flux-density Relationmentioning

confidence: 99%

“…The nature of the variation of the flux with the density is still not clearly understood [40] since the details of the complex experimental setup can strongly influence the empirical results. [40]. At low densities the data indicate a linear dependence of the flow on the density.…”

Section: Flux-density Relationmentioning

confidence: 99%

“…4 A, B) then has the so-called 'inverse-λ form'. Figure 5 shows an experimental verification of a hysteresis loop [40] at a transition from a free flow to a congested state.…”

Section: Fig 4 Schematic Representation Of Fundamental Diagrams Conmentioning

confidence: 99%

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Statistical physics of vehicular traffic and some related systems

2000

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In the so-called "microscopic" models of vehicular traffic, attention is paid explicitly to each individual vehicle each of which is represented by a "particle"; the nature of the "interactions" among these particles is determined by the way the vehicles influence each others' movement. Therefore, vehicular traffic, modeled as a system of interacting "particles" driven far from equilibrium, offers the possibility to study various fundamental aspects of truly nonequilibrium systems which are of current interest in statistical physics. Analytical as well as numerical techniques of statistical physics are being used to study these models to understand rich variety of physical phenomena exhibited by vehicular traffic. Some of these phenomena, observed in vehicular traffic under different circumstances, include transitions from one dynamical phase to another, criticality and self-organized criticality, metastability and hysteresis, phase-segregation, etc. In this critical review, written from the perspective of statistical physics, we explain the guiding principles behind all the main theoretical approaches. But we present detailed discussions on the results obtained mainly from the so-called "particle-hopping" models, particularly emphasizing those which have been formulated in recent years using the language of cellular automata.

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Section: Fig 4 Schematic Representation Of Fundamental Diagrams Conmentioning

confidence: 90%

Section: Flux-density Relationmentioning

confidence: 99%

Section: Flux-density Relationmentioning

confidence: 99%

“…4 A, B) then has the so-called 'inverse-λ form'. Figure 5 shows an experimental verification of a hysteresis loop [40] at a transition from a free flow to a congested state.…”

Section: Fig 4 Schematic Representation Of Fundamental Diagrams Conmentioning

confidence: 99%

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Statistical physics of vehicular traffic and some related systems

2000

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“…Since shockwaves are caused by variation in speed differentials, the two traffic streams have different traffic density with the leading traffic stream's density greater than the following traffic stream. It is generally accepted that, for uninterrupted traffic flow, there is a density-speed relationship [13]. In our simulation, we assume the so-called triangular fundamental diagram [14] [15] with density ρ and speed V.…”

Section: A Traffic Scenariosmentioning

confidence: 99%

Multi-Hop Broadcasting in Vehicular Ad Hoc Networks with Shockwave Traffic

Chen

Jin

Regan

2010

2010 7th IEEE Consumer Communications and Networking Conference

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Abstract-A primary goal of intelligent transportation systems (ITS) is to improve road safety. The ability for vehicles to communicate is a promising way to alleviate traffic accidents by reducing the response time associated with human reaction to nearby drivers. In addition the limitations of standard driving can be overcome by providing drivers with instantaneous information about complications up ahead. Shockwaves, induced by vehicle speed differentials, are a typical mobility pattern that occurs with the formation and propagation of vehicle queues. These induce sudden braking and increase the occurrence of traffic incidents. In this paper, we investigate safety applications in highways with shockwave mobility and different lane configurations in vehicular ad hoc networks (VANET). We evaluate the performance of multi-hop broadcast communication using the ns-2 simulator with vehicles following a shockwave mobility pattern in fully-connected traffic streams. We propose mechanism to improve broadcast reliability using dynamic transmission range that leverages our understanding of fundamental traffic flow relationships.

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Traffic flow models with ‘slow‐to‐start’ rules

1997

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Abstract. We investigate two models for 'traffic flow with modified acceleration ('slow-to-start') rules. Even in the simplest case w , , , = 1 these rules break the 'particle-hole' symmetry of the model. We determine the fundamental diagram (flow -density relationship) using the so-called car-oriented mean-field approach (COMF) which yields the exact solution of the basic model with w,,,, = 1.Here we find that this is no longer true for the models with modified acceleration rules, but the results are still in good agreement with simulations. We also compare the effects of the two different slow-to-start rules and discuss their relevance for real traffic. In addition, in one of these models we find a new phase transition to a completely jammed state.

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Empirical analysis of freeway flow-density relationships

Cited by 182 publications

References 3 publications

Statistical physics of vehicular traffic and some related systems

Statistical physics of vehicular traffic and some related systems

Multi-Hop Broadcasting in Vehicular Ad Hoc Networks with Shockwave Traffic

Traffic flow models with ‘slow‐to‐start’ rules

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