New Safety and Service Guides for Sight Distance

Pfefer, R C

doi:10.1061/tpejan.0000593

Cited by 3 publications

(2 citation statements)

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“…The perception sight distance is based on the first perception of an object in the visual field at which the driver perceives movement (angular velocity). In [56] velocitydependent perception sight distances are presented that, for velocities up to 128 km/h, are larger than 9 s. We therefore have chosen h to be 6 s as a lower bound for the time-headway. Besides, our simulations show, that a good agreement with empirical data can only be obtained for h ≥ 6.…”

Section: B Calibration Of the Modelmentioning

confidence: 99%

Empirical test for cellular automaton models of traffic flow

et al. 2004

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Based on a detailed microscopic test scenario motivated by recent empirical studies of singlevehicle data, several cellular automaton models for traffic flow are compared. We find three levels of agreement with the empirical data: 1) models that do not reproduce even qualitatively the most important empirical observations, 2) models that are on a macroscopic level in reasonable agreement with the empirics, and 3) models that reproduce the empirical data on a microscopic level as well. Our results are not only relevant for applications, but also shed new light on the relevant interactions in traffic flow.

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Section: B Calibration Of the Modelmentioning

confidence: 99%

Empirical test for cellular automaton models of traffic flow

et al. 2004

View full text Add to dashboard Cite

show abstract

“…The perception sight distance is based on the first perception of an object in the visual field at which the driver perceives movement (angular velocity). In [22] velocity-dependent perception sight distances are presented which, for velocities up to 128 km h −1 , larger than 9s. We therefore have chosen h to be 6 s as a lower bound for the time-headway.…”

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confidence: 99%

Towards a realistic microscopic description of highway traffic

Knospe¹,

Santen²,

Schadschneider

et al. 2000

J. Phys. A: Math. Gen.

345

198

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Simple cellular automata models are able to reproduce the basic properties of highway traffic. The comparison with empirical data for microscopic quantities requires a more detailed description of the elementary dynamics. Based on existing cellular automata models we propose an improved discrete model incorporating anticipation effects, reduced acceleration capabilities and an enhanced interaction horizon for braking. The modified model is able to reproduce the three phases (free-flow, synchronized, and stop-and-go) observed in real traffic. Furthermore we find a good agreement with detailed empirical single-vehicle data in all phases.Cellular automata (CA) models for traffic flow [1] allow for a multitude of new applications. Since their introduction it is possible to simulate large realistic traffic networks using a microscopic model faster than real time [2,3]. But also from a theoretical point of view, these kind of models, which belong to the class of one-dimensional driven lattice gases [4], are of particular interest. Driven lattice gases allow us to study generic non-equilibrium phenomena, e.g. boundary-induced phase transitions [5]. Now, almost ten years after the introduction of the first CA models, several theoretical studies and practical applications have improved the understanding of empirical traffic phenomena (for reviews, see e.g. [6][7][8][9][10][11]). CA models have proved to be a realistic description of vehicular traffic, in particular in dense networks [2,3].Already the first CA model of Nagel and Schreckenberg [1] (hereafter cited as NaSch model) leads to a quite realistic flow-density relation (fundamental diagram). Furthermore, spontaneous jam formation has been observed. Thereby the NaSch model is a minimal model in the sense that any further simplification of the model leads to an unrealistic behaviour. In the last few years extended CA models have been proposed which are able to reproduce even more subtle effects, e.g. meta-stable states of highway traffic [12]. Unfortunately, the comparison of simulation results with empirical data on a microscopic level is not that satisfactory. So far the existing models fail to reproduce the microscopic structure observed in measurements of real traffic [13]. But in highway traffic in particular, a correct representation of the microscopic details is necessary because they largely determine the stability of a traffic state and therefore also the collective behaviour of the system. From our point of view a realistic traffic model should satisfy the following criteria. First it should reproduce, on a microscopic level, empirical data sets, and second, a very efficient implementation of the model for large-scale computer simulations should be possible. Efficient implementations are facilitated if a discrete model with local interactions is used.Our approach is based on a driving strategy which comprises four aspects:(i) At large distances the cars move (apart from fluctuations) with their desired velocity v max .(ii) At intermediate distances drivers...

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Basic Design Considerations

Underwood¹

1991

The Geometric Design of Roads

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New Safety and Service Guides for Sight Distance

Cited by 3 publications

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Empirical test for cellular automaton models of traffic flow

Empirical test for cellular automaton models of traffic flow

Towards a realistic microscopic description of highway traffic

Basic Design Considerations

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