Simplified cellular automaton model for city traffic

Simon, P.M.; Nagel, Kai

doi:10.1103/physreve.58.1286

Cited by 84 publications

(39 citation statements)

References 12 publications

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“…Then, one can follow the prescriptions of the NaSch model for describing the positions, speeds and accelerations of the vehicles [275,276] as well as for taking into account the interactions among the vehicles moving along the same street. Moreover, one should flip the color of the signal periodically at regular interval of T (T ≫ 1) time steps where, during each unit of the discrete time interval every vehicle facing green signal should get an opportunity to move forward from one cell to the next.…”

Section: Marriage Of the Nasch Model And The Bml Model; A "Unified" Cmentioning

confidence: 99%

“…The intrinsic stochasticity of the dynamics, which triggers the onset of jamming, is similar to that in the NaSch model, while the phenomenon of complete jamming through self-organization as well as the final jammed configurations (see The "unified" model has been formulated intentionally to keep it as simple as possible and at the same time capture some of interesting features of the NaSch model as well as the BML model. We believe that this model can be generalized (i) to allow traffic flow both ways on each street which may consist of more than one lane, (ii) to make more realistic rules for the right-of-the-way at the crossings and turning of the vehicles, (iii) to implement different types of synchronization or staggering of traffic lights [276] (including green-wave), etc.…”

Section: Marriage Of the Nasch Model And The Bml Model; A "Unified" Cmentioning

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: Marriage Of the Nasch Model And The Bml Model; A "Unified" Cmentioning

confidence: 99%

Section: Marriage Of the Nasch Model And The Bml Model; A "Unified" Cmentioning

confidence: 99%

Statistical physics of vehicular traffic and some related systems

2000

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“…More realistic vehicular traffic models have been developed as generalizations of the BML model [19][20][21][22]. Such generalizations are essentially an extension BML model for which the streets have an arbitrary length (instead of a single cell) and vehicles traveling between the intersections behave according to the NaSch model.…”

Section: Related Workmentioning

confidence: 99%

“…In the work presented by Simon and Nagel [19], the authors developed a more elaborate combination of the BML and NaSch models. Streets with different capacities can be modeled.…”

Section: Related Workmentioning

confidence: 99%

Deliberative Self-Organizing Traffic Lights with Elementary Cellular Automata

2017

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Self-organizing traffic lights have shown considerable improvements compared to traditional methods in computer simulations. Self-organizing methods, however, use sophisticated sensors, increasing their cost and limiting their deployment. We propose a novel approach using simple sensors to achieve self-organizing traffic light coordination. The proposed approach involves placing a computer and a presence sensor at the beginning of each block; each such sensor detects a single vehicle. Each computer builds a virtual environment simulating vehicle movement to predict arrivals and departures at the downstream intersection. At each intersection, a computer receives information across a data network from the computers of the neighboring blocks and runs a self-organizing method to control traffic lights. Our simulations showed a superior performance for our approach compared with a traditional method (a green wave) and a similar performance (close to optimal) compared with a self-organizing method using sophisticated sensors but at a lower cost. Moreover, the developed sensing approach exhibited greater robustness against sensor failures.

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“…Many models, such as in Ref. [7,12,13] have been developed to deal with driving on urban networks. To our knowledge, previous models normally implicitly assume that the headways (=distance/speed) are 1 second, that is, 2-second rule is not considered in those models.…”

Section: Introductionmentioning

confidence: 99%

A Realistic Cellular Automata Model to Simulate Traffic Flow at Urban Roundabouts

Wang

Liu

2005

Lecture Notes in Computer Science

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Abstract. In this paper a realistic cellular automata model is proposed to simulate traffic flow at single-lane roundabouts. The proposed model is built on fine grid Cellular Automata (CA), so it is able to simulate actual traffic flow more realistically. Several important novel features are employed in our model. Firstly, 1.5-second rule is used for the headway (=distance /speed) in carfollowing process. Secondly, vehicles movement on urban streets are simulated based on the assumption of speed changes following a Gaussian (normal) distribution and is calibrated with the field data. Thirdly, driver behavior is modeled by using a truncated Gaussian distribution. Numerical results show that our method is feasible and valid.

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Simplified cellular automaton model for city traffic

Cited by 84 publications

References 12 publications

Statistical physics of vehicular traffic and some related systems

Statistical physics of vehicular traffic and some related systems

Deliberative Self-Organizing Traffic Lights with Elementary Cellular Automata

A Realistic Cellular Automata Model to Simulate Traffic Flow at Urban Roundabouts

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