A new approach for modeling of Fundamental Diagrams

Wu, Ning

doi:10.1016/s0965-8564(01)00043-x

Cited by 51 publications

(49 citation statements)

References 5 publications

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“…It should be noted again that the ANFIS model was trained based on actual data obtained on German highways. The previously mentioned paper [24] is one of the most signifi cant in the recent history of traffi c fl ow theory studies. One of the conclusions which the author has come to in that paper, is that the sequence distance is not a function of speed, which explains the paradox shown in the above fi gure.…”

Section: Discussion Of the Resultsmentioning

confidence: 99%

“…The new model of the basic traffi c fl ow diagram as a function of homogenous states, which was confi rmed by research conducted on German highways, is one of the most important papers in the recent history of traffi c fl ow theory studies [24]. According to the model, the basic traffi c fl ow diagram can entirely be defi ned using the following fi ve key parameters: desired speed, sequence distance between vehicles in the fl ow, average traffi c fl ow speed, average forced fl ow sequence distance and forced fl ow vehicle density.…”

Section: Introductionmentioning

confidence: 93%

“…Figure 1. [24] shows a diagram of interdependence between speed and traffi c fl ow density on German highway A43, for a saturated state of fl ow. The author has determined that the form of the curve shown in the fi gure is identical for highways and other categories of motorways.…”

Section: Introductionmentioning

confidence: 99%

“…This model is based on a neuro-fuzzy logic system and also on subtractive clustering of data used for training a neural network. The data for the training of the neural network have been taken from the paper [24]. That data has been obtained from measurements carried out on German highways.…”

Section: Introductionmentioning

confidence: 99%

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Modelling of the Interdependence Between Speed and Traffic Flow Density. A Neuro – Fuzzy Logic Approach

Davidović

Stevanovic

2016

JTTTP

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Abstract. The speed-traffi c fl ow density interdependence diagram has a number of varia ons, star ng with the theore cal model, through various empirical models that were developed and models based on actual research done on traffi c fl ow. The func onal interdependence is obtained using the Sugeno fuzzy logic system, where representa ve values proposed in HCM 2010 have been adopted as parameters of output associa on func ons. Subsequently the neural network is trained based on actual traffi c fl ow data, which by adjus ng the associa on func on of the fuzzy logic system yields an output form of the basic traffi c fl ow diagram. It was no ced that this hybrid expert system produces be er output results by applying the "subtrac ve clustering" method on data that are used for training a neural network. Finally, the model was tested on several input data groups, and the interdependence between speed and traffi c fl ow density is shown in graphical form.Keyword. Basic traffi c fl ow diagram, traffi c fl ow theory, neural networks, fuzzy logic, subtrac ve clustering, hybrid expert systems.

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Section: Discussion Of the Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Modelling of the Interdependence Between Speed and Traffic Flow Density. A Neuro – Fuzzy Logic Approach

Davidović

Stevanovic

2016

JTTTP

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“…The association between speed, flow and density is often referred to as the fundamental diagram. As Wu (2002) points out, the fundamental identity specifies the fundamental diagram only up to one degree of freedom. In other words, one has to impose an additional constraint on any pair of the three variables in order to specify the fundamental diagram fully.…”

Section: Introductionmentioning

confidence: 99%

Using principal curves to analyse traffic patterns on freeways

Einbeck

Dwyer

2011

Transportmetrica

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Investigating cultural aspects in the fundamental diagram using convolutional neural networks and virtual agent simulation

Favaretto

Santos²,

Balotin³

et al. 2019

Computer Animation & Virtual

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This paper presents a study, organized in two phases, regarding group behavior in a controlled experiment focused on differences in an important attribute that vary across cultures—personal spaces. First, we want to study and compare the spatial behavior different populations adopt with respect to their personal space. Second, we want to use simulation of virtual agents to artificially generate movements of people in similar situations and validate them using real video sequences. Our main goal is to be able to extract from video sequences and then simulate variations in populations in a coherent way with literature that studies cultural aspects. In addition to the cultural aspects, we also investigate the personality model in the studied videos using OCEAN (Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism). Finally, we propose a way to simulate the fundamental diagram experiment from other countries using the OCEAN psychological trait model as input. Results indicate that the simulated countries have consistent characteristics with the expected literature.

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A new approach for modeling of Fundamental Diagrams

Cited by 51 publications

References 5 publications

Modelling of the Interdependence Between Speed and Traffic Flow Density. A Neuro – Fuzzy Logic Approach

Modelling of the Interdependence Between Speed and Traffic Flow Density. A Neuro – Fuzzy Logic Approach

Using principal curves to analyse traffic patterns on freeways

Investigating cultural aspects in the fundamental diagram using convolutional neural networks and virtual agent simulation

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