Freeway traffic data prediction via artificial neural networks for use in a fuzzy logic ramp metering algorithm

Cynthia Taylor; Deirdre Meldrum

Freeway traffic data prediction via artificial neural networks for use in a fuzzy logic ramp metering algorithm

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A multi-layer perceptron type of artificial neural network predicts congested freeway data while demonstrating robustness to faulty loop detector data. Test results on historical data from the I-5 freeway in Seattle, Washington demonstrate that a neural network can successfully predict volume and occupancy one minute in advance, as well as fill in the gaps for missing data with an appropriate prediction. The volume and occupancy predictions will be used as inputs to a fuzzy logic ramp metering algorithm currently under development.

Original language	English (US)
Title of host publication	Intelligent Vehicles Symposium, Proceedings
Editors	Anon
Place of Publication	Piscataway, NJ, United States
Publisher	IEEE
Pages	308-313
Number of pages	6
State	Published - 1994
Externally published	Yes
Event	Proceedings of the Intelligent Vehicles'94 Symposium - Paris, Fr Duration: Oct 24 1994 → Oct 26 1994

Other

Other	Proceedings of the Intelligent Vehicles'94 Symposium
City	Paris, Fr
Period	10/24/94 → 10/26/94

ASJC Scopus subject areas

General Engineering

Cite this

@inproceedings{5566d49abc8c4272b7cd009f89d396d7,

title = "Freeway traffic data prediction via artificial neural networks for use in a fuzzy logic ramp metering algorithm",

abstract = "A multi-layer perceptron type of artificial neural network predicts congested freeway data while demonstrating robustness to faulty loop detector data. Test results on historical data from the I-5 freeway in Seattle, Washington demonstrate that a neural network can successfully predict volume and occupancy one minute in advance, as well as fill in the gaps for missing data with an appropriate prediction. The volume and occupancy predictions will be used as inputs to a fuzzy logic ramp metering algorithm currently under development.",

author = "Cynthia Taylor and Deirdre Meldrum",

year = "1994",

language = "English (US)",

pages = "308--313",

editor = "Anon",

booktitle = "Intelligent Vehicles Symposium, Proceedings",

publisher = "IEEE",

note = "Proceedings of the Intelligent Vehicles'94 Symposium ; Conference date: 24-10-1994 Through 26-10-1994",

}

TY - GEN

T1 - Freeway traffic data prediction via artificial neural networks for use in a fuzzy logic ramp metering algorithm

AU - Taylor, Cynthia

AU - Meldrum, Deirdre

PY - 1994

Y1 - 1994

N2 - A multi-layer perceptron type of artificial neural network predicts congested freeway data while demonstrating robustness to faulty loop detector data. Test results on historical data from the I-5 freeway in Seattle, Washington demonstrate that a neural network can successfully predict volume and occupancy one minute in advance, as well as fill in the gaps for missing data with an appropriate prediction. The volume and occupancy predictions will be used as inputs to a fuzzy logic ramp metering algorithm currently under development.

AB - A multi-layer perceptron type of artificial neural network predicts congested freeway data while demonstrating robustness to faulty loop detector data. Test results on historical data from the I-5 freeway in Seattle, Washington demonstrate that a neural network can successfully predict volume and occupancy one minute in advance, as well as fill in the gaps for missing data with an appropriate prediction. The volume and occupancy predictions will be used as inputs to a fuzzy logic ramp metering algorithm currently under development.

UR - http://www.scopus.com/inward/record.url?scp=0028700296&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0028700296&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0028700296

SP - 308

EP - 313

BT - Intelligent Vehicles Symposium, Proceedings

A2 - Anon, null

PB - IEEE

CY - Piscataway, NJ, United States

T2 - Proceedings of the Intelligent Vehicles'94 Symposium

Y2 - 24 October 1994 through 26 October 1994

ER -

Freeway traffic data prediction via artificial neural networks for use in a fuzzy logic ramp metering algorithm

Abstract

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ASJC Scopus subject areas

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