Parameterization of traffic flow using Sammon-Fuzzy clustering

Parameterization of traffic flow using Sammon-Fuzzy clustering

Modelling the traffic conditions has become necessary in the modern connected society. We have attempted to use clustering algorithms to classify traffic flow in and around Pune city into classes representing geographical locations of sampling of the data. The algorithm employs Sammon's mapping...

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Hauptverfasser: Deshpande, Jaidev, Dande, Ketan, Deshpande, Varun, Abhyankar, Aditya
Format: Tagungsbericht
Sprache:eng
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Cities and towns
Clustering algorithms
Fluid flow measurement
Global Positioning System
Organizing
Sampling methods
Time measurement
Traffic control
Vehicles
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creator Deshpande, Jaidev
Dande, Ketan
Deshpande, Varun
Abhyankar, Aditya
description Modelling the traffic conditions has become necessary in the modern connected society. We have attempted to use clustering algorithms to classify traffic flow in and around Pune city into classes representing geographical locations of sampling of the data. The algorithm employs Sammon's mapping along with fuzzy clustering algorithms to cluster the data. Such high-end parameterization of traffic flow can help in better control and real-time modelling methods. The algorithm is applied to two different databases - traffic inside the city and traffic outside it and approximately 95% accuracy is obtained across vivid conditions.
doi_str_mv 10.1109/ICVES.2009.5400320
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subjects Cities and towns
Clustering algorithms
Fluid flow measurement
Global Positioning System
Organizing
Sampling methods
Time measurement
Traffic control
Vehicles
title Parameterization of traffic flow using Sammon-Fuzzy clustering
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