In this paper, we propose a fuzzy system to control vehicle traffic flows on a street network. At a given point of the street network, data are collected by a peripheral unit equipped with infrared sensors. Row data are sent by the GSM/GPRS network to a centralized data processing server, where a simple set of fuzzy rules is employed to classify the row data samples into three flow states corresponding to flowing, intense and congested conditions. The core of the system is constituted by a neuro-fuzzy system, which is used to predict the time series constituted by the fuzzy membership of traffic measures to the three predefined flow states. We report the results concerning the comparison tests we carried out using an ANFIS network synthesized by a hyperplane clustering procedure and some well-known prediction techniques used as benchmarks.

A neuro-fuzzy system for the prediction of the vehicle traffic flow / Panella, Massimo; Rizzi, Antonello; FRATTALE MASCIOLI, Fabio Massimo; Martinelli, Giuseppe. - STAMPA. - 2955 LNAI(2006), pp. 110-118. ((Intervento presentato al convegno 5th International Workshop on Fuzzy Logic and Applications, WILF 2003 tenutosi a Naples nel 9 October 2003 through 11 October 2003. - LECTURE NOTES IN COMPUTER SCIENCE. [10.1007/10983652_15].

A neuro-fuzzy system for the prediction of the vehicle traffic flow

PANELLA, Massimo;RIZZI, Antonello;FRATTALE MASCIOLI, Fabio Massimo;MARTINELLI, Giuseppe
2006

Abstract

In this paper, we propose a fuzzy system to control vehicle traffic flows on a street network. At a given point of the street network, data are collected by a peripheral unit equipped with infrared sensors. Row data are sent by the GSM/GPRS network to a centralized data processing server, where a simple set of fuzzy rules is employed to classify the row data samples into three flow states corresponding to flowing, intense and congested conditions. The core of the system is constituted by a neuro-fuzzy system, which is used to predict the time series constituted by the fuzzy membership of traffic measures to the three predefined flow states. We report the results concerning the comparison tests we carried out using an ANFIS network synthesized by a hyperplane clustering procedure and some well-known prediction techniques used as benchmarks.
Fuzzy Logic and Applications
9783540310198
02 Pubblicazione su volume::02a Capitolo, Articolo o Contributo
A neuro-fuzzy system for the prediction of the vehicle traffic flow / Panella, Massimo; Rizzi, Antonello; FRATTALE MASCIOLI, Fabio Massimo; Martinelli, Giuseppe. - STAMPA. - 2955 LNAI(2006), pp. 110-118. ((Intervento presentato al convegno 5th International Workshop on Fuzzy Logic and Applications, WILF 2003 tenutosi a Naples nel 9 October 2003 through 11 October 2003. - LECTURE NOTES IN COMPUTER SCIENCE. [10.1007/10983652_15].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/112450
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