“Gap acceptance” behaviour oversees pedestrians crossing manoeuvre at unsignalized road crossings. From a scientific point of view, the study of pedestrians behaviour has a particular interest, since the underlying factors of behavioural interaction between pedestrians and motor vehicles drivers have a strong non-deterministic component, which makes their simulation very complex. In this paper a Fuzzy logic model for representation and simulation of pedestrian behaviour in such a manoeuvre is proposed. The calibration of Fuzzy model membership functions is executed through an Adaptive Neural Network which considers a sample of “gap acceptance” decisions collected on field. The analysis method is at first theoretically defined and then applied to a real pedestrian crossing.

An Adaptive Neuro-Fuzzy Inference System for Simulation of Pedestrians Behaviour at Unsignalized Roadway Crossings

OTTOMANELLI, Michele;
2010-01-01

Abstract

“Gap acceptance” behaviour oversees pedestrians crossing manoeuvre at unsignalized road crossings. From a scientific point of view, the study of pedestrians behaviour has a particular interest, since the underlying factors of behavioural interaction between pedestrians and motor vehicles drivers have a strong non-deterministic component, which makes their simulation very complex. In this paper a Fuzzy logic model for representation and simulation of pedestrian behaviour in such a manoeuvre is proposed. The calibration of Fuzzy model membership functions is executed through an Adaptive Neural Network which considers a sample of “gap acceptance” decisions collected on field. The analysis method is at first theoretically defined and then applied to a real pedestrian crossing.
Soft Computing in Industrial Applications
978-3-642-11281-2
Springer
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/11003
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