“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.
|Titolo:||An Adaptive Neuro-Fuzzy Inference System for Simulation of Pedestrians Behaviour at Unsignalized Roadway Crossings|
|Titolo del libro:||Soft Computing in Industrial Applications|
|Data di pubblicazione:||2010|
|Digital Object Identifier (DOI):||10.1007/978-3-642-11282-9_27|
|Appare nelle tipologie:||2.1 Contributo in volume (Capitolo o Saggio)|