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Please use this identifier to cite or link to this item: http://hdl.handle.net/10077/5960

Title: Bus speed estimation by neural networks to improve the automatic fleet management
Authors: Salvo, G.
Amato, G.
Zito, Pietro
Keywords: Radial Basis Neural Network
Public Transport Performances
AVM system
Issue Date: 2007
Publisher: EUT Edizioni Università di Trieste
ISTIEE Istituto per lo studio dei trasporti nell’integrazione economica europea
Citation: G. Salvo, G. Amato, P. Zito, "Bus speed estimation by neural networks to improve the automatic fleet management", in: European Transport / Trasporti Europei, XIII (2007) 37, pp. 93-104.
Series/Report no.: European Transport / Trasporti Europei
Abstract: In the urban areas, public transport service interacts with the private mobility. Moreover, on each link of the urban public transport network, the bus speed is affected by a high variability over time. It depends on the congestion level and the presence of bus way or no. The scheduling reliability of the public transport service is crucial to increase attractiveness against private car use. A comparison between a Radial Basis Function network (RBF) and Multi layer Perceptron (MLP) was carried out to estimate the average speed, analysing the dynamic bus location data achieved by an AVMS (Automatic Vehicle Monitoring System). Collected data concern bus location, geometrical parameters and traffic conditions. Public Transport Company of Palermo provided these data.
URI: http://hdl.handle.net/10077/5960
ISSN: 1825-3997
Appears in Collections:European Transport / Trasporti Europei (2007) 37/XIII

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