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Bus speed estimation by neural networks to improve the automatic fleet management
Salvo, G.
Amato, G.
Zito, Pietro
2007
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.
Series
European Transport / Trasporti Europei
Publisher
EUT Edizioni Università di Trieste
ISTIEE Istituto per lo studio dei trasporti nell’integrazione economica europea
Source
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.
Languages
en
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