Traffic count is fundamental for monitoring traffic flows on a transportation network and for the solution of different problems (as, for example, the estimation of the Origin/Destination demand matrix). Different techniques and instruments, each one with specific advantages and disadvantages, can be used for counting the vehicles on a transportation network. In this paper the use of a passive acoustic detector together with two neural networks working sequentially is proposed for counting the cars on the urban roads. The results obtained with this system are satisfactory and comparable with the existing ones. The proposed system also shows a large improvement of the cost/benefit ratio.

Calabro´, A., Postorino, M., Sarne', G. (2002). An Acoustic Passive Detector for Traffic Counts with Neural Networks. In Neural Nets WIRN Vietri-01 - Perspectives in Neural Computing (pp.215-220). DEU : springer [doi: 10.1007/978-1-4471-0219-9_23].

An acoustic passive detector for traffic counts with neural networks

SARNE' G
2002

Abstract

Traffic count is fundamental for monitoring traffic flows on a transportation network and for the solution of different problems (as, for example, the estimation of the Origin/Destination demand matrix). Different techniques and instruments, each one with specific advantages and disadvantages, can be used for counting the vehicles on a transportation network. In this paper the use of a passive acoustic detector together with two neural networks working sequentially is proposed for counting the cars on the urban roads. The results obtained with this system are satisfactory and comparable with the existing ones. The proposed system also shows a large improvement of the cost/benefit ratio.
No
paper
Scientifica
TRAFFIC DETECTOR; ACOUSTIC SIGNATURE; NEURAL NETWORK;
English
NEURAL NETS WIRN VIETRI-01 (WIRN ’01),
978-1-85233-505-2
NEURAL NETS WIRN VIETRI-01 (WIRN ’01),
Calabro´, A., Postorino, M., Sarne', G. (2002). An Acoustic Passive Detector for Traffic Counts with Neural Networks. In Neural Nets WIRN Vietri-01 - Perspectives in Neural Computing (pp.215-220). DEU : springer [doi: 10.1007/978-1-4471-0219-9_23].
Calabro´, A; Postorino, M; Sarne', G
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/299193
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