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Title:
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Framework for Traffic Pattern Identification: Required Step for Short-term Forecasting
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Author:
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Casas Vilaró, Jordi; Ruiz de Villa, Alex; Torday, Alexandre
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Other authors:
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Universitat de Vic. Facultat d'Empresa i Comunicació; Australasian Transport Research Forum (35è: 2012: Brisbane, Queensland, Australia); ATRF 2012 |
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Notes:
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In the world of transport management, the term ‘anticipation’ is gradually replacing ‘reaction’. Indeed, the
ability to forecast traffic evolution in a network should ideally form the basis for many traffic management strategies
and multiple ITS applications. Real-time prediction capabilities are therefore becoming a concrete need for the
management of networks, both for urban and interurban environments, and today’s road operator has increasingly
complex and exacting requirements. Recognising temporal patterns in traffic or the manner in which sequential
traffic events evolve over time have been important considerations in short-term traffic forecasting. However, little
work has been conducted in the area of identifying or associating traffic pattern occurrence with prevailing traffic
conditions. This paper presents a framework for detection pattern identification based on finite mixture models using
the EM algorithm for parameter estimation. The computation results have been conducted taking into account the
traffic data available in an urban network. |
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Subject(s):
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-Transport
-Circulació |
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Rights:
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Tots els drets reservats
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Document type:
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Conference Object |
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Published by:
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Australian Transport Research Forum
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Share:
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