Agent-based framework for the assessment of drivers' decision-making

• Tipo: Artigo em Revista Científica Internacional
• Data: 2000

Autores

Rosaldo J. F. Rossetti (Autor) Outra; Bampi, S (Autor) Outra; Liu, R (Autor) Outra; Van, VD (Autor) Outra

Revista

Título: Knowledge Discovery from Sensor Data

Vol. 10

Páginas: 387-392

ISSN: 1550-4786

Editora: IEEE

Indexação

Scopus - 28 Citações

Outras Informações

ID Authenticus: P-008-P9K

Abstract (EN): This paper addresses the complexity of modelling drivers' behaviour by the adoption of agent-based techniques. As human factors are central to Intelligent Transportation Systems (ITS), it has become imperative to consider the uncertainty and variability inherent in drivers' behaviour for simulation frameworks aimed at assessing ITS technologies. An agent-based extension to an existing microscopic simulation model, DRACULA, is suggested, which aims at benefiting from characteristics such as reasoning capabilities and autonomy, offered by agent-based approaches. The scope of this work is particularly concerned with the departure time and route choice processes in a commuter scenario.

Idioma: Inglês

Tipo (Avaliação Docente): Científica