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

• Type: Article in International Scientific Journal
• Date: 2000

Authors

Rosaldo J. F. Rossetti (Author) Other; Bampi, S (Author) Other; Liu, R (Author) Other; Van, VD (Author) Other

Journal

Title: Knowledge Discovery from Sensor Data

Vol. 10

Pages: 387-392

ISSN: 1550-4786

Publisher: IEEE

Indexing

Scopus - 28 Citations

Other information

Authenticus ID: 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.

Language: English

Type (Professor's evaluation): Scientific