Rossetti, R. and Lui, R. (2005) An agent-based approach to assess drivers’ interaction with pre-trip information systems. Journal of Intelligent Transportation Systems., 9 (1). pp. 1-10. ISSN 1547-2442
Abstract
This article reports on the practical use of a multi-agent microsimulation framework to address the issue of assessing drivers’ responses to pretrip information systems. The population of drivers is represented as a community of autonomous agents, and travel demand results from the decision-making deliberation performed by each individual of the population as regards route and departure time. A simple simulation scenario was devised, where pretrip information was made available to users on an individual basis so that its effects at the aggregate level could be observed. The simulation results show that the overall performance of the system is very likely affected by exogenous information, and these results are ascribed to demand formation and network topology. The expressiveness offered by cognitive approaches based on predicate logics, such as the one used in this research, appears to be a promising approximation to fostering more complex behavior modelling, allowing us to represent many of the mental aspects involved in the deliberation process.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | Copyright held by Taylor and Francis. This version has been uploaded in accordance with their self archiving policy. |
Keywords: | Cognitive Agents; Pretrip Information Systems; Driver Behavior Modelling; Microscopic Simulation |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) |
Depositing User: | Adrian May |
Date Deposited: | 01 Oct 2007 10:14 |
Last Modified: | 25 Oct 2016 06:20 |
Published Version: | http://dx.doi.org/10.1080/15472450590912529 |
Status: | Published |
Publisher: | Taylor & Francis |
Identification Number: | DOI: 10.1080/15472450590912529 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:3385 |
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