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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/21127

Title: Organizational-based model and agent-based simulation for long-term carpooling
Authors: Hussain, Iftikhar
Knapen, Luk
Galland, S.
Yasar, Ansar-Ul-Haque
Bellemans, Tom
Janssens, Davy
Wets, Geert
Issue Date: 2016
Abstract: Modeling the interaction between individual agents becomes progressively important in recent research. Carpooling for commuters is a specific transportation problem where cooperation between agents is essential while executing their daily schedule. Organization-based modeling provides the ability to determine where the relationships between agents exist and how these relationships influence the results. This paper presents both the design of an organizational model that is mapped to an agent-based simulation model and a proof of concept implementation. It analyzes various effects of agent interaction and behavior adaptation for sets of candidate carpoolers. The goal is to limit the interactions of autonomous agents, to enable communication to trigger the negotiation process within social groups. The start of the carpooling process depends on the individuals’ objectives and intention to carpool. The success of negotiation highly depends on the trip departure time preference, on the individuals’ profile, route optimization and on the effect of constraining activities. In order to cooperate individuals adapt their agenda according to personal preferences and limitations. The carpooling social network was established using results predicted by the FEATHERS operational activity-based model for Flanders (Belgium). From the simulation’s discussions, it is possible to portray the real picture of the potential carpoolers throughout their carpooling period. The Janus (multi-agent) platform is used for simulating the interactions of autonomous individuals.
Notes: Hussain, I (reprint author), Hasselt Univ, Transportat Res Inst IMOB, Wetenschapspk 5 Bus 6, B-3590 Diepenbeek, Belgium. iftikhar.hussain@uhasselt.be
URI: http://hdl.handle.net/1942/21127
DOI: 10.1016/j.future.2016.02.019
ISI #: 000381843200011
ISSN: 0167-739X
Category: A1
Type: Journal Contribution
Validation: ecoom, 2017
Appears in Collections: Research publications

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