Abstract
In recent years, there has been a growing interest in the social dimension of travel, and how travel decisions are influenced not only by the global state of the transportation system, but also by joint decisions and interactions with social contacts. Empirical studies pointed out the relevance of certain types of social interactions to model travel behavior correctly: synchronization of household members has been identified as significantly influencing individual’s travel decisions, and friendships were shown to influence the choice of leisure locations.
Multiagent approaches, by representing decision making at the level of the individual, seem to be one of the most promising approaches to take into account such interactions when forecasting.
The work presented here extends a state of the art multiagent simulation software, MATSim, with capabilities to capture joint decisions. It consists of a general framework to allow arbitrary joint behaviors to be represented, without constraints on the topology of the social network. An implementation of this framework for the important case of intrahousehold ride sharing is proposed, and demonstrated on a simple test scenario.
The results show that the extended process is able to find the expected state, and is mature for validation against travel diary data.
The work presented in this paper is part of the project ‘EUNOIA: Evolutive User-centric Networks for Intra-urban Accessibility’, funded under the European Union’s Seventh Framework Programme.
Notes
This paper is part of a special issue on Agent-based Microsimulation Techniques