Abstract
Individuals choose locations for conducting specific activities generally under limited information conditions and update their mental map during traveling and implementing activities. In an earlier study, we proposed a Bayesian belief network to model an individual's mental map and spatial learning. In this paper, we develop complementary measures of expected utility and information gain and show how they can be integrated in a dynamic utility function of locations. The proposed model can be seen as an extension of the existing discrete choice model to account for the dynamics of location choice following from learning. Numerical simulations illustrate the model and demonstrate mental-map and learning impacts on location choice.
Original language | English |
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Title of host publication | Proceedings of the 83rd Annual Meeting of the Transportation Research Board, January 11-15, Washington DC (CD-rom) |
Publication status | Published - 2004 |
Event | 83rd Transportation Research Board Annual Meeting - Washington, United States Duration: 11 Jan 2004 → 15 Jan 2004 |
Conference
Conference | 83rd Transportation Research Board Annual Meeting |
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Country/Territory | United States |
City | Washington |
Period | 11/01/04 → 15/01/04 |