This chapter describes the pedestrian navigation method reflecting individual preference for route selection, and discusses the validity of the fuzzy measures and integrals model applied to route selection. The presented method selects the route with the highest subjective satisfaction degree which is estimated by a road satisfaction degree evaluation model (RSEM). The RSEM applies fuzzy measures and integrals to calculate the subjective satisfaction degrees of a road. The input to the RSEM is a set of road attributes expressing subjective impression of a road. The road attributes are decided according to the individual preference expressed by fuzzy measures. Experimental results and analyses of the RSEM show that the route selected by the presented method is preferable to other routes and the RSEM is individualized appropriately.
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Akasaka, Y., Onisawa, T. (2008). Personalized Pedestrian Navigation System with Subjective Preference Based Route Selection. In: Da Ruan, Hardeman, F., van der Meer, K. (eds) Intelligent Decision and Policy Making Support Systems. Studies in Computational Intelligence, vol 117. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78308-4_5
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DOI: https://doi.org/10.1007/978-3-540-78308-4_5
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