In this paper, a method for fusing fuzzy data relevant both to drivers' experience and provided information is presented. Expected travel time is then updated according to the results of fusion. The method takes into account the "compatibility" of data originating from different sources, and provides information about acceptability of results. Influence of uncertainty on drivers' compliance with provided information is examined in detail, according to uncertainty-based Information Theory.
Fuzzy Data Fusion for Updating Information in Modeling Drivers’ Choice Behavior / Dell’Orco, Mauro; Marinelli, Mario (LECTURE NOTES IN COMPUTER SCIENCE). - In: Emerging Intelligent Computing Technology and Applications. With Aspects of Artificial Intelligence : 5th International Conference on Intelligent Computing, ICIC 2009 Ulsan, South Korea, September 16-19, 2009. Proceedings / [a cura di] De-Shuang Huang; Kang-Hyun Jo; Hong-Hee Lee; Hee-Jun Kang; Vitoantonio Bevilacqua. - STAMPA. - Berlin; Heidelberg : Springer, 2009. - ISBN 978-3-642-04019-1. - pp. 1075-1084 [10.1007/978-3-642-04020-7_115]
Fuzzy Data Fusion for Updating Information in Modeling Drivers’ Choice Behavior
Mauro Dell’Orco;Mario Marinelli
2009-01-01
Abstract
In this paper, a method for fusing fuzzy data relevant both to drivers' experience and provided information is presented. Expected travel time is then updated according to the results of fusion. The method takes into account the "compatibility" of data originating from different sources, and provides information about acceptability of results. Influence of uncertainty on drivers' compliance with provided information is examined in detail, according to uncertainty-based Information Theory.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
