Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
New Travel Demand Models with Back-Propagation Network
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 03
Adaptive Routing of Cruising Taxis by Mutual Exchange of Pathways
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II
Optimization of Vehicle Assignment for Car Sharing System
KES '07 Knowledge-Based Intelligent Information and Engineering Systems and the XVII Italian Workshop on Neural Networks on Proceedings of the 11th International Conference
Improved travel time prediction algorithms for intelligent transportation systems
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part II
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There are many prior works of modeling travel behaviors. Most of them are investigated under the assumption that many kinds of data such as that of Person Trip (PT), which surveys travel behaviors, are available. Therefore, they do not consider an application to cities where the survey is not examined. In this paper, we propose a method for estimating travel behaviors using zone characteristics which is obtained from structural data of city. Focusing on dependent relationships between travel behaviors and city structure, we estimate the travel behaviors by means of the relationships. We first define trip and zone characteristics, and then introduce our method. With our method, we make use of Bayesian network constructed with PT data and the structural data. In addition, we show the effectiveness of our method through evaluation experiments.