碩士 / 國立臺灣科技大學 / 工業管理系 / 98 / Nowadays, the technology on Advanced Traveler Information Systems (ATIS) becomes more and more progressive. This well-developed technology not only keeps travelers from getting lost, but greatly decreases the time people spend on searching the routes to destination. Navigation system provides drivers some choices on selecting routes, for example, shortest time, shortest distance, use of freeways, etc. However, the path which system provides is not always the “optimal” one, since drivers may consider other factors such as familiarity of the route, traffic condition, weather condition, personal preference, and so on. Therefore, the importance of self-learning ability in systems becomes essential and significant.
Due to these facts, this research is mainly about building an adaptive driving route guidance system. In other words, our objective is to add human preference into current navigation system. In this study, we will use Fuzzy-Neural Network (FNN) to format this system. FNN takes advantage of two major techniques, fuzzy and neural network. Fuzzy logic provides a way to model vague attributes by transforming variables between crisp and linguistic values. And from neural network, we can easily make the system learn by itself. At the end, the system will continuously modify and improve the model to generate better results corresponding to the user’s inclination. In this way, the system will be able to act like driver’s thinking logic.
| Identifer | oai:union.ndltd.org:TW/098NTUS5041075 |
| Date | January 2010 |
| Creators | Hsin-Yin Hsu, 許馨尹 |
| Contributors | Shuo-Yan Chou, 周碩彥 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | en_US |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 57 |
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