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Personalized Route Planning System Based on Driver Preference
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AI
DOI：10.3390/s22010011.png)
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摘要
En 中文
At present, most popular route navigation systems only use a few sensed or measured attributes to recommend a route. Yet the optimal route considered by drivers needs be based on multiple objectives and multiple attributes. As a result, these existing systems based on a single or few attributes may fail to meet such drivers' needs. This work proposes a driver preference-based route planning (DPRP) model. It can recommend an optimal route by considering driver preference. We collect drivers' preferences, and then provide a set of routes for their choice when they need. Next, we present an integrated algorithm to solve DPRP, which speeds up the search process for recommending the best routes. Its computation cost can be reduced by simplifying a road network and removing invalid sub-routes. Experimental results demonstrate its effectiveness.
Keyword:
optimization
personalization
preference
route planning
crowd sensing
global positioning system
geographic information system
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期刊
IF:
3.5
论文数:
7.2W
被引数:
20.9W
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