| Pervasive Computing and Computer Human Interaction |
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| Scenic travel route planning based on multi sourced and heterogeneous crowdsourced data |
| CHEN Xia, CHEN Chao, LIU Kai |
1.Center of Automotive Collaborative Innovation, Chongqing University, Chongqing 400044, China
2. School of Computer Science, Chongqing University, Chongqing 400044, China |
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Abstract A scenic travel route planning system was proposed based on multisourced and heterogeneous crowdsourced data, aiming to recommend the best scenic travel route between two given points with length constraint. Firstly, the basic road network extracted from OpenStreetMap (OSM), the mobile social network and media data were integrated to score the beauty of each roadsegment and get the model of scenic road network. Secondly, a rulebased scenic route planning algorithm was proposed to maximize the overall scenic route values under the given constraints. Finally, San Francisco was selected as experimental object. The experimental results show that the proposed scenic route planning algorithm can achieve excellent performance.
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Published: 01 June 2016
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多源异构众包数据风景旅行路线规划
提出基于多源异构众包数据的风景路线规划系统,为用户推荐给定两点间景色最优的旅行路线,满足路线长度约束.从开放街道地图（OSM）提取基本路网、融合移动社交网络和媒体数据,对每个路段进行风景值刻画,实现风景路网建模.提出基于规则的风景路线规划算法,满足给定约束的同时实现整体路线风景值的最大化.选取美国旧金山作为实验对象进行验证,结果表明：提出的规划算法能实现路线风景值的最大化.
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