期刊文献+

基于临增兴趣点的城市交通导航时空数据查询

Spatio-temporal data query of urban traffic navigation based on temporary additional point of interest
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摘要 为了更好地提高城市交通导航时空数据查询效率,本文建立了城市交通导航数据模型,提出了一种城市交通导航时空索引—Urban Traffic Navigation R-tree,并在此基础上研究了基于临增兴趣点的城市交通导航时空数据查询方法,并通过实验证明该方法能较有效、准确地满足城市交通导航服务。 In order to enhance the query efficiency of urban traffic navigation spatio-temporal data, the paper presented an urban traffic navigation data model firstly, then it proposed a novel saptio-temporal index for the urban traffic network, which is called Urban Traffic Navigation R-tree. Finally, it put forward a spatio-tempora] data query method based on the temporary additional point of interest. The experimental result demonstrated the efficiency and accurac2~ of the proposed method, which could serve for the transportation navigation.
出处 《测绘科学》 CSCD 北大核心 2013年第6期133-136,共4页 Science of Surveying and Mapping
基金 国家自然科学基金委青年基金(41001216) 吉林建筑工程学院青年科技发展基金(J20111007)
关键词 临增兴趣点 城市交通 导航数据模型 移动车辆 时空数据查询 temporary additional point of interest urban traffic navigation navigation data model mobile vehicle spatio-tempo- ral data query
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参考文献8

  • 1高立兵.汽车导航系统的动态路径规划优化模型与算法研究[J].甘肃联合大学学报(自然科学版),2012,26(1):55-58. 被引量:4
  • 2Frentzos E. Indexing Objects Moving on Fixed Networks [ C ]//SSTD' 03. Santorini island, Greece ,2003.
  • 3Almeida V, Giting R H. Indexing the Trajectories of Mov- ing Objects in Networks [ C ]//SSDBM' 04. Santorini is- land, Greece, 2004.
  • 4陈海永,王于同.基于交通网络的移动对象时空模型(TNMOST)[J].中国水运,2007,5(12):120-122.
  • 5殷海燕.基于动态交通信息的导航时空数据模型研究[D].长春:吉林大学交通学院,2009.
  • 6Gfiting R H, Almeida V T, Ding Z. Modeling and Quer- ying Moving Objects in Networks [ J ]. The VLDB Journal, 2005,15(2) :165-190.
  • 7陈子军,任彩平,刘文远.路网中查询点速度不确定的连续k近邻查询方法[J].小型微型计算机系统,2011,32(3):430-434. 被引量:4
  • 8Brinkhoff T. A framework for Generating Network-Based Moving Objects [ J ]. GeoInformatica,2002,6 (2).

二级参考文献15

  • 1杨易,谷正气,胡林,罗国青,容哲.病毒进化遗传算法在动态路径规划中的运用研究[J].汽车工程,2007,29(1):67-70. 被引量:4
  • 2Roussopoulos N, Kelley S, Vincent F. Nearest neighbor queries [ C]. Proceedings of the 1995 ACM SIGMOD International Conference on Management of Data. San Jose, 1995,71-79.
  • 3Hjaltason G R, Samet H. Distance browsing in spatial databases [J]. ACM Transactions on Database Systems, 1999, 24(2) :265- 318.
  • 4Papadias D, Zhang J, Mamoulis N, et al. Query processing in spatial network databases[ C]. Proceedings of 29th International Conference on Very Large Data Bases. Berlin, 2003,802-813.
  • 5Kolahdouzan M R,Shahabi C. Continuous K nearest neighbor queries in spatial network databases [ C ]. Proceedings of the Second Workshop on Spatio-temporal Database Management, Toronto, 2004,33-40.
  • 6Cho H J, Chung C W. An efficient and sealable approach to can queries in a road network[C]. Proceedings of the 31st International Conference on Very Large Data Bases,Trondheim, 2005, 865-876.
  • 7Mouratidis K, Yiu M L, Papadias D, et al. Continuous nearest neighbor monitoring in road networks[C]. Proceedings of the 32nd International Conference on Very Large Data Bases, Seoul, 2006, 43-54.
  • 8Huang Yuan-ko, Chen Zhi-wei, Li qiang. Continuous K-newest neighbor query over moving objects in road networks[C]. Proceedings of the Joint International Conferences on Advances in Data and Web Management ( APWeb/WAIM 2009). Suzhou, 2009,27-38.
  • 9Huang Yuan-ko,Chen Chao-chun,Li qiang. Continuous K-nearest neighbor query for moving objects with uncertain velocity [ Z ]. GeoInformatica, 2009.
  • 10DIJKTRA E W. A note on two problems in connection with graphs[J]. Numerische Mathematik, 1959,2 (4) :295-301.

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