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Road Networks

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Encyclopedia of Database Systems
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Synonyms

Road network databases; Road vector data;Spatial network databases

Definition

In vector space, the distance between two objects can be computed as a function of the components of the vectors representing the objects. A typical distance function for multidimensional vector spaces is the well-known Minkowski metric, with the Euclidean metric as a popular case for two-dimensional space. Therefore, the distance computation in multidimensional vector spaces is fast because its complexity depends on the number of dimensions which is limited to two or three in geospatial applications. However, with road-networks, the distance between two objects is measured by their network distance, i.e., the length of the shortest path through the network edges that connects the two locations. This computationally expensive network-based metric mainly depends on the connectivity of the network. For example, representing a road network as a graph with e weighted edges and vvertices, the complexity...

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  1. Almeida VTD, Güting RH. Indexing the trajectories of moving objects in networks. GeoInformatica. 2005;9(1):33–60.

    Article  Google Scholar 

  2. Cho H.-J, Chung C.-W. An efficient and scalable approach to cnn queries in a road network. In: Proceedings of the 31st International Conference on Very Large Data Bases; 2005. p. 865–876.

    Google Scholar 

  3. Güting H, de Almeida T, Ding Z. Modeling and querying moving objects in networks. VLDB J. 2006;15(2):165–90.

    Article  Google Scholar 

  4. Hu H, Lee DL, Lee VCS. Distance indexing on road networks. In: Proceedings of the 32nd International Conference on Very Large Data Bases; 2006. pp. 894–905.

    Google Scholar 

  5. Hu H, Lee DL, Xu J. Fast nearest neighbor search on road networks. In: Advances in Database Technology, Proceedings of the 10th International Conference on Extending Database Technology; 2006. p. 186–203.

    Google Scholar 

  6. Huang X, Jensen CS, Saltenis S. The islands approach to nearest neighbor querying in spatial networks. In: Proceedings of the 9th International Symposium on Advances in Spatial and Temporal Databases; 2005. p. 73–90.

    Chapter  Google Scholar 

  7. Jensen CS, Kolářvr J, Pedersen TB, Timko I. Nearest neighbor queries in road networks. In: Proceedings of the 11th ACM International Symposium on Advances in Geographic Information Systems; 2003. p. 1–8.

    Google Scholar 

  8. Kolahdouzan MR, Shahabi C. Voronoi-based k nearest neighbor search for spatial network databases. In: Proceedings of the 30th International Conference on Very Large Data Bases; 2004. p. 840–51.

    Chapter  Google Scholar 

  9. Ku W-S, Zimmermann R, Wang H, Wan C-N. Adaptive nearest neighbor queries in travel time networks. In: Proceedings of the 13th ACM International Symposium on Advances in Geographic Information Systems; 2005. p. 210–19.

    Google Scholar 

  10. Papadias D, Zhang J, Mamoulis N, Tao Y. Query processing in spatial network databases. In: Proceedings of the 29th International Conference on Very Large Data Bases; 2003. p. 790–801.

    Chapter  Google Scholar 

  11. Pfoser D, Jensen CS. Indexing of network constrained moving objects. In: Proceedings of the 11th ACM International Symposium on Advances in Geographic Information Systems; 2003. p. 25–32.

    Google Scholar 

  12. Sankaranarayanan J, Alborzi H, Samet H. Efficient query processing on spatial networks. In: Proceedings of the 13th ACM International Symposium on Advances in Geographic Information Systems; 2005. p. 200–09.

    Google Scholar 

  13. Shahabi C, Kolahdouzan MR, Sharifzadeh M. A road network embedding technique for k-nearest neighbor search in moving object databases. In: Proceedings of the 10th ACM International Symposium on Advances in Geographic Information Systems; 2002. p. 94–100.

    Google Scholar 

  14. Sharifzadeh M, Shahabi C. Processing optimal sequenced route queries using voronoi diagrams. GeoInformatica. 2008;12(4):411–33.

    Article  Google Scholar 

  15. Yiu ML, Mamoulis N, Papadias D. Aggregate nearest neighbor queries in road networks. IEEE Trans Knowl Data Eng. 2005;17(6):820–3.

    Article  Google Scholar 

  16. Fleischmann B, Gietz M, Gnutzmann S. Time-varying travel times in vehicle routing. Transp Sci. 2004;38(2):160–73.

    Article  Google Scholar 

  17. Demiryurek U, Banaei-Kashani F, Shahabi C. A case for time-dependent shortest path computation in spatial networks. In: Proceedings of the 18th SIGSPATIAL ACM International Symposium on Advances in Geographic Information Systems; 2010. p. 474–77.

    Google Scholar 

  18. Cooke L, Halsey E. The shortest route through a network with time-dependent internodal transit times. J Math Anal Appl. 1966.

    Google Scholar 

  19. Dreyfus SE. An appraisal of some shortest-path algorithms. Oper Res. 1969;17(3).

    Article  MATH  Google Scholar 

  20. Ding B, Yu JX, Qin L. Finding time-dependent shortest paths over large graphs. EDBT In: Advances in Database Technology, Proceedings of the 11th International Conference on Extending Database Technology; 2008. p. 205–16.

    Google Scholar 

  21. Delling D, Wagner D. Time-dependent route planning. Robust and Online Large-Scale Optimization 2009; p. 207–30.

    Google Scholar 

  22. Demiryurek U, Kashani FB, Shahabi C, Ranganathan A. Online computation of fastest path in time-dependent spatial networks, SSTD, 2011.

    Google Scholar 

  23. Smith B, Demetsky M. Traffic flow forecasting: comparison of modeling approaches. J Transp Eng. 1997;123(4):261–6.

    Article  Google Scholar 

  24. Pan B, Demiryurek U, Shahabi C. Utilizing real-world transportation data for accurate traffic prediction. In: Proceedings of the 12th IEEE International Conference on Data Mining; 2012. p. 595–604.

    Google Scholar 

  25. Clark S. Traffic prediction using multivariate nonparametric regression. J Transp Eng. 2003;129(2):161–7.

    Article  Google Scholar 

  26. Pan B, Demiryurek U, Shahabi C, Gupta C. Forecasting spatiotemporal impact of traffic incidents on road networks. In: Proceedings of the 13th IEEE International Conference on Data Mining; 2013. p. 587–96.

    Google Scholar 

  27. Demiryurek U, Kashani FB, Shahabi C. Efficient K-nearest neighbor search in time-dependent spatial networks. In: Proceedings of the 21th International Conference on Database and Expert Systems Applications; 2010; p. 432–49.

    Google Scholar 

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Correspondence to Cyrus Shahabi .

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Shahabi, C. (2018). Road Networks. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_319

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