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Road network simplification for location-based services

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Abstract

Road-network data compression or simplification reduces the size of the network to occupy less storage with the aim to fit small form-factor routing devices, mobile devices, or embedded systems. Simplification (a) reduces the storage cost of memory and disks, and (b) reduces the I/O and communication overhead. There are several road network compression techniques proposed in the literature. These techniques are evaluated by their compression ratios. However, none of these techniques takes into consideration the possibility that the generated compressed data can be used directly in Map-matching operation which is an essential component for all location-aware services. Map-matching matches a measured latitude and longitude of an object to an edge in the road network graph. In this paper, we propose a novel simplification technique, named COMA, that (1) significantly reduces the size of a given road network graph, (2) achieves high map-matching quality on the simplified graph, and (3) enables the generated compressed road network graph to be used directly in map-matching and location-based applications without a need to decompress it beforehand. COMA smartly deletes those nodes and edges that will not affect the graph connectivity nor causing much of ambiguity in the map-matching of objects’ location. COMA employs a controllable parameter; termed a conflict factor \(\mathcal {C}\), whereby location aware services can trade the compression gain with map-matching accuracy at varying granularity. We show that the time complexity of our COMA algorithm is O(|N|log|N|). Intensive experimental evaluation based on a real implementation and data demonstrates that COMA can achieve about a 75% compression-ratio while preserving high map-matching quality. Road Network, Simplification, Compression, Spatial, Location, Performance, Accuracy, Efficiency, Scalability.

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Acknowledgments

We extend our thanks to Anas Basalamah (Umm Al-Qura University), Amruta Khot, Aqeel Rustum, and Ankur Teredesai (University of Washington Tacoma) for their comments and support in the initial phase of the work. This research is partially funded by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant Agreement No. 860621. It is also partially supported by the Spanish Ministry of Science, Innovation and Universities (grants RTI2018-099646-B-I00, TIN2017-84796-C2-1-R, TIN2017-90773-REDT, and RED2018-102641-T) and the Galician Ministry of Education, University and Professional Training (grants ED431F2018/02, ED431C2018/29, ED431G/08 and ED431G2019/04). Some of the previous grants were co-funded by the European Regional Development Fund (ERDF/FEDER program).

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Authors and Affiliations

  1. Department of Computer Science, Department of Computer Science and Statistics, University of Rhode Island, Kingston, RI, USA

    Abdeltawab Hendawi

  2. Faculty of Computers and Artificial Intelligence, Cairo University, Giza, Egypt

    Abdeltawab Hendawi & Ayman Taha

  3. Department of Computer Science, University of Virginia - Charlottesville, 85 Engineer’s Way, Charlottesville, VA, 22904-4740, USA

    John A. Stankovic

  4. School of Computer Science, Technological University Dublin, Dublin, Ireland

    Ayman Taha

  5. Centro Singular de Investigacion en Tecnoloxias Intelixentes, Universidade de Santiago de Compostela, Santiago, Spain

    Shaker El-Sappagh

  6. University of Virginia - Charlottesville, 85 Engineer’s Way, Charlottesville, VA, 22904-4740, USA

    Amr A. Ahmadain

  7. School of Engineering and Technology, University of Washington Tacoma, 1900 Commerce Street, Tacoma, WA, 98402-3100, USA

    Mohamed Ali

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  1. Abdeltawab Hendawi
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  2. John A. Stankovic
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Correspondence to Abdeltawab Hendawi.

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Hendawi, A., Stankovic, J.A., Taha, A. et al. Road network simplification for location-based services. Geoinformatica 24, 801–826 (2020). https://doi.org/10.1007/s10707-020-00406-x

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