Region-Aware Route Planning

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STORANDT, Sabine, 2018. Region-Aware Route Planning. 16th International Symposium, W2GIS 2018. A Coruña, Spain, May 21, 2018 - May 22, 2018. In: LUACES, Miguel R., ed. and others. Web and Wireless Geographical Information Systems : 16th International Symposium, W2GIS 2018, A Coruña, Spain, May 21-22, 2018, Proceedings. Cham:Springer, pp. 101-117. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-319-90052-0. Available under: doi: 10.1007/978-3-319-90053-7_11

@inproceedings{Storandt2018Regio-43343, title={Region-Aware Route Planning}, year={2018}, doi={10.1007/978-3-319-90053-7_11}, number={10819}, isbn={978-3-319-90052-0}, issn={0302-9743}, address={Cham}, publisher={Springer}, series={Lecture Notes in Computer Science}, booktitle={Web and Wireless Geographical Information Systems : 16th International Symposium, W2GIS 2018, A Coruña, Spain, May 21-22, 2018, Proceedings}, pages={101--117}, editor={Luaces, Miguel R.}, author={Storandt, Sabine} }

<rdf:RDF xmlns:dcterms="" xmlns:dc="" xmlns:rdf="" xmlns:bibo="" xmlns:dspace="" xmlns:foaf="" xmlns:void="" xmlns:xsd="" > <rdf:Description rdf:about=""> <dspace:isPartOfCollection rdf:resource=""/> <bibo:uri rdf:resource=""/> <dcterms:title>Region-Aware Route Planning</dcterms:title> <dcterms:isPartOf rdf:resource=""/> <dc:language>eng</dc:language> <dc:date rdf:datatype="">2018-09-20T13:27:39Z</dc:date> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dcterms:available rdf:datatype="">2018-09-20T13:27:39Z</dcterms:available> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dcterms:abstract xml:lang="eng">We consider route planning queries in road or path networks which involve a user preference expressed in relation to a spatial region, as e.g. ‘from Nanjing to Shanghai along Yangtze river’ or ‘from home to work through Central Park’. To answer such queries, we carefully define relevant subgraphs of the network for each region-of-interest and guide the route towards them. To extract these subgraphs, we need to solve several non-trivial geometric problems (as computing weak visibility regions), which require to interpret the embedded network both as a graph and as an arrangement of line segments. We describe a suitable preprocessing framework, taking the special structure of road networks into account to increase its performance. Our query answering algorithm then allows to trade detour length against time spent within or close to the desired region. Using acceleration techniques, region-aware routes can be planned efficiently even in networks with millions of edges, and also when considering large or complex regions.</dcterms:abstract> <dc:creator>Storandt, Sabine</dc:creator> <dcterms:issued>2018</dcterms:issued> <dc:contributor>Storandt, Sabine</dc:contributor> </rdf:Description> </rdf:RDF>

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