Joachim Gudmundsson, Martin P. Seybold, Sampson Wong
{"title":"弗雷谢特距离下现实输入图的地图匹配查询","authors":"Joachim Gudmundsson, Martin P. Seybold, Sampson Wong","doi":"10.1145/3643683","DOIUrl":null,"url":null,"abstract":"<p>Map matching is a common preprocessing step for analysing vehicle trajectories. In the theory community, the most popular approach for map matching is to compute a path on the road network that is the most spatially similar to the trajectory, where spatial similarity is measured using the Fréchet distance. A shortcoming of existing map matching algorithms under the Fréchet distance is that every time a trajectory is matched, the entire road network needs to be reprocessed from scratch. An open problem is whether one can preprocess the road network into a data structure, so that map matching queries can be answered in sublinear time. </p><p>In this paper, we investigate map matching queries under the Fréchet distance. We provide a negative result for geometric planar graphs. We show that, unless SETH fails, there is no data structure that can be constructed in polynomial time that answers map matching queries in <i>O</i>((<i>pq</i>)<sup>1 − <i>δ</i></sup>) query time for any <i>δ</i> > 0, where <i>p</i> and <i>q</i> are the complexities of the geometric planar graph and the query trajectory, respectively. We provide a positive result for realistic input graphs, which we regard as the main result of this paper. We show that for <i>c</i>-packed graphs, one can construct a data structure of \\(\\tilde{O}(cp) \\) size that can answer (1 + ε)-approximate map matching queries in \\(\\tilde{O}(c^4 q \\log ^4 p) \\) time, where \\(\\tilde{O}(\\cdot) \\) hides lower-order factors and dependence on ε.</p>","PeriodicalId":50922,"journal":{"name":"ACM Transactions on Algorithms","volume":"3 1","pages":""},"PeriodicalIF":0.9000,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Map matching queries on realistic input graphs under the Fréchet distance\",\"authors\":\"Joachim Gudmundsson, Martin P. Seybold, Sampson Wong\",\"doi\":\"10.1145/3643683\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Map matching is a common preprocessing step for analysing vehicle trajectories. In the theory community, the most popular approach for map matching is to compute a path on the road network that is the most spatially similar to the trajectory, where spatial similarity is measured using the Fréchet distance. A shortcoming of existing map matching algorithms under the Fréchet distance is that every time a trajectory is matched, the entire road network needs to be reprocessed from scratch. An open problem is whether one can preprocess the road network into a data structure, so that map matching queries can be answered in sublinear time. </p><p>In this paper, we investigate map matching queries under the Fréchet distance. We provide a negative result for geometric planar graphs. We show that, unless SETH fails, there is no data structure that can be constructed in polynomial time that answers map matching queries in <i>O</i>((<i>pq</i>)<sup>1 − <i>δ</i></sup>) query time for any <i>δ</i> > 0, where <i>p</i> and <i>q</i> are the complexities of the geometric planar graph and the query trajectory, respectively. We provide a positive result for realistic input graphs, which we regard as the main result of this paper. We show that for <i>c</i>-packed graphs, one can construct a data structure of \\\\(\\\\tilde{O}(cp) \\\\) size that can answer (1 + ε)-approximate map matching queries in \\\\(\\\\tilde{O}(c^4 q \\\\log ^4 p) \\\\) time, where \\\\(\\\\tilde{O}(\\\\cdot) \\\\) hides lower-order factors and dependence on ε.</p>\",\"PeriodicalId\":50922,\"journal\":{\"name\":\"ACM Transactions on Algorithms\",\"volume\":\"3 1\",\"pages\":\"\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2024-01-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Transactions on Algorithms\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1145/3643683\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Algorithms","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1145/3643683","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
Map matching queries on realistic input graphs under the Fréchet distance
Map matching is a common preprocessing step for analysing vehicle trajectories. In the theory community, the most popular approach for map matching is to compute a path on the road network that is the most spatially similar to the trajectory, where spatial similarity is measured using the Fréchet distance. A shortcoming of existing map matching algorithms under the Fréchet distance is that every time a trajectory is matched, the entire road network needs to be reprocessed from scratch. An open problem is whether one can preprocess the road network into a data structure, so that map matching queries can be answered in sublinear time.
In this paper, we investigate map matching queries under the Fréchet distance. We provide a negative result for geometric planar graphs. We show that, unless SETH fails, there is no data structure that can be constructed in polynomial time that answers map matching queries in O((pq)1 − δ) query time for any δ > 0, where p and q are the complexities of the geometric planar graph and the query trajectory, respectively. We provide a positive result for realistic input graphs, which we regard as the main result of this paper. We show that for c-packed graphs, one can construct a data structure of \(\tilde{O}(cp) \) size that can answer (1 + ε)-approximate map matching queries in \(\tilde{O}(c^4 q \log ^4 p) \) time, where \(\tilde{O}(\cdot) \) hides lower-order factors and dependence on ε.
期刊介绍:
ACM Transactions on Algorithms welcomes submissions of original research of the highest quality dealing with algorithms that are inherently discrete and finite, and having mathematical content in a natural way, either in the objective or in the analysis. Most welcome are new algorithms and data structures, new and improved analyses, and complexity results. Specific areas of computation covered by the journal include
combinatorial searches and objects;
counting;
discrete optimization and approximation;
randomization and quantum computation;
parallel and distributed computation;
algorithms for
graphs,
geometry,
arithmetic,
number theory,
strings;
on-line analysis;
cryptography;
coding;
data compression;
learning algorithms;
methods of algorithmic analysis;
discrete algorithms for application areas such as
biology,
economics,
game theory,
communication,
computer systems and architecture,
hardware design,
scientific computing