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Path-based queries on trajectory data

Published: 04 November 2014 Publication History

Abstract

In traffic research, management, and planning a number of path-based analyses are heavily used, e.g., for computing turn-times, evaluating green waves, or studying traffic flow. These analyses require retrieving the trajectories that follow the full path being analyzed. Existing path queries cannot sufficiently support such path-based analyses because they retrieve all trajectories that touch any edge in the path. In this paper, we define and formalize the strict path query. This is a novel query type tailored to support path-based analysis, where trajectories must follow all edges in the path. To efficiently support strict path queries, we present a novel NET work-constrained TRAjectory index (NETTRA). This index enables very efficient retrieval of trajectories that follow a specific path, i.e., strict path queries. NETTRA uses a new path encoding scheme that can determine if a trajectory follows a specific path by only retrieving data from the first and last edge in the path. To correctly answer strict path queries existing network-constrained trajectory indexes must retrieve data from all edges in the path. An extensive performance study of NETTRA using a very large real-world trajectory data set, consisting of 1.7 million trajectories (941 million GPS records) and a road network with 1.3 million edges, shows a speed-up of two orders of magnitude compared to state-of-the-art trajectory indexes.

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Cited By

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  • (2022)Efficient Trajectory Matching Algorithm Based on Spatial Coordinate RotationJournal of Computer-Aided Design & Computer Graphics10.3724/SP.J.1089.2022.1883434:01(44-53)Online publication date: 2-Dec-2022
  • (2022)Improved structures to solve aggregated queries for trips over public transportation networksInformation Sciences: an International Journal10.1016/j.ins.2021.10.079584:C(752-783)Online publication date: 1-Jan-2022
  • (2022)Using Compressed Suffix-Arrays for a compact representation of temporal-graphsInformation Sciences: an International Journal10.1016/j.ins.2018.07.023465:C(459-483)Online publication date: 21-Apr-2022
  • Show More Cited By

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cover image ACM Conferences
SIGSPATIAL '14: Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
November 2014
651 pages
ISBN:9781450331319
DOI:10.1145/2666310
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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New York, NY, United States

Publication History

Published: 04 November 2014

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Author Tags

  1. analysis
  2. network-constrained indexing
  3. performance
  4. spatio-temporal indexing
  5. trajectories

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  • Research-article

Funding Sources

  • EU FP7 REDUCTION project
  • EU FP7 DATASIM project
  • Greek GSRT project Live Roads

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SIGSPATIAL '14
Sponsor:
  • University of North Texas
  • Microsoft
  • ORACLE
  • Facebook
  • SIGSPATIAL

Acceptance Rates

SIGSPATIAL '14 Paper Acceptance Rate 39 of 184 submissions, 21%;
Overall Acceptance Rate 257 of 1,238 submissions, 21%

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Cited By

View all
  • (2022)Efficient Trajectory Matching Algorithm Based on Spatial Coordinate RotationJournal of Computer-Aided Design & Computer Graphics10.3724/SP.J.1089.2022.1883434:01(44-53)Online publication date: 2-Dec-2022
  • (2022)Improved structures to solve aggregated queries for trips over public transportation networksInformation Sciences: an International Journal10.1016/j.ins.2021.10.079584:C(752-783)Online publication date: 1-Jan-2022
  • (2022)Using Compressed Suffix-Arrays for a compact representation of temporal-graphsInformation Sciences: an International Journal10.1016/j.ins.2018.07.023465:C(459-483)Online publication date: 21-Apr-2022
  • (2020)Fast subtrajectory similarity search in road networks under weighted edit distance constraintsProceedings of the VLDB Endowment10.14778/3407790.340781813:12(2188-2201)Online publication date: 14-Sep-2020
  • (2020)Efficient Path Query Processing Over Massive Trajectories on the CloudIEEE Transactions on Big Data10.1109/TBDATA.2018.28689366:1(66-79)Online publication date: 1-Mar-2020
  • (2019)A NUMA-aware Trajectory Store for Travel-Time EstimationProceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems10.1145/3347146.3359371(209-218)Online publication date: 5-Nov-2019
  • (2019)Analyzing Trajectories Using a Path-based APIProceedings of the 16th International Symposium on Spatial and Temporal Databases10.1145/3340964.3340990(198-201)Online publication date: 19-Aug-2019
  • (2019)PATHFINDERProceedings of the 16th International Symposium on Spatial and Temporal Databases10.1145/3340964.3340978(90-99)Online publication date: 19-Aug-2019
  • (2018)Enhanced Indexing and Querying of Trajectories in Road Networks via String AlgorithmsACM Transactions on Spatial Algorithms and Systems10.1145/32002004:1(1-41)Online publication date: 15-Jun-2018
  • (2018)Accurate Fuel Estimates Using CAN Bus Data and 3D Maps2018 19th IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM.2018.00045(257-265)Online publication date: Jun-2018
  • Show More Cited By

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