Adaptive Travel-Time Estimation: A Case for Custom Predicate Selection

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3 Citations (Scopus)

Abstract

Travel-time estimation for paths in a road network often relies on pre-computed histograms that are usually available on a road segment level. Then the pre-computed histograms of the segments of a path are convolved to obtain a histogram that estimates the travel time. With the growing sizes of trajectory datasets, it becomes possible to compute histograms for increasingly longer sub-paths. Since pre-computation is infeasible for all sub-paths in a road network, we propose computing histograms on-the-fly, i.e., during routing. Such an on-the-fly method must filter the underlying trajectory dataset by spatio-temporal predicates to obtain the relevant trajectories and offers the opportunity to apply additional filtering predicates to the trajectories with little overhead. We report on a study showing that considerable improvements in accuracy of the histograms obtained for paths can be obtained by choosing filtering predicates that not only adapt to the intended start of a trip, but also to the driver and the weather. We also make the cases for a sub-path partitioning based on segment categories since there are significant differences between road types when applying our on-the-fly method.
Original languageEnglish
Title of host publicationProceedings - 19th IEEE International Conference on Mobile Data Management, MDM 2018
Number of pages10
PublisherIEEE
Publication date13 Jul 2018
Pages96-105
ISBN (Print)978-1-5386-4134-7
ISBN (Electronic)978-1-5386-4133-0
DOIs
Publication statusPublished - 13 Jul 2018
Event19th IEEE International Conference on Mobile Data Management, MDM 2018 - Aalborg, Denmark
Duration: 25 Jun 201828 Jun 2018

Conference

Conference19th IEEE International Conference on Mobile Data Management, MDM 2018
CountryDenmark
CityAalborg
Period25/06/201828/06/2018
SponsorAalborg University, Center for Data-Intensive Systems (DAISY), Aalborg University, IEEE, IEEE Technical Committee on Data Engineering (TCDE), Otto Monsted Foundation
SeriesIEEE International Conference on Mobile Data Management (MDM)
ISSN2375-0324

Keywords

  • query processing
  • trajectory databases
  • travel time estimation

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    Waury, R., Jensen, C. S., & Torp, K. (2018). Adaptive Travel-Time Estimation: A Case for Custom Predicate Selection. In Proceedings - 19th IEEE International Conference on Mobile Data Management, MDM 2018 (pp. 96-105). IEEE. IEEE International Conference on Mobile Data Management (MDM) https://doi.org/10.1109/MDM.2018.00026