@inproceedings{9773e5fa33cf411089d4e74f1e3831db,
title = "Adaptive Travel-Time Estimation: A Case for Custom Predicate Selection",
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.",
keywords = "query processing, trajectory databases, travel time estimation",
author = "Robert Waury and Jensen, {Christian S{\o}ndergaard} and Kristian Torp",
year = "2018",
month = jul,
day = "13",
doi = "10.1109/MDM.2018.00026",
language = "English",
isbn = "978-1-5386-4134-7",
series = "IEEE International Conference on Mobile Data Management (MDM)",
publisher = "IEEE",
pages = "96--105",
booktitle = "Proceedings - 19th IEEE International Conference on Mobile Data Management, MDM 2018",
address = "United States",
note = "19th IEEE International Conference on Mobile Data Management, MDM 2018 ; Conference date: 25-06-2018 Through 28-06-2018",
}