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Discovery of driving patterns by trajectory segmentation

Published: 31 October 2016 Publication History

Abstract

Telematics data is becoming increasingly available due to the ubiquity of devices that collect data during drives, for different purposes, such as usage based insurance (UBI), fleet management, navigation of connected vehicles, etc. Consequently, a variety of data-analytic applications have become feasible that extract valuable insights from the data. In this paper, we address the especially challenging problem of discovering behavior-based driving patterns from only externally observable phenomena (e.g. vehicle's speed). We present a trajectory segmentation approach capable of discovering driving patterns as separate segments, based on the behavior of drivers. This segmentation approach includes a novel transformation of trajectories along with a dynamic programming approach for segmentation. We apply the segmentation approach on a real-word, rich dataset of personal car trajectories provided by a major insurance company based in Columbus, Ohio. Analysis and preliminary results show the applicability of approach for finding significant driving patterns.

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Cited By

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  • (2024)On Splitting Raw TrajectoriesProceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems10.1145/3678717.3691258(561-564)Online publication date: 29-Oct-2024
  • (2022)Unlicensed Taxi Detection Model Based on Graph EmbeddingElectronics10.3390/electronics1120341011:20(3410)Online publication date: 20-Oct-2022
  • (2022)Application of Artificial Intelligence in an Unsupervised Algorithm for Trajectory Segmentation Based on Multiple Motion FeaturesWireless Communications & Mobile Computing10.1155/2022/95409442022Online publication date: 1-Jan-2022
  • Show More Cited By

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      cover image ACM Other conferences
      SIGSPATIAL PhD '16: Proceedings of the 3rd ACM SIGSPATIAL PhD Symposium
      October 2016
      22 pages
      ISBN:9781450345842
      DOI:10.1145/3003819
      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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      Publication History

      Published: 31 October 2016

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      Author Tags

      1. driving patterns
      2. segmentation
      3. trajectory

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      • Microsoft
      • ORACLE
      • Facebook

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      Cited By

      View all
      • (2024)On Splitting Raw TrajectoriesProceedings of the 32nd ACM International Conference on Advances in Geographic Information Systems10.1145/3678717.3691258(561-564)Online publication date: 29-Oct-2024
      • (2022)Unlicensed Taxi Detection Model Based on Graph EmbeddingElectronics10.3390/electronics1120341011:20(3410)Online publication date: 20-Oct-2022
      • (2022)Application of Artificial Intelligence in an Unsupervised Algorithm for Trajectory Segmentation Based on Multiple Motion FeaturesWireless Communications & Mobile Computing10.1155/2022/95409442022Online publication date: 1-Jan-2022
      • (2022)A Survey and Experimental Study on Privacy-Preserving Trajectory Data PublishingIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.3174204(1-1)Online publication date: 2022
      • (2021)semi-Traj2Graph: Identifying Fine-grained Driving Style with GPS Trajectory Data via Multi-task LearningIEEE Transactions on Big Data10.1109/TBDATA.2021.3063048(1-1)Online publication date: 2021
      • (2019)A Graph-Based Visual Query Method for Massive Human Trajectory DataIEEE Access10.1109/ACCESS.2019.29483047(160879-160888)Online publication date: 2019
      • (2018)Telematics and Road Safety2018 2nd International Conference on Telematics and Future Generation Networks (TAFGEN)10.1109/TAFGEN.2018.8580482(103-108)Online publication date: Jul-2018
      • (2017)Trajectory Annotation by Discovering Driving PatternsProceedings of the 3rd ACM SIGSPATIAL Workshop on Smart Cities and Urban Analytics10.1145/3152178.3152184(1-4)Online publication date: 7-Nov-2017
      • (2017)Characterizing Driving Context from Driver BehaviorProceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems10.1145/3139958.3139992(1-4)Online publication date: 7-Nov-2017

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