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Personalized route planning in road networks

Published: 03 November 2015 Publication History

Abstract

Computing shortest paths in road networks with millions of nodes and edges is challenging on its own. In the last few years, several preprocessing-based acceleration techniques have been developed to enable query answering orders of magnitudes faster than a plain Dijkstra computation. But most of these techniques work only if the metric which determines the optimal path is static or rarely changes. In contrast to that, we aim at answering personalized route planning queries. Here, every single query comes with a specification of its very own metric. This increases the combinatorial complexity of the problem significantly. We develop new preprocessing schemes that allow for real-time personalized route planning in huge road networks while keeping the memory footprint of the preprocessed data and subsequent queries small.

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Cited By

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  • (2023)Fast One-to-Many Multicriteria Shortest Path SearchIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.328206924:10(10410-10419)Online publication date: Oct-2023
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  • (2023)Digital Twin of a Driver-in-the-Loop Race Car Simulation With Contextual Reinforcement LearningIEEE Robotics and Automation Letters10.1109/LRA.2023.32796188:7(4107-4114)Online publication date: Jul-2023
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Published In

cover image ACM Conferences
SIGSPATIAL '15: Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems
November 2015
646 pages
ISBN:9781450339674
DOI:10.1145/2820783
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: 03 November 2015

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Author Tags

  1. personalization
  2. route planning

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SIGSPATIAL '15 Paper Acceptance Rate 38 of 212 submissions, 18%;
Overall Acceptance Rate 257 of 1,238 submissions, 21%

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Cited By

View all
  • (2023)Fast One-to-Many Multicriteria Shortest Path SearchIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.328206924:10(10410-10419)Online publication date: Oct-2023
  • (2023)MOOP: An Efficient Utility-Rich Route Planning Framework Over Two-Fold Time-Dependent Road NetworksIEEE Transactions on Emerging Topics in Computational Intelligence10.1109/TETCI.2023.32419307:5(1554-1570)Online publication date: Oct-2023
  • (2023)Digital Twin of a Driver-in-the-Loop Race Car Simulation With Contextual Reinforcement LearningIEEE Robotics and Automation Letters10.1109/LRA.2023.32796188:7(4107-4114)Online publication date: Jul-2023
  • (2023)Promoting favorable routes through visual communication: a design study for creating ‘Social’ route maps for the case of air pollutionInternational Journal of Cartography10.1080/23729333.2022.215978110:1(68-93)Online publication date: 15-Mar-2023
  • (2022)Polestar++: An Intelligent Routing Engine for National-Wide Public TransportationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.3153711(1-1)Online publication date: 2022
  • (2022)A Dynamic and Scalable User-Centric Route Planning Algorithm Based on Polychromatic Sets TheoryIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2021.308502623:3(2762-2772)Online publication date: Mar-2022
  • (2022)Enjoy the most beautiful scene now: a memetic algorithm to solve two-fold time-dependent arc orienteering problemFrontiers of Computer Science: Selected Publications from Chinese Universities10.1007/s11704-019-8364-114:2(364-377)Online publication date: 11-Mar-2022
  • (2021)2TD Path-Planner: Towards a More Realistic Path Planning System over Two-Fold Time-Dependent Road Networks [Application Notes]IEEE Computational Intelligence Magazine10.1109/MCI.2021.306187916:2(78-98)Online publication date: May-2021
  • (2021)Personalized route recommendation through historical travel behavior analysisGeoInformatica10.1007/s10707-021-00453-y26:3(505-540)Online publication date: 10-Nov-2021
  • (2020)Scalable unsupervised multi-criteria trajectory segmentation and driving preference miningProceedings of the 9th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data10.1145/3423336.3429348(1-10)Online publication date: 3-Nov-2020
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