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Towards a parameter tuning approach for a map-matching algorithm

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Map Matching Algorithms (MMA) are developed to solve spatial ambiguities that arise in the process of assigning GPS measurements onto a digital roadway network. There is a lack of systematic parameter tuning approaches for optimizing the MMA performance. Thus, a novel integrated framework is proposed for a systematic calibration of the parameters of a post-processing MMA. The calibration approach consists of an Instance-specific Parameter Tuning Strategy (IPTS) that employs Fuzzy Logic principles. The proposed fuzzy IPTS tool determines the best algorithm parameter values by using instance-specific information a priori to the execution of the MMA. A preliminary prototype of an IPTS system is designed based on real-world data, which identifies the explanatory variables that condition the MMA performance. The implementation of the fuzzy IPTS tool on real-word data yields an enhanced MMA performance in the solution quality and computational time compared to the results of the execution of the MMA with constant algorithm settings.
Original languageEnglish
Title of host publication2017 IEEE International Conference on Vehicular Electronics and Safety (ICVES)
ISBN (Electronic)978-1-5090-5677-4
ISBN (Print)978-1-5090-5678-1
Publication statusPublished - 27 Jul 2017
Event2017 IEEE International Conference on Vehicular Electronics and Safety (ICVES) - Vienna, Austria
Duration: 27 Jun 201728 Jun 2017


Conference2017 IEEE International Conference on Vehicular Electronics and Safety (ICVES)


  • RIES_2017_cright_IEEE_Towards a Parameter Tuning Approach for a Map-Matching Algorithm

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    Accepted author manuscript (Post-print), 402 KB, PDF document

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