An Instance-Specific Parameter Tuning Approach Using Fuzzy Logic for a Post-Processing Topological Map-Matching Algorithm

Resultado de la investigación: Article

Resumen

Map Matching Algorithms (MMAs) are developed to solve spatial ambiguities that arise in the process of assigning GPS measurements onto a digital roadway network. Scarce systematic parameter tuning approaches exist in the literature for optimizing MMA performance. Thus, a novel 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 algorithm-specific parameter values based on instance-specific information a priori to the execution of the MMA. Finally, the proposed IPTS tool is able to adjust to two particular decision maker preferences on algorithm performance, namely solution quality and computational time.

Idioma originalEnglish
Número de artículo8463456
Páginas (desde-hasta)87-97
Número de páginas11
PublicaciónIEEE Intelligent Transportation Systems Magazine
Volumen10
N.º4
DOI
EstadoPublished - 24 sep 2018

Huella dactilar

Fuzzy logic
Tuning
Processing
Calibration
Global positioning system

Keywords

    ASJC Scopus subject areas

    • Automotive Engineering
    • Mechanical Engineering
    • Computer Science Applications

    Citar esto

    @article{59f72b1b4fdb40509e13524db167aa8a,
    title = "An Instance-Specific Parameter Tuning Approach Using Fuzzy Logic for a Post-Processing Topological Map-Matching Algorithm",
    abstract = "Map Matching Algorithms (MMAs) are developed to solve spatial ambiguities that arise in the process of assigning GPS measurements onto a digital roadway network. Scarce systematic parameter tuning approaches exist in the literature for optimizing MMA performance. Thus, a novel 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 algorithm-specific parameter values based on instance-specific information a priori to the execution of the MMA. Finally, the proposed IPTS tool is able to adjust to two particular decision maker preferences on algorithm performance, namely solution quality and computational time.",
    keywords = "Calibration, Electronic mail, Fuzzy logic, Global Positioning System, Roads, Tools, Tuning",
    author = "Carola Blazquez and Jana Ries and Miranda, {Pablo Andres} and Roberto Leon",
    year = "2018",
    month = "9",
    day = "24",
    doi = "10.1109/MITS.2018.2867527",
    language = "English",
    volume = "10",
    pages = "87--97",
    journal = "IEEE Intelligent Transportation Systems Magazine",
    issn = "1939-1390",
    publisher = "Institute of Electrical and Electronics Engineers Inc.",
    number = "4",

    }

    TY - JOUR

    T1 - An Instance-Specific Parameter Tuning Approach Using Fuzzy Logic for a Post-Processing Topological Map-Matching Algorithm

    AU - Blazquez, Carola

    AU - Ries, Jana

    AU - Miranda, Pablo Andres

    AU - Leon, Roberto

    PY - 2018/9/24

    Y1 - 2018/9/24

    N2 - Map Matching Algorithms (MMAs) are developed to solve spatial ambiguities that arise in the process of assigning GPS measurements onto a digital roadway network. Scarce systematic parameter tuning approaches exist in the literature for optimizing MMA performance. Thus, a novel 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 algorithm-specific parameter values based on instance-specific information a priori to the execution of the MMA. Finally, the proposed IPTS tool is able to adjust to two particular decision maker preferences on algorithm performance, namely solution quality and computational time.

    AB - Map Matching Algorithms (MMAs) are developed to solve spatial ambiguities that arise in the process of assigning GPS measurements onto a digital roadway network. Scarce systematic parameter tuning approaches exist in the literature for optimizing MMA performance. Thus, a novel 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 algorithm-specific parameter values based on instance-specific information a priori to the execution of the MMA. Finally, the proposed IPTS tool is able to adjust to two particular decision maker preferences on algorithm performance, namely solution quality and computational time.

    KW - Calibration

    KW - Electronic mail

    KW - Fuzzy logic

    KW - Global Positioning System

    KW - Roads

    KW - Tools

    KW - Tuning

    UR - http://www.scopus.com/inward/record.url?scp=85053292445&partnerID=8YFLogxK

    U2 - 10.1109/MITS.2018.2867527

    DO - 10.1109/MITS.2018.2867527

    M3 - Article

    VL - 10

    SP - 87

    EP - 97

    JO - IEEE Intelligent Transportation Systems Magazine

    JF - IEEE Intelligent Transportation Systems Magazine

    SN - 1939-1390

    IS - 4

    M1 - 8463456

    ER -