This article considers the problem of high-level decision process for autonomous vehicles on highways. The goal is to select a predictive reference trajectory among a set of candidate ones, issued from a trajectory generator. This selection aims at optimizing multi-criteria functions, such as safety, legal rules, preferences and comfort of passengers, or energy consumption. This work introduces a new framework for Multi-Criteria Decision Making (MCDM). The proposed approach adopts fuzzy logic theory to deal with heterogeneous criteria and arbitrary functions. Moreover, the consideration of uncertain vehicle's sensors data is done using the Dempster-Shafer Theory with fuzzy sets in order to provide a risk assessment. Simulation results using datasets collected under the NGSIM program are presented on car following cases, and extended to lane changing situations.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Multi-Criteria Decision Making for Autonomous Vehicles using Fuzzy Dempster-Shafer Reasoning


    Beteiligte:


    Erscheinungsdatum :

    01.06.2018


    Format / Umfang :

    1544030 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    MULTI-CRITERIA DECISION MAKING FOR AUTONOMOUS VEHICLES USING FUZZY DEMPSTER-SHAFER REASONING

    Claussmann, Lauréne / O Brien, Marie / Glaser, Sébastien et al. | British Library Conference Proceedings | 2018




    Implementation of a multi-criteria tracking based on the dempster-Shafer theory

    Magnier, Valentin / Gruyer, Dominique / Godelle, Jerome | IEEE | 2015


    Evidential Dominance for Decision Making in the Setting of Dempster-Shafer Theory

    Inuiguchi, M. / Shirai, T. / Sakawa, M. | British Library Online Contents | 1994