Abstract Automotive industry is currently facing two global changes. There is a transition from the vehicles with internal combustion engines to the various hybrid and fully electrical vehicles. Another transition is the introduction of more intelligence and communication capabilities what creates a trend toward the development and application of fully autonomous vehicles. Both transitions are complex and decisions on the optimal pathways depend on the big data, but also on incomplete and inconsistent knowledge and expectations. Considering the fuzziness of the global business, social, ethical, and other domains, the paper presents results of the investigation and the application of fuzzy logic in a decision-making process of the transition to autonomous vehicles, conducted by car manufacturers. It considers the crisp and fuzzy information, outcomes, and actions and compares the values of additional information.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Managing Transition to Autonomous Vehicles Using Bayesian Fuzzy Logic


    Contributors:


    Publication date :

    2019-01-01


    Size :

    13 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Intelligent landing of autonomous aerial vehicles using fuzzy logic control

    Saghafi, Fariborz / Pouya, Soha / Khansari Zadeh, S. M. | IEEE | 2009


    MANAGING AUTONOMOUS VEHICLES

    VAUGHN ROBERT LAWSON / GRESHAM TIMOTHY J / KUKIS COREY et al. | European Patent Office | 2017

    Free access

    Managing autonomous vehicles

    DELIZIO ANDREW | European Patent Office | 2021

    Free access

    MANAGING AUTONOMOUS VEHICLES

    DELIZIO ANDREW | European Patent Office | 2020

    Free access

    MANAGING AUTONOMOUS VEHICLES

    DELIZIO ANDREW | European Patent Office | 2021

    Free access