Life-saving advanced driver-assistance systems (ADASs) and autonomous vehicles (AVs) are the fastest growing technology segment in the automotive market. Artificial intelligence (AI) is one of the most critical components in ADAS and AV. Machine learning (ML), deep Learning (DL), simulators, cloud computing, and embedded hardware platforms are entering the equation of ADAS and AV innovation, especially at level four and level five automation, where the classic rule-based ADAS functions reach their limits. This chapter reviews the basic concepts and recent applications of AI in ADAS and AV, including supervised learning, unsupervised learning, reinforcement learning, DL architectures in AVs, mostly used DL algorithms, edge cases and safety, training datasets, simulators, and infrastructures.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Basics and Applications of AI in ADAS and Autonomous Vehicles


    Contributors:
    Li, Yan (editor) / Shi, Hualiang (editor) / Li, Yan (author) / Huang, Zhiheng (author)


    Publication date :

    2022-10-28


    Size :

    32 pages




    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    ADAS CONTROL SYSTEM AND METOHD FOR ADAS AND AUTONOMOUS VEHICLES

    KIM TAE JIN | European Patent Office | 2022

    Free access

    Light Source Authentication in ADAS/Autonomous Vehicles

    Ansari, Asadullah / KAMALAKANNAN, DINESH / Velusamy, Kabilan et al. | SAE Technical Papers | 2021


    Light Source Authentication in ADAS/Autonomous Vehicles

    Ansari, Asadullah / Das, Pamela / Aziz, Mohammad et al. | British Library Conference Proceedings | 2021


    ADAS in Autonomous Driving

    Ng, Tian Seng | Springer Verlag | 2021


    Incorporating high fidelity physics into ADAS and autonomous vehicles simulation

    Sovani, Sandeep / Johnson, Lee / Duysens, Jacques | Springer Verlag | 2017