Autonomous driving has become a prominent topic with the rise of intelligent urban vision in communities. Advancements in automated driving technology play a significant role in the intelligent transportation system. Autonomous vehicles (AVs) rely heavily on sensor technologies as they are responsible for navigating safely through their environment and avoiding obstacles. This paper aims to outline the vital role of sensor fusion in intelligent transportation systems. Sensor fusion is the process of combining data from multiple sensors to obtain more comprehensive measurements and greater cognitive abilities than a single sensor could achieve. By merging data from different sensors, it ensures that driving decisions are based on reliable data, with improved accuracy, reliability, and robustness in AVs. This paper provides a comprehensive review of AV capacity, impacts, planning, technological challenges, and omitted concerns. We used state-of-the-art evaluation tools to check the performance of different sensor fusion algorithms in AVs. This paper will help us to determine our position, direction, the impacts of AVs on society, the need for smart city mobility outcomes, and the way to solve the auto industry challenges in the future. The analysis of AV systems from the perspective of sensor fusion in this research is expected to be beneficial to current and future researchers.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Robust Cognitive Capability in Autonomous Driving Using Sensor Fusion Techniques: A Survey


    Contributors:
    Nawaz, Mehmood (author) / Tang, Jeff Kai-Tai (author) / Bibi, Khadija (author) / Xiao, Shunli (author) / Ho, Ho-Pui (author) / Yuan, Wu (author)


    Publication date :

    2024-05-01


    Size :

    3382400 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Multi-sensor fusion for autonomous driving

    Zhang, Xinyu / Li, Jun / Li, Zhiwei et al. | TIBKAT | 2023


    Sensor Fusion Algorithm that Has Resilience under Autonomous Driving Conditions: A Survey

    Park, Sung Bum ;Kwon, Hyeok Chan ;Lee, Dong Hoon | Trans Tech Publications | 2017


    SENSOR FUSION FOR AUTONOMOUS DRIVING TRANSITION CONTROL

    CHANDY ASHOK | European Patent Office | 2018

    Free access

    VEHICLE WITH AUTONOMOUS DRIVING CAPABILITY

    MIKAEL KARLSSON / ANDERS KELLSTROEM | European Patent Office | 2021

    Free access

    Sensor fusion for autonomous driving transition control

    CHANDY ASHOK | European Patent Office | 2019

    Free access