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    Motion Comfort Optimization for Autonomous Vehicles: Concepts, Methods, and Techniques

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    Motion_Comfort_Optimization_for_Autonomous_Vehicles_Concepts_Methods_and_Techniques.pdf (6.395Mb)
    Date
    2024
    Author
    Aledhari, Mohammed
    Rahouti, Mohamed
    Qadir, Junaid
    Qolomany, Basheer
    Guizani, Mohsen
    Al-Fuqaha, Ala
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    Abstract
    This article outlines the architecture of autonomous driving and related complementary frameworks from the perspective of human comfort. The technical elements for measuring autonomous vehicle (AV) user comfort and psychoanalysis are listed here. At the same time, this article introduces the technology related to the structure of automatic driving and the reaction time of automatic driving. We also discuss the technical details related to the automatic driving comfort system, the response time of the AV driver, the comfort level of the AV, motion sickness, and related optimization technologies. The function of the sensor is affected by various factors. Since the sensor of automatic driving mainly senses the environment around a vehicle, including 'the weather' which introduces the challenges and limitations of second-hand sensors in AVs under different weather conditions. The comfort and safety of autonomous driving are also factors that affect the development of autonomous driving technologies. This article further analyzes the impact of autonomous driving on the user's physical and psychological states and how the comfort factors of AVs affect the automotive market. Also, part of our focus is on the benefits and shortcomings of autonomous driving. The goal is to present an exhaustive overview of the most relevant technical matters to help researchers and application developers comprehend the different comfort factors and systems of autonomous driving. Finally, we provide detailed automated driving comfort use cases to illustrate the comfort-related issues of autonomous driving. Then, we provide implications and insights for the future of autonomous driving.
    DOI/handle
    http://dx.doi.org/10.1109/JIOT.2023.3287489
    http://hdl.handle.net/10576/66060
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    • Computer Science & Engineering [‎2482‎ items ]

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