Shortcomings of Ultrasonic Obstacle Detection for Vehicle Driver Assistance and Profiling

Obuhuma, James I.; Okoyo, Henry O.; McOyowo, Sylvester O.

doi:10.5815/ijitcs.2019.06.04

Cited by 4 publications

(1 citation statement)

References 22 publications

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“…Ultrasonic sensors use sound waves to detect objects in close proximity to the vehicle. They are particularly useful for parking assistance and obstacle detection at low speeds, enhancing the safety of autonomous vehicles during maneuvers (Obuhuma, Okoyo & McOyowo, 2019, Toa & Whitehead, 2020. Actuators and control mechanisms translate decisions made by embedded systems into physical actions, enabling the vehicle to navigate its environment autonomously.…”

Section: State-of-the-art Technologies Empowering Embedded Systemsmentioning

confidence: 99%

A comprehensive review of embedded systems in autonomous vehicles: Trends, challenges, and future directions

Sedat Sonko,

Emmanuel Augustine Etukudoh,

Kenneth Ifeanyi Ibekwe

et al. 2024

World J. Adv. Res. Rev.

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The integration of embedded systems in autonomous vehicles represents a transformative paradigm shift in the automotive industry, offering unprecedented opportunities for enhanced safety, efficiency, and user experience. This comprehensive review explores the current landscape of embedded systems in autonomous vehicles, delving into emerging trends, persistent challenges, and future directions that shape the trajectory of this rapidly evolving field. The review begins by examining the foundational concepts of embedded systems in the context of autonomous vehicles, elucidating the intricate interplay between hardware and software components. It surveys the state-of-the-art technologies that empower these systems, including advanced sensors, actuators, and communication protocols, highlighting their pivotal roles in perception, decision-making, and control aspects of autonomous driving. One of the prominent trends discussed in this review is the increasing reliance on artificial intelligence (AI) and machine learning algorithms within embedded systems. The incorporation of these intelligent algorithms enables vehicles to adapt and learn from real-world scenarios, enhancing their ability to navigate diverse and dynamic environments. Additionally, the review sheds light on the growing emphasis on connectivity and edge computing, illustrating how embedded systems leverage these technologies to facilitate seamless communication between vehicles and their surrounding infrastructure. Despite the promising advancements, the review critically examines the persistent challenges that impede the widespread adoption of embedded systems in autonomous vehicles. Issues such as safety concerns, cybersecurity threats, and regulatory frameworks are analyzed, providing insights into the complex ecosystem in which these technologies operate. In addressing the future directions of embedded systems in autonomous vehicles, the review envisions a trajectory marked by continuous innovation and collaboration across industries. It anticipates the evolution of embedded systems towards more robust, adaptive, and fault-tolerant architectures, paving the way for increased autonomy and widespread deployment of autonomous vehicles. This comprehensive review provides a holistic understanding of embedded systems in autonomous vehicles, encapsulating current trends, challenges, and future directions. As the automotive landscape undergoes a paradigm shift, this review serves as a valuable resource for researchers, practitioners, and policymakers seeking to navigate the dynamic terrain of autonomous vehicle technology.

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Section: State-of-the-art Technologies Empowering Embedded Systemsmentioning

confidence: 99%