Preprint Review Version 2 Preserved in Portico This version is not peer-reviewed

Practical Autonomous Driving: A Survey of Challenges and Opportunities

Version 1 : Received: 7 February 2022 / Approved: 8 February 2022 / Online: 8 February 2022 (15:42:51 CET)
Version 2 : Received: 4 October 2023 / Approved: 6 October 2023 / Online: 10 October 2023 (12:28:06 CEST)

How to cite: De, S.; Saha, D.; Sallam, K.; Mohamed, A.; Radwan, I. Practical Autonomous Driving: A Survey of Challenges and Opportunities. Preprints 2022, 2022020123. https://doi.org/10.20944/preprints202202.0123.v2 De, S.; Saha, D.; Sallam, K.; Mohamed, A.; Radwan, I. Practical Autonomous Driving: A Survey of Challenges and Opportunities. Preprints 2022, 2022020123. https://doi.org/10.20944/preprints202202.0123.v2

Abstract

Autonomous Driving (AD) has become a prominent research area in the field of Artificial Intelligence (AI) and Machine Learning (ML) in recent years. This opens the door wider for self-driving cars to surpass conventional vehicles in the current market share. Despite its apparent simplicity, AD is composed of complex and heterogeneous systems, which are in need of a high level of coordination and alignment to ensure both full automation and safety. Therefore, numerous research studies have been conducted over the last few years to facilitate such coordination and accelerate the capacity of these types of vehicles to be self-managed in complex situations. The paper summarises these approaches that led to building what is known nowadays as the autonomous driving pipeline. Moreover, although skepticism exists regarding the practicality of AD as a viable alternative to traditional vehicles, extensive research suggests the multiple benefits of relying on them for mobility. While challenges remain in implementing AD in the real world, including regulation and technical issues, substantial progress in recent years indicates a growing acceptance of AD in the near future. This paper further explores the advantages and opportunities of the conducted such systems in facilitating the practicality of Autonomous Driving.

Keywords

cnn; ann; robotics; machine learning; ann; artificial intelligence

Subject

Computer Science and Mathematics, Robotics

Comments (1)

Comment 1
Received: 10 October 2023
Commenter: Shuvodeep De
Commenter's Conflict of Interests: Author
Comment: Paper revised, updated and contributing authors added. Also, abstract and introduction substantially modified. The figures have been changed and their references/sources added.
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