Artificial Intelligence and Software Modeling Approaches in Autonomous Vehicles for Safety Management: A Systematic Review

Abbasi, Shirin; Rahmani, Amir Masoud

doi:10.3390/info14100555

Cited by 7 publications

(4 citation statements)

References 76 publications

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“…With the intersection of material science and bioscience at the biointerface, the advent of Computer-Assisted Organic Synthesis (CAOS) (Sankaranarayanan and Jensen, 2023) has emerged as a powerful tool for synthetic planning. In recent years, the exponential growth in reaction datasets and computational power has paved the way for the development of advanced machine learning (ML) and artificial intelligence (AI) models specifically tailored for CAOS programs (Abbasi and Rahmani, 2023). These models exhibit the capability to accurately predict individual synthetic and retrosynthetic reactions, offering valuable insights for chemists in designing synthetic pathways.…”

Section: Integration Of Ai In Retrosynthesis and Reaction Predictionmentioning

confidence: 99%

The recent advances in the approach of artificial intelligence (AI) towards drug discovery

Khan,

Raza,

Shahbaz

et al. 2024

Front. Chem.

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Artificial intelligence (AI) has recently emerged as a unique developmental influence that is playing an important role in the development of medicine. The AI medium is showing the potential in unprecedented advancements in truth and efficiency. The intersection of AI has the potential to revolutionize drug discovery. However, AI also has limitations and experts should be aware of these data access and ethical issues. The use of AI techniques for drug discovery applications has increased considerably over the past few years, including combinatorial QSAR and QSPR, virtual screening, and denovo drug design. The purpose of this survey is to give a general overview of drug discovery based on artificial intelligence, and associated applications. We also highlighted the gaps present in the traditional method for drug designing. In addition, potential strategies and approaches to overcome current challenges are discussed to address the constraints of AI within this field. We hope that this survey plays a comprehensive role in understanding the potential of AI in drug discovery.

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Section: Integration Of Ai In Retrosynthesis and Reaction Predictionmentioning

confidence: 99%

The recent advances in the approach of artificial intelligence (AI) towards drug discovery

Khan,

Raza,

Shahbaz

et al. 2024

Front. Chem.

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“…Communication protocols enable seamless data exchange between vehicles and infrastructure, fostering a connected and cooperative environment. Key communication technologies include; Vehicle-to-Vehicle (V2V) Communication allows vehicles to share real-time information with each other, such as speed, position, and traffic conditions (Abbasi & Rahmani, 2023, Singh, 2023. This enables collaborative decision-making, improving overall traffic flow and enhancing safety by preventing collisions.…”

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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“…While these aspects hold minimal significance in traditional vehicles, self-driving cars can potentially trigger damage, accidents, and diminished safety. Numerous challenges have arisen in this realm, primarily stemming from the intricacies of system design and the critical demands of data collection at the network level, which subsequently inform decision-making processes [37].…”

Section: Technological Overview Of Autonomous Vehiclesmentioning

confidence: 99%

Driving Sustainability: Carbon Footprint, 3D Printing, and Legislation concerning Electric and Autonomous Vehicles

Jovanović,

Mateo Sanguino,

Damjanović

et al. 2023

Sensors

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In recent years, there has been a remarkable development in the technology and legislation related to electric and autonomous vehicles (i.e., EVs/AVs). This technological advancement requires the deployment of the most up-to-date supporting infrastructure to achieve safe operation. Further infrastructure is needed for Level 5 vehicles, namely the introduction of super-fast wireless 5G technology. To achieve harmony between the rapid technological advancement of EVs/AVs and environmental preservation, enacting legislation related to their sustainable use is vital. Thus, this manuscript provides a review of the technological development of EVs/AVs, with a special focus on carbon footprints and the implementation of additive manufacturing using recycled materials. While EVs have a 12.13% increased carbon footprint compared to conventional vehicles, AVs with basic and advanced intelligence features have an increased carbon footprint of 41.43% and 99.65%, respectively. This article emphasizes that the integration of 3D-printed components has the potential to offset this impact with a substantial 60% reduction. As a result, custom-made solutions involving 3D printing are explored, leading to greater speed, customization, and cost-effectiveness for EVs/AVs. This article also lists the advantages and disadvantages of the existing legislation in Spain, the United Kingdom, and the western Balkans, demonstrating various approaches to promoting electric mobility and the development of autonomous vehicles. In Spain, initiatives like the MOVES program incentivize EV adoption, while the UK focuses on expanding the EV market and addressing concerns about EVs’ quiet operation. In the western Balkans, the adoption of legislation lags behind, with limited incentives and infrastructure for EVs. To boost sales, legal mechanisms are necessary to reduce costs and improve accessibility, in addition to offering subsidies for the purchase of EVs. To this end, an analysis of the incentive measures proposed for the development and use of renewable power sources for the supply of energy for EVs/AVs is presented.

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Artificial Intelligence and Software Modeling Approaches in Autonomous Vehicles for Safety Management: A Systematic Review

Cited by 7 publications

References 76 publications

The recent advances in the approach of artificial intelligence (AI) towards drug discovery

The recent advances in the approach of artificial intelligence (AI) towards drug discovery

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

Driving Sustainability: Carbon Footprint, 3D Printing, and Legislation concerning Electric and Autonomous Vehicles

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