Automotive Intelligence Embedded in Electric Connected Autonomous and Shared Vehicles Technology for Sustainable Green Mobility

Vermesan, Ovidiu; John, Reiner; Pype, Patrick; Daalderop, G. H. O.; Kriegel, Kai; Mitić, G.; Lorentz, Vincent; Bahr, Roy; Sand, Hans Erik; Bockrath, Steffen; Waldhör, Stefan · 2021 · OpenAlex-citations

DOI: 10.3389/ffutr.2021.688482

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Summary

This review paper addresses the technological convergence required to realize Electric Connected Autonomous and Shared (ECAS) vehicles as a cornerstone of sustainable green mobility. Motivated by the European Green Deal’s goal of climate neutrality by 2050 and the need to mitigate environmental degradation, the authors examine how digitalization accelerates the integration of perception, computing, connectivity, and propulsion systems. The paper aims to provide an overview of advances in artificial intelligence (AI) and related technologies that enable ECAS vehicles to function as intelligent agents, optimizing performance, safety, and decision-making while transitioning from traditional ownership models to multimodal, shared mobility services. The authors conduct a comprehensive review of existing literature, standards, and technological frameworks. They analyze the evolution of automotive architectures from domain controllers to zonal and federated edge/cloud-centric systems. The study evaluates the role of AI definitions—Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI), and Artificial Superintelligence (ASI)—in replicating human cognitive capabilities such as reasoning, learning, and collaboration. The paper also assesses regulatory frameworks, including SAE J3016 automation levels and various ISO and CEN standards for safety, cybersecurity, and interoperability. It explores the integration of Vehicle-to-Everything (V2X) communication, edge computing, Internet of Things (IoT), and swarm intelligence to create holistic intrinsic and extrinsic intelligence within the automotive ecosystem. Key findings indicate that ECAS vehicles must leverage AI to match or exceed human driver capabilities by locating, sensing, comprehending, and acting within dynamic environments. The convergence of electrification, automation, connectivity, and digitalization allows vehicles to operate as "edge micro servers on wheels," utilizing swarm intelligence to exchange data with infrastructure and other vehicles. This connectivity supports cooperative mobility, energy management, and real-time decision-making. The review highlights that achieving trustworthiness in AI-based hardware and software is critical, requiring transparency, explainability, and adherence to rigorous safety standards. The paper identifies that while ANI currently supports specific tasks like machine vision, future deployment relies on advancing toward AGI for full autonomy, supported by robust cybersecurity and standardized regulatory guidelines. The significance of this work lies in its holistic framework for understanding the technological and regulatory prerequisites for sustainable mobility. It underscores that digital technologies are essential enablers for decarbonization and efficiency, transforming vehicles into interconnected nodes within a broader Internet of Vehicles (IoV) and Internet of Energy (IoE). The authors conclude that successful implementation requires addressing open challenges in AI trustworthiness, standardization, and the integration of intrinsic vehicle intelligence with extrinsic infrastructure capabilities. This review provides a roadmap for industry stakeholders to develop safe, secure, and efficient ECAS systems that align with global sustainability goals and evolving consumer demands for shared, autonomous transportation.

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