Hardcover: 352 pagesYear: 2014Publisher: Oxford University PressISBN-13: 978-0199678112“The first ultraintelligent machine is the last invention that man need ever make, provided that the machine i...

Superintelligence: Paths, Dangers, Strategies

The rapid evolution of autonomous technology in the field of automotive and information technology (IT) has made it possible to implement autonomous vehicles (AVs) for public passenger transport. Although the shuttle bus transport capacities currently in use are low (maximum 15 people), the use of these transport units in large urban agglomerations is beneficial for society. The current paper is written to review the current AV implementation with respect to shuttle buses with its direct implications in their scientific evolution, with direct links to the legal and social aspects of public transportation all over the world. A critical aspect that is presented in the paper is the legal framework of autonomous driving, which is extremely uneven around the globe, with the direct impact of autonomous shuttle bus exploitation. As the legislation on AVs presents some shortcomings in the approval, registration, and public road implementation of these vehicles, many of the world’s major cities have found ways to integrate them into testing programs, establishing the basis for future comprehensive legislative measures in this highly dynamic scientific domain. The current technological solutions adopted by several autonomous shuttle bus producers will be presented with an exhaustive overview of each major component. The aspects of the control algorithm, with its complicated layers of security and perturbance factors, will be explained in detail. Thus, in some countries/cities, autonomous shuttle buses have been implemented on less-traveled routes where they can travel at speeds up to 25 km/h without hindering the public’s circulation, such as university campuses, industrial areas, airports, and sports bases. Some countries/cities use autonomous shuttle buses for pilot programs related to passenger transport, while others use them in postal transport and others for scientific purposes. In all of these situations, the first step in autonomous driving has been taken. The paper also makes an evaluation of the social factors that are a consequence of the mass introduction of autonomous driving as a means of public transportation. Autonomous shuttle buses are becoming a part of everyday life in big cities. Their acceptance as a strategic means of transport depends on their efficiency in daily services; through its efficiency, this means of transport will become a game-changer once its benefits become not only known but experienced by a large number of users.

Autonomous Shuttle Bus for Public Transportation: A Review

Battery electric vehicles (BEVs) and fuel cell electric vehicles (FCEVs), whose exhaust pipes emit nothing, are examples of zero-emission automobiles. FCEVs should be considered an additional technology that will help battery-powered vehicles to reach the aspirational goal of zero-emissions electric mobility, particularly in situations where the customers demand for longer driving ranges and where using batteries would be insufficient due to bulky battery trays and time-consuming recharging. This study stipulates a current evaluation of the status of development and challenges related to (i) research gap to promote fuel-cell based HEVs, (ii) key barriers of fuel-cell based HEVs, (iii) advancement of electric mobility and their power drive, (iv) electrochemistry of fuel cell technology for FCEVs, (v) power transformation topologies, communication protocols, and advanced charging methods, (vi) recommendations and future prospects of fuel-cell HEVs, and (vii) current research trends of EVs, and FCEVs. This article discusses key challenges with fuel cell electric mobility, such as low fuel cell performance, cold starts, problems with hydrogen storage, cost-reduction, safety concerns, and traction systems. The operating characteristics and applications of several fuel-cell technologies are investigated for FCEVs and FCHEVs. An overview of the fuel cell is provided, which serves as the primary source of energy for FCHEVs, along with comparisons and its electrochemistry. The study of power transformation topologies, communication protocols, and enhanced charging techniques for FCHEVs has been studied analytically. Recent technology advancements and the prospects for FCHEVs are discussed in order to influence the future vehicle market and to attain the aim of zero emissions. 

Fuel Cell-based Hybrid Electric Vehicles: An Integrated Review of Current Status, Key Challenges, Recommended Policies, and Future Prospects

The automotive sector digitalization accelerates the technology convergence of perception, computing processing, connectivity, propulsion, and data fusion for electric connected autonomous and shared (ECAS) vehicles, bringing new computing paradigms at the edge with embedded cognitive capabilities into the vehicle domains and data infrastructure to provide holistic intrinsic and extrinsic intelligence for new mobility applications. Innovation occurs predominantly in ECAS vehicles' architectures, intelligent functions, operations, and automotive digital infrastructure. Artificial Intelligence (AI), cellular/wireless connectivity, edge computing, Internet of Things (IoT), Internet of Intelligent Things, digital twins (DTs), virtual/augmented reality (VR/AR) and distributed ledger technologies (DLTs) converge to facilitate vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I) and vehicle-to-everything (V2X) communication and automation. Expanding automotive intelligence at the vehicle and mobility system level allows the Internet of Vehicles (IoV) and Internet of Energy (IoE) to become the key enabling technologies to realize future autonomous driving scenarios that embed cognition and autonomous functions. Vehicles become intelligent connected edge micro-servers on wheels, powered by software, smart virtual functions and integrated into the digital infrastructure. Electrification, automation, connectivity, digitalization, decarbonization, decentralization, and standardization are the main drivers that unlock intelligent vehicles' potential for sustainable green mobility applications. ECAS vehicles act as autonomous agents using swarm intelligence to communicate and exchange information either directly or indirectly with each other and the infrastructure, accessing independent services such as energy, high-definition maps, routs, infrastructure information, traffic lights, tolls, parking (micropayments) and finding emergent/intelligent solutions. Digitalization is also radically transforming the powertrains in electric vehicles (EVs). For example, in the battery domain, the batteries' architectures are optimizing the cables to the sensors and sensing point. Innovations like smart battery cells assembled in complex battery systems, with wireless communication between the smart cells and the central battery management system (BMS), enable ultra-high-speed interaction with the smart battery cell parameters. The article presents ECAS vehicles' evolution towards domain controller, zonal vehicle, and federated vehicle/edge/cloud-centric based on distributed intelligence at the vehicle and infrastructure level architectures and the role of AI techniques and methods to implement the different autonomous driving and optimization functions for sustainable green mobility.

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

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.

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

This chapter presents the Internet of Vehicles (IoV) concept, technologies and applications used to realise intelligent functions, optimise vehicle performance, control, and decision-making for future electric, connected, autonomous, and shared (ECAS) vehicles mobility scenarios. The concept addresses the convergence of the edge intelligence embedded in the vehicles based on Artificial Intelligence (AI) technologies with the cooperative, collaborative intelligence distributed into the Internet of Things (IoT) devices and edge computing infrastructure federated with the hierarchical cognitive processes and analytics in physical, network, infrastructure, and data spaces. IoV integrates and links the ECAS vehicles’ domains with the intra-vehicle networks, vehicle-to-everything (V2X) networks, the processing and cognitive functions provided by federated platforms using the intelligent edge and cloud computing infrastructure. The cognitive transformation of vehicles and the integration of immersive technologies, i.e., virtual reality (VR) and augmented reality (AR) combined with intelligent connectivity, IoT, Distributed Ledger Technologies (DLTs), digital twins (DTs), data, knowledge, security/privacy requirements and learning platforms provide the technological foundation of IoV allowing for entirely new services, applications, and user experiences. The paper advances the latest architectural concepts for ECAS vehicles. It proposes an IoV 3D multi-layered architecture that combines AI, edge computing and connectivity as part of the functional layers while integrating the system properties and trustworthiness properties into the overall architecture to provide efficient new mobility applications and services. The proposed system of systems concept for IoV applications allows for distributed intelligent functions to be embedded into the edge and cloud infrastructure for ECAS vehicles to provide a computing, processing, and intelligent connectivity continuum for IoV applications and services.

Internet of Vehicles – System of Systems Distributed Intelligence for Mobility Applications

As urban populations increase, issues such as traffic jams, pollution and road fatalities will grow in tandem. More than half of the world’s population now lives in urban areas (54 %), and growth is expected to accelerate in years to come.

Intelligent Transport Systems: The Trials Making Smart Mobility a Reality

The goal of this chapter is to give a high-level overview about the importance of privacy and security provisions in autonomous vehicles. It describes where we currently are, where the challenges with security and privacy may be in the context of autonomous vehicles, and what should be done to deal with those challenges. Thereby, it is also important to take the user into account, as he/she has to trust the autonomous vehicle and the company behind it; otherwise autonomous vehicles will not get accepted. Trust here is related to security, privacy but also safety

Privacy and Security in Autonomous Vehicles

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

Internet of Vehicles – System of Systems Distributed Intelligence for Mobility Applications

Intelligent Transport Systems: The Trials Making Smart Mobility a Reality

Privacy and Security in Autonomous Vehicles