Preface

Vehicles play a crucial role in modern society, contributing significantly to various aspects of life. Vehicles provide mobility for people and goods, facilitating travel and transportation of goods over short and long distances. They enable commuting to work, school, healthcare facilities, and recreational activities, thus enhancing overall accessibility and quality of life. The automotive industry is a major contributor to the global economy. It creates millions of jobs worldwide, directly and indirectly, in manufacturing, sales, services, and related sectors. Additionally, vehicles support other industries by transporting raw materials and finished goods, fostering economic growth and development.

Vehicles ushered in the era of autonomy, first through assisted driving and second with the goal of reaching full autonomy in driving, parking, and so on. Vehicles face numerous challenges, ranging from technological limitations to social and environmental concerns. Addressing these challenges requires a holistic approach involving collaboration between governments, industry players, academia, and civil society to foster innovation, sustainability, and resilience in the automotive sector.

As part of this innovation, vehicular networks based on vehicular communications, also known as V2X (Vehicle-to-Everything) communication, refers to the exchange of data between vehicles (V2V), infrastructure (V2I), pedestrians (V2P), and other entities such as cyclists and road operators (V2R). This communication enables vehicles to interact with their surroundings, improving safety, efficiency, and convenience on the road.

This book discusses different aspects related to vehicular networks. It is organized into two sections. The first section, "Application Fields", begins with Chapter 1, "Introductory Chapter: Vehicles Everywhere, and Vehicular Communications Should Follow!". The introductory chapter gives an overview of the different and most recent and innovative applications of modern industries for vehicles, such as automated guided vehicles (AGV) in smart maritime ports or in logistics companies, and more. The main idea of this introduction is that where we have vehicles, we should also have vehicular networks, which are necessary to overcome some of the previously cited challenges. Chapter 2, "C-V2X Vision in the Chinese Roadmap: Standardization, Field Tests, and Industrialization", analyzes activities and applications of vehicular communications in the special case of China, which is a large country with a large population and huge number of used vehicles either in private lives or industries. China continuously and actively focuses on and contributes to C-V2X technology development. Starting from the standardization progress, the chapter presents several Chinese-specific use cases and communication messages for complicated urban traffic. Based on these higher-layer protocols, annual field tests are conducted to determine the interoperability among chipsets, modules, security certificates, and original equipment manufacturers (OEMs). Putting forth effort on industry standards and tests, China is fast commercializing C-V2X

based road services (e.g., robotaxi, robot bus) in representative cities. Thus, in this chapter, we highlight advanced Chinese C-V2X philosophy. Chapter 3, "Mapping the Applications of Vehicular Communications in the Context of Smart Maritime Ports", discusses the very special use case of autonomous vehicles in smart maritime ports to load/unload or transport containers. In the smart maritime port environment, vehicular applications are adopted everywhere, such as AGVs to transport containers, unmanned aerial vehicles for different port operations, and more. This chapter discusses some concrete examples of these vehicular applications in the smart port environment and the adequate and optimal vehicular communication technologies to be deployed to support a reliable data transmission for these applications.

The second section, "Advanced Approaches", presents some advanced approaches to optimize the functioning of vehicular communications, such as machine learning as part of artificial intelligence. It also explores how to address some of the major challenges facing vehicular communications, like security issues. As vehicles become more connected and reliant on digital systems, they are increasingly vulnerable to cybersecurity threats such as hacking, malware, and data breaches. Safeguarding vehicle cybersecurity requires implementing robust security measures, including encryption, intrusion detection systems, and secure software development practices. Therefore, Chapter 4, "Secure Vehicular Networking: Architectures, Applications, Attacks, and Challenges", delves into the intricate details of vehicular communications, exploring their architectures, characteristics, applications, and governing standards. Furthermore, it elucidates the concept of communication security within these networks, outlining the existing models of attackers, classifications of attacks, and fundamental security mechanisms. The comprehensive overview sheds light on the critical aspects of securing vehicular networks in the ever-evolving landscape of communication technology. Machine learning (ML), as an integral part of artificial intelligence (AI), has recently been used in wireless networks to provide continuous information to deal with culturally challenging issues. Chapter 5, "VANET: A Machine Learning Approach", examines recent progress in the use of ML in automotive networks. It differentiates the obvious characteristics of multifunctional vehicle networks and promotes the use of ML to deal with subsequent difficulties. Chapter 6, "Speed Control of Inflow Vehicles for Merging Support on Motorways with Limited I2V Communication", discusses the speed control of inflow vehicles for merging support on motorways through the special scenario of automated driving in a limited V2I infrastructure environment.

> **Abdelfatteh Haidine** National School of Applied Sciences El Jadida (ENSAJ), University Chouaib Doukkali, El Jadida, Morocco

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Section 1

Application Fields
