###### Abstract  
Autonomous vehicles (AVs), defined as vehicles capable of navigation and decision-making independent of human intervention, represent a revolutionary advancement in transportation technology. These vehicles operate by synthesizing an array of sophisticated technologies, including sensors, cameras, GPS, radar, light imaging detection and ranging (LiDAR), and advanced computing systems. These components work in concert to accurately perceive the vehicle's environment, ensuring the capacity to make optimal decisions in real-time. At the heart of AV functionality lies the ability to facilitate intercommunication between vehicles and with critical road infrastructure--a characteristic that, while central to their efficacy, also renders them susceptible to cyber threats. The potential infiltration of these communication channels poses a severe threat, enabling the possibility of personal information theft or the introduction of malicious software that could compromise vehicle safety. This paper offers a comprehensive exploration of the current state of AV technology, particularly examining the intersection of autonomous vehicles and emotional intelligence. We delve into an extensive analysis of recent research on safety lapses and security vulnerabilities in autonomous vehicles, placing specific emphasis on the different types of cyber attacks to which they are susceptible. We further explore the various security solutions that have been proposed and implemented to address these threats. The discussion not only provides an overview of the existing challenges but also presents a pathway toward future research directions. This includes potential advancements in the AV field, the continued refinement of safety measures, and the development of more robust, resilient security mechanisms. Ultimately, this paper seeks to contribute to a deeper understanding of the safety and security landscape of autonomous vehicles, fostering discourse on the intricate balance between technological advancement and security in this rapidly evolving field. autonomous vehicles; cyber security AV attacks; AV attacks; AV safety; emotional intelligence; blockchain in AVs; big data and AVs; real-time decision making +
Footnote †: journal: Cybersecurity and Privacy  
0000-0000-0000-0000-0000-0000-0000-0000-0000-0000-0000-0000-00000-00000-00000-00000-00000-00000-00000-00000-00000-00000-00000-00000-00000-00000-00000-00000-00000-000000-00000-000000-00000-000000-000000-000000-0000 are engineered to handle all aspects of dynamic driving tasks under all conditions. They are capable of independently operating, even when faced with challenging road and climatic circumstances. The onus of safe operation under every driving condition is entirely on the vehicle's systems, requiring no human intervention. These vehicles have been developed to be capable of handling all parts of dynamic driving activities on their own, even when faced with difficult road and climatic circumstances. The utilization of accurate, trustworthy, and dependable sensor technologies is essential to their functioning. A conceptual representation of the functional architecture of these FAVs can be viewed in Figure 1.  
Prominent examples of such vehicles in today's landscape include the Google Driverless Car [1], AnnieWAY [2], and Stanford Shelley [3]. These vehicles leverage light imaging detection and ranging (LiDAR) technology to detect objects and recognize traffic signs. The sensor data collected by these technologies form a foundation in mission planning, and the onboard automated systems use this information to make key operational decisions. For instance, if an obstacle is detected by LiDAR, the mission plan of the vehicle adjusts to evade a potential collision. On the other hand, the growing complexity of AVs also brings about the emergence of new difficulties. An important concern that is emerging is the urge to ensure the safety and resilience of AV sensors in the face of cyber attacks.