Safe Data-Driven Control in Autonomous Vehicles and Transportation Systems

Safe data-driven control systems are necessary for large-scale automation in contemporary transport networks, including networked autonomous cars. In this research, methods, issues, and possible developments in autonomous vehicle system safety are examined. The chapter discusses important subjects including real-time data processing, cybersecurity, sensor fusion, and AI-enabled predictive modelling. evaluating Examine how VANETs may enhance communication between infrastructure, ad hoc networks, and automobiles. In addition, learn how crucial expert diagnostic systems are for prompt problem identification and fixing. The focus of the article is on encryption, authentication, and anomaly detection as it examines cybersecurity threats and countermeasures. Studies contrasting regional adoption and accident rates demonstrate the benefits of autonomous vehicles for both transport efficiency and traffic safety. The highlights underscore the need of strict safety equipment and multi-tiered security to increase closure and confidence in autonomous transportation systems.