Balajti, IstvanFarhat, Georges2023-12-202023-12-202023-12-01https://hdl.handle.net/2437/364137In enhancing driving safety, this investigation employs a combination of artificial intelligence (AI) and advanced radar systems to proactively predict and prevent collisions, thereby elevating overall vehicle safety. The study delves into the pivotal role played by radar-based systems in preempting crashes, highlighting key concepts that advocate for the collaborative use of AI and radar to bolster road safety, drawing insights from pertinent literature. Going beyond theoretical considerations, the research takes an empirical approach, conducting a thorough risk evaluation, identifying potential obstacles, and formulating safety protocols. Utilizing carefully designed measurement setups for processing radar signals, the study aims to facilitate effective braking and smooth cruising, outlining four crucial measurement steps and techniques for data interpretation and evaluation. Through systematic operation and testing initiatives, the research critically examines the effectiveness of collision prevention through simulations and theoretical foundations. Furthermore, the paper explores future directions by investigating how the integration of technology into smart transportation systems could further enhance road safety. This endeavor represents a significant stride in advancing vehicle safety by integrating AI and radar technologies. The research aspires to cultivate an environment where individuals feel safer whether driving personal vehicles or utilizing public transit. Through the provision of proactive collision avoidance services and competence development programs, the goal is to foster an atmosphere conducive to safety for all individuals involved.59 pagesenDriving safetyAIRadar systemsCollision AnticipationRoad safety EnhancementDEENK Témalista::Engineering Sciences::EngineeringHozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében.