• Payal Thakur
• Navjot Singh Talwandi
• Shanu Khare
• Rohini

For autonomous vehicles to gain general acceptance and earn the public's trust, safety must be achieved. To provide safer selfdriving cars, this article investigates the potential of artificial intelligence (AI) in two ways: AI-based assessment and collision avoidance systems. Utilizing AI's capacity to examine enormous volumes of sensor data from cameras, LiDAR, and radar is the first part of the strategy. The AI can comprehend the surrounding environment, including traffic patterns, road conditions, and pedestrian behavior, thanks to its real-time evaluation. With historical data and real-time scenarios, machine learning algorithms can be trained to recognize possible risks and anticipate the actions of pedestrians and other vehicles. The second part is about collision avoidance systems driven by AI. The AI can make important decisions quickly by constantly evaluating the surroundings and foreseeing any threats. To avoid a collision, this can entail starting actions like braking, swerving, or changing speed. The study explores several AI methods that can be used for this, including reinforcement learning and deep learning. Furthermore, discussed are the difficulties and restrictions posed by AI in autonomous cars, such as the limitations of the sensors, moral issues that must be considered when making decisions, and the requirement for strict safety regulations. Overall, this study makes the case that AI-based evaluation and collision avoidance systems have great potential to make autonomous cars safer and pave the road for a day when self-driving cars will be dependable and effective

"AUTONOMOUS VEHICLE SAFETY: AI-BASED ASSESSMENT AND COLLISION AVOIDANCE SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 1, page no.e225-e232, January-2025, Available :http://www.jetir.org/papers/JETIR2501429.pdf

"AUTONOMOUS VEHICLE SAFETY: AI-BASED ASSESSMENT AND COLLISION AVOIDANCE SYSTEM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 1, page no. ppe225-e232, January-2025, Available at : http://www.jetir.org/papers/JETIR2501429.pdf