• Shreya Mehare
• Rutuja Lohakare
• Rutuja Dahikar
• Sanyukta Padole
• Esha Juware

Ensuring driving safety and preventing fatal collisions in autonomous vehicles are imperative tasks, highlighting the crucial importance of sharing raw sensor information among these vehicles. This practice enhances their ability to see through obstacles, ultimately safeguarding the driving experience. This paper focuses on developing an autonomous driving system using a Raspberry Pi model with 2GB of RAM. The system employs live image processing to detect road signs, with a specific emphasis on recognizing and responding to stop signs. Upon detecting a stop sign, the system autonomously halts the vehicle. Additionally, the system incorporates lane-following capabilities through image processing, ensuring the vehicle stays within designated lanes. To enhance safety, an ultrasonic sensor is integrated to detect objects, prompting the system to come to a stop when obstacles are identified. This comprehensive approach combines computer vision and sensor technologies to create a functional autonomous driving prototype suitable for real-world applications.

Autonomous Driving, Image Processing, Python programming, Raspberry Pi.

"Research on Autonomous Driving Vehicle ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.e879-e882, April-2024, Available :http://www.jetir.org/papers/JETIR2404499.pdf

"Research on Autonomous Driving Vehicle ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppe879-e882, April-2024, Available at : http://www.jetir.org/papers/JETIR2404499.pdf