Autonomous Car and Lane Detection
Keywords:
Convolutional Neural Network, Self Driving Car, Computer Vision, Computer VisionAbstract
In This Paper, Simulation of autonomous car using Convolutional Neural Network(CNN) and Deep Neural Network(DNN’s) is proposed. Real-time Lane is detected using various mathematical computation and advanced libraries of Python are used. Libraries like Numpy, Pandas, Keras and Computer Vision are used in this Project. As there are various stages of autonomy of cars, This project demonstrate the higher level of autonomous car. Which include self driving steering, along with Traffic Sign Detection, and acceleration of car with high accuracy. Open CV i.e Computer Vision Library is used to play with real-time images captured while driving a car.
References
“SELF DRIVING CAR USING DEEP Q-LEARNING” Akhilesh Thete, Chinmay Toley, Shreyas Inamdar
“Self-Driving Car based on Image Processing with Machine Learning” Prof. Shilpa Satre, Vinayak Bhat, Pranay Gadhave, Nikhil Jadhav
“Self-Driving Cars: Automation Testing Using Udacity Simulator” Shahzeb Ali
“Self Driving Car Using Machine Learning” Tej Kurani, Nidhip Kathiriya, Uday Mistry, Prof. Lukesh Kadu, Prof. Harish Motekar]
“Open CV based autonomous RC Car”, B,Sabith, K.Akila, S,Krishna Kumar, D.Mohan
“A Study on Google Driverless Car” K Ismail Ashish , Assistant Prof. Kavitha S.N.
“Autonomous Vehicles: Levels, Technologies, Impacts and Concerns” Mohsin Raza.
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