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Steering Wheel Angle Prediction from Dashboard Data Using CNN Architecture by Manas Kumar Rath; Tanmaya Swain; Tapaswini Samanta; Shobhan Banerjee; Prasanta Kumar Swain is a book available to read on EtoBox.

What is Steering Wheel Angle Prediction from Dashboard Data Using CNN Architecture about?

Various innovations on self-driving cars are trending in the automobile industry these days. The general approach for AI applications is to collect the data through various sensors that are fit in a car, process them through appropriate techniques, and then train a model upon which one can try and test the efficiency of the model. Many companies like Tesla, Uber, Waymo (a subsidiary of Google), and Mercedes are already working with a lot of sensor-captured data and high computation power. The sensors range from normal cameras to high-end ultrasonic and LIDAR sensors. Whatever be the data that we capture, the basic intention is to move swiftly through a path given various twists and turns, and other traffic conditions, where the car needs to be correctly steered as per the external environment. We should know that more the data we capture, more shall be the complexity of the system, hence more will be the required computational power for that. In this paper, we present a simple model where we capture data through a front dashboard camera, process it through a CNN, and predict the appropriate steering angles based on the external traffic conditions, where we have acquired a significa

Author

Manas Kumar Rath; Tanmaya Swain; Tapaswini Samanta; Shobhan Banerjee; Prasanta Kumar Swain

Publisher

SPRINGER VERLAG, SINGAPOR

Published

2022

Language

EN

ISBN

9789811946769

Subjects

Engineering, Computer Science, Technology