Curve Path Prediction and Vehicle Detection in Lane Roads Using Deep Learning for Autonomous Vehicles
G. Pavithra1, N. M. Dhanya2
1G. Pavithra, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore (Tamil Nadu), India.
2N. M. Dhanya, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore (Tamil Nadu), India.
Manuscript received on 23 April 2019 | Revised Manuscript received on 02 May 2019 | Manuscript Published on 08 May 2019 | PP: 167-170 | Volume-7 Issue-5S3 February 2019 | Retrieval Number: E11310275S19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: There is always a huge demand for the development of the self-driving cars since they are the future of the autonomous vehicles. In the field of autonomous vehicles, problems still remains unsolved when there occurs any obstacle in the road lane while driving. In Self-driving cars, Lane detection is considered to be the most important part in reducing the number of accidents and risks. In this paper we have discovered the methodologies existing in the lane detection, the advantages and disadvantages of models. We have proposed a model that can detect lane in the straight and curved roads and detect vehicle existing in the lane. We have implemented a deep learning algorithm for the Vehicle Detection. The proposed methodology has been successfully applied to the dataset, the results are recorded and the performance metrics are tabulated. We have also discussed on the future scope of the Lane detection.
Keywords: Lane Detection, Deep Learning, Convolutional Neural Network.
Scope of the Article: Deep Learning