Understanding the Perception of Road Segmentation and Traffic Light Detection using Machine Learning Techniques
Anusha A. Nandargi1, Arun S Tigadi2, Ashwini Bagewadi3, Amey Joshi4, Ajinkya Jadhav5
1Anusha A. Nandargi*, Department of Electronics and Communication, KLE Dr. M. S. Sheshgiri college of Engineering and Technology, Visvesvaraya Technological University, Belagavi, Karnataka, India.
2Ashwini Bagewadi, Department of Electronics and Communication, KLE Dr. M. S. Sheshgiri college of Engineering and Technology, Visvesvaraya Technological University, Belagavi, Karnataka, India.
3Amey Joshi, Department of Electronics and Communication, KLE Dr. M. S. Sheshgiri college of Engineering and Technology, Visvesvaraya Technological University, Belagavi, Karnataka, India.
4Ajinkya Jadhav, Department of Electronics and Communication, KLE Dr. M. S. Sheshgiri college of Engineering and Technology, Visvesvaraya Technological University, Belagavi, Karnataka, India.
5Dr. Arun S. Tigadi*, Assistant professor , Department of E and C , K.L.E DR. M.S. Sheshgiri College of Engineering and Technology. Udyambhag, Belagavi, Karnataka , India.
Manuscript received on May 02, 2020. | Revised Manuscript received on May 21, 2020. | Manuscript published on May 30, 2020. | PP: 2698-2704 | Volume-9 Issue-1, May 2020. | Retrieval Number: A3103059120/2020©BEIESP | DOI: 10.35940/ijrte.A3103.059120
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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: Advanced Driving Assistance System (ADAS) has seen tremendous growth over the past 10 years. In recent times, luxury cars, as well as some newly emerging cars, come with ADAS application. From 2014, Because of the entry of the European new car assessment programme (EuroNCAP) [1] in the AEBS test, it helped gain momentum the introduction of ADAS in Europe [1]. Most OEMs and research institutes have already demonstrated on the self-driving cars [1]. So here, a focus is made on road segmentation where LiDAR sensor takes in the image of the surrounding and where the vehicle should know its path, it is fulfilled by processing a convolutional neural network called semantic segmentation on an FPGA board in 16.9ms [3]. Further, a traffic light detection model is also developed by using NVidia Jetson and 2 FPGA boards, collectively named as ‘Driving brain’ which acts as a super computer for such networks. The results are obtained at higher accuracy by processing the obtained traffic light images into the CNN classifier [5]. Overall, this paper gives a brief idea of the technical trend of autonomous driving which throws light on algorithms and for advanced driver-assistance systems used for road segmentation and traffic light detection.
Keywords: ADAS, Traffic-light detection, Road-segmentation, Convolutional neural network.
Scope of the Article: Machine Learning