Open AccessIntelligent Speed Adaptive System using Image Regression Method for Highway and Urban Roads
Author(s) -
Bhavesh Sharma,
J. Ali
Publication year - 2021
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5121/csit.2021.111718
Subject(s) - computer science , adaptability , reliability (semiconductor) , frame (networking) , frame rate , field (mathematics) , artificial intelligence , real time computing , computer vision , artificial neural network , object detection , convolutional neural network , machine learning , simulation , pattern recognition (psychology) , telecommunications , ecology , power (physics) , physics , mathematics , quantum mechanics , pure mathematics , biology
Intelligent Speed Adaptive System (ISAS) is an emerging technology in the field of autonomous vehicles. However, the public acceptance rate of ISAS is drastically low because of several downfalls i.e. reliability and low accuracy. Various researchers have contributed methodologies to enhance the traffic prediction scores and algorithms to improve the overall adaptability of ISAS. The literature is scarce for Image Regression in this range of application. Computer vision has proved its iota in stream of object detection in self-driving technology in which most of the models are assisted through the complex web of neural nets and live imaging systems. In this article, some major issues related to the present technology of the ISAS and discussed new methodologies to get higher prediction accuracy to control the speed of vehicle through Image Regression technique to develop a computer vision model to predict the speed of vehicle with each frame of live images.