Analysis on Lane Changing Prediction and Speed Control of an Autonomous Vehicle using Machine Learning
Abstract
ABSTRACT
Lane changing and speed control has always been a major concern regarding autonomous driving. In this paper we have discussed about the work done in lane changing & different approaches used in autonomous vehicle. DRL and DQN have shown very promising results. Also, somewhere KELM also beats the best rule-based machine learning algorithms. After taking a close look at each approach several methodologies have arrived for preparation and testing. In this paper we have compared the different models based on machine learning which includes using a Dataset from the cloud, using stimulators for designing & implementation and using real time external information using sensors. Also we have discussed about the challenges & future scope in autonomous driving.
Keywords: Autonomous driving, lane change prediction, machine learning, speed control, autonomous vehicles.
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PDFDOI: https://doi.org/10.37628/ijocspl.v6i2.632
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