In addition to the neural network and specific algorithms, self-driving cars have five core components that help them optimize operation in real time, namely: computer vision, sensor fusion, localization, path planning, and control. With good data collection sensors, these pieces of information are processed and results are obtained as actions. These features also enable these intelligent machines to provide solutions to problems occurring in advance of real time by predicting events through the swift processing of data.įor example, autonomous vehicles can predict a potential threat like a car collision ahead or behind and take a decision in real time to avert it. These serve to collect data, analyze objects, and make accurate decisions while on the road. These are Artificial Intelligence (AI) and Machine Language (ML) based object detection algorithms. #1: Detection AlgorithmsĪutonomous vehicles have neural networks and specific algorithms. Let’s dive into some of the benefits of these vehicles. For the record, AI and cars have a mutual history, and it was the dream of scientists to create intelligent machines that could think and act for themselves which gave birth to autonomous vehicles, or self-driving cars, which have turned out to become one of the best innovations of AI technology. The American computer scientist Eliezer Yudkowsky argues that by far the greatest danger about artificial intelligence is that people conclude too early that they understand it.

'It is expected that the combination of blockchain technology and self-driving cars will create a far better autonomous system.' -Jude Chukwudozie Click To Tweet Autonomous Vehicle Benefits

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