Role of Artificial Intelligence Techniques in Active Safety using Image Processing for Autonomous Driving Vehicles

Delia Moga, I. Filip
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Abstract

This paper presents a study on the importance of using Artificial Intelligence methods in developing self-driving vehicles. Advances in Artificial Intelligence are one of the key enablers of the Autonomous Vehicles development. There are several ways to increase the level of autonomy of a vehicle and make it capable to avoid or prevent crashes. Advanced Driver Assistance Systems will help autonomous vehicles become a reality. Image processing of various traffic scenarios can be drastically improved by the use of the superior degrees of computer processing and computer vision techniques. With the help of convolutional neural networks (CNNs), not only that a single object can be detected and tracked in a sequence, but all relevant objects can be detected and classified for further processing. CNN s, the current state-of-the art for efficiently implementing deep neural networks for vision, are more efficient because they reuse a lot of weights across the image. Also, an introduction in synthetic data generation field is presented as a way to overcome the lack of labeled datasets for training networks.
人工智能技术在自动驾驶汽车图像处理主动安全中的作用
本文介绍了在开发自动驾驶汽车中使用人工智能方法的重要性。人工智能的进步是自动驾驶汽车发展的关键推动力之一。有几种方法可以提高车辆的自主水平,使其能够避免或防止碰撞。先进的驾驶辅助系统将帮助自动驾驶汽车成为现实。利用先进的计算机处理技术和计算机视觉技术,可以大大提高各种交通场景的图像处理水平。在卷积神经网络(cnn)的帮助下,不仅可以检测和跟踪序列中的单个对象,还可以检测和分类所有相关对象以进行进一步处理。CNN是目前最先进的用于有效实现深度神经网络视觉的技术,它的效率更高,因为它们在图像上重用了很多权重。此外,本文还介绍了合成数据生成领域,以克服训练网络缺乏标记数据集的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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