Abstract
Self-driving cars are a hot research topic in science and technology, which has a great influence on social and economic development. Deep learning is one of the current key areas in the field of artificial intelligence research. It has been widely applied in image processing, natural language understanding, and so on. In recent years, more and more deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results. This paper presents a review of recent research on theories and applications of deep learning for self-driving cars. This survey provides a detailed explanation of the developments of self-driving cars and summarizes the applications of deep learning methods in the field of self-driving cars. Then the main problems in self-driving cars and their solutions based on deep learning methods are analyzed, such as obstacle detection, scene recognition, lane detection, navigation and path planning. In addition, the details of some representative approaches for self-driving cars using deep learning methods are summarized. Finally, the future challenges in the applications of deep learning for self-driving cars are given out.
Highlights
The rapid development of artificial intelligence has greatly promoted the progress of unmanned driving, such as self-driving cars, unmanned aerial vehicles, and so on [1,2]
One of the Deep Reinforcement Learning (DRL) methods is Deep Q-Network (DQN), which can utilize a deep neural network to map the relationships of actions and states, which is similar to the Q-learning method [42]
The main problems that must be addressed in self-driving cars include obstacle detection, scene recognition, lane recognition, and so on, which will be introduced in detail as follows
Summary
The rapid development of artificial intelligence has greatly promoted the progress of unmanned driving, such as self-driving cars, unmanned aerial vehicles, and so on [1,2]. We introduce the theoretical foundation of the main deep learning methods used for self-driving cars. (3) An overview of the applications in self-driving cars based on deep learning is given out, and the details of some representative approaches are summarized.
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