During software development, collaborative development has become the mainstream trend for large-scale software development, and code review has become an important workflow of it. However, there are some problems in manual code review such as mismatch and knowledge limitations of reviewers, then the quality and efficiency of code review may be poor, and the code repair after review also takes time and effort for developers. It is urgently needed for researchers to improve the code review process and make it automated. This study provides a systematic survey of research related to code review automation, and focuses on 4 main directions: Reviewer recommendation, automated code quality estimation, review comment generation, and automated code refinement. The 148 high-quality publications related to this topic have been collected, and a technical classification and analysis have been carried out in this research field. Then, the evaluation methods of each task in directions are briefly summarized, and some benchmarks and open-source tools are listed. Finally, the key challenges and insights are proposed for future research.