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 reviewer mismatch and reviewer knowledge limitations, 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's urgently needed for researchers to improve the code review process and make it automated. This paper 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. We have collected 148 high-quality publications related to this topic, and carried out a technical classification and analysis in this research field. Then we briefly summarize the evaluation methods of each task in directions, and list some benchmarks and open-source tools. Finally, we propose the key challenges and insights for future research.