Xia, ZXZXXiaLai, WCWCLaiTsao, LWLWTsaoHsu, LFLFHsuYu, CCHCCHYuShuai, HHHHShuaiWEN-HUANG CHENG2023-02-202023-02-2020211932-4529https://scholars.lib.ntu.edu.tw/handle/123456789/628548Autonomous vehicles, also known as self-driving cars, have the capability to perceive the environment, locate its position, and safely drive to the destination without any human intervention. This field has made amazing improvements because of the advanced technologies and progress of the artificial intelligence (AI) field. While the existing surveys have addressed many topics, e.g., vehicle sensors, perception, and object detection, none of the existing works summarize the work studying the ability of human-like understanding, e.g., common sense reasoning. Therefore, in this article, we present a novel system flow for empowering autonomous vehicles to understand the traffic scene and summarize the state of the art research.Cognition; Automobiles; Roads; Predictive models; Visualization; Three-dimensional displays; Planning; VISION[SDGs]SDG11A Human-Like Traffic Scene Understanding System: A Surveyjournal article10.1109/MIE.2020.29707902-s2.0-85098789430WOS:000638261600003https://api.elsevier.com/content/abstract/scopus_id/85098789430