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A Human-Like Traffic Scene Understanding System: A Survey
IEEE Industrial Electronics Magazine ( IF 5.6 ) Pub Date : 2020-12-14 , DOI: 10.1109/mie.2020.2970790
Zi-Xiang Xia , Wei-Cheng Lai , Li-Wu Tsao , Lien-Feng Hsu , Chih-Chia Hu Yu , Hong-Han Shuai , Wen-Huang Cheng

Autonomous 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.

中文翻译:

类似于交通场景的理解系统:一项调查

自动驾驶汽车,也称为自动驾驶汽车,具有感知环境,定位环境并安全驾驶到目的地的能力,而无需任何人工干预。由于人工智能(AI)领域的先进技术和进步,该领域已取得了惊人的进步。尽管现有的调查涉及许多主题,例如车辆传感器,感知和物体检测,但没有一项现有的工作总结了研究类似于人类的理解能力(例如常识推理)的工作。因此,在本文中,我们提出了一种新颖的系统流程,以使自动驾驶汽车能够了解交通场景并总结最新的研究现状。
更新日期:2020-12-14
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