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The Application of Computer Vision in Responding to the Emergencies of Autonomous Driving

机译:计算机愿景在自主驾驶紧急情况下的应用

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Nowadays, artificial intelligence is developing rapidly, and greatly promotes the appearance of relevant industries. Automated driving is one of those hot industries. With the development of autonomous vehicles, higher requirements such as intervention when an accident or system failure occurs mean more problems. Many shortcomings arose during emergencies. For example, the system cannot make a correct judgment in a short time and calculate the most suitable solution. This paper analyzes several algorithms for emergency situations at the current stage of autonomous vehicles from the perspective of computer vision. In addition, this paper finds suitable algorithms by collecting, collating and researching literature. Although these algorithms can solve the problems in most cases, there are still defects. For example, there are problems such as incomplete consideration and insufficient optimization. This paper also proposes possible solutions to the defects of each algorithm: The algorithm of edge recognition algorithm under extreme weather is added. Besides, the HMM model is used to optimize the pedestrian motion recognition algorithm. In addition, the standard of driver behavior recognition is also optimized. It is hoped that autonomous vehicles will have a more comprehensive emergency handling system in the future such as faster emergency response and more accurate decision.
机译:如今,人工智能发展迅速,大大促进了相关产业的外观。自动驾驶是那些热门行业之一。随着自主车辆的发展,当发生事故或系统故障时,诸如干预的更高的要求意味着更多的问题。在紧急情况下出现了许多缺点。例如,系统不能在短时间内进行正确的判断并计算最合适的解决方案。本文从计算机视野中分析了自动车辆当前阶段的若干算法。此外,本文通过收集,整理和研究文献找到合适的算法。虽然这些算法可以在大多数情况下解决问题,但仍有缺陷。例如,存在诸如不完整的考虑和优化不足之类的问题。本文还提出了对每种算法的缺陷的可能解决方案:添加了极端天气下的边缘识别算法算法。此外,HMM模型用于优化行人运动识别算法。此外,还优化了驾驶员行为识别的标准。希望自治车辆在未来具有更全面的紧急处理系统,例如更快的应急响应和更准确的决定。

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