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Perception is influenced by perceptual set, context, motivation, and emotion. Perceptual set, or perceptual expectancy, refers to the tendency to perceive things in a particular way, influenced by previous experiences and expectations. This phenomenon affects the interpretation of stimuli, creating a set of mental tendencies and assumptions that impact sensory perceptions of sound, taste, touch, and sight.
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Perception is a fundamental psychological process that enables individuals to organize, interpret, and consciously experience sensory information. This process is crucial for understanding and interacting with the world around us. It includes both bottom-up and top-down processing, each playing a distinct role in how we perceive our environment.
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Global Positioning System (GPS) technology has revolutionized navigation and positioning, but its accuracy is often compromised by various errors. These errors, stemming from environmental, satellite, and receiver-related factors, require careful mitigation to ensure reliable performance across applications.Atmospheric ErrorsGPS signals travel through the Earth’s ionosphere and troposphere, introducing delays which affect accuracy. The ionosphere is strongly influenced by charged particles,...
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GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
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基于车辆基础设施合作系统的恶劣天气感知方法:一项审查

Jizhao Wang1, Zhizhou Wu1,2, Yunyi Liang3

  • 1School of Mechanical Engineering, Xinjiang University, Urumqi 830017, China.

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概括
此摘要是机器生成的。

智能互联汽车 (ICV) 在恶劣天气中难以感知. 本研究回顾了数据处理,传感器融合和合作感知方法,以提高自动驾驶的准确性和扩大感知范围.

关键词:
在ICV中,ICV是ICV.恶劣的天气状况造成了恶劣的天气条件.自动驾驶自动驾驶的自动驾驶.数据预处理数据的预处理.多传感器信息融合信息融合车辆 基础设施 合作 感知

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科学领域:

  • 自动驾驶技术 自动驾驶技术
  • 环境感知系统环境感知系统
  • 智能运输系统 智能运输系统

背景情况:

  • 自动驾驶在很大程度上依赖于环境感知.
  • 恶劣的天气和传感器限制降低了智能互联汽车 (ICV) 的感知精度和视野.
  • 目前的ICV仅限于特定的操作场景,因为存在感知挑战.

研究的目的:

  • 分析现有关于图像/点云处理和ICVs合作感知的研究.
  • 总结关键方面,包括数据预处理,多传感器数据融合和车辆基础设施合作感知.
  • 确定未来的研究方向,以提高恶劣天气中的合作感知.

主要方法:

  • 在雪,雨和雾条件下对点云和图像数据的数据预处理技术的审查.
  • 分析多传感器数据融合研究,包括图像,点云和组合图像点云融合.
  • 检查车辆基础设施合作感知策略,用于信息融合和共享.

主要成果:

  • 数据预处理方法有效地处理传感器数据的恶劣天气挑战.
  • 多传感器融合技术通过结合互补数据来提高感知稳定性.
  • 合作感知策略,包括融合和共享,扩大ICV感知范围并优化信息分布.

结论:

  • 合作感知对于克服自动驾驶的局限性至关重要,特别是在恶劣的天气中.
  • 需要进一步的研究来优化数据融合和信息共享,以实现强大的ICV感知.
  • 开发先进的合作感知方法将使自动驾驶在更具挑战性的环境条件下成为可能.