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首页> 外文期刊>International Journal of Information Technology and Computer Science >Shortcomings of Ultrasonic Obstacle Detection for Vehicle Driver Assistance and Profiling
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Shortcomings of Ultrasonic Obstacle Detection for Vehicle Driver Assistance and Profiling

机译：超声波障碍物检测对车辆驾驶员辅助和分析的缺点

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Obstacle detection is a challenging problem that has attracted much attention recently, especially in the context of research in self-driving car technologies. A number of obstacle detection technologies exist. Ultrasound is among the commonly used technologies due to its low cost compared to other technologies. This paper presents some findings on the research that has been carried out by the authors with regard to vehicle driver assistance and profiling. It discusses an experiment for detection of obstacles in a vehicle driver’s operational environment using ultrasound technology. Experiment results clearly depict the capabilities and limitations of ultrasound technology in detection of obstacles under motion and obstacles with varied surfaces. Ultrasound’s wavelength, beam width, directionality among others are put into consideration. Pros and cons of other technologies that could replace ultrasound, for instance RADAR and LIDAR technologies are also discussed. The study recommends sensor fusion where several types of sensor technologies are combined to complement one another. The study was a technical test of configurable technology that could guide future studies on obstacle detection intending to use infrared, sound, radio or laser technologies particularly when both the sensor and obstacle are in motion and when obstacles have differing unpredictable surface properties.
机译：障碍物检测是一个具有挑战性的问题，最近引起了很多关注，特别是在自动驾驶汽车技术研究的背景下。存在许多障碍物检测技术。超声波由于与其他技术相比成本低而成为常用技术之一。本文介绍了作者进行的有关车辆驾驶员辅助和配置文件研究的一些发现。它讨论了使用超声技术检测车辆驾驶员操作环境中的障碍物的实验。实验结果清楚地说明了超声技术在检测运动中的障碍物和表面变化的障碍物方面的功能和局限性。超声波的波长，光束宽度，方向性都已考虑在内。还讨论了可以替代超声的其他技术的利弊，例如RADAR和LIDAR技术。这项研究建议传感器融合，其中几种类型的传感器技术组合在一起可以互相补充。这项研究是对可配置技术的技术测试，可以指导将来打算使用红外，声音，无线电或激光技术的障碍物检测研究，特别是当传感器和障碍物都在运动中并且障碍物具有不同的不可预测的表面特性时。

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