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Obstacle Detection, Driver Profiling, Ultrasound, Ultrasonic Sensors, Bayesian Network, 2TBN, Sensor Fusion, Driver Assistance
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.
James I. Obuhuma, Henry O. Okoyo, Sylvester O. McOyowo, "Shortcomings of Ultrasonic Obstacle Detection for Vehicle Driver Assistance and Profiling", International Journal of Information Technology and Computer Science(IJITCS), Vol.11, No.6, pp.28-36, 2019. DOI:10.5815/ijitcs.2019.06.04
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