Study on Image Correction and Optimization of Mounting Positions of Dual Cameras for Vehicle Test

Si-Ho Lee, Bong-Ju Kim and Seon-Bong Lee
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Si-Ho Lee: Department of Mechanical Engineering, Keimyung University, Daegu 42601, Korea
Bong-Ju Kim: Department of Mechanical Engineering, Keimyung University, Daegu 42601, Korea
Seon-Bong Lee: Division of Mechanical and Automotive Engineering, Keimyung University, Daegu 42601, Korea

Energies, 2021, vol. 14, issue 16, 1-19

Abstract: Among surrounding information-gathering devices, cameras are the most accessible and widely used in autonomous vehicles. In particular, stereo cameras are employed in academic as well as practical applications. In this study, commonly used webcams are mounted on a vehicle in a dual-camera configuration and used to perform lane detection based on image correction. The height, baseline, and angle were considered as variables for optimizing the mounting positions of the cameras. Then, a theoretical equation was proposed for the measurement of the distance to the object, and it was validated via vehicle tests. The optimal height, baseline, and angle of the mounting position of the dual camera configuration were identified to be 40 cm, 30 cm, and 12°, respectively. These values were utilized to compare the performances of vehicles in stationary and driving states on straight and curved roads, as obtained by vehicle tests and theoretical calculations. The comparison revealed the maximum error rates in the stationary and driving states on a straight road to be 3.54% and 5.35%, respectively, and those on a curved road to be 9.13% and 9.40%, respectively. It was determined that the proposed method is reliable because the error rates were less than 10%.

Keywords: autonomous vehicle; dual camera; real vehicle test; test scenario (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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