Research on Predictive Control Algorithm of Vehicle Turning Path Based on Monocular Vision

Abstract

To solve the issue that the monocular vision vehicle navigation system is limited by the field of vision acquired by the charge-coupled device camera and cannot acquire navigation turning path information throughout the turning process, decreasing the vehicle turning control accuracy, this paper proposed a turning control algorithm based on monocular vision vehicle turning path prediction. Firstly, the camera’s distortion was adjusted. Secondly, the camera imaging model was built, and the turning path’s position information was determined using the imaging position relationship. The vehicle motion model was built in accordance with the vehicle steering mode. Lastly, the cornering trajectory of a vehicle was estimated using the vehicle’s front axle length and front-wheel adjustment data, determining the vehicle turning point and turn operations on the basis of the projected relationship between the vehicle turning track and the turning path position. The experimental results showed that the proposed algorithm can effectively measure the position parameters of the cornering path and complete vehicle cornering control. The maximum absolute error of intercept and slope in turn path position parameters were 0.2525 m and 0.014 m, respectively. The cornering control accuracy was 0.093 m and 0.085 m, which met the vehicle navigation cornering control requirements. At the same time, the research can provide theoretical reference for research on precise navigation control of other cornering vehicles and other path guidance modes.

Increased plane identification precision with stereo identification

“…Stereo vision, a type of 3D imaging system, captures information simultaneously from different views, containing 3D object information. Stereo vision styles include monocular vision [1][2][3][4], binocular vision [5][6][7][8][9], and multiview stereo vision [10][11][12], the latter being a more complex binocular variant.…”