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International Journal of Automotive Technology > Volume 21(4); 2020 > Article
International Journal of Automotive Technology 2020;21(4): 1001-1011.
doi: https://doi.org/10.1007/s12239-020-0095-7
LANE KEEPING CONTROL BASED ON MODEL PREDICTIVE CONTROL UNDER REGION OF INTEREST PREDICTION CONSIDERING VEHICLE MOTION STATES
Zeng Li, Gaojian Cui, Shaosong Li, Niaona Zhang, Yunsheng Tian, Xiaoqiang Shang
Changchun University of Technology
PDF Links Corresponding Author.  Shaosong Li , Email. lishaosong@ccut.edu.cn
ABSTRACT
To address the failure to consider vehicle states in region of interest (ROI) prediction, we propose the use of a Kalman filter to estimate the position of vehicles relative to lanes by vehicle states on the basis of a vehicle–road micro traffic model in the world coordinate system. The central position of the ROI is determined through a combination of optimal preview time theory with the ROI prediction. The range of the ROI is determined by offsetting upward, downward, leftward, and rightward from the central position of the ROI. The left and right ROI are processed separately to detect lane lines. Simulation results show that the proposed prediction method reduces the ROI range, and the model predictive control controller can make the vehicle run smoothly from the initial position to the road centerline.
Key Words: Kalman filter, Lane keeping control, Model predictive control, ROI prediction, Vision-based vehicle
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