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http://dx.doi.org/10.4218/etrij.2021-0129

Building a mathematics model for lane-change technology of autonomous vehicles  

Phuong, Pham Anh (Faculty of Information Technology, University of Education, Da Nang University)
Phap, Huynh Cong (Vietnam-Korea University of Information and Communication Technologies, Da Nang University)
Tho, Quach Hai (University of Arts, Hue University)
Publication Information
ETRI Journal / v.44, no.4, 2022 , pp. 641-653 More about this Journal
Abstract
In the process of autonomous vehicle motion planning and to create comfort for vehicle occupants, factors that must be considered are the vehicle's safety features and the road's slipperiness and smoothness. In this paper, we build a mathematical model based on the combination of a genetic algorithm and a neural network to offer lane-change solutions of autonomous vehicles, focusing on human vehicle control skills. Traditional moving planning methods often use vehicle kinematic and dynamic constraints when creating lane-change trajectories for autonomous vehicles. When comparing this generated trajectory with a man-generated moving trajectory, however, there is in fact a significant difference. Therefore, to draw the optimal factors from the actual driver's lane-change operations, the solution in this paper builds the training data set for the moving planning process with lane change operation by humans with optimal elements. The simulation results are performed in a MATLAB simulation environment to demonstrate that the proposed solution operates effectively with optimal points such as operator maneuvers and improved comfort for passengers as well as creating a smooth and slippery lane-change trajectory.
Keywords
autonomous vehicle; intelligent transportation systems; lane change; motion planning;
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