@article{ref1,
title="An obstacle avoidance path planning and evaluation method for intelligent vehicles based on the B-spline algorithm",
journal="Sensors (Basel)",
year="2023",
author="Zhang, Yulong and Wang, Pengwei and Cui, Kaichen and Zhou, Hengheng and Yang, Jinshan and Kong, Xiangcun",
volume="23",
number="19",
pages="-",
abstract="To meet the real-time path planning requirements of intelligent vehicles in dynamic traffic scenarios, a path planning and evaluation method is proposed in this paper. Firstly, based on the B-spline algorithm and four-stage lane-changing theory, an obstacle avoidance path planning algorithm framework is constructed. Then, to obtain the optimal real-time path, a comprehensive real-time path evaluation mechanism that includes path safety, smoothness, and comfort is established. Finally, to verify the proposed approach, co-simulation and real vehicle testing are conducted. In the dynamic obstacle avoidance scenario simulation, the lateral acceleration, yaw angle, yaw rate, and roll angle fluctuation ranges of the ego-vehicle are ±2.39 m/s(2), ±13.31°, ±13.26°/s, and ±0.938°, respectively. The results show that the proposed algorithm can generate real-time, available obstacle avoidance paths. And the proposed evaluation mechanism can find the optimal path for the current scenario.<p /> <p>Language: en</p>",
language="en",
issn="1424-8220",
doi="10.3390/s23198151",
url="http://dx.doi.org/10.3390/s23198151"
}