基于时间延迟动态预测的自动驾驶控制

赵建辉; 高洪波; 张新钰; 张颖麟

doi:10.16511/j.cnki.qhdxxb.2018.21.011

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清华大学学报（自然科学版） ›› 2018, Vol. 58 ›› Issue (4) : 432-437. DOI: 10.16511/j.cnki.qhdxxb.2018.21.011

汽车工程

基于时间延迟动态预测的自动驾驶控制

赵建辉¹, 高洪波², 张新钰³, 张颖麟⁴

作者信息 +

Automatic driving control based on time delay dynamic predictions

ZHAO Jianhui¹, GAO Hongbo², ZHANG Xinyu³, ZHANG Yinglin⁴

Author information +

文章历史 +

摘要

由于驾驶过程中的延迟和前视距离等因素，无人车无法准确跟踪规划轨迹。该文通过选择简化的自行车车辆模型，在纯跟踪模型的基础上对原有的算法进行优化，提出了一种基于动态延迟预测的自动驾驶控制方法。通过车辆运动学模型预测延迟后的车辆运动方向和位置信息，并根据行驶方向和轨迹方向之间的偏差值，获得最佳前视距离。MATLAB仿真结果表明，改进的算法可以以7 m/s的行驶速度跟踪规划轨迹，平均误差可以控制在0.3 m以内，跟踪性能优于传统的纯跟踪方法。

Abstract

Signal delays, limited frontal view distances and other factors during self-driving limit the ability of self-driving cars to accurately track their planning trajectory. A simplified bicycle model was used to optimize a classical pure tracking model in an automatic driving control method based on dynamic delay prediction. A vehicle kinematics model is used to predict the vehicle motion direction and position after the delay. The optimal front sight distance is obtained according to difference between driving the actual direction and the tracking direction. MATLAB simulations show that this algorithm can track the planning trajectory at a maximum speed of 7 m/s with the average error controlled to within 0.3 m. Thus, the tracking performance is better than the traditional pure pursuit method.

导出引用

赵建辉, 高洪波, 张新钰, 张颖麟. 基于时间延迟动态预测的自动驾驶控制[J]. 清华大学学报（自然科学版）. 2018, 58(4): 432-437 https://doi.org/10.16511/j.cnki.qhdxxb.2018.21.011

ZHAO Jianhui, GAO Hongbo, ZHANG Xinyu, ZHANG Yinglin. Automatic driving control based on time delay dynamic predictions[J]. Journal of Tsinghua University(Science and Technology). 2018, 58(4): 432-437 https://doi.org/10.16511/j.cnki.qhdxxb.2018.21.011

中图分类号： TP399

参考文献

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基金

国家重点研究和发展计划（2016YFB0100903）；北京市科学技术委员会重大专项（d171100005017002，d171100005117002）；中国博士后基金（2017M620765）

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收稿日期	出版日期
2017-12-30	2018-04-15
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2018-04-15

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