快速路互通交织区超车换道行为控制方法

doi:10.13229/j.cnki.jdxbgxb.20240783

摘要/Abstract

摘要：

本文聚焦快速路互通交织区的超车换道行为，旨在分析超车换道车辆对换道空间的选择特征并探索超车换道行为的控制方法。通过实时的轨迹数据提取，分析超车换道车辆不同阶段的间隙选择和换道点选择的差异性。依托机器学习的方法对换道持续时间和换道空间选择变化进行了预测，并基于预测结果建立了超车换道行为速度优化控制模型，利用元胞自动机仿真环境对模型控制效果进行了检验。结果表明：控制模型下车辆选择“优”“良”等级换道间隙和最佳换道点位置的比例相比实际值最高可分别提升18.86和6.89个百分点。同时，控制模型下交织区三条车道的运行速度可分别提升6.91%、1.71%和3.85%，且各车道的时空利用率也具有更好的均衡性。

关键词: 互通交织区, 超车换道行为, 换道间隙, 元胞自动机, 速度优化控制

Abstract:

This study focuses on the overtaking lane-changing behavior in urban expressway interchange weaving areas， aiming to analyze the lane-change space selection characteristics of overtaking vehicles and explore control methods for overtaking lane-change behavior. Utilizing real-time trajectory data， this study analyzes the differences in gap selection and lane-changing point selection across various stages of the overtaking process. Machine learning methods were used to predict lane-change duration and lane-change space selection changes. Based on the prediction results， a speed optimization control model for overtaking lane-change behavior was established. The control effect of the model was then tested using a cellular automata simulation environment. The results show that under the control model， the proportion of vehicles selecting "excellent" and "good" grade lane-change gaps and the optimal lane-change point position increased by up to 18.86 and 6.89 percentage points compared to actual values. Additionally， the operating speeds of the three lanes in the weaving area increased by 6.91%， 1.71%， and 3.85%， respectively， and the spatiotemporal utilization rates of the lanes also exhibited better balance.

Key words: interchange weaving area, overtaking lane-change behavior, lane-change gap, cellular automata, speed optimization control

中图分类号:

U491

马健霄,怀硕,赵顗,李铭浩,陈雨欣,赵思雨. 快速路互通交织区超车换道行为控制方法[J]. 吉林大学学报(工学版), 2026, 56(2): 431-442.

Jian-xiao MA,Shuo HUAI,Yi ZHAO,Ming-hao LI,Yu-xin CHEN,Si-yu ZHAO. Behavior control method of overtaking lane-changing in expressway interchanging weaving area[J]. Journal of Jilin University(Engineering and Technology Edition), 2026, 56(2): 431-442.

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	OLC第一阶段			OLC第二阶段
	RF	R	RB	RF	R	RB
1/4位数	22.08	20	13.92	17.51	25.25	14.44
中位数	28.90	28.84	16.42	29.70	38.38	22.32
3/4位数	54.40	72.28	28.45	71.03	54.61	48.02

换道过程	1/4位数	中位数	3/4位数
OLC第一阶段	41.08	60.04	88.15
OLC第二阶段	41.66	51.88	66.09

参数	含义
m	车辆纵向位置
n	车辆横向位置
disFront	与前方车辆距离
disRightFront	与右前方车辆纵向距离
disRightBack	与右后方车辆纵向距离
vFront	前方车辆速度
vRightFront	右前方车辆速度
vRightBack	右后方车辆速度
v	车辆当前速度
a	车辆加速度
disBack	与后方车辆距离
disLeftFront	与左前方车辆纵向距离
disLeftBack	与左后方车辆纵向距离
vBack	后方车辆速度
vLeftFront	左前方车辆速度
vLeftBack	左后方车辆速度

参数	取值
n_estimators	200
max_depth	10
min_samples_split	2
min_samples_leaf	1
max_features	log2
random_state	1
class_weight	balanced

参数	取值
隐藏层层数	2
隐藏层神经元个数	64
隐藏层激活函数	ReLU
初始学习率	0.001
epochs	40
batch_size	64
Dropout	0.25
损失函数	MSE