车路协同下基于元胞自动机的精细交通流模型

李珣; 程硕; 吴丹丹; 张蕾; 王晓华

doi:10.3969/j.issn.0258-2724.20220830

车路协同下基于元胞自动机的精细交通流模型

doi: 10.3969/j.issn.0258-2724.20220830

1.
西安工程大学电子信息学院，陕西西安 710048
2.
西北工业大学自动化学院，陕西，西安 710129

基金项目: 国家自然科学基金项目（61971339）；陕西省自然科学基础研究计划项目（2022JM407）

详细信息

作者简介:
李珣（1981—），男，教授，研究方向为多移动机器人协同控制技术，E-mail：lixun@xpu.edu.cn

中图分类号: U495
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- 文章访问数: 37
- HTML全文浏览量: 27
- PDF下载量: 9
- 被引次数: 0
出版历程
- 收稿日期: 2022-11-30
- 修回日期: 2023-04-27
- 网络出版日期: 2024-10-22

Refined Traffic Flow Model Based on Cellular Automaton Under Cooperative Vehicle Infrastructure System

1.
School of Electronics and Information, Xi’an Polytechnic University, Xi’an 710048, China
2.
School of Automation, Northwest Polytechnical University, Xi’an 710129, China

摘要

摘要:
针对经典元胞自动机交通流模型中元胞尺寸难以准确表达车辆间位置关系的问题，提出通过细化元胞尺寸对基于元胞自动机的双车道模型（symmetric two-lane cellular automaton，STCA）进行改进的方案. 首先，分析城市道路双车道环境下的位置、速度、加速度以及车辆间的相互影响，并基于元胞自动机搭建相应数值模型，特别地，针对现有基于元胞自动机的交通流模型与实际车辆行驶现象不符的问题，改进其道路尺寸和元胞表征形式，建立精细化元胞自动机车道模型；其次，结合实际车路环境，对STCA模型中的道路堵塞、换道等行为重新定义，并将车道规则与精细化车道模型相结合，建立新的交通流模型STCA-CH；最后，与STCA、STCA-I、STCA-S、STCA-M模型相对比，通过分析在不同车辆密度下的平均速度、平均流量、换道频率及时空图，验证STCA-CH模型有效性. 结果表明，STCA-CH模型的换道频率相较于STCA-M模型提高约21.14%，最大平均流量较STCA-I、STCA-S和STCA-M模型分别提升约25.76%、11.3%和3.75%.
- 交通工程 /
- 微观交通对象 /
- 车路协同 /
- 元胞自动机模型 /
- 细元胞
Abstract:
The cell size in the classical cellular automaton-based traffic flow model makes it difficult to express the position relationship of vehicles accurately. Therefore, a scheme to improve the symmetric two-lane cellular automaton (STCA) model by refining the cell size was presented. Firstly, the position, speed, acceleration, and interaction of vehicles in the urban road two-lane environment were analyzed, and the numerical model of these characteristics was built based on the cellular automaton. Especially, the road size and the cellular representation form in the model were improved to solve the problem that the existing traffic flow model based on cellular automaton does not conform to the vehicle driving phenomenon on the actual road. Secondly, according to the real vehicle infrastructure environment, road congestion, lane changing, and other behaviors in the STCA model were redefined, and the lane rules were combined with the refined lane model. A new traffic flow model, namely STCA-CH, was established. Finally, the model was compared with STCA, STCA-I, STCA-S, and STCA-M models, and the validity of the STCA-CH model was verified by analyzing the average speed, average flow, lane changing frequency, and space-time diagram under different vehicle densities. The results show that the lane changing frequency of the STCA-CH model is about 21.14% higher than that of the STCA-M model, and the maximum average flow is about 25.76%, 11.3%, and 3.75% higher than that of the STCA-I, STCA-S, and STCA-M models respectively.
- traffic engineering /
- microscopic traffic objects /
- cooperative vehicle infrastructure system (CVIS) /
- cellular automaton model /
- refined cell

HTML全文

图 1 元胞自动机双车道车辆位置、速度示意

Figure 1. Vehicle position and speed in STCA model

下载: 全尺寸图片幻灯片

图 2 精细化的双车道车辆速度、位置示意

Figure 2. Vehicle position and speed in refined STCA model

下载: 全尺寸图片幻灯片

图 3 道路阻塞示意

Figure 3. Road congestion

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图 4 5种模型在不同车辆密度下的平均速度、平均流量对比

Figure 4. Comparison of average speed and average flow of five models under different vehicle densities

下载: 全尺寸图片幻灯片

图 5 5种模型在不同车辆密度下的换道频率对比

Figure 5. Comparison of lane changing frequencies of five models under different vehicle densities

下载: 全尺寸图片幻灯片

图 6 不同遵守率下双车道模型的平均速度、平均流量对比

Figure 6. Comparison of average speed and average flow for two-lane model under different compliance rates

下载: 全尺寸图片幻灯片

表 1 5种元胞自动机交通流模型的时空图对比

Table 1. Comparison of space-time diagrams of five kinds of cellular automaton-based traffic flow models

车道 SCTA STCA-I STCA-S STCA-M STCA-CH

左车道

右车道

下载: 导出CSV

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