基于混合交通随机均衡的路侧单元布置优化方法

曾明华; 贺静; 杨晓光

doi:10.3963/j.jssn.1674-4861.2026.01.016

基于混合交通随机均衡的路侧单元布置优化方法

doi: 10.3963/j.jssn.1674-4861.2026.01.016

1.
广东技术师范大学汽车与交通工程学院，广州 510665
2.
江西制造职业技术学院汽车与航空学院，南昌 330095
3.
同济大学交通运输工程学院，上海 201804

基金项目:

国家自然科学基金项目 72571229

广州市科技计划项目 2024B03J1326

详细信息

通讯作者:
曾明华（1977—），博士，教授. 研究方向：交通运输系统优化、智能交通系统. Email：zmhcsu@163.com

中图分类号: U491.4
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- 被引次数: 0
出版历程
- 收稿日期: 2025-08-08
- 网络出版日期: 2026-08-28

Roadside Unit Deployment Optimization Based on Mixed Traffic Stochastic Equilibrium

1.
School of Automotive and Traffic Engineering, Guangdong Polytechnic Normal University, Guangzhou 510665, China
2.
School of Automotive and Aviation, Jiangxi Technical College of Manufacturing, Nanchang 330095, China
3.
School of Transportation Engineering, Tongji University, Shanghai 201804, China

摘要

摘要: 现有路侧单元（roadside units，RSUs）布局研究未充分考量无人驾驶车辆（autonomous vehicles，AVs）与人类驾驶车辆（human-driven vehicles，HVs）混合交通场景，难以保障车载自组织网络（vehicular ad hoc networks，VANETs）的连通性和覆盖性。为提升VANETs性能，研究混合交通随机路径选择下的RSUs布局。为刻画AVs路径选择行为，构建了基于通信概率的改进路径长度Logit模型，并基于该改进型Logit模型建立了AV-HV混合交通随机用户均衡（stochastic user equilibrium，SUE）数学规划模型。考虑AVs和HVs混合交通对RSUs布置的影响，设计了综合考虑通信概率和覆盖性的加权目标函数，建立了以该SUE数学规划模型为下层的RSUs布置优化的双层规划模型。进而，设计了基于速度监控策略的改进二进制粒子群求解算法。数值实验结果表明：①所提出的模型与算法是可行有效的，能够为不同交通需求找到整个网络连通性和覆盖性大于90%且平衡RSUs的数量与通信半径的最优布局方案；②当道路交通中的AVs比例超过5%时，优化布置RSUs可使VANETs具有较高的连通性和覆盖性；③较大通信半径（0.8 km）时的连通性和覆盖性随19~34范围内的RSU数量减少而缓慢下降但始终保持在较高水平，通信半径为0.6 km（0.4 km）时先缓慢后显著下降（先显著后缓慢下降）且最终均接近于0.4的低值；④AVs比例较低时AV-HV混合交通总需求对连通性和覆盖性的边际影响较大。
- 城市交通 /
- 车载自组织网络 /
- 路侧单元 /
- 布置优化 /
- 混合交通 /
- 双层规划
Abstract: Existing studies on roadside unit (RSU) deployment insufficiently consider mixed traffic scenarios involving autonomous vehicles (AVs) and human-driven vehicles (HVs), making it difficult to ensure the connectivity and coverage of vehicular ad hoc networks (VANETs). To enhance VANET performance, research on RSU deployment under the impact of stochastic route choice of mixed traffic is conducted. To depict the route choice behavior of AVs, an improved path-size logit model is proposed based on communication probability, and a stochastic user equilibrium (SUE) mathematical programming model is established for mixed HV and AV traffic. Considering the impact of the mixed traffic with AVs and HVs on the RSUs deployment, a weighted objective function is designed to comprehensively considering both communication probability and coverage and establish a bi-level programming model for RSUs layout optimization with the aforementioned SUE mathematical programming as the lower-level model. An improved binary particle swarm optimization algorithm incorporating a speed monitoring strategy is designed to solve the bi-level model. Numerical experiments yield the following finds. ①The proposed model and algorithm are feasible and effective and can achieve, for different traffic demands, optimal deployment schemes with network connectivity and coverage greater than 90% and with balanced number of RSUs and communication radius. ②When AVs modal share exceeds 5%, optimized RSU deployment enables VANETs to achieve relatively high connectivity and coverage. ③With a large communication radius of 0.8 km, connectivity and coverage decrease slowly as the number of RSUs varies within the range of 19 to 34 but remain at a high level. With a communication radius of 0.6 km (0.4 km), connectivity and coverage decline slowly at first and then significantly (significantly at first and then slowly) and finally approach a low value of 0.4. ④A lower AV modal share incidates a greater marginal impact of total demand of mixed AV and HV traffic on connectivity and coverage.
- urban traffic /
- vehicular ad hoc network /
- roadside unit /
- deployment optimization /
- mixed traffic /
- bi-level programming

HTML全文

图 1 Nguyen-Dupuis路网与路侧单元侯选位置

Figure 1. Nguyen-Dupuis network and RSU candidate positions

下载: 全尺寸图片幻灯片

图 2 不同AV占比时通信网络连通及覆盖性能

Figure 2. Communication network performance under different AVs ratios

下载: 全尺寸图片幻灯片

图 3 各OD需求与AV占比情形通信网络连通及覆盖性能

Figure 3. Communication network performance for different OD demands and AVs ratios

下载: 全尺寸图片幻灯片

图 4 各OD需求和通信半径下通信网络连通及覆盖性能

Figure 4. Communication network performance under different OD demands and communication radii

下载: 全尺寸图片幻灯片

图 5 2种AV占比、5种通信半径下通信网络连通及覆盖性能超过90%所需RSUs个数

Figure 5. RSUs number for five communication radii if the communication network performance achieves at least 90% under two AV ratios

下载: 全尺寸图片幻灯片

图 6 2种通信半径下实现通信网络90%以上连通及覆盖性能的RSUs布设方案

Figure 6. RSUs deployment schemes for two radii to achieve at least 90% connectivity and coverage of communication network

下载: 全尺寸图片幻灯片

表 1 Nguyen-Dupuis网络特征

Table 1. Nguyen-Dupuis network characteristics

路段编号	$ t_{a}^{0}/\text{min} $	C_a/(veh/h)	l_a/km	路段编号	$ t_{a}^{0}/\text{min} $	C_a/(veh/h)	l_a/km
1	3.5	600	3.6	11	4.5	800	2.4
2	4.5	800	1.8	12	5.0	800	1.8
3	4.5	600	1.8	13	4.5	400	3.0
4	6.0	400	3.0	14	3.0	800	2.9
5	1.5	600	1.8	15	3.5	600	1.9
6	4.5	600	2.4	16	4.0	800	2.4
7	2.5	600	2.9	17	3.5	800	3.6
8	6.5	800	2.4	18	7.0	400	6.0
9	2.5	400	1.9	19	5.5	400	2.9
10	4.5	600	2.4

下载: 导出CSV

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