借用城市公交专用道行驶的智能网联车辆轨迹优化方法

付凤杰; 李博林; 金盛

doi:10.3963/j.jssn.1674-4861.2024.06.011

借用城市公交专用道行驶的智能网联车辆轨迹优化方法

doi: 10.3963/j.jssn.1674-4861.2024.06.011

付凤杰^{1, 2,},
李博林²,
金盛^2, ,

1.
浙江警察学院公共安全风险治理实验室杭州 310053
2.
浙江大学智能交通研究所杭州 310058

基金项目:

国家重点研发计划项目 2023YFB4302600

国家自然科学基金项目 72361137006

浙江省自然科学基金杰出青年基金项目 R23E080015

浙江省基础公益研究计划项目 LGF22F030008

详细信息

作者简介:
付凤杰(1990—)，博士，讲师. 研究方向：交通管理工程、智能交通系统等. E-mail：fufengjie@zjjcxy.cn

通讯作者:
金盛(1982—)，博士，教授. 研究方向：交通信息工程及控制、智能交通系统等. E-mail：jinsheng@zju.edu.cn

中图分类号: U491.5+4U495
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- 文章访问数: 43
- HTML全文浏览量: 18
- PDF下载量: 8
- 被引次数: 0
出版历程
- 收稿日期: 2023-12-05
- 网络出版日期: 2025-03-08

Trajectory Optimization for Connected Automated Vehicles Borrowing Urban Dedicated Bus Lane

FU Fengjie^{1, 2
,},
LI Bolin²,
JIN Sheng^{2
, ,}

1.
Laboratory of Public Safety Risk Governance, Zhejiang Police College, Hangzhou 310053, China
2.
Institute of Intelligent Transportation Systems, Zhejiang University, Hangzhou 310058, China

摘要

摘要: 智能网联车辆(connected and automated vehicle，CAV)利用公交车运行的间隙，借用公交专用道通行，能够减少与人工驾驶车辆(human driving vehicle，HDV) 混合运行的相互干扰，进一步提升公交专用道的利用效率，是当前混合交通流环境下提升CAV运行效率的重要方式之一。以公交专用道上公交车辆的运行轨迹、公交专用道物理信息以及交通信号配时方案为约束，同时考虑CAV在港湾式公交停靠站的超车行为，构建了CAV借用公交专用道通行的轨迹优化模型。通过将模型分解为子模型并在时空上进行网格划分，提出了模型求解的具体流程，建立了基于类贪婪算法的求解方法，并采用MATLAB和yalmip求解工具进行模型求解。以杭州市莫干山路公交专用道为实例开展数值仿真，分析了港湾式公交停靠站、公交停靠时间、交通信号配时参数等因素对模型结果的影响，进一步验证了模型的有效性。结果表明：公交停靠时间会显著影响CAV的运行速度，随着公交停靠时间的增加，CAV运行速度呈现先增后减的趋势。通过公交站点的停靠时间与交通信号配时的协同优化，可以有效提升CAV的运行效率。同时，与存在部分港湾式公交停靠站相比，全部设置港湾式公交停靠站可以使CAV运行速度提升10%。
- 交通控制 /
- 智能网联车辆 /
- 轨迹优化 /
- 公交专用道
Abstract: Connected and automated vehicles (CAV) can reduce the mutual interference with human driving vehicles (HDV), thereby enhancing the utilization efficiency of bus lanes, which is one of the important ways to improve the operation efficiency of CAV in the current mixed traffic flow environment. The trajectory optimization model of CAV utilizing bus lanes is proposed, taking into account the constraints of bus lane trajectory, the physical characteristics of the bus lane, and the traffic signal timing scheme. This model incorporates the overtaking behavior of CAVs at harbor bus stops.The model is decomposed into sub-models and meshed in time and space to elucidate the specific process of model solution. The solution method is established based on a greedy algorithm-like algorithm, and the model is solved using MATLAB and yalmip solving tools. To illustrate the efficacy of the proposed model, numerical simulations are conducted for the bus lane on Moganshan Road in Hangzhouas a case study.These simulations analyzed the impact of various factors, including harbor-style bus stop, bus stop time, and traffic signal timing parameters on the model results, and further verified the effectiveness of the model. The results show that the bus stop time will significantly affect the CAV travel speed, and with the increase of bus stopping time, the CAV travel speed will increase first and then decrease. The results show that a collaborative optimization of bus stop time and traffic signal timing can enhance the operational efficiency of CAV. Furthermore, the presence of harbor-style bus stops has been found to augment the CAV operation speed by 10% when compared to the absence of such infrastructure.
- traffic control /
- connected and automated vehicle /
- trajectory optimization /
- dedicated bus lane

HTML全文

图 1 公交专用道内公交车和CAV的时空图

Figure 1. Time-space graph for bus and CAV in bus lanes

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图 2 CAV在公交专用道行驶的2种基本轨迹

Figure 2. Two basic trajectories for CAV in a bus lane

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图 3 时间离散化时路段的时空关系图

Figure 3. Time-space graph of one section with time discretized

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图 4 典型实证道路的物理结构与交通需求

Figure 4. Physical features and traffic demand of typical empirical roads

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图 5 公交车不同停靠时间下的CAV平均速度

Figure 5. Average CAV speed at different stop times

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图 6 不同场景下的CAV时空轨迹图

Figure 6. Spatiotemporal trajectory diagram of CAV in different scenarios

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