个人快速交通系统智能协同控制与优化

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doi:10.12202/j.0476-0301.2022091

孙沐霖,
赵春晓^,

北京建筑大学电气与信息工程学院，北京建筑大学未来城市设计高精尖创新中心，100044，北京

基金项目:国家自然科学基金重点资助项目(62031003)

详细信息

通讯作者:
赵春晓（1964.2—），男，博士，教授. 研究方向：WEB智能信息系统、复杂系统. E-mail:chunxiao@bucea.edu.cn

中图分类号:U495；TP273
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- 文章访问数:23
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- PDF下载量:6
- 被引次数:0
出版历程
- 收稿日期:2022-04-18
- 录用日期:2022-05-17
- 刊出日期:2022-11-27

Cooperative intelligent control and optimization of personal rapid transportation

SUN Mulin,
ZHAO Chunxiao^,

School of Electrical and Information Engineering, Beijing University of Civil Engineering and Architecture,Advanced Innovation Center for Future Urban Design, Beijing University of Civil Engineering and Architecture,100044,Beijing,China

摘要

摘要:提出了一种新型智能协同控制运行方案，基于个人快速交通(PRT)车辆的运行规则与车辆间的自组织关系，以自底向上的方式建立动态知识图谱，用以辅助车辆运行决策；通过领航者-跟随者策略在车辆行驶过程中形成虚拟车队运行，在此基础上，将滚动优化策略与粒子群算法(PSO)相结合，对车辆的加速度和减速度进行滚动优化调整，缩短了PRT车辆形成虚拟编队的运行时间，进一步提高了PRT系统的运输能力．结果表明：智能协同控制运行方案使得PRT车辆形成虚拟编队所耗时间平均减少了约38%，每小时运输客流量平均提高了约1.5倍；该运行方案保证了PRT系统运行的高效性和安全性，符合低碳出行、绿色发展的需要．
- 个人快速交通系统/
- 动态知识图谱/
- 虚拟编队/
- 滚动优化/
- 粒子群算法
Abstract:Traditional personal rapid transportation(PRT) vehicles have limited number of single vehicle seats, and have the challenge of complex and changeable driving environment, therefore are difficult to meet actual traffic demand of large volume of urban transportation．A new intelligent cooperative control operation scheme is proposed to solve this problem．Operation rules of PRT vehicles and self-organization relationship among vehicles are used to establish dynamic knowledge maps in a bottom-up manner to assist decision-making of vehicle operation．The leader-follower strategy is used to form virtual fleet operation during actual vehicle driving．Rolling optimization strategy and particle swarm optimization (PSO) algorithm are combined to adjust rolling acceleration of vehicles, resulting in shortened running time of PRT vehicles forming a virtual formation, and further improved transport capacity of PRT system．Intelligent cooperative control operation scheme is found to reduce the time spent by PRT vehicles to form a virtual formation by 38%, passenger flow per hour is increased 1.5 times．This operation scheme ensures high efficiency and safety of PRT system operation, and meets the needs of low-carbon travel and green development．
- personal rapid transportation system/
- dynamic knowledge graph/
- virtual formation/
- rolling optimization/
- particle swarm optimization (PSO)

HTML全文

图 1PRT运行概念知识网络模型

a_后、d_前后分别为后车加速度、前后2车间的距离；v_后、v_max分别为后车速度、最大速度；d_l为前后2车间的最小安全距离．

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图 2领航者-跟随者策略示意

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图 3PRT车辆跟随模型概念

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图 4参数寻优收敛曲线

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图 5滚动优化情况

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图 6PRT系统运行情况

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表 1仿真主体及属性

编号	主体	属性
1	数量	0~20
2	初始速度/（km·h⁻¹）	0~5
3	最大速度/（km·h⁻¹）	60
4	加速度/（m·s⁻²）	−1.2~1.2
5	编队跟车距离l/m	10
6	车队间隔距离/m	60

下载: 导出CSV

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