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交通信息物理系统中的车辆协同运行优化调度

原豪男 郭戈

原豪男, 郭戈. 交通信息物理系统中的车辆协同运行优化调度. 自动化学报, 2019, 45(1): 143-152. doi: 10.16383/j.aas.c180354
引用本文: 原豪男, 郭戈. 交通信息物理系统中的车辆协同运行优化调度. 自动化学报, 2019, 45(1): 143-152. doi: 10.16383/j.aas.c180354
YUAN Hao-Nan, GUO Ge. Vehicle Cooperative Optimization Scheduling in Transportation Cyber Physical Systems. ACTA AUTOMATICA SINICA, 2019, 45(1): 143-152. doi: 10.16383/j.aas.c180354
Citation: YUAN Hao-Nan, GUO Ge. Vehicle Cooperative Optimization Scheduling in Transportation Cyber Physical Systems. ACTA AUTOMATICA SINICA, 2019, 45(1): 143-152. doi: 10.16383/j.aas.c180354

交通信息物理系统中的车辆协同运行优化调度

doi: 10.16383/j.aas.c180354
基金项目: 

国家自然科学基金 61573077

国家自然科学基金 61273107

详细信息
    作者简介:

    原豪男 大连海事大学控制科学与工程学硕士研究生.主要研究方向为智能交通.E-mail:yhn5220@163.com

    通讯作者:

    郭戈 东北大学教授. 1998 年获得东北大学博士学位. 主要研究方向为智能交通系统, 运动目标检测跟踪网络. 本文通信作者. E-mail: geguo@yeah.net

Vehicle Cooperative Optimization Scheduling in Transportation Cyber Physical Systems

Funds: 

Supported by National Natural Science Foundation of China 61573077

Supported by National Natural Science Foundation of China 61273107

More Information
    Author Bio:

    Master student at the School of Control Science and Engineering, Dalian Maritime University. His main research interest is intelligent transportation system

    Corresponding author: GUO Ge Professor at Northeastern University. He received his Ph. D. degree from Northeastern University in 1998. His research interest covers intelligent transportation system, moving target detection and tracking with network. Corresponding author of this paper
  • 摘要: 运输成本及温室气体的排放是衡量智能交通系统的重要指标,有效的运输调度可以降低运输成本和环境损害.针对路网中集成环保型货车的运输问题,本文提出一种基于交通信息物理系统(Transportation cyber physical system,TCPS)的大规模车辆协同调度及合并方案,以最大限度地降低运输成本和碳排放量.首先,采用局部调度策略,结合领队车辆选择算法及聚类分析,构建可合并车辆集合;然后,通过数学规划方法,实现每个车队集合中车辆路径与速度的改进优化处理;最后,通过突发情况的简易处理说明本文调度策略的可扩展性.仿真实验表明,用本文方法将车辆编组合并成车队行驶,较固定路径合并策略可显著降低路网中货运车辆的整体油耗.
    1)  本文责任编委 陈德旺
  • 图  1  车辆换路合并示意图

    Fig.  1  The schematic diagram of vehicle merging

    图  2  车辆调度系统

    Fig.  2  Vehicle scheduling system

    图  3  车辆与车辆集合的关系示意图

    Fig.  3  The schematic diagram of the relationship between vehicles and vehicle sets

    图  4  信息传输机制

    Fig.  4  Information transmission mechanism

    图  5  车辆运输任务

    Fig.  5  Vehicle transportation tasks

    图  6  本文策略调度策略的仿真结果

    Fig.  6  The simulation results of scheduling strategy in this paper

    图  7  固定路径合并策略的仿真结果

    Fig.  7  The simulation results of fixed path merging strategy

    图  8  两种策略的模拟调度的油耗对比

    Fig.  8  Comparison of the fuel consumption of the simulation of two strategies

    图  9  拥堵对车辆合并的影响

    Fig.  9  Congestion impact on vehicle merging

    图  10  考虑交通状况的车辆调度结果

    Fig.  10  Vehicle scheduling results considering actual traffic conditions

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出版历程
  • 收稿日期:  2018-05-28
  • 录用日期:  2018-09-27
  • 刊出日期:  2019-01-20

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