系统仿真学报 ›› 2023, Vol. 35 ›› Issue (11): 2419-2428.doi: 10.16182/j.issn1004731x.joss.22-0599

• 论文 • 上一篇    下一篇

面向宽窄交替航道的船舶交通元胞自动机模型

孙瑀隆(), 郑建风(), 韩佳轩, 李超   

  1. 大连海事大学 交通运输工程学院,辽宁 大连 116026
  • 收稿日期:2022-06-01 修回日期:2022-06-24 出版日期:2023-11-25 发布日期:2023-11-23
  • 通讯作者: 郑建风 E-mail:ylsun0124@dlmu.edu.cn;jfzheng@dlmu.edu.cn
  • 第一作者简介:孙瑀隆(1996-),男,博士生,研究方向为物流系统建模与仿真、物流信息管理。E-mail:ylsun0124@dlmu.edu.cn
  • 基金资助:
    国家自然科学基金(71871036)

A Cellular Automata Model for Simulating Ships Passing Through Waterways with Alternating Wide and Narrow Sections

Sun Yulong(), Zheng Jianfeng(), Han Jiaxuan, Li Chao   

  1. Transportation Engineering College, Dalian Maritime University, Dalian 116026, China
  • Received:2022-06-01 Revised:2022-06-24 Online:2023-11-25 Published:2023-11-23
  • Contact: Zheng Jianfeng E-mail:ylsun0124@dlmu.edu.cn;jfzheng@dlmu.edu.cn

摘要:

为了提高宽窄交通航道的通行效率,针对宽窄交替的结构特点,以基尔运河为例,根据其航道宽窄段交替结构的特点,建立了双向船舶交通流元胞自动机模型研究基尔运河的船舶交通流仿真。根据基尔运河的实际结构建立元胞空间,并基于固定闭塞理论和移动闭塞理论建立演化规则。基尔运河的结构导致大型船舶无法在狭窄的区间内同时通过,为了描述该现象,在元胞自动机模型中建立了合适的等待规则。在仿真分析中,主要讨论了不同船舶入流率、大小船舶比例、船舶间安全距离的影响。在仿真结果的基础上,进一步研究了基尔运河船舶交通流改善的瓶颈识别和改进策略。结果表明,基尔运河窄段长度过长是瓶颈所在,其使得运河内船舶大量停泊等待。

关键词: 水路运输, 基尔运河, 元胞自动机模型, 船舶交通流, 瓶颈识别

Abstract:

For improving the traffic efficiency of wide and narrow alternating waterways, considering Kiel Canal as an example, according to the structural characteristics of Kiel Canal with alternating width and narrow sections, a two-way ship traffic flow cellular automata model is established, and the simulation of ships passing through Kiel Canal is studied. Cellular space is set up according to the actual structure of Kiel Canal, and the evolution rules are set up based on the fixed block theory and moving block theory. In particular, due to the structure of Kiel Canal, large ships cannot pass simultaneously in the narrow section. Therefore, appropriate waiting rules are established in the cellular automata model. In the simulation and analysis, the influence of different ship inflow rates, proportions of large and small ships, and safety distance between ships is mainly discussed. Based on the simulation results, the bottleneck identification and improvement strategy are further studied for improving ships passing through Kiel Canal. The results show that the bottleneck lies in the long narrow section of Kiel Canal, which makes a large number of ships waiting in the canal.

Key words: waterway transportation, Kiel Canal, cellular automata model, ship traffic flows, bottleneck identification

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