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

doi:10.16182/j.issn1004731x.joss.22-0599

Abstract

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

CLC Number:

U612.3

Sun Yulong, Zheng Jianfeng, Han Jiaxuan, Li Chao. A Cellular Automata Model for Simulating Ships Passing Through Waterways with Alternating Wide and Narrow Sections[J]. Journal of System Simulation, 2023, 35(11): 2419-2428.

Figures/Tables 14

Table 1

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Fig. 9

Fig. 10

Fig. 11

Table 2

Fig. 12

References 16

1	Zheng Jianfeng, Zhang Wenlong, Qi Jingwen, et al. Canal Effects on a Liner Hub Location Problem[J]. Transportation Research Part E: Logistics and Transportation Review, 2019, 130: 230-247.
2	Andersen T, Joakim Høgset Hove, Fagerholt K, et al. Scheduling Ships with Uncertain Arrival Times Through the Kiel Canal[J]. Maritime Transport Research, 2021, 2: 100008.
3	Meisel F, Fagerholt K. Scheduling Two-way Ship Traffic for the Kiel Canal: Model, Extensions and a Matheuristic[J]. Computers & Operations Research, 2019, 106: 119-132.
4	Lübbecke Elisabeth, Marco E Lübbecke, Möhring Rolf H. Ship Traffic Optimization for the Kiel Canal[J]. Operations Research, 2019, 67(3): 791-812.
5	张琦, 肖文锦, 潘刚. 基于元胞自动机的轨道交通客流拥堵传播研究[J]. 交通运输系统工程与信息, 2017, 17(4): 83-89.
	Zhang Qi, Xiao Wenjin, Pan Gang. A CA-based Simulation Model of Urban Railway Large Passenger Flow Congestion Transmission[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(4): 83-89.
6	邱小平, 于丹, 孙若晓, 等. 基于安全距离的元胞自动机交通流模型研究[J]. 交通运输系统工程与信息, 2015, 15(2): 54-60.
	Qiu Xiaoping, Yu Dan, Sun Ruoxiao, et al. Cellular Automata Model Based on Safety Distance[J]. Journal of Transportation Systems Engineering and Information Technology, 2015, 15(2): 54-60.
7	张海, 倪少权, 吕苗苗. 基于元胞自动机模型的地铁列车折返间隔分析[J]. 交通运输工程与信息学报, 2021, 19(2): 37-45.
	Zhang Hai, Ni Shaoquan, Miaomiao Lü. Analysis of Subway Trains' Turn-back Headway Based on the Cellular Automaton Model[J]. Journal of Transportation Engineering and Information, 2021, 19(2): 37-45.
8	施俊庆, 李志强, 李素兰, 等. 考虑双向交通的城市路网交通流元胞自动机模型[J]. 交通运输系统工程与信息, 2017, 17(2): 90-96.
	Shi Junqing, Li Zhiqiang, Li Sulan, et al. A Cellular Automaton Model of Urban Road Network Considering Bidirectional Traffic[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(2): 90-96.
9	刘展宏, 杨秀建, 吴相稷, 等. 基于元胞自动机的雾天车辆跟驰建模与仿真[J]. 系统仿真学报, 2021, 33(10): 2399-2410.
	Liu Zhanhong, Yang Xiujian, Wu Xiangji, et al. Modeling and Simulation of Car Following in Fog Based on Cellular Automata[J]. Journal of System Simulation, 2021, 33(10): 2399-2410.
10	Sun Zhuo, Chen Zhonglong, Hu Hongtao, et al. Ship Interaction in Narrow Water Channels: A Two-lane Cellular Automata Approach[J]. Physica A: Statistical Mechanics and its Applications, 2015, 431: 46-51.
11	Qi Le, Zheng Zhongyi, Longhui Gang. Marine Traffic Model Based on Cellular Automaton: Considering the Change of the Ship's Velocity Under the Influence of the Weather and Sea[J]. Physica A: Statistical Mechanics and Its Applications, 2017, 483: 480-494.
12	Qi Le, Ji Yuanyuan, Balling R, et al. A Cellular Automaton-based Model of Ship Traffic Flow in Busy Waterways[J]. The Journal of Navigation, 2021, 74(3): 605-618.
13	戴林伟. 双向航道船舶交通流元胞自动机模型及仿真[J]. 上海海事大学学报, 2019, 40(1): 27-31, 64.
	Dai Linwei. Cellular Automaton Model and Simulation of Ship Traffic Flow in Two-way Waterway[J]. Journal of Shanghai Maritime University, 2019, 40(1): 27-31, 64.
14	刘宗杨, 周春辉, 赵俊男, 等. 基于元胞自动机的航道通过能力建模与仿真[J]. 系统仿真学报, 2021, 33(10): 2478-2487.
	Liu Zongyang, Zhou Chunhui, Zhao Junnan, et al. Modeling and Simulation of Channel Passage Capacity Based on Cellular Automata[J]. Journal of System Simulation, 2021, 33(10): 2478-2487.
15	周华亮, 高自友, 李克平. 准移动闭塞系统的元胞自动机模型及列车延迟传播规律的研究[J]. 物理学报, 2006, 55(4): 1706-1710.
	Zhou Hualiang, Gao Ziyou, Li Keping. Cellular Automaton Model for Moving-like Block System and Study of Train's Delay Propagation[J]. Acta Physica Sinica, 2006, 55(4): 1706-1710.
16	李峰, 高自友, 李克平. 固定闭塞系统中列车流的特性分析[J]. 物理学报, 2007, 56(6): 3158-3165.
	Li Feng, Gao Ziyou, Li Keping. Analysis of the Property of Train Flow in the Fixed Autoblock Systems[J]. Acta Physica Sinica, 2007, 56(6): 3158-3165.

序号	宽段	窄段
17	75(+40)	/
18	/	180(-240)
19	200(+160)	/
20	/	210(-170)
21	205(+170)	/

[1]	Yangsheng Jiang, Sichen Wang, Kuan Gao, Meng Liu, Zhihong Yao. Cellular Automata Model of Mixed Traffic Flow Composed of Intelligent Connected Vehicles’ Platoon [J]. Journal of System Simulation, 2022, 34(5): 1025-1032.
[2]	Li Nan, Wei Zhuobin, He Xuejun, Zhang Shiyun. Research on Highline Cable Parametric Design Platform of Alongside Replenishment at Sea [J]. Journal of System Simulation, 2016, 28(7): 1481-1488.