-
摘要: 为保障“岸基驾控,船端值守”模式下船舶的安全高效航行与稳定作业控制,提出了船舶远程驾驶控制系统的定义和“船-岸-云”协同的跨域融合架构;针对随机通信环境下的时变网络传输时延问题,建立递增冗余重传和时延容忍补偿相结合的视频通信处理机制,使用Luenberger状态观测器改进网络化控制性能,避免由于环境干扰或模型失配引起的控制量偏移;以内河典型64 TEU模型船为研究原型,开发系统的模块化功能和标准接口协议,在690 km外控制站验证了方法的有效性。研究结果表明:与直航和路径跟随相比,回转工况对网络波动表现出更高的敏感程度,在极限转角位置和转速抖动处船载底层硬件设备响应时间由124.53 ms上升至135.76 ms;经优化后的视频通信处理机制能够消除5%丢包和40 ms网络抖动影响,端到端传输时延稳定在150~200 ms,视频卡顿率控制在1.2%以内;路径跟随最大横向偏移误差为1.54 m,平均误差为0.61 m,有效提升了远程驾驶控制系统的稳定性与可靠性,能够满足船舶远程驾驶典型业务场景需求;接管时由于驾驶员需要一定时间熟悉船舶当前的驾驶任务和运动状态,系统立刻退出控制回路的方式会导致偏移的增加并出现短暂的抖动和振荡。
-
关键词:
- 水路运输 /
- 岸基驾控 /
- Luenberger状态观测器 /
- 时延容忍补偿 /
- 网络化控制
Abstract: To ensure safe and efficient navigation and stable operation control under the "shore-based control supplemented by onboard monitoring and watch-keeping" mode, the definition of ship remote-driving control system and "ship-shore-cloud" cross-domain collaborative integrated fusion architecture were proposed. Aiming at the network time-varying delay problem under stochastic communication environments, incremental redundant retransmission and delay-tolerance compensation methods were integrated to establish the video communication processing mechanism. The Luenberger state observer was constructed to improve the networked control performance, and the control quantity offset caused by environmental interference or model mismatch could be avoided. A typical 64 TEU inland water model ship was taken as the research prototype to develop the system's modularized functions and standard interface protocols, and the effectiveness of the proposed method was verified at a control station 690 km away. Experimental results indicate that turning is more sensitive to network fluctuations compared with straight and path-following conditions. Specifically, the responding time of shipboard underlying hardware increases from 124.53 ms to 135.76 ms at the ultimate turning angle and rotation jitters. After optimization, the influence of 5% packet loss and 40 ms network jitters is eliminated, the end-to-end transmission delay is stabilized at 150-200 ms, and the video stutter rate is controlled within 1.2% by the video communication processing mechanism. The maximum lateral offset error of the path following is 1.54 m, with an average error of 0.61 m, improving the stability and reliability of remote-driving control system effectively, so that it can meet the requirements of typical remote-driving scenarios. As the driver needs some time to familiar with the ship's current steering task and motion state, immediate exit from the control loop will result in increased offsets, temporary jitter, and oscillations during take-over. -
表 1 船舶远程驾驶典型业务需求
Table 1. Typical requirements of ship remote driving
类型 业务需求 功能特征 基础数据采集与处理 视频监控 通过船载视频采集设备实时回传视频数据,为岸基驾驶员完成航行决策提供持续的航行环境监测 导航定位 融合来自全球导航卫星系统(Global Navigation Satellite System, GNSS)和惯性导航系统(Inertial Navigation System, INS)采集到的船舶位置姿态信息,提升导航定位精度,为岸基驾驶员提供精确的运动状态和位置信息 状态反馈 实时采集与回传船舶的航行状态和硬件设备控制执行反馈信息 任务决策 航路规划 结合船舶位置和环境感知信息设置航行路径,发送航路信息,为船端提供航行建议与决策支持 风险预警 根据船舶航行状态和环境感知信息,辨识可能存在的风险,发出预警信号 应用执行 实时操控 驾驶员在驾驶位置之外的远程控制站或控制位置对船舶航行实时发送桨舵控制指令 自动控制 驾驶员或控制站设置航行任务,由船载智能系统在设定工况或运行范围内完成船舶的操纵任务 驾驶接管 包括接管请求响应和主动干预2种模式,受控船舶遇到船载智能系统无法处理的状况时,向岸基发送接管请求,由岸基操作人员决定是否介入,当网络环境较差或系统失效时由船端值守员主动进行干预 表 2 船型参数
Table 2. Parameters of ship
参数 数值 船长/m 3.606 型宽/m 0.697 吃水/m 0.153 排水体积/m3 0.336 方形系数 0.875 螺旋桨直径/m 0.09 舵展舷比 1.47 表 3 船载底层硬件设备响应性能测试
Table 3. Response performance test of onboard substrate hardware equipment
舵角/(°) 舵机响应
时间/ms螺旋桨转速/(r·s-1) 船舶速度/(m·s-1) 螺旋桨响应
时间/ms-35 147.89 -35 -1.09 113.78 -25 126.61 -25 -0.83 114.77 -15 131.70 -15 -0.46 107.76 -5 120.69 -5 -0.11 104.77 0 128.61 0 0.00 124.53 5 125.67 5 0.23 111.16 15 135.76 15 0.83 112.53 25 133.92 25 1.12 107.76 35 146.47 35 1.69 105.69 -
[1] LI Zhi-hong, ZHANG Di, HAN Bing, et al. Risk and reliability analysis for maritime autonomous surface ship: a bibliometric review of literature from 2015 to 2022[J]. Accident: Analysis and Prevention, 2023, 187: 107090. doi: 10.1016/j.aap.2023.107090 [2] 严新平, 贺亚鹏, 贺宜, 等. 水路交通技术发展趋势[J]. 交通运输工程学报, 2022, 22(4): 1-9. doi: 10.19818/j.cnki.1671-1637.2022.04.001YAN Xin-ping, HE Ya-peng, HE Yi, et al. Development trends of waterway transportation technology[J]. Journal of Traffic and Transportation Engineering, 2022, 22(4): 1-9. (in Chinese) doi: 10.19818/j.cnki.1671-1637.2022.04.001 [3] NEGENBORN R R, GOERLANDT F, JOHANSEN T A, et al. Autonomous ships are on the horizon: here's what we need to know[J]. Nature, 2023, 615(7950): 30-33. doi: 10.1038/d41586-023-00557-5 [4] 张宝晨, 耿雄飞, 李亚斌, 等. 船舶智能航行技术研发进展[J]. 科技导报, 2022, 40(14): 51-56.ZHANG Bao-chen, GENG Xiong-fei, LI Ya-bin, et al. Development status and trend of intelligent navigation technology[J]. Science and Technology Review, 2022, 40(14): 51-56. (in Chinese) [5] 袁雪, 姜爱华. 基于IMO分级的MASS岸基操控人员法律地位探析[J]. 中国海洋大学学报(社会科学版), 2023(1): 34-48.YUAN Xue, JIANG Ai-hua. Analysis of the legal status of shore control center operators of MASS based on IMO classification[J]. Journal of Ocean University of China (Social Sciences), 2023(1): 34-48. (in Chinese) [6] 严新平, 李晨, 刘佳仑, 等. 新一代航运系统体系架构与关键技术研究[J]. 交通运输系统工程与信息, 2021, 21(5): 22-29, 76.YAN Xin-ping, LI Chen, LIU Jia-lun, et al. Architecture and key technologies for new generation of waterborne transportation system[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(5): 22-29, 76. (in Chinese) [7] CHENT T T, UTNE I B, WU B, et al. A novel system-theoretic approach for human-system collaboration safety: case studies on two degrees of autonomy for autonomous ships[J]. Reliability Engineering and System Safety, 2023, 237: 109388. doi: 10.1016/j.ress.2023.109388 [8] 陈宇航, 朱宇, 韩冰, 等. 远程遥控模式下的船舶信息管理系统设计[J]. 上海船舶运输科学研究所学报, 2022, 45(5): 23-28.CHEN Yu-hang, ZHU Yu, HAN Bing, et al. Design of an information management system for intelligent remote operation of ships[J]. Journal of Shanghai Ship and Shipping Research Institute, 2022, 45(5): 23-28. (in Chinese) [9] LONGO G, ORLICH A, MERLO A, et al. Enabling real-time remote monitoring of ships by lossless protocol transformations[J]. IEEE Transactions on Intelligent Transportation Systems, 2023, 24(7): 7285-7295. doi: 10.1109/TITS.2023.3258365 [10] HÖYHTYÄ M, MARTIO J. Integrated satellite-terrestrial connectivity for autonomous ships: survey and future research directions[J]. Remote Sensing, 2020, 12(15): 2507. doi: 10.3390/rs12152507 [11] 李昌振, 陈伟, 王觉, 等. 面向智能内河航运通信的无线信道测量与典型信道特征[J]. 交通运输工程学报, 2022, 22(4): 322-333. doi: 10.19818/j.cnki.1671-1637.2022.04.025LI Chang-zhen, CHEN Wei, WANG Jue, et al. Wireless channel measurement and typical channel characteristics for intelligent inland navigation communications[J]. Journal of Traffic and Transportation Engineering, 2022, 22(4): 322-333. (in Chinese) doi: 10.19818/j.cnki.1671-1637.2022.04.025 [12] ZENG H, WANG T J, ZHANG J D, et al. A novel encryption scheme in ship remote-control against differential fault attack[J]. Applied Sciences, 2022, 12(16): 8278. doi: 10.3390/app12168278 [13] CHEN S J, XIONG X, WEN Y Q, et al. State compensation for maritime autonomous surface ships' remote-control[J]. Journal of Marine Science and Engineering, 2023, 11(2): 450. doi: 10.3390/jmse11020450 [14] 周翔宇, 吴兆麟, 王凤武, 等. 自主船舶的定义及其自主水平的界定[J]. 交通运输工程学报, 2019, 19(6): 149-162. doi: 10.19818/j.cnki.1671-1637.2019.06.014ZHOU Xiang-yu, WU Zhao-lin, WANG Feng-wu, et al. Definition of autonomous ship and its autonomy level[J]. Journal of Traffic and Transportation Engineering, 2019, 19(6): 149-162. (in Chinese) doi: 10.19818/j.cnki.1671-1637.2019.06.014 [15] WRÓBEL K, GIL M, MONTEWKA J. Identifying research directions of a remotely-controlled merchant ship by revisiting her system-theoretic safety control structure[J]. Safety Science, 2020, 129: 104797. doi: 10.1016/j.ssci.2020.104797 [16] CHENG Ting-ting, VEITCH E A, UTNE I B, et al. Analysis of human errors in human-autonomy collaboration in autonomous ships operations through shore control experimental data[J]. Reliability Engineering and System Safety, 2024, 246: 110080. [17] DOMINGUEZ-PERY C, VUDDARAJU L N R. From human automation interactions to social human autonomy machine teaming in maritime transportation[C]//Springer. Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation: IFIP WG 8.6 International Conference on Transfer and Diffusion of IT. Berlin: Springer, 2020: 45-56. [18] ZHANG Ming-yang, ZHANG Di, YAO Hou-jie, et al. A probabilistic model of human error assessment for autonomous cargo ships focusing on human-autonomy collaboration[J]. Safety Science, 2020, 130: 104838. [19] THIEME C A, RAMOS M A, HOLTE E A, et al. New Design Solutions and Procedures for Ensuring Meaningful Human Control and Interaction with Autonomy: Automated Ferries in Profile[M]//JOHANSSON T M, FERNANDEZ J E, DALAKLIS D, et al. Autonomous Vessels in Maritime Affairs: Law and Governance Implications. Berlin: Springer International Publishing, 2023: 213-242. [20] 向林浩, 唐伟强, 周增辉. 中国船级社"5G+"船舶实时远程检验技术解决方案[J]. 中国船检, 2021(1): 52-55.XIANG Lin-hao, TANG Wei-qiang, ZHOU Zeng-hui. "5G+" ship real-time remote inspection technology solution of China Classification Society[J]. China Ship Survey, 2021(1): 52-55. (in Chinese) [21] 孟广玮, 张青亮, 姜旭阳. 深远海养殖工船船岸一体化系统构建[J]. 船舶工程, 2020, 42(增2): 83-85, 126.MENG Guang-wei, ZHANG Qing-liang, JIANG Xu-yang. Construction of ship-shore integration system in deep ocean aquaculture engineering ship[J]. Ship Engineering, 2020, 42(S2): 83-85, 126. (in Chinese) [22] 高月红, 杨昊天, 尹宁, 等. 5G系统中CBGHARQ技术的分析与展望[J]. 通信技术, 2021, 54(2): 363-368.GAO Yue-hong, YANG Hao-tian, YIN Ning, et al. Analysis and prospect of CBG HARQ technique in 5G system[J]. Communications Technology, 2021, 54(2): 363-368. (in Chinese) [23] DUAN Wei, GU Jin-yuan, WEN Miao-wen, et al. Emerging technologies for 5G-IoV networks: applications, trends, and opportunities[J]. IEEE Network, 2020, 34(5): 283-289. [24] WANG Le, LI Shi-jie, LIU Jia-lun, et al. Design and implementation of a testing platform for ship control: a case study on the optimal switching controller for ship motion[J]. Advances in Engineering Software, 2023, 178: 103427. [25] JIANG Pei-wen, WEN Chao-kai, JIN Shi, et al. Wireless semantic communications for video conferencing[J]. IEEE Journal on Selected Areas in Communications, 2022, 41(1): 230-244. [26] GOLAGHAZADEH F, COULOMBE S, ROBERT J M. Residual packet loss rate analysis of 2-D parity forward error correction[J]. Signal Processing: Image Communication, 2022, 102: 116597. [27] LI T H, SIVARAMAN V, FAN L J, et al. Reparo: loss-resilient generative codec for video conferencing[J]. arXiv, 2023, DOI: 10.48550/arXiv.2305.14135. [28] ZHAO Y, ZHOU A, CHEN X. Reducing latency in interactive live video chat using dynamic reduction factor[C]//IEEE. 2020 IEEE Wireless Communications and Networking Conference. New York: IEEE, 2020: 9120837. [29] 柳粟杰, 杨秀芝, 陈平平, 等. 实时视频传输的帧级别前向纠错信道编码[J]. 厦门大学学报(自然科学版), 2020, 59(6): 964-971.LIU Su-jie, YANG Xiu-zhi, CHEN Ping-ping, et al. Frame-level forward error correction channel coding for real-time video transmission[J]. Journal of Xiamen University (Natural Science), 2020, 59(6): 964 -971. (in Chinese) [30] 张睿, 朱敏, 张冀, 等. 面向5G的递增冗余HARQ传输方案研究[J]. 北京邮电大学学报, 2018, 41(5): 92-97.ZHANG Rui, ZHU Min, ZHANG Ji, et al. Study on 5G incremental redundancy HARQ transmission strategy[J]. Journal of Beijing University of Posts and Telecommunications, 2018, 41(5): 92-97. (in Chinese) [31] WANG H B, RANGANATHAN S V S, WESEL R D. Variable-length coding with shared incremental redundancy: design methods and examples[J]. IEEE Transactions on Communications, 2019, 67(9): 5981-5995. [32] ZHAO Yun-bo, PAN Xiao-kang, YU Shi-ming. Predictive event-triggered control for disturbanced wireless networked control systems[J]. Journal of Systems Science and Complexity, 2021, 34(3): 1028-1043. [33] ZHANG Xian-ming, HAN Qing-long, GE Xiao-hua, et al. Networked control systems: a survey of trends and techniques[J]. IEEE/CAA Journal of Automatica Sinica, 2019, 7(1): 1-17. [34] DENG Y, LÉCHAPPÉ V, MOULAY E, et al. Predictor-based control of time-delay systems: a survey[J]. International Journal of Systems Science, 2022, 53(12): 2496-2534. [35] 赵东东, 闫磊, 周兴文, 等. 基于Luenberger观测器的不确定系统鲁棒状态反馈设计[J]. 上海交通大学学报, 2024, 58(4): 492-497.ZHAO Dong-dong, YAN Lei, ZHOU Xing-wen, et al. Robust state feedback design for uncertain systems based on Luenberger observer[J]. Journal of Shanghai Jiao Tong University, 2024, 58(4): 492-497. (in Chinese) [36] 佟世文, 钱殿伟, 于庆林, 等. 基于简化模型预测的网络化控制系统设计[J]. 控制工程, 2021, 28(2): 367-374.TONG Shi-wen, QIAN Dian-wei, YU Qing-lin, et al. Networked control system design based on simplified model prediction[J]. Control Engineering of China, 2021, 28(2): 367-374. (in Chinese) [37] 范绍帅, 荣志强, 田辉, 等. 基于载波相位的高精度室内快速定位算法[J]. 通信学报, 2022, 43(1): 172-181.FAN Shao-shuai, RONG Zhi-qiang, TIAN Hui, et al. High-precision indoor fast positioning algorithm based on carrier phase[J]. Journal on Communications, 2022, 43(1): 172-181. (in Chinese) [38] MORALES J J, KASSAS Z M. Tightly coupled inertial navigation system with signals of opportunity aiding[J]. IEEE Transactions on Aerospace and Electronic Systems, 2021, 57(3): 1930-1948. [39] JIANG Chang-hui, CHEN Shuai, CHEN Yu-wei, et al. Research on a chip scale atomic clock driven GNSS/SINS deeply coupled navigation system for augmented performance[J]. IET Radar, Sonar and Navigation, 2019, 13(2): 326-331.