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An Unmanned Traffic Command System for Controlled Waterway in Inland River: An Edge-centric IoT Approach

Zechen Li* Tong Liu Su Li* Lang You* Shan Liang* ( )Dejun Wang*, 
School of Automation, Chongqing University, Chongqing 400044, P. R. China
School of Computer Science, The University of Sheffield, 211 Portobello, Sheffield S1 4DP, UK
Changjiang Waterway Bureau, Wuhan, Hubei 430014, P. R. China

This paper was recommended for publication in its revised form by editorial board member, Xi Chen.

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Abstract

The controlled waterway in the upper reaches of the Yangtze River has become a bottleneck for shipping due to its curved, narrow and turbulent characteristics. Consequently, the competent authorities must establish controlled one-way waterways and signal stations to ensure traffic safety. These signal stations are often located in remote and uninhabited mountainous areas, causing great difficulties in the living and working conditions for the staff. Therefore, the trend has emerged toward unmanned and remote traffic command at signal stations. The vessels passing through it must obey the signal revealed by the Intelligent Vessel Traffic Signaling System (IVTSS) to pass in one direction. The accuracy of signals is directly related to traffic safety and efficiency. However, the unreliability of vessel sensing sensors in these areas and the latency of transmission and computation of large amounts of sensing data may negatively impact IVTSS. Hence, more information from the physical world is needed to ensure the stable operation of IVTSS, and we proposed an edge-computing-centric sensing and execution system based on IoT architecture to enhance the reliability of IVTSS. We conducted experiments using plug-and-play methods, reducing the command and recording error rates by 89.47% and 86.27%, respectively, achieving the goal of real-time perception control.

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Unmanned Systems
Pages 79-93

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Cite this article:
Li Z, Liu T, Li S, et al. An Unmanned Traffic Command System for Controlled Waterway in Inland River: An Edge-centric IoT Approach. Unmanned Systems, 2026, 14(1): 79-93. https://doi.org/10.1142/S2301385025500839

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Received: 11 May 2024
Accepted: 19 October 2024
Published: 10 December 2024
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