Introduction

Maritime transportation is the primary mode of goods transport in international trade, characterized by low freight costs and high traffic volume. Particularly with the rapid growth of global trade, maritime transportation has established a relatively stable network of routes. However, as countries increasingly explore and utilize both surface and underwater resources, certain waters have been designated as local temporary prohibited navigation areas, where construction and military activities occur. Consequently, some established shipping routes may pass through these restricted zones. Although the local maritime authorities issue navigation announcements prior to the enforcement of such restrictions, allowing vessels to adjust their routes accordingly, the continued advancement of marine traffic informatization has made the automatic route design for ships navigating these temporary prohibited areas an important aspect of route optimization. With the rapid development of intelligent maritime transportation and the rise of big data in maritime industries, theoretical research on navigation restrictions can not only address key challenges but also enrich the theoretical foundations of intelligent maritime transportation.

With the rapid development of maritime transportation and the increasing size and speed of ships, ship density in coastal waters has risen, leading to a higher frequency of maritime accidents. To enhance navigation safety, ship navigation and positioning systems have evolved toward greater informatization and intelligence, driven by advancements in science and technology. Early methods of navigation, such as fixing positions with landmarks and celestial navigation, gradually gave way to more advanced technologies, including the radio direction finder (1921), radar (1935), Loran-A (1943), Loran-C (1958), satellite navigation systems (1964), and the Global Positioning System (1993). These systems, along with other specialized electronic positioning equipment, have transformed maritime navigation. The integration of these technologies with electronic charts enables modern systems to combine information from GPS, ARPA, AIS, and other navigation tools, offering ship pilots comprehensive functions such as chart displays, route planning, and real-time monitoring, significantly improving the safety of navigation.

In the 1990s, the International Maritime Organization (IMO) defined the Integrated Bridge System (IBS) as a unified system encompassing various functions, including navigation control, collision avoidance, centralized information display, alarm monitoring, communication, and automation of navigation management and control. While both traditional positioning systems and advanced integrated electronic systems have been employed to assist ship navigation, little attention has been given to the macro-level control and management of ship traffic flow in navigable waters. However, traffic flow regulation from a broader perspective has already been successfully implemented in the road transportation sector. Drawing on the successful experiences of Intelligent Transportation Systems (ITS), the concept of “ship navigation intelligent guidance” and the development of a ship traffic flow guidance system are essential for realizing intelligent maritime transportation.

Intelligent technology is a leading force in modern industrial advancements, with widespread applications across various sectors. In the transportation industry, intelligent vehicles, intelligent ships, and smart vehicle management systems are developing rapidly. The evolution of intelligent transportation systems has the potential to significantly enhance transportation efficiency. Furthermore, the emergence of autonomous vehicles, although still in the development phase, is expected to play a key role in shaping the future transportation infrastructure of intelligent cities.

Compared to road-based intelligent transportation, the development of intelligent maritime transportation is relatively underdeveloped and faces several constraints. The objective factors affecting ship navigation are complex and can lead to a variety of accidents. In contrast to road transportation, the cost of ship transportation accidents is significantly higher, which greatly limits the progress of intelligent maritime transportation. Despite these challenges, research in intelligent waterborne transportation has made continuous strides. To ensure ship navigation safety, research on risk identification has advanced considerably. Methods such as Bayesian networks1,2,3, Fuzzy Set Analysis (FSA)4, data envelopment analysis5, and fault tree analysis6 have been applied to assess ship collision risks. Additionally, Automatic Identification System (AIS) data is widely used in risk assessment7,8, and with the ongoing development of big data technologies, AIS-based collision risk assessments offer substantial advantages. Furthermore, some researchers have developed risk assessment frameworks by proposing relevant standards or integrating them with formal safety assessment guidelines issued by higher-level maritime organizations9,10,11.

The International Regulations for Preventing Collisions at Sea (COLREGs) are a set of rules established by the International Maritime Organization (IMO) to prevent collisions and ensure the safety of life and property at sea. Since their introduction, COLREGs have served as the primary framework for maritime traffic safety and have been foundational in studies related to ship navigation, including collision avoidance and risk assessment. Researchers have explored various topics using COLREGs as a guiding framework, such as collision risk prediction12,13, ship route planning14,15, and autonomous ship navigation16. These studies hold significant practical implications for improving maritime safety.

The development of intelligent ships represents a new branch of marine intelligent transportation. This includes advancements in intelligent ship design, navigation control, collision avoidance theory, and other related areas. Intelligent ship design primarily focuses on the development of autonomous navigation systems17,18,19,20,21. Although marine intelligent transportation is still in its early stages, current research is largely centered on improving ship navigation safety. The Vessel Traffic Service (VTS) is a critical system deployed in busy ports and channels, playing an increasingly vital role in ensuring ship safety22. The deployment of VTS has laid a strong foundation for the broader development of marine intelligent transportation. Moreover, VTS serves as an embryonic system for marine intelligent transportation, and further development based on VTS can leverage existing research to accelerate progress in this field.

Existing research on marine intelligent transportation reveals that its theoretical framework is underdeveloped, lacking the foundational research and guidance necessary to support its rapid advancement. Unlike intelligent transportation systems for road traffic, there is no established definition for ship navigation guidance, which has hindered the progress of marine intelligent transportation. This gap significantly restricts theoretical research and delays the application of marine intelligent transportation concepts in practice. To address this, the present study analyzes the similarities and differences between ships and vehicles, as well as between ship and vehicle traffic flow. It proposes a theoretical framework for ship navigation guidance, integrating insights from road traffic systems. This framework offers a theoretical foundation to support the development of maritime intelligent transportation.

The structure of this paper is as follows: Section “Feasibility analysis of ship navigating intelligent guidance system” presents a feasibility analysis of the concept of an intelligent navigation system for ship navigation. Section “Related theoretical definitions of ship navigation intelligent guidance” defines the key theoretical concepts related to ship navigation intelligent guidance. Section “System architecture design of ship navigation intelligent guidance system” outlines the basic framework for implementing an intelligent guidance system for ship navigation. Section “Core algorithm and model of ship navigation intelligent guidance system” introduces the core algorithms and models underlying the ship navigation intelligent guidance system. Section “Experiment and analysis” details three sets of experiments conducted to validate the core algorithms and models, followed by an analysis of the experimental results. Finally, Section “Conclusion” discusses the conclusions of the study.

Feasibility analysis of ship navigating intelligent guidance system

Investigation and analysis of ship navigating accidents

Ship navigation safety is crucial for ensuring the efficient, orderly, and stable operation of marine traffic. Analyzing ship navigation accident data provides valuable insights into the causes of accidents. By identifying these causes and developing regulatory measures to address them, and by implementing these measures within application systems, the likelihood of accidents can be significantly reduced, thereby enhancing the overall safety of maritime transportation.

Statistics of ship navigation accident data

A total of 67 ship navigation accidents from 2010 to 2020 were collected and analyzed through field research methods for various maritime management departments. To better understand collision incidents between different types of ships, the accidents were categorized into 8 groups based on the type of ship involved. The frequency and statistical probability of each type of accident are illustrated in Fig. 1.

Fig. 1
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Classification and statistics of navigation accidents.

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The analysis of the 67 accident cases resulted in the identification of five distinct accident types. The frequency of each accident type is presented in Table 1.

Table 1 Statistics of various types of accidents.
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Cause analysis of ship navigation accidents

An investigation into the causes of ship navigation accidents reveals that these incidents result from multiple factors. Through a detailed analysis of the risk factors associated with each accident, ten key risk factors were identified, as shown in Table 2.

Table 2 List of risk factors and accidents involved.
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By analyzing and refining the risk mechanisms of ship accidents, the key risk factors in marine traffic incidents can be accurately identified. Based on these factors, relevant strategies are developed, and a directional risk identification method is proposed. Through a combination of guidance and supervision, the likelihood of ship navigation accidents can be reduced, ensuring the smooth and efficient operation of maritime traffic.

Analysis of communication and navigation equipment for navigation guidance

Ship communication and navigation equipment plays a crucial role in facilitating communication both between ships and between ships and shore-based management centers. Since the development of these systems, basic equipment such as radar, the Automatic Identification System (AIS), Very High Frequency (VHF) radios, and the Electronic Chart Display and Information System (ECDIS) have become widely adopted. Additionally, integrated systems like the Integrated Navigation System (INS) and the Integrated Bridge System (IBS) have emerged as important tools, further enhancing navigation capabilities on ships.

The Automatic Identification System (AIS) is a digital navigation aid that consists of both shore-based stations and shipborne equipment. The system transmits dynamic ship information (such as course over ground (COG), speed over ground (SOG), coordinates, heading (HDG), etc.) and static information (such as MMSI, call sign, IMO number, etc.) through communication channels. One of the main advantages of AIS is that it combines dynamic and static information, which allows shore-based centers and other vessels to clearly identify ships. However, a limitation of AIS is that its data updates occur at intervals, rather than in real time, and AIS data transmission can sometimes be subject to distortion.

The basic principle of radar is to detect objects within a certain range by emitting radar waves, allowing the system to determine the object’s azimuth and distance. Shipborne radar systems can calculate and display various target information, including course, speed, and direction, using an automatic radar plotter. The primary advantage of radar is its ability to provide real-time, accurate azimuth and distance data. However, a limitation of radar is that it cannot identify key information about the target, such as the ship’s identification parameters, since it only locates the object using radar waves. The combination of AIS signals and radar data effectively addresses this limitation. With the widespread adoption of AIS, this integration enables real-time and precise azimuth and distance information, while also providing the ship’s identification parameters.

The Electronic Chart Display and Information System (ECDIS) presents traditional paper charts on a computer screen after digital processing. It integrates data from various communication and navigation equipment, which is transferred through an interface for display. This system significantly enhances the ability of navigation personnel to access surrounding ship information and provides a visual monitoring platform for ship supervisors.

MF, HF, and VHF are common communication modes used for maritime mobile services, with VHF being the primary means of communication between Vessel Traffic Service (VTS) centers and ships within their jurisdiction. VHF enables real-time communication between ships, allowing managers to receive up-to-date information from the ship’s crew. However, the main limitation of VHF is its restricted data transmission capacity, as it can only transmit voice messages. This makes it challenging to transfer digital information or more complex data, such as professional plans or detailed operational information.

The Integrated Bridge System (IBS) is an advanced and more robust automatic navigation system built upon the Integrated Navigation System (INS). The system components of the IBS are illustrated in Fig. 2.

Fig. 2
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System composition of IBS.

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The IBS offers the advantage of consolidating signals from existing communication and navigation equipment while providing visual display capabilities. Additionally, the IBS includes functions such as integrated driving and control, collision avoidance assistance, communication support, and alarm security monitoring. This makes it a sophisticated system for assisting with ship navigation and operation.

A ship’s navigation is influenced by various factors, including the presence of other vessels and environmental conditions. Real-time communication between ships is essential to coordinate navigation, particularly when vessels approach one another. The development of communication and navigation equipment has enabled shore-based command centers to monitor the real-time position and status of ships. Currently, these systems provide a solid foundation for intelligent navigation guidance, supporting functions such as ship positioning, identification, and information visualization. However, the communication methods between ships and between ships and shore remain relatively outdated. Therefore, it is crucial to leverage the strengths of existing equipment while addressing its shortcomings in the design of intelligent navigation systems. This approach is essential for ensuring the safe and efficient development of water transportation systems.

Requirement analysis of ship navigation intelligent guidance system

The main functions of road traffic guidance involve implementing an overall control or optimization scheme for the transportation system, directing each unit (i.e., vehicle) to achieve macro-level adjustments and optimizations. However, there are significant differences between ship navigation and vehicle operation. While the original route may meet the requirements for ship navigation, altering the ship’s route can significantly impact the economic efficiency of navigation. The economic viability of ship navigation is crucial to ensuring the profitability of maritime transport. Therefore, intelligent guidance in ship navigation primarily focuses on addressing situations where the original route is no longer suitable for safe and efficient navigation.

Route design is a complex and detailed process that requires relevant data to be gathered before a ship embarks on its journey. However, the establishment of temporary local navigation restrictions—such as those due to construction or military activities—can occur unexpectedly and may not be accounted for during the route design phase. As a result, some pre-designed routes may intersect with these temporarily prohibited areas. In such cases, the application of ship navigation guidance can help ensure both the safety of navigation and the economic efficiency of the ship as it navigates through these restricted zones.

There are both similarities and differences between vessel traffic and vehicle traffic. Based on the analysis of vessel traffic accidents and the evaluation of countermeasures, the use of guidance technology can significantly improve the operational safety of waterborne traffic by helping ship operators avoid certain accident risks.

Additionally, as the number of ships increases, the traffic flow in congested waters also rises. However, limited resources for ship navigation and the lack of effective traffic flow management compromise both navigational safety and the efficiency of maritime transportation. Consequently, there is an urgent need for the development of intelligent guidance systems for ship navigation.

Based on the functional requirements of the ship navigation intelligent guidance system, the following system requirements have been established:

Requirement 1: The system should capture real-time ship status data. This data can then be analyzed to generate effective traffic flow guidance for ships.

Requirement 2: A global ship navigation guidance scheme should be developed, from which individual navigation plans for each ship can be generated to achieve overall navigational goals.

Requirement 3: The system should enable dynamic monitoring of ship navigation states, implement risk detection strategies, and promptly identify potential navigation risks.

Given the current limitations of communication and navigation equipment, communication between ships and between ships and shore remains relatively basic (e.g., voice messages transmitted unilaterally via VHF and text messages sent via AIS). The implementation of an intelligent ship navigation guidance system can address these shortcomings. Therefore, the following requirement is proposed:

Requirement 4: Enhance communication between ships by establishing diversified information transmission channels, such as images and other data, to facilitate the sharing of navigation guidance plans.

Requirement 5: Improve ship navigation risk notifications to ensure that pilots can effectively understand and respond to potential navigation risks.

Related theoretical definitions of ship navigation intelligent guidance

By analyzing the differences in scale and maneuverability between ships and vehicles, the unique characteristics of ship navigation are identified. These insights provide theoretical support for traffic flow analysis and the development of related theoretical concepts in intelligent ship navigation guidance.

Analysis of similarities and differences between ships and vehicles

Size

There are significant size differences between ships and vehicles. Large ships can be several times, or even tens of times, larger in length, width, and height compared to smaller ships. To illustrate these variations, four typical ship profiles of different scales are presented for comparison in Fig. 3.

Fig. 3
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Schematic of ship size comparison (Ship length: Patrol boat: 12 m; Tug: 60 m; Multi-purpose bulk vessel: 176 m; LNG carrier: 310 m).

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In contrast, the size difference between large and small vehicles is comparatively smaller. For example, according to China’s standard (Limits of Dimensions, Axle Load, and Masses for Road Vehicles GB 1589-2004), vehicle sizes are outlined in Table 3.

Table 3 Maximum limits for the outline dimensions of motor vehicles, trailers and motor vehicles.
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Operating environment

The operating environments of ships and vehicles differ significantly. Ships can navigate as long as the waters are suitable for their draft, whereas vehicles are confined to roads with clearly defined width and load-bearing limitations. As maritime traffic has developed, the concept of a traffic separation system has been introduced in ship navigation. The International Maritime Organization (IMO) adopted the “General Provisions on Ships’ Routing” and implemented the deployment of traffic separation systems. Figure 4 illustrate the traffic separation system off the ChengShan Jiao promontory and the system in the Yangtze Estuary Deepwater Channel.

Fig. 4
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The cases of traffic separation system.

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The implementation of the traffic separation system has established common navigation rules for ships and vehicles. While the system is applied in key waters, ships retain the freedom to navigate in most other areas. Thus, although the operating environments of ships and vehicles differ, there are also certain similarities in their navigation principles.

Maneuverability

Maneuverability is a key factor in assessing the performance differences between ships and vehicles during motion. By analyzing these differences in maneuverability, we can distinguish between ship traffic flow guidance and vehicle traffic flow guidance. This analysis allows for a clearer definition of ship navigation guidance and the development of an effective and safe guidance implementation strategy.

Maneuverability refers to the ability of a vehicle or ship to respond accurately to the operator’s instructions. For vehicles, traditional maneuverability typically concerns the ability to maintain or change direction. In contrast, ship maneuverability has a broader definition, extending to performance aspects such as speed changes, acceleration, deceleration, and stopping, reflecting the complexities of navigation.

Comparing these concepts, vehicle maneuverability requires a more precise coordination between the driver and the vehicle, while ship maneuverability tends to be less responsive. To quantitatively compare maneuverability, we can examine braking performance. The empirical values for the emergency stopping distances of certain ships are presented in Table 4, while the required braking distance for unloaded vehicles in China is shown in Table 5.

Table 4 Emergency stopping distance of part types of ships.
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Table 5 Braking distance requirements for cars.
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By comparing the braking data of ships and vehicles, it is evident that the stopping distance for ships is strongly influenced by their size, whereas for vehicles, the impact is less pronounced. Section “Size” discusses the dimensional differences between ships and vehicles. Based on the braking distance data, it is clear that the stopping distance for vehicles is significantly shorter than that of ships.

Another key measure of maneuverability is steering characteristics. For ships, this is typically represented by the turning radius, while for vehicles, the minimum turning radius is used. Table 6 shows the turning radius for various types of ships at maximum rudder angle, as well as the minimum turning radius for several types of vehicles.

Table 6 Turning radius of part types of ships with maximum rudder angle and Minimum turning radius of part types of vehicles.
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The data provided in Table 6 indicates that ships occupy much more space than vehicles when turning. As a result, special considerations are required at turning points when designing ship guidance systems, which inevitably leads to differences in traffic flow guidance methods between ships and vehicles.

Summary of similarities and differences between ships and vehicles

The comparison of data between ships and vehicles leads to the following conclusions which are shown as Table 7.

Table 7 Conclusion on the discrepancy and similarities between ships and vehicles.
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Analysis of similarities and differences between ship traffic flow and vehicle traffic flow

Traffic flow research focuses on analyzing the overall movement characteristics of transportation systems. In the context of vehicle traffic flow guidance, the goal is to optimize traffic flow on a global scale. By comparing the characteristics of ship and vehicle traffic flow, both the similarities and differences are examined to better understand how each operates and to inform the development of effective guidance systems.

Quantitative analysis

Flow, speed, and density are key parameters in traffic flow research. Figure 5a presents the annual data for ship flow in the main channel of Tianjin Port and the Dagusha channel (statistics from the AIS management center of the China Maritime Administration). Figure 5b shows statistics from a monitoring point on Beijing’s Fourth Ring Road, based on data from the traffic measurement video and data-sharing platform of the Department of Mechanics and Engineering Science, Fudan University (http://traflow.fudan.edu.cn/).

Fig. 5
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Comparison of ship traffic flow and road traffic flow.

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The ship traffic flow in the Tianjin Port channels serves as a typical example of coastal areas in China. Similarly, the design of Beijing’s Fourth Ring Road and the intelligent management of vehicles reflect the current state of intelligent road management across the country.

The annual statistics for ship traffic in the main channel and Dagusha channel of Tianjin Port are presented in Fig. 6a. Similarly, the statistics for vehicle traffic over a 0.5-h period on Beijing’s Fourth Ring Road are shown in Fig. 6b.

Fig. 6
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Comparison of ship traffic flow and vehicle traffic flow. (a) Statistics result of annual inflow of Tianjin Port main channel and Dagusha channel. (b) Statistics result of the vehicles passing by in 0.5 h on the Fourth Ring Road in Beijing.

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The total traffic flow at Tianjin Port for one year is 61,939 (inflow: 31,336; outflow: 30,603). On the west side of Beijing’s Fourth Ring Road, the vehicle traffic flow during an off-peak 0.5-h period is 2,464 vehicles. By estimating the annual vehicle flow based on this 0.5-h data, the annual traffic volume for this section is approximately 3 × 108 vehicles (18 h per day, 365 days). While there may be some margin of error in the vehicle traffic flow estimate, the order of magnitude is relatively accurate. Comparing the two traffic flow datasets, it is evident that the total volume of ship traffic flow is significantly smaller than that of vehicle traffic flow.

To better express the relationship between traffic flow and the environment, and to reflect the density of traffic flow, a new calculation method is proposed: the Subject-Limiting Width Ratio (S-LWR). This parameter represents the ratio of the width of the traffic equipment to the restricted width of the operating environment. It is used to quantify the degree to which the traffic environment restricts the movement of traffic equipment.

The International Maritime Organization (IMO) and the Permanent International Asso-ciation of Navigation Congresses (PIANC) typically factor in ship length (L) when determining channel width requirements, as ship length is a key parameter in assessing turning behavior. However, in evaluating the relationship between traffic flow and the environment, the width ratio can serve as an indicator of spatial relationships. It reflects the extent to which the environment accommodates ships or vehicles, thereby indirectly gauging the degree of operational freedom for ships and vehicles.

The main channel of Tianjin Port is 765 m wide, while the Dagusha channel is 375 m wide. Compared to the width of the ship traffic flow, the actual navigation range of ships in these channels is slightly wider, due to the varying draft requirements based on ship size. For example, with a ship width of 30 m (medium-sized ship), the S-LWR values for the two channels of Tianjin Port are 0.04 and 0.08, respectively. On the other hand, the width of Beijing’s Fourth Ring Road is approximately 15 m, with vehicles measuring about 2.5 m wide, resulting in an S-LWR value of approximately 0.17 for vehicles.

By comparing the S-LWR values, it is evident that ships experience greater freedom in their navigation channels than vehicles on the road. The primary reason for this difference lies in the disparity in maneuverability, while a secondary factor is the difference in mandatory traffic management requirements.

There is also a clear difference in the speed of traffic flow between ships and vehicles. According to “The Implementation Details for the Safety Supervision Management for the VTS in the Harbour of Tianjin,” issued by the Tianjin Maritime Administration of China, the speed of vessels with a deadweight tonnage of 80,000 tons or more in the main channel of Tianjin Port shall not exceed 10 knots, while the speed of smaller ships is limited to 12 knots. The minimum speed for ships in the main channel of the new port is 4 knots.

In contrast, the speed limit for vehicles on Beijing’s Fourth Ring Road is 80 km/h. To facilitate comparison, the speed data for both ships and vehicles have been converted into the same unit, as shown in Table 8.

Table 8 Comparison of speed limit range.
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Although ships and vehicles may not always operate at the restricted speed during actual navigation or operation, this speed is generally set by regulatory authorities as the safety limit, based on typical operating speeds. It reflects the overall speed level of traffic flow at a specific location and can be used to quantitatively compare the speed differences between two traffic flows.

By comparing the speed limits of ship and vehicle traffic flow, it is evident that there are significant differences in their respective speeds. Due to the discrepancies in size and maneuverability between the two types of traffic, the speed distribution within each flow also differs considerably. This variation has a notable impact on the definition and implementation of ship traffic flow guidance.

Qualitative analysis

Vehicle traffic flow refers to the movement of vehicles on the road, while ship traffic flow pertains to the continuous movement of ships on water. Some scholars have analyzed road traffic flow using fluid dynamics and probability theory23,24,25. They proposed four basic properties: systematicness, restriction, delay, and following. The operation of ships, however, is influenced by both internal factors, such as flow composition, ship technical status, speed, and the ship pilot, as well as external factors, including channel scale, wind, wave, and current conditions. Based on a review of traffic flow research, ship traffic flow is characterized by five basic properties: systematicness, duality, limitation, variability, and interconnectedness.

By comparing the definitions and properties of ship and vehicle traffic flow, along with the results of their comparison, the following conclusions can be drawn:

Commonalities between ship traffic flow and vehicle traffic flow:

  1. 1.

    Systematic Property: Both types of traffic flow exhibit systematic characteristics. Traffic flow is composed of a certain number of individual units, and once these units form a system, the overall traffic flow system exhibits distinct attributes compared to a single unit.

  2. 2.

    Restrictive Property: Both ship and vehicle traffic flows are subject to restrictions imposed by environmental factors, which can lead to congestion or traffic jams.

  3. 3.

    Time-Varying and Space-Varying Properties: Both ship and vehicle traffic flows are influenced by changes over time and space, meaning their dynamics vary in both dimensions.

The discrepancies between ship traffic flow and road traffic flow are as follows:

  1. 1.

    Response Ability: As discussed in Section “Operating environment”, vehicles have a much stronger response ability to drivers’ instructions compared to ships. This increased responsiveness in vehicles reduces the likelihood of accidents, whereas the slower response of ships contributes to a higher probability of collision. As a result, ships in ship traffic flow often rely on specialized communication methods (e.g., VHF communication) to coordinate collision avoidance.

  2. 2.

    Traffic Separation Systems and Speed Regulation: Although the International Maritime Organization (IMO) recommended the use of traffic separation systems as early as 1967, their implementation has been slow over the past decades. The international regulations for preventing collisions at sea only require ships to maintain a safe speed at all times, without clearly defining the scope of “safe speed.” This results in a dual characteristic for ship drivers within ship traffic flow: they are subject to both traffic management regulations and the freedom to adjust vessel speed and relative positions between ships. Ship speed and course can be adjusted flexibly to modify the relative position between vessels, ensuring navigation safety. In contrast, changes in vehicle speed and direction in road traffic flow are largely influenced by other vehicles, limiting flexibility.

The discrepancies between ship traffic flow and road traffic flow are as follows:

  1. 1.

    Combined with the analysis result in section “Operating environment”, the response ability of vehicles to drivers’ instructions is much stronger than that of ships, which makes the probability of ship collision accident higher than that of vehicles. Therefore, ships in ship traffic flow will adopt special methods to communicate (Such as VHF Communication) and coordinate ship collision avoidance.

  2. 2.

    In contrast, although IMO began to recommend the traffic separation system as early as 1967, the development of traffic separation system is still very slow in the past decades. The international regulations for preventing collisions at sea only stipulates that ships should use safe speed at any time. However, the scope of safe speed is not clearly defined. Therefore, the ship driver has the property of dual in the ship traffic flow. The driver is subject to both traffic management and freedom of vessel speed and relative position between vessels. The speed and course can be changed flexibly to change the relative position between ships under the condition of ensuring navigation safety. While the change of vehicle speed and direction is greatly affected by other vehicles in road traffic flow relatively.

Summary of similarities and differences between ship traffic flow and vehicle traffic flow

Through qualitative and quantitative comparisons of vehicle traffic flow and ship traffic flow, the following conclusions can be drawn which are shown as Table 9.

Table 9 Conclusion on the qualitative and quantitative comparisons of vehicle traffic flow and ship traffic flow.
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Theory of ship intelligent navigation guidance

Definition of ship intelligent navigation guidance

The theoretical analysis and comparison of the similarities and differences between ships and vehicles reveal that the primary distinctions between ship traffic flow and vehicle traffic flow stem from their inherent attributes. Based on the previous analysis and drawing upon the concept of road vehicle traffic flow guidance, the definition of the relevant theoretical system is as follows:

Definition 1: “Ship navigation intelligent guidance”

Ship navigation guidance involves utilizing accurate navigation data from ship equipment, along with real-time meteorological, hydrological, and traffic conditions within the navigational area. This approach aims to ensure the safe operation of vessels. The primary method of achieving this guidance is through ship navigation systems, supported by additional guidance technologies, to manage and regulate the flow of ship traffic.

The definition of “Ship navigation intelligent guidance” requires clarification of several key concepts, outlined as follows:

Definition 2: “ Ship navigation intelligent guidance region”

The ship navigation intelligent guidance region refers to the effective area where navigation guidance is applied. This region is not restricted to the waters under the jurisdiction of a single state. With advancements in navigation technology, ships may eventually be guided across global waters.

Definition 3: “The client of Ship navigation intelligent guidance system”

The client of the ship navigation intelligent guidance system interacts with the system’s server, seamlessly incorporating the system’s macro-control directives into the ship’s route planning. This device facilitates the overall control of ship traffic flow.

The attributes of ship intelligent navigation guidance

The purpose of ship intelligent navigation guidance is to ensure that ships navigate through the guidance area safely, efficiently, and on time. The system should possess the following attributes:

Attribute 1: Scientificity

The safety of ship navigation has long been a priority within the maritime industry. As the number of ships and their sizes continue to grow, the risks associated with navigation also increase. As a technology designed to ensure safe navigation by regulating and controlling ship traffic flow, ship navigation guidance must be both scientifically grounded and practical.

Attribute 2: Non-mandatory

As an effective tool for the macro-control of ship traffic flow, ship intelligent navigation guidance must adhere to the principle of ship navigation: while ensuring the safety of the ship, the ship’s pilot retains the right to determine the speed and course. Therefore, navigation guidance personnel should respect the varying conditions of different ships in the waters and avoid using mandatory prompts that interfere with a ship’s maneuvering decisions.

Attribute 3: Immediacy

Ship navigation is subject to greater uncertainty than vehicle navigation and is more easily affected by environmental factors. Therefore, it is crucial to adjust the guidance plan promptly in response to changes in environmental conditions, ensuring real-time and effective safety guidance for vessels.

Attribute 4: Pertinence

Given the significant differences in maneuverability among various types and sizes of ships, which result in distinct motion characteristics, it is essential to develop tailored guidance schemes that are specifically suited to the navigation characteristics of each ship type.

Attribute 5: Systematicness

Based on the definition of ship intelligent navigation guidance and drawing from the development of road vehicle guidance systems, it is clear that ship navigation guidance cannot rely on a single piece of equipment. Therefore, it is essential to establish a comprehensive guidance system that integrates various types of equipment to ensure effective navigation control.

Attribute 6: Interactivity

Given the practical aspects of ship navigation supervision, it is essential for ships to communicate with the local maritime authorities when entering certain areas. However, with the development and implementation of the ship navigation guidance system, this interaction can gradually be replaced by direct communication through the guidance system.

Capability analysis of ship navigation intelligent guidance system

The most effective way to realize the practical value of the theory of ship navigation intelligent guidance is through its application. By comparing and analyzing ships and vehicles, as well as ship and vehicle traffic flows, and integrating vehicle traffic flow guidance theory, the definitions and attributes of ship navigation intelligent guidance are proposed.

Based on the analysis of the requirements for the ship navigation intelligent guidance system in Section “Feasibility analysis of ship navigating intelligent guidance system”, this system can effectively monitor and address some of the existing ship navigation safety issues. Through ship navigation intelligent guidance, the overall operation of ship traffic flow can be controlled at a macro level, while also managing the micro-navigation risks between individual ships.

Capability 1: Compatibility with Communication and Navigation Equipment Interfaces

The long development history and widespread use of maritime communication and navigation equipment have resulted in a diverse range of devices. Based on the analysis in Section “Analysis of communication and navigation equipment for navigation guidance”, the ship navigation intelligent guidance system must be compatible with the existing communication and navigation equipment interfaces. Additionally, the system should be designed to accommodate future advancements, ensuring compatibility with new equipment interfaces.

Capability 2: Ship Traffic Flow Data Analysis and Navigation Guidance Scheme Generation

As a crucial tool for controlling ship traffic flow, the ship navigation intelligent guidance system must possess the ability to analyze ship traffic flow data. Based on the results of this analysis, the system should be capable of generating scientifically sound and practical guidance schemes for managing ship traffic flow within the guidance area.

Capability 3: Real-time Navigation Guidance Scheme Updates

Due to the unpredictable impact of meteorological and hydrological conditions on ship traffic flow, the ship navigation intelligent guidance system must be capable of modifying and optimizing the guidance scheme in real time to adapt to these changes.

Capability 4: Generation of Navigation Guidance Scheme for Individual Ships

To effectively manage the overall guidance of the area, the system must use the analysis of ship flow and density within the guidance area to develop navigation schemes tailored to individual ship route planning.

Capability 5: Identification of Ship Navigation Risks

A key distinction between ship navigation equipment and vehicle navigation equipment is that ship navigation systems must prioritize ship safety while providing navigation services. Therefore, the ship navigation intelligent guidance system must be capable of identifying potential navigation risks.

Capability 6: Early Warning of Ship Navigation Risks

The system should be capable of sending navigation safety warnings to ships at risk, in a specific format. This will help the pilot identify potential navigation risks and enhance the overall safety of the ship.

Establishment of ship navigation intelligent guidance theoretical system

The development of a ship navigation guidance theoretical system is essential for effectively implementing intelligent ship navigation guidance. Based on an analysis of ship navigation accidents and the current state of ship communication and navigation equipment, this paper presents a demand analysis for the ship navigation intelligent guidance theoretical system.

While the development of intelligent transportation systems for road traffic is relatively mature, with both theoretical and practical advancements in vehicle guidance systems, this paper adopts a similar approach to construct a ship navigation intelligent guidance theoretical system, informed by road traffic guidance theory. Through qualitative and quantitative comparisons of vehicles and ships, as well as vehicle and ship traffic flows, the similarities and differences between these two types of traffic are identified. Based on this analysis, a theoretical system for ship navigation intelligent guidance is proposed. The theoretical system of ship navigation intelligent guidance encompasses relevant definitions, attributes of core content, and its practical deployment and expansion. The construction process of the ship navigation intelligent guidance theoretical system is outlined in sections “Feasibility analysis of ship navigating intelligent guidance system” and “Related theoretical definitions of ship navigation intelligent guidance” and illustrated in Fig. 7.

Fig. 7
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The construction process of ship navigation intelligent guidance theoretical system.

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System architecture design of ship navigation intelligent guidance system

System architecture of the management side of ship navigation intelligent guidance system

Building on the definition of ship navigation intelligent guidance, this paper analyzes the system architectural design of the ship navigation intelligent guidance system. Currently, the supervision of navigable waters primarily relies on the Vessel Traffic Service (VTS). However, despite years of development, there are still limitations in the supervision of ship navigation. VTS is a system equipped with AIS base stations, radar, CCTV, VHF, and shipboard terminals to monitor ships sailing within harbors and entering or leaving ports.

Based on the proposed theory of ship intelligent navigation guidance and the ship intelligent navigation guidance system, AIS base stations, radar, CCTV, and VHF are key communication and navigation tools for obtaining ship navigation information. With the ongoing advancement of computer technology, the processing capacity and display capabilities of the VTS system can be optimized. Consequently, two deployment types for the monitoring center of the ship navigation intelligent guidance system are proposed (Table 10).

Table 10 Two deployment types for the monitoring center of the ship navigation intelligent guidance system.
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System architecture of shipboard client side of ship navigation intelligent guidance system

The shipboard client equipment of the ship navigation intelligent guidance system is a key component for enabling intelligent navigation guidance on ships. Its primary function is to communicate with the system server, transmitting the ship’s basic information and receiving navigation guidance instructions. Based on the analysis in Section “Analysis of communication and navigation equipment for navigation guidance”, IBS is a well-established ship navigation assistance system with strong compatibility, having already integrated the signal acquisition and fusion capabilities for communication and navigation equipment. Therefore, the benefits of incorporating the shipboard client equipment into IBS are as follows:

  1. 1.

    The shipboard client equipment of the ship navigation intelligent guidance system can directly receive communication and navigation signals from IBS, eliminating the need to collect and decode these signals again.

  2. 2.

    Integrating the shipboard client equipment into IBS allows for the seamless reception and display of the ship navigation guidance scheme, reducing the number of devices that ship pilots need to operate.

  3. 3.

    The integrated driving control function of IBS enables the automatic implementation of the guidance scheme approved by the pilot, eliminating the need for manual adjustments and simplifying the ship guidance process.

Core algorithm and model of ship navigation intelligent guidance system

To meet the fundamental requirements of ship navigation guidance, the ship navigation intelligent guidance system must integrate three core algorithms: the route design algorithm, the ship domain model, and the especial cautious navigation angle model.

Route design algorithm

The ship navigation intelligent guidance system provides a safe route recommendation for ships, considering factors such as open sea conditions, primary waters, and the presence of multiple ships26. To plan a safe shipping route, the first step is selecting an appropriate method for constructing the environmental model. Current research identifies several approaches, including the visualization method27, Voronoi diagram method28, Maklink diagram method29, tangent diagram method30, grid method31, and PRM algorithm32, among others. In this study, a novel environment modeling algorithm is employed33, which used the Delaunay triangulation algorithm for environmental model construction. The Delaunay environment model enables the identification of navigable waters based on factors such as ship draft and tide height, while the tangent graph method is employed to construct a navigable network within these waters. The safe navigation path is then determined within this network. The specific implementation of this algorithm can be found in reference33, and the various stages of the algorithm are illustrated in Fig. 8.

Fig. 8
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Flowchart of Ship Route Design Algorithm.

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Ship domain model

The ship domain model is a key tool for ensuring ship navigation safety. First introduced by Japanese scholar Fujii34, the model has evolved significantly over time. With advancements in information technology and further research, the ship domain model has developed into several variations, including statistical-based models35,36, intelligent algorithm-based models37, and analytical-based models38. The focus of this paper is ship navigation guidance within navigable construction waters. To address this, the ship domain model for ships with limited maneuverability is adopted39. This model emphasizes the navigation characteristics of ships with restricted maneuverability and integrates relevant requirements from the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs). The model’s parameters, defined by elliptical boundaries, are calculated using numerical methods that account for ship-to-ship interactions and ship maneuvering dynamics. Additionally, to make complex numerical models more applicable to real-world ship navigation supervision, a ship parameter estimation model is proposed. This model estimates the various parameters needed for numerical calculations based on limited ship data. The specific model and implementation details can be found in reference39. The calculation process for the ship domain model is illustrated in Fig. 9.

Fig. 9
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Parameter calculation method for ship domain model.

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The especial cautious navigation angle model

Building on the ship domain model, an Especial Cautious Navigation Angle (ECNA) model is employed to further enhance ship navigation safety and visualize collision risks in the developed ship navigation intelligent guidance system40. The ECNA model is an extension of both the PPC and PAD models. While the PAD model expands potential collision points between two ships into a possible collision area, its visualization capability diminishes in areas with high ship density. To address this limitation, the ECNA model is introduced.

The ECNA model, an extension of the PAD model, further refines the collision risk visualization by defining a range of especial cautious navigation angles. This range improves the clarity and effectiveness of the visual representation, providing ship operators and navigation managers with clear collision risk warnings. The basic evolution path and various modes of the ECNA model are illustrated in Fig. 10.

Fig. 10
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Evolution and several modes of ECNA model.

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Experiment and analysis

Experimental scheme

To evaluate the effectiveness of the proposed ship navigation intelligent guidance system, three sets of experiments were conducted. The experimental plan is outlined in Table 11.

Table 11 Experimental scheme.
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Experimental platform

A prototype of the ship navigation intelligent guidance system, based on AIS, has been developed following the theory and framework of intelligent ship navigation guidance. This system prototype has been implemented and demonstrated in the Shenzhen–Zhongshan Link construction water area, with its performance shown in Fig. 11.

Fig. 11
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Application demonstration effect of the prototype of ship navigation intelligent guidance system.

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The software system for the prototype is developed by C++, and the system utilizes a C/S architecture to implement the proposed framework. AIS equipment serves as the data source for the ship. Several algorithms have been implemented, including the ship route design algorithm, ship domain model, and the Especial Cautious Navigation Angle Model. During the application demonstration, the system communicates through the network of communication operators.

Experimental data and scenarios

The experiment is based on real-world ship trials, with the author using an experimental platform to conduct tests aboard the ship. The platform collects AIS data from nearby vessels and, in combination with its ability to reproduce AIS data, allows for the repetition of simulation experiments following the real-world trials. To verify the effectiveness of the ship navigation guidance system proposed in this paper, the experimental water chart is provided in Fig. 12.

Fig. 12
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Experimental water area.

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Experimental result

Experiment of route design algorithm

To verify the effectiveness of the route design algorithm in the ship navigation intelligent guidance system, a route was planned for the experimental ship (MMSI: 41322XXXX), with the destination set at 113° 52.212′ E and 22° 22.187′ N. Additionally, to thoroughly assess the practical application of the route design algorithm, three more sets of experiments were conducted, involving route planning for ships with MMSIs 41351XXXX, 41390XXXX, and 21245XXXX. The experimental results are shown in Fig. 13.

Fig. 13
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Experimental results of route design algorithm.

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An island lies between the selected ship and its destination, preventing a direct route to the destination. As a result, the ship navigation intelligent guidance system planned a safe navigation route for the selected ship, taking into account factors such as the ship’s draft, obstacle information (including the island), and destination details, to assist in safe navigation.

Experiment of ship domain model

To verify the effectiveness of the ship domain model integrated into the ship navigation intelligent guidance system, the model was loaded onto the ship with MMSI 41390XXXX. Once the model was loaded, the system automatically detected any ship information entering the ship domain. If a ship crosses the boundary of the domain, the system prompts a notification in the information box, indicating that the ship has breached the domain boundary. In the visualization interface, ships that invade the boundary are highlighted with red circles, as shown in Fig. 14.

Fig. 14
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Experimental results of ship domain model.

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In densely trafficked waters, the ship domain model can directly identify ships that encroach upon the safe area and display various types of alarm prompts in the system. This feature enhances the ability of system users to detect potential collision threats near the loaded ship domain model, thereby improving the safety of ship navigation.

Experiment of the especial cautious navigation angle model

The visualization of ship collision risks is crucial when using ship navigation intelligent guidance system. While ship domain models have been tested for collision threat detection in previous research, their visualization display has proven insufficient for practical application systems. To address this, the ship navigation intelligent guidance system incorporates the Especial Cautious Navigation Angle (ECNA) model, an extension of collision avoidance geometry derived from the PPC and PAD models. In this experiment, the system loaded the ECNA model for the ship with MMSI 41349XXXX. The triggering effect of the ECNA model during encounters with different ships is shown in Fig. 15.

Fig. 15
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Experimental results of ECNA.

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To facilitate the display of the ECNA model triggered by the selected ship, the system has developed a dedicated sub-interface for showing the ECNA model of the selected ship. This interface offers multiple settings, allowing users to choose different units for measuring the distance between the selected ship and surrounding ships. Additionally, users can opt to display the full ECNA model or only show the ECNA model for the selected ship’s forward direction. For information related to other ships, users can select options to display MMSI, speed, or choose not to display these details. These features enhance user convenience, simplify operation, and aid in the effective detection of collision risks.

Experimental analysis

The experiment in this study aims to validate the effectiveness of the proposed ship navigation intelligent guidance system. This system integrates multiple algorithms to enable ship navigation guidance functionality. The three core algorithms central to the system were selected for experimentation. The data used in the experiment was collected from actual ship trials, providing the advantage of being able to repeatedly reproduce the navigation scenarios. The experimental results demonstrate that the ship navigation intelligent guidance system proposed in this paper is highly operable in practical applications. It meets the relevant requirements outlined in the proposed ship navigation intelligent guidance concept, thereby confirming the effectiveness and practicality of the system.

The ship navigation intelligent guidance system proposed in this article integrates multiple algorithms and models, and its effectiveness has been validated in the experimental section. The effectiveness of these algorithms is further supported by the detailed design and thorough testing documented in three other papers published during the development of this system. The references for these three algorithms or models are listed in Table 12.

Table 12 References for application models and algorithms.
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This experiment not only evaluated the practical application effects of three models/algorithms but also assessed the feasibility and effectiveness of integrating multiple models/algorithms into a single system. The system is designed as an induction tool for overseeing navigation safety in navigable construction waters. Addressing this practical issue, the study provides a preliminary exploration of intelligent ship navigation theory and introduces the foundational principles of ship navigation guidance, including relevant attributes and features.

The ship navigation intelligent guidance system proposed in this article is developed based on the theoretical framework for ship navigation guidance outlined within the paper. Taking into account the unique characteristics of ships, the study analyzes the approximate and differential attributes of ships and vehicles. Relevant theories from vehicle guidance systems and road intelligent transportation are introduced to enrich the basic theory of ship intelligent transportation. Guided by this theoretical foundation, a prototype of the ship navigation intelligent guidance system was developed, and on-site experiments were conducted at the Shenzhen–Zhongshan Link construction site. The system is capable of collecting real-time AIS data and other relevant information, which is then stored for later reproduction and analysis. The experiment described in this paper was conducted within this context.

Experiments have demonstrated that integrating multiple algorithms into a single intelligent guidance system for ship navigation is feasible. This system is designed to address the specific challenges of navigation guidance in construction zones within navigable water areas. Its versatility extends beyond typical navigable or open waters, making it applicable in more complex environments, such as waters with multiple obstacles, aquaculture zones, fishing areas, and other specialized water types. By analyzing the unique characteristics of each environment, the system can be configured with appropriate parameters and operated according to specific needs.

As intelligent ship technology continues to evolve, there is an increasing demand for features such as autonomous navigation, risk identification, and collision avoidance. The guidance system and its associated algorithms and models, as presented in this paper, offer strong support for the development of intelligent ships. This is particularly evident when intelligent ships navigate through complex, construction, or restricted water areas. The system enables safe navigation supervision through communication technologies, addressing navigation challenges by planning safe routes and avoiding tight situations using appropriate algorithms. Thus, the ship guidance theory proposed in this paper not only provides theoretical support for intelligent water transportation but also serves as a valuable reference for advancing ship intelligence.

Conclusion

With the rapid advancement of information technology, many sectors are increasingly adopting intelligent systems. As a crucial component of the transportation industry, the development of maritime transportation has become more urgent. This paper proposes theoretical research and system design for ship navigation intelligent guidance, specifically addressing situations where a ship’s original route crosses a temporarily restricted navigation area. The key conclusions are as follows:

  1. 1.

    This paper provides a thorough analysis of the similarities and differences between ships and vehicles, as well as between ship and vehicle traffic flow. Drawing on the concept of road traffic flow guidance, it introduces the definition and attributes of ship navigation intelligent guidance. Based on the unique characteristics of ships and their traffic flow, the paper proposes a framework for a ship navigation intelligent guidance system tailored to ship traffic flow management.

  2. 2.

    The definition and attributes of ship navigation intelligent guidance enhance the fundamental theory in the field of martime intelligent transportation, offering valuable insights for future studies on various forms of ship traffic flow guidance. Moreover, the concept of ship traffic flow guidance contributes significantly to improving ship traffic flow management, providing a theoretical foundation for reducing congestion in specific water areas and enhancing navigation safety in specialized waters.

  3. 3.

    Two methods for constructing a ship navigation intelligent guidance system are proposed and their respective advantages are analyzed. Additionally, the paper outlines the deployment strategy for the shipboard client equipment within the ship navigation intelligent guidance system. The construction schemes provided offer a practical reference for advancing the application of ship navigation guidance theory.

  4. 4.

    Given the growing water traffic and increasingly complex safety challenges, the theory of ship navigation intelligent guidance presents significant potential for regulating ship traffic flow. Implementing effective navigation guidance in high-risk or congested waters can greatly contribute to improving navigation safety and ensuring smoother water traffic flow.