The effects of air traffic conflict geometry have been well investigated in prior studies, particularly in the context of the pilot, though little in the context of the air traffic control officer (ATCO). No study to date has investigated the effects of conflict geometry on human factors variables of ATCOs through objective and physiological approaches. This study examines the effects of conflict geometries on ATCO situation awareness, stress level and brain activity during conflict resolution. Fifteen participants were instructed to resolve six different conflict geometries: crossing level, crossing non-level, converging level, converging non-level, overtaking level, and overtaking non-level. The results indicate that converging and crossing conflicts led to lower situation awareness (SA), higher stress level, and higher theta activation at the temporal and parietal lobes. Level conflict led to lower SA. The findings offer two implications, providing insights for the formal guidelines in ATC conflict resolution training and provision of inputs for the conflict resolution aid development.

New navigation-related technologies and complex ships' systems are associated with a considerable amount of information and alerts on navigational bridges. Each alert triggers a process conducted by the Officer Of the Watch (OOW), which includes data collection and interpretation, decision making, as well as appropriate actions. In the case of too many alerts or poorly managed alerts, the workload of the OOW may significantly increase, and situational awareness may be compromised, increasing the risk of errors. The main goal of this research is to analyse OOW actions triggered by the alerts. The research methods included an experiment on a bridge simulator with experienced officers, a questionnaire survey and a series of interviews. The main outcomes encompass the frequency of the alerts and the number and the processing times of single actions conducted upon an alert. The results indicate that, on average, during one watch, an OOW spends 22·4 minutes conducting 64 actions triggered by 16 alerts. However, officers consider 45% of the alerts as over-prioritised and distracting at the moment of their notification.

The lane-level map, which contains the lane-level information severely lacking in widely used commercial navigation maps, has become an essential data source for autonomous driving systems. The linking relations between lane-level map and commercial navigation map can facilitate an autonomous driving system mapping information between different applications using different maps. In this paper, an approach is proposed to build the linking relations automatically. The different topology networks are first reconstructed into similar structures. Then, to build the linking relations automatically, the adaptive multi-filter algorithm and forward path exploring algorithm are proposed to detect corresponding junctions and paths, respectively. The approach is validated by two real data sets of more than 150 km of roads, mainly highway. The linking relations for nearly 94% of the total road length have been built successfully.

With more and more missions around the Moon, a communication/navigation constellation around the Moon is necessary. Halo orbits, due to their unique geometry, are extensively studied by researchers for this purpose. A dedicated survey is carried out in this work to analyse the coverage ability of halo orbits. It is found that a two-satellite constellation is enough for continuous one-fold coverage of the north or the south polar regions but never both. A three-satellite constellation is enough for continuous one-fold coverage of both north and south polar regions. A four-satellite constellation can cover nearly 100% of the whole lunar surface. In addition, the coverage ability of another special orbit – distant retrograde orbit (DRO) – is analysed for the first time in this study. It is found that three satellites on DROs can cover 99·8% of the lunar surface, with coverage gaps at polar caps. A four-satellite constellation moving on spatial DROs can cover nearly the whole lunar surface. By combining halo orbits and DROs, we design a five-satellite constellation composed of three halo orbit satellites and two DRO satellites. This constellation can provide 100% continuous one-fold coverage of the whole lunar surface.

Human fatigue is a major risk factor in transportation that contributes, directly or indirectly, to a large number of traffic accidents. Though many studies have investigated fatigue-inducing factors in transportation to manage human fatigue more efficiently, there are limited studies related to vessel traffic service (VTS). To fill this gap, this work aims to determine the key causal factors and symptoms of human fatigue with a focus on VTS operations. Achieving this aim is hindered by the problems of no standard definition of task-related fatigue and limited data sources. To solve these problems, this paper proposes a novel definition of task-related human fatigue, a task-driven approach for identifying causal factors and a causal network-based approach for selecting key causal factors. Twelve key causal factors of human fatigue in VTS were identified and analysed. In addition, it was found that VTS operators suffered from multidimensional fatigue, especially physical fatigue. The results provide a foundation and future directions for designing interventions to manage human fatigue.

Superimposing Electronic Navigational Chart (ENC) data on marine radar images can enrich information for navigation. However, direct image superposition is affected by the performance of various instruments such as Global Navigation Satellite Systems (GNSS) and compasses and may undermine the effectiveness of the resulting information. We propose a data fusion algorithm based on deep learning to extract robust features from radar images. By deep learning in this context we mean employing a class of machine learning algorithms, including artificial neural networks, that use multiple layers to progressively extract higher level features from raw input. We first exploit the ability of deep learning to perform target detection for the identification of marine radar targets. Then, image processing is performed on the identified targets to determine reference points for consistent data fusion of ENC and marine radar information. Finally, a more intelligent fusion algorithm is built to merge the marine radar and electronic chart data according to the determined reference points. The proposed fusion is verified through simulations using ENC data and marine radar images from real ships in narrow waters over a continuous period. The results suggest a suitable performance for edge matching of the shoreline and real-time applicability. The fused image can provide comprehensive information to support navigation, thus enhancing important aspects such as safety.

Obstacle avoidance navigation for an unmanned surface vessel is a research focus for ship autonomy in which the real-time requirement in practical application is very serious, and always necessitates a complicated structure model to guarantee real-time performance. This paper proposes the grid cell activation model to reduce the complexity of modelling and to simplify an obstacle avoidance algorithm. Combined with the goal-oriented probability model to design a dynamic positive-loss-rate expectation evaluation function, it produces the proper strategy for obstacle avoidance. Case studies on multi-obstacle layouts and special circumstances are conducted and presented. The results indicate that the grid cell obstacle avoidance algorithm can effectively implement obstacle avoidance planning and ensure real-time requirements. A comparison with the potential field algorithm is performed, which shows good results and verifies the feasibility of the algorithm.

In the process of composing a double-differenced positioning model, it is difficult to separate different frequency signals between code division multiple access (CDMA) systems, the single-difference ambiguity of the pivot satellite and phase differential inter-system biases (PDISBs). Hence it is difficult to calibrate in advance the bias between systems in order to build an inter-system model which only needs one pivot satellite. Based on analysis of the stability of PDISB parameters for non-overlapping frequency CDMA systems, this study adopts a particle filter to estimate the fractional part of the PDISBs (F-PDISBs) between the systems and proposes a particle filter-based inter-system positioning model. Results show that the F-PDISBs and code DISBs for the baselines with the same receiver types and some with different receiver types are rather stable over time and for these baselines it is feasible to use a particle filter to estimate the F-PDISB parameters in the initial stage. Having attained the F-PDISBs, the inter-system model can be constructed to improve positioning accuracy in complex operational environments.

A simple scheme is presented for mapping the 2D probability density for an observer's position, defined by any number of lines of position (LOPs) on the surface of the Earth, assuming that the LOPs result from uncorrelated observations that have normally distributed errors. Although the mapping can be used to determine the position fix corresponding to the LOPs (which is consistent with other methods), its intended use is computing the total probability that the observer is located within (or outside) some specified area of interest, such as a zone of avoidance around a navigational hazard. Numerical experiments with areas where the average total interior probability is known, such as the triangles and polygons formed by nearly convergent LOPs, show that the method provides correct answers. The numerical experiments also revealed that theoretical probabilities associated with commonly used error ellipses are overstated for navigational solutions based on small numbers of LOPs.

Alarm fatigue is a critical safety issue, as it can increase workload and impair operators' situational awareness. This paper proposes a design methodology to enhance the interaction between alarm systems and operators. Through input from VTS personnel as the fundamental design requirements, a user requirement-driven design framework is proposed. It integrates quality function deployment, the theory of inventive problem solving, and software quality characteristics into three design phases. In Phase I, user requirements are obtained from the analysis of current working processes. Phase II investigates the specific non-functional design requirements of vessel alarm systems and the contradictions. In Phase III, the innovative principles generated with the contradiction matrix were analysed. A case study was conducted to verify and illustrate this framework, resulting in a conceptualisation design of a smart vessel alarm system.

The time it takes to acquire a satellite signal is one of the most important parameters for a Global Navigation Satellite System (GNSS) receiver. The Parallel Frequency space search acquisition Algorithm (PFA) runs faster than the Parallel Code phase search acquisition Algorithm (PCA) when the approximate phase of Pseudo-Random Noise (PRN) code and the approximate value of a Doppler shift are known. However, a large amount of data is needed to be dealt with by the Fast Fourier Transform (FFT) in a traditional PFA algorithm because it processes a narrow-band signal with the initial sampling frequency after the PRN code is stripped. In order to reduce the computational complexity of the traditional PFA algorithm, a down-conversion module and a downsampling module were added to the traditional PFA in the work reported here. Experiments demonstrated that this method not only succeeded in acquiring BeiDou B1I signals, but also the time for acquirement was reduced by at least 80% with the modified PFA algorithm compared with the traditional PFA algorithm. The loss in Signal-to-Noise Ratio (SNR) did not exceed 0·5 dB when the number of coherent points was less than 500.

Lifeboats are essential life-saving equipment for all types of water-going vessels and offshore platforms. Lifeboat simulators have been created specifically for offshore personnel to practice in conditions that are normally too risky for live training. As simulation training is a relatively new alternative, there is a need to assess how training performed with a simulator compares with conventional training. This study was performed to evaluate how skills acquired with different training approaches transferred to an emergency scenario. Over a period of one year, participants received quarterly training in one of three ways: using live boats, computer-based training or a simulator. Following training, participants were evaluated on their ability to launch and manoeuvre a lifeboat in a plausible emergency. The study results suggest a benefit to performing training with realistic lifeboat controls and practicing using representative emergency scenarios. Insights are provided on how training can be modified to increase competence.

This paper introduces an approach for solving a safe ship trajectory planning problem. The algorithm, utilising the concept of a discrete artificial potential field and a path optimisation algorithm, calculates an optimised collision-free trajectory for a ship. The method was validated by simulation tests with the use of real navigational data registered on board the research and training ship Horyzont II. Results of simulation studies demonstrate that the approach is capable of finding a collision-free trajectory in near-real time, and this proves its applicability in commercial collision avoidance systems for ships. The paper contributes to the development of decision support systems for ships and autonomous navigation.

Autonomous ships are gaining in importance and are expected to shape the future of the global shipping industry. This evolutionary shift raises serious issues about compliance with the International Regulations for Preventing Collisions at Sea 1972 (COLREGs). This paper reviews the literature on autonomous ships from the perspective of the obligations of good seamanship imposed by COLREGs. The authors conclude that to facilitate the introduction of autonomous ships, the application barriers presented by COLREGs need to be analysed. With this goal, this paper presents a perspective from navigational practice. Four nautical scientists and two deck officers were invited to give their opinions. The analysis indicates that COLREGs require further elaboration and amendments to eliminate uncertainty of interpretation. In particular, the paper highlights the need to amend the ‘look-out’ rule (COLREGs Rule 5) to permit look-out by ‘computer vision’ alone while, at the same time, preserving the distinction between vessels navigating in restricted visibility and in sight of one another.

The tight combination model improves the positioning accuracy of the Global Navigation Satellite System (GNSS) in complex environments by increasing the redundancy of observation. However, the ambiguity cannot be calculated directly because of the correlation between it and the phase difference inter-system bias (DISB) in the model. This paper proposes a method of DISB estimation based on the principle of maximum ratio. From the data analysis, for the standard deviation of code DISB, the improvement of the method can up to 0·179 m with the poor quality data. In addition, compared to the parameter combination method, the standard deviation of all the phase DISB was deceased with the method in the paper. About the phase DISB of GPS L1/Galileo E1, the standard deviation decreased from 0·014/0·022/0·009/0·051 cycles to 0·006/0·015/0·004/0·029 cycles of four baselines, which represents the improvement of 57·14/31·82/55·56/43·14%. About the phase DISB of GPS L1/BDS B1, the standard deviation decreased from 0·014/0·061/0·010/0·052 cycles to 0·002/0·005/0·009/0·004 cycles of four baselines, which represents the improvement of 85·71/91·80/10·00/92·31%.