The location of the wreck of Shackleton's ship the Steam Yacht Endurance is recorded in the expedition log books as 68°39′30′′S 52°26′30′′W. The methods and assumptions that went into obtaining this fix are examined in detail by consulting the original log entries with a view to understanding the size of the errors and uncertainties it may be subject to and providing guidance to possible future searches. It is found that a dearth of navigational sights around the time of the sinking, the inevitable growth of uncertainties in the chronometer time since rating and other factors, introduce the possibility of errors in the position of several nautical miles in both latitude and longitude.

This article presents research on how frequently seafarers utilise functions and information available on an Integrated Navigation System to perform navigation duties. Using an online questionnaire, the study collected data from 601 members of the global seafaring community. The results provide an overview of the frequency of use for each feature, together with factors affecting the use and associated usability issues. The study finds that the use of navigation equipment is situation-dependent and affected by administrative factors, experience and professional habits, characteristics of the sailing area, traffic conditions, weather conditions, ship management factors and geographical location. Additionally, information overload, particularly with overlay and alert management functions, was found to be the major issue with existing systems. The findings of this study can be applied to improve menu tree structure, display layout, and interaction methods on the interface of navigation systems, such as making frequently-used features more readily available or easier to access.

Four on-road studies were conducted in the Clifton area of Nottingham, UK, aiming to explore the relationships between driver workload and environmental engagement associated with ‘active’ and ‘passive’ navigation systems. In a between-subjects design, a total of 61 experienced drivers completed two experimental drives comprising the same three routes (with overlapping sections), staged one week apart. Drivers were provided with the navigational support of a commercially-available navigation device (‘satnav’), an informed passenger (a stranger with expert route knowledge), a collaborative passenger (an individual with whom they had a close, personal relationship) or a novel interface employing a conversational natural language ‘NAV-NLI’ (Navigation Natural Language Interface). The NAV-NLI was created by curating linguistic intercourse extracted from the earlier conditions and delivering this using a ‘Wizard-of-Oz’ technique. This term describes a research experiment in which subjects interact with a computer system that they believe to be autonomous, but which is actually being operated or partially operated by an unseen human being. The different navigational methods were notable for their varying interactivity and the preponderance of environmental landmark information within route directions. Participants experienced the same guidance on each of the two drives to explore changes in reported and observed behaviour. Results show that participants who were more active in the navigation task (collaborative passenger or NAV-NLI) demonstrated enhanced environmental engagement (landmark recognition, route-learning and survey knowledge) allowing them to reconstruct the route more accurately post-drive, compared to drivers using more passive forms of navigational support (SatNav or informed passenger). Workload measures (the Tactile Detection Task (TDT) and the National Aeronautical and Space Administration Task Load Index (NASA-TLX)) indicated no differences between conditions, although SatNav users and collaborative passenger drivers reported lower workload during their second drive. The research demonstrates clear benefits and potential for a navigation system employing two-way conversational language to deliver instructions. This could help support a long-term perspective in the development of spatial knowledge, enabling drivers to become less reliant on the technology and begin to re-establish associations between viewing an environmental feature and the related navigational manoeuvre.

E-navigation poses significant challenges for shipping. The analysis of the legal norms in the International Regulations for Preventing Collisions at Sea (COLREGS) and court decisions supports the use of information technology on the bridge for the purpose of improving navigational safety. However, the current regulatory and standardisation requirements hamper the introduction of new information streams in navigational systems and remove the incentives for investment in navigation technology. The liability arising from navigational failures will remain on the employer of the crew irrespective of how the additional navigational information is provided to the navigational systems. The shipowner's liability may depend on the way information streams are provided to the ship only within the context of the Civil Liability Convention (CLC) 1992 and other similar pollution conventions where the characterisation of the navigational system as a navigational aid or an aid to navigation may decide the issue of liability. Research on the legal background of these terms underlines the need for a clear distinction between the two terms to be made. An interpretation is proposed which ensures that the CLC liability exception operates in accordance with the underlying legal requirements.

Effective technical methods for verifying the authenticity and accuracy of Automatic Identification System (AIS) data, which are important for safe navigation and traffic regulation, are still lacking. In this study, we propose a new method to verify AIS data by using video images taken by an Unmanned Aerial Vehicle (UAV). An improved ViBe algorithm is used to extract the ship target image from the video images and the ship's spatial position is calculated using a monocular target-positioning algorithm. The positioning results are compared with the position, speed and course data of the same ship in AIS, and the authenticity and accuracy of the AIS data are verified. The results of the experiment conducted in the inland waterways of Huangpu River in Shanghai, China, show that AIS signals can be automatically checked and verified by a UAV in real time and can thus improve the supervision efficiency of maritime departments.

A conventional Differential GPS (DGPS) techniques-based velocity and acceleration method (named here as ‘DVA’) may be difficult to implement in the Antarctic as there is a sparse distribution of reference stations over Antarctica. Thus, in order to overcome the baseline limitations and to obtain highly accurate and reliable velocity and acceleration estimates for airborne gravimetry, a network-based velocity and acceleration determination approach (named here as ‘NVA’), which introduces a wide network of stations and is independent of precise clock information, is applied. Here its performance for velocity and acceleration determination is fully exploited by using Global Positioning System (GPS), GLONASS, Galileo and BeiDou observations. Additionally, a standalone receiver-based method named ‘SVA’, which requires precise clock information, is also implemented for comparison. During static tests and a flight experiment over Antarctica, it was found that the NVA method yields more robust results than the SVA and DVA methods when applied to a wide area network. Moreover, the addition of GLONASS, Galileo and BeiDou systems can increase the accuracy of velocity and acceleration estimates by 39% and 43% with NVA compared to a GPS-only solution.

The control segment in satellite navigation systems is responsible for estimating satellite orbit and clock bias which is required for a reliable Position, Navigation and Timing (PNT) user service. Initial orbit determination is a crucial step which accounts for all unknowns/anomalous parameters such as satellite orbit manoeuvres, on board and receiver clock frequency variations and environmental effects. It is vital that the estimates of the orbits and clock are insensitive to these factors. In this paper, an initial orbit determination method is presented using existing robust methodology for estimation of initial satellite position and its propagation using a variant of the Kalman Filter (KF) which allows the initial position determination process to be independent of satellite and receiver anomalies. The derivation of this KF variant is presented. Preliminary results obtained from simulated data are shown. The said method is checked for robustness by comparing results obtained for a given satellite position data set with that from the conventional Kalman Filter. The conventional KF exhibits divergence due to anomalies which are eliminated by the use of the method presented in this paper.

The quality of Automatic Identification System (AIS) data is of fundamental importance for maritime situational awareness and navigation risk assessment. To improve operational efficiency, a deep learning method based on Bi-directional Long Short-Term Memory Recurrent Neural Networks (BLSTM-RNNs) is proposed and applied in AIS trajectory data restoration. Case studies have been conducted in two distinct reaches of the Yangtze River and the capability of the proposed method has been evaluated. Comparisons have been made between the BLSTM-RNNs-based method and the linear method and classic Artificial Neural Networks. Satisfactory results have been obtained by all methods in straight waterways while the BLSTM-RNNs-based method is superior in meandering waterways. Owing to the bi-directional prediction nature of the proposed method, ship trajectory restoration is favourable for complicated geometry and multiple missing points cases. The residual error of the proposed model is computed through Euclidean distance which decreases to an order of 10 m. It is considered that the present study could provide an alternative method for improving AIS data quality, thus ensuring its completeness and reliability.

With the evolving Global Navigation Satellite System (GNSS) landscape, the International GNSS Service (IGS) has started the Multi-GNSS Experiment (MGEX) to produce precise products for new generation systems. Various analysis centres are working on the estimation of precise orbits, clocks and bias for Galileo, Beidou and Quasi-Zenith Satellite System (QZSS) satellites. However, at the moment these products can only be used for post-processing applications. Indeed, the IGS Real-Time service only broadcasts Global Positioning System (GPS) and Globalnaya Navigatsionnaya Sputnikovaya Sistema (GLONASS) corrections. In this research, a simulator of multi-GNSS observations and real-time precise products has been developed to analyse the performance of GPS-only, Galileo-only and GPS plus Galileo Precise Point Positioning (PPP). The error models in the simulated orbits and clocks were based on the difference between the GPS Real-Time and the Final products. Multiple scenarios were analysed, considering different signals combined in the Ionosphere Free linear combination. Results in a simulated open area environment show better performance of the Galileo-only case over the GPS-only case. Indeed, up 33% and 29% of improvement, respectively, in the accuracy level and convergence time can be observed when using the full Galileo constellation compared to GPS. The dual constellation case provides good improvements, in particular in the convergence time (47% faster than GPS). This paper will also consider the impact of different linear combinations of the Galileo signals, and the potential of the E5 Alternative Binary Offset Carrier (AltBOC) signal. Even though it is significantly more precise than E5a, the PPP performance obtained with the Galileo E1-E5a combination is either better or similar to the one with Galileo E1-E5. The reason for this inconsistency was found in the use of the ionosphere free combination with E1. Finally, alternative methods of ionosphere error mitigation are considered in order to ensure the best possible positioning performance from the Galileo E5 signal in multi-frequency PPP.

The maritime transport industry is increasingly reliant on computing and communication technologies, and the need for cyber risk management of critical systems and assets on vessels is becoming critically important. In this paper, a comprehensive cyber risk assessment of a ship is presented. An experimental process consisting of assessment preparation activities, assessment conduct and results communication has been developed. The assessment conduct relies on a survey developed and performed by interviewing a ship's crew. Computational vulnerability scanning of the ship's Electronic Chart Display and Information System (ECDIS) is introduced as a specific part of this cyber security assessment. The assessment process presented has been experimentally tested by evaluating the cyber security level of Kobe University's training ship Fukae-maru. For computational vulnerability scanning, an industry-leading software tool has been used, and a quantitative cyber risk analysis has been conducted to evaluate cyber risks on the ship.

In this paper, a novel Voronoi-Visibility (VV) path planning algorithm, which integrates the merits of a Voronoi diagram and a Visibility graph, is proposed for solving the Unmanned Surface Vehicle (USV) path planning problem. The VM (Voronoi shortest path refined by Minimising the number of waypoints) algorithm was applied for performance comparison. The VV and VM algorithms were compared in ten Singapore Strait missions and five Croatian missions. To test the computational time, a high-resolution, large spatial dataset was used. It was demonstrated that the proposed algorithm not only improved the quality of the Voronoi shortest path but also maintained the computational efficiency of the Voronoi diagram in dealing with different geographical scenarios, while also keeping the USV at a configurable clearance distance c from coastlines. Quantitative results were generated by comparing the Voronoi, VM and VV algorithms in 2,000 randomly generated missions using the Singapore dataset.

This paper proposes a bi-level model from the perspective of game theory to describe the effect of the rise of Arctic shipping routes on traditional routes and their response. The upper-level model demonstrates the competition between shipping companies that maximise their own profits via speed adjustment, which can be presented as a generalised Nash equilibrium problem and is solved by the generalised reduced-gradient method. The lower-level model illustrates the response of customers who reassign their demands with an elastic total demand, which is presented as a logit-type multi-path assignment problem and is solved by the iterative balancing method. A case study is used to examine the rationality of the proposed model and algorithm.

This paper introduces a scheme for waypoint-based path-following control for an Unmanned Robot Sailboat (URS) in the presence of actuator gain uncertainty and unknown environment disturbances. The proposed scheme has two components: intelligent guidance and an adaptive neural controller. Considering upwind and downwind navigation, an improved version of the integral Line-Of-Sight (LOS) guidance principle is developed to generate the appropriate heading reference for a URS. Associated with the integral LOS guidance law, a robust adaptive algorithm is proposed for a URS using Radial Basic Function Neural Networks (RBF-NNs) and a robust neural damping technique. In order to achieve a robust neural damping technique, one single adaptive parameter must be updated online to stabilise the effect of the gain uncertainty and the external disturbance. To ensure Semi-Global Uniform Ultimate Bounded (SGUUB) stability, the Lyapunov theory has been employed. Two simulated experiments have been conducted to illustrate that the control effects can achieve a satisfactory performance.

This paper presents a taxonomy of human wayfinding behaviours. For the purposes of this paper, wayfinding is purposeful navigating in everyday life, in man-made environments, traversing an environment or aiming for an objective with which the individual is unfamiliar. The taxonomy is developed through a review of wayfinding literature from research and practice, user studies conducted specifically for this research and a process of thinking by designing. This taxonomy can also be applied to navigating in documents printed on paper and on-screen, but this paper concentrates on behaviours in environmental space. This taxonomy creates twelve categories of behaviour differentiated by the characteristics of the information that they use. The categories of behaviour are also separated into three groups: social, semantic and spatial. This paper briefly describes and gives examples of each of the categories of behaviour. This is followed by insights into the behaviours from user studies conducted by the author. (This paper borrows its title from Cohen, 2015).

Aircraft accidents are extremely rare in the aviation sector. However, their consequences can be very dramatic. One of the most important problems is runway excursions, when an aircraft exceeds the end (overrun) or the side (veer-off) of the runway. After performing exploratory analysis and hypothesis tests, a Bayesian-network-based approach was considered to provide information from risk scenarios involving landing procedures. The method was applied to a real database containing key variables related to landing operations on three runways. The objective was to analyse the effects over runway overrun excursions of failing to fulfil expert recommendations upon landing. For this purpose, the most influential variables were analysed statistically, and several scenarios were built, leading to a runway ranking based on the risk assessed.

In this paper, adaptive noise estimation is used along with a previously proposed Huber-based robust algorithm for cooperative localisation of Autonomous Underwater Vehicles (AUVs). The Huber-based robust cooperative localisation algorithm named Huber-based Iterative Divided Difference Filtering (HIDDF), proposed in our previous work, effectively achieved a robust result against abnormal measurement noise, enhanced the stability of the filtering algorithm and improved the performance of cooperative localisation state estimation. However, its performance could be significantly further improved if it could estimate the system's noise statistical properties online in real time and then adaptively adjust the filtering gain matrix accordingly. In this paper, a novel adaptive noise estimation algorithm is proposed based on a covariance matching method. The proposed algorithm is suitable for adaptively estimating Gaussian and non-Gaussian measurement as well as process noise. The efficacy of the proposed algorithm has been verified through simulation results. In order to further verify the effectiveness of the proposed algorithm in practical systems, lake tests were conducted. Then, based on offline test data, the performance of the cooperative positioning algorithm under dual-pilot and single-pilot schemes was simulated. The advantages and feasibility of the algorithm are analysed and compared through performance comparison. Cooperative localisation accuracy of the previously proposed Huber-based robust algorithm has been enhanced significantly when used with the proposed adaptive noise estimation algorithm.

Clustering methods that use a similarity measurement for evaluating vessel trajectories are important for mining spatial distribution information in water transportation. To better measure the similarity of vessel trajectories, a novel similarity measure is proposed based on the dynamic time warping distance, which considers the course change of track points and the meaning at the route level. Parallel experiments were conducted based on a month of Automatic Identification System (AIS) data collected from the Zhoushan Islands area, China. After evaluation of the accuracy and the cluster degree, the novel measure demonstrated its capabilities for distinguishing different vessel trajectories and detecting similar vessel trajectories with high accuracy and has a better performance compared to some existing methods.

Real-time Precise Point Positioning (PPP) has been evolved as a cost-effective technique for highly precise maritime positioning. For a long period, maritime PPP technology has mainly relied on the Global Positioning System (GPS). With the revitalisation of GLONASS and the emerging BeiDou navigation satellite system (BDS), it is now feasible to investigate real-time navigation performance of multi-constellation maritime PPP with GPS, BDS and GLONASS. In this contribution, we focus on maritime PPP performance using real world maritime kinematic data and real-time satellite correction products. The results show that BDS has lower position accuracy and slower convergence time than GPS. The BDS and GPS combination has the best performance among the dual-constellation configurations. Meanwhile, the integration of BDS, GLONASS and GPS significantly improves the position accuracy and the convergence time. Some outliers in the single constellation configuration can be mitigated when multi-constellation observations are utilised.

Maritime accident statistics reveal that ship collisions are among the most frequent and severe accidents. The same statistics indicate that most of them are caused by human error, mainly due to breaches of the International Regulations for Preventing Collisions at Sea (COLREGs) and to the lack of communication between ships. There are also special situations where there is some ambiguity in the application of the COLREGs. In such occasions, and if there is no communication between the ships involved, compliance with the Rules may still end up in a collision. This article brings a new approach to Collision Avoidance Systems (CAS) and presents the earliest stages in the development of safety functions for the reduction of ship-to-ship collision risk on the high seas. These functions will help the concerned ships achieve coordinated compliance with the COLREGs. Functional safety standards are applied and, in their implementation, real, accessible electronic programmable systems (hardware and software) will be used.

In Air Traffic Control (ATC), aircraft altitude data is used to keep an aircraft within a specified minimum distance vertically from other aircraft, terrain and obstacles to reduce the risk of collision. Two types of altitude data are downlinked by radar; actual flight level (Mode C) and selected altitude (Mode S). Flight level indicates pressure altitude, also known as barometric altitude used by controllers for aircraft vertical separation. ‘Selected altitude’ presents intent only, and hence cannot be used for separation purposes. The emergence of Global Navigation Satellite Systems (GNSSs) has enabled geometric altitude on board and to the controllers via the Automatic Dependent Surveillance-Broadcast (ADS-B) system. In addition, ADS-B provides quality indicator parameters for both geometric and barometric altitudes. Availability of this information will enhance Air Traffic Management (ATM) safety. For example, incidents due to Altimetry System Error (ASE) may potentially be avoided with this information. This work investigates the use and availability of these parameters and studies the characteristics of geometric and barometric data and other data that complement the use of these altitude data in the ADS-B messages. Findings show that only 8·7% of the altitude deviation is < 245 feet (which is a requirement of the International Civil Aviation Organization (ICAO) to operate in Reduced Vertical Separation Minimum (RVSM) airspace). This work provides an alert/guidance for future ground or airborne applications that may utilise geometric/barometric altitude data from ADS-B, to include safety barriers that can be found or analysed from the ADS-B messages itself to ensure ATM safety.