Digital Cognitive Companions for Marine Vessels : On the Path Towards Autonomous Ships

As for the automotive industry, industry and academia are making extensive efforts to create autonomous ships. The solutions for this are very technology-intense. Many building blocks, often relying on AI technology, need to work together to create a complete system that is safe and reliable to use. Even when the ships are fully unmanned, humans are still foreseen to guide the ships when unknown situations arise. This will be done through teleoperation systems.In this thesis, methods are presented to enhance the capability of two building blocks that are important for autonomous ships; a positioning system, and a system for teleoperation.The positioning system has been constructed to not rely on the Global Positioning System (GPS), as this system can be jammed or spoofed. Instead, it uses Bayesian calculations to compare the bottom depth and magnetic field measurements with known sea charts and magnetic field maps, in order to estimate the position. State-of-the-art techniques for this method typically use high-resolution maps. The problem is that there are hardly any high-resolution terrain maps available in the world. Hence we present a method using standard sea-charts. We compensate for the lower accuracy by using other domains, such as magnetic field intensity and bearings to landmarks. Using data from a field trial, we showed that the fusion method using multiple domains was more robust than using only one domain. In the second building block, we first investigated how 3D and VR approaches could support the remote operation of unmanned ships with a data connection with low throughput, by comparing respective graphical user interfaces (GUI) with a Baseline GUI following the currently applied interfaces in such contexts. Our findings show that both the 3D and VR approaches outperform the traditional approach significantly. We found the 3D GUI and VR GUI users to be better at reacting to potentially dangerous situations than the Baseline GUI users, and they could keep track of the surroundings more accurately. Building from this, we conducted a teleoperation user study using real-world data from a field-trial in the archipelago, where the users should assist the positioning system with bearings to landmarks. The users experienced the tool to give a good overview, and despite the connection with the low throughput, they managed through the GUI to significantly improve the positioning accuracy

Robust Terrain-Aided Navigation through Sensor Fusion

To make autonomous, affordable ships feasible in the real world, they must be capable of safely navigating without fully relying on GPS, high-resolution 3D maps, or high-performance navigation sensors. We suggest a method for estimating the position using affordable navigation sensors (compass and speed log or inertial navigation sensor), sensors used for perception of the environment (cameras, echo sounder, magnetometer), and publicly available maps (sea charts and magnetic intensity anomalies maps). A real-world field trial has shown that the proposed fusion mechanism provides accurate and robust navigation, applicable for affordable autonomous ships

Remote Operation of Unmanned Surface Vessel through Virtual Reality

An unmanned ship can be designed without considering humancomfort, and can thus be constructed lighter, smaller and less expensive.It can carry out missions in rough terrain or be in areaswhere it would be dangerous for a human to operate. By not havingto support a crew, lengthy missions can be accepted, enabling, e.g.reconnaissance missions, or reducing emissions by lowering thespeed.Breakthroughs with autonomous systems enable more advancedunmanned surface vessels (USVs), but to be able to handle complexmissions in a dynamic environment, a human operator is stillassumed an effective decision maker. Thus, we propose a methodfor remote operation of a USV, where the operator uses VirtualReality (VR) to comprehend the surrounding environment. Greatimportance has been given to the ability to perform safe navigation,by designing a Graphical User Interface (GUI) that guides the operatorthrough the navigation process, by presenting the importantinformation at the right place in the right orientation

Long-term exposure to transportation noise and risk of incident stroke:A pooled study of nine scandinavian cohorts

BACKGROUND: Transportation noise is increasingly acknowledged as a cardiovascular risk factor, but the evidence base for an association with stroke is sparse. OBJECTIVE: We aimed to investigate the association between transportation noise and stroke incidence in a large Scandinavian population. METHODS: We harmonized and pooled data from nine Scandinavian cohorts (seven Swedish, two Danish), totaling 135,951 participants. We identified residential address history and estimated road, railway, and aircraft noise for all addresses. Information on stroke incidence was acquired through link-age to national patient and mortality registries. We analyzed data using Cox proportional hazards models, including socioeconomic and lifestyle con-founders, and air pollution. RESULTS: During follow-up (median = 19:5 y), 11,056 stroke cases were identified. Road traffic noise (Lden ) was associated with risk of stroke, with a hazard ratio (HR) of 1.06 [95% confidence interval (CI): 1.03, 1.08] per 10-dB higher 5-y mean time-weighted exposure in analyses adjusted for indi-vidual-and area-level socioeconomic covariates. The association was approximately linear and persisted after adjustment for air pollution [particulate matter (PM) with an aerodynamic diameter of ≤2:5 lm (PM2:5 ) and NO2 ]. Stroke was associated with moderate levels of 5-y aircraft noise exposure (40–50 vs. ≤40 dB) (HR = 1:12; 95% CI: 0.99, 1.27), but not with higher exposure (≥50 dB, HR = 0:94; 95% CI: 0.79, 1.11). Railway noise was not associated with stroke. DISCUSSION: In this pooled study, road traffic noise was associated with a higher risk of stroke. This finding supports road traffic noise as an important cardiovascular risk factor that should be included when estimating the burden of disease due to traffic noise. https://doi.org/10.1289/EHP8949

Smart Technologies for Unmanned Surface Vessels : On the Path Towards Full Automation

As for the automotive industry, large efforts are being made by industry andacademia to create autonomous ships. Te solutions for this is very technologyintense, as many building blocks, often relying on AI technology, need to worktogether to create a complete system that is safe and reliable to use. Even whenthe ships are fully unmanned, humans are still foreseen to guide the ships whenunknown situations arise. Tis will be done through teleoperation systems.In this thesis, methods are presented to enhance the capability of two building blocks that are important for autonomous ships; a positioning system, and asystem for remote supervision.Te positioning system has been constructed to not rely on GPS (Global Positioning System), as this system can be jammed or be spoofed. Instead, it usesBayesian calculations to compare the bottom depth and magnetic field measurements with known sea charts and magnetic field maps, in order to estimate theposition. State-of-the-art techniques for this method normally use low-accuracynavigation sensors and high-resolution maps. Te problem is that there are hardlyany high-resolution maps available in the world, hence we present a method of theopposite; namely using high-accuracy navigation sensors and low-resolution maps(normal sea charts). Te results from a 20h test-run gave a mean position error of10.2m, which would in most cases be accurate enough for navigation purpose.In the second building block, we investigated, how 3D and VR approachescould support the remote operation of unmanned ships with a low bandwidthconnection, by comparing respective GUIs with a Baseline GUI following the currently applied interfaces in such contexts. Our findings show, that both the 3Dand VR approaches outperform the traditional approach significantly. We foundthe 3D GUI and VR GUI users to be better at reacting to potentially dangeroussituations compared to the Baseline GUI users, and they could keep track of thesurroundings more accurately

Underwater Terrain Navigation Using Standard Sea Charts and Magnetic Field Maps

Many ships today rely on Global Navigation Satellite Systems (GNSS), for their navigation, where GPS (Global Positioning System) is the most well-known. Unfortunately, the GNSS systems make the ships dependent on external systems, which can be malfunctioning, be jammed or be spoofed. There are today some proposed techniques where, e.g., bottom depth measurements are compared with known maps using Bayesian calculations, which results in a position estimation. Both maps and navigational sensor equipment are used in these techniques, most often relying on high-resolution maps, with the accuracy of the navigational sensors being less important. Instead of relying on high-resolution maps and low accuracy navigation sensors, this paper presents an implementation of the opposite, namely using low-resolution maps, but compensating this by using high accuracy navigational sensors and fusing data from both bottom depth measurements and magnetic field measurements. The results from the simulated tests, described in this paper, show that the position error is below 25m throughout the whole test, and that the mean of the error is below 13m, which in most cases would be accurate enough to use for navigation

Long-Term Accuracy in Sea Navigation without using GNSS Systems

Many ships today rely on Global Navigation Satellite System (GNSS), for their navigation, where GPS (Global Positioning System) is the most well known. Unfortunately, the GNSS systems make the ships dependent on external systems, which can be malfunctioning, be jammed or be spoofed. There are today some proposed techniques where, e.g. bottom depth measurements are compared with known maps using Bayesian calculations, which results in a position estimation. Both maps and navigational sensor equipment are used in these techniques , most often relying on high accuracy maps, with the accuracy of the navigational sensors being less important. Instead of relying on high accuracy maps and low accuracy navigation sensors, this paper presents an idea of the opposite, namely using low accuracy maps, but compensating this by using high accuracy navigational sensors and fusing data from both bottom depth measurements and magneticfield measurements

Remote Supervision of an Unmanned Surface Vessel - a Comparison of Interfaces

We compared three different Graphical User Interfaces (GUI) that we have designed and implemented to enable human supervision of an unmanned ship. Our findings indicate that a 3D GUI presented either on a screen or in a Virtual Reality (VR) setting provides several objective and subjective benefits compared to a Baseline GUI representing traditional tools

VR Teleoperation to support a GPS-free Positioning System in a Marine Environment

Small autonomous surface vehicles (ASV) will need both teleoperation support and redundant positioning technology to comply with expected future regulations. When at sea, they are limited by a satellite communication link with low throughput. We have designed and implemented a graphical user interface (GUI) for teleoperation using a communication link with low throughput, and one positioning system, independent of the Global Positioning System (GPS), supported by the teleoperation tool. We conducted a user study (N=16), using real-world data from a field trial, to validate our approach, and to compare two variants of the graphical user interface (GUI). The users experienced that the tool gives a good overview, and despite the connection with the low throughput, they managed through the GUI to significantly improve the positioning accuracy