Multimodal Network Architecture for Shared Situational Awareness amongst Vessels.

To shift the paradigm towards Industry 4.0, maritime domain aims to utilize shared situational awareness (SSA) amongst vessels. SSA entails sharing various heterogeneous information, depending on the context and use case at hand, and no single wireless technology is equally suitable for all uses. Moreover, different vessels are equipped with different hardware and have different communication capabilities, as well as communication needs. To enable SSA regardless of the vessel's communication capabilities and context, we propose a multimodal network architecture that utilizes all of the network interfaces on a vessel, including multiple IEEE 802.11 interfaces, and automatically bootstraps the communication transparently to the applications, making the entire communication system environment-aware, service-driven, and technology-agnostic. This paper presents the design, implementation, and evaluation of the proposed network architecture which introduces virtually no additional delays as compared to the Linux communication stack, automates communication bootstrapping, and uses a novel application-network integration concept that enables application-aware networks, as well as network-aware applications. The evaluation was conducted for several IEEE 802.11 flavors. Although inspired by SSA for vessels, the proposed architecture incorporates several concepts applicable in other domains. It is modular enough to support existing, as well as emerging communication technologies.

Dynamic Semantic World Models and Increased Situational Awareness for Highly Automated Inland Waterway Transport.

Automated surface vessels must integrate many tasks and motions at the same time. Moreover, vessels as well as monitoring and control services need to react to physical disturbances, to dynamically allocate software resources available within a particular environment, and to communicate with various other actors in particular navigation and traffic situations. In this work, the responsibility for the situational awareness is given to a mediator that decides how: 1) to assess the impact of the actual physical environment on the quality and performance of the ongoing task executions; 2) to make sure these tasks satisfy the system requirements; and 3) to be robust against disturbances. This paper proposes a set of semantic world models within the context of inland waterway transport, and discusses policies and methodologies to compose, use, and connect these models. Model-conform entities and relations are composed dynamically, that is, corresponding to the opportunities and challenges offered by the actual situation. The semantic world models discussed in this work are divided into two main categories: 1) the semantic description of a vessel's own properties and relationships, called the internal world model, or body model, and 2) the semantic description of its local environment, called the external world model, or map. A range of experiments illustrate the potential of using such models to decide the reactions of the application at runtime. Furthermore, three dynamic, context-dependent, ship domains are integrated in the map as two-dimensional geometric entities around a moving vessel to increase the situational awareness of automated vessels. Their geometric representations depend on the associated relations; for example, with: 1) the motion of the vessel, 2) the actual, desired, or hypothesised tasks, 3) perception sensor information, and 4) other geometries, e.g., features from the Inland Electronic Navigational Charts. The ability to unambiguously understand the environmental context, as well as the motion or position of surrounding entities, allows for resource-efficient and straightforward control decisions. The semantic world models facilitate knowledge sharing between actors, and significantly enhance explainability of the actors' behaviour and control decisions.