Integrity, the Key Enabler for Autonomous Vessels and Other Vehicles

Abstract

Autonomous transport is the future of the transport industry and will revolutionise the landscape of vehicle design and operations. The operation of remote and autonomous vehicles will need to be at least as safe as the existing ones. They have potential to reduce human-based errors, to improve the efficiency of some operations, and to be the enabler of new applications. Additionally, this new transport applications may modify some existing risks as well as create new types of risks. In this frame, safety and integrity becomes more and more important. Integrity is a key enabler for the Autonomous Vessels and also for other autonomous transport applications (e.g. autonomous cars, Drones and UAVs). GMV has been actively working for more than a decade on safety technologies (and integrity in particular) at user level for the maritime, road, aviation and rail domains. As part of the integrity concept, the IBPL family of algorithms (IBPL and KIPL) was developed by GMV to provide Protection Levels for different applications, especially those that take place in harsh environments. These algorithms provide an integrity layer that could be important for the safety of those applications. Taking into account the stringent requirements that the autonomous transport might have in terms of accuracy, availability and continuity, these algorithms can be also complemented by different GNSS augmentation systems (SBAS, PPP corrections services, etc) in order to fulfil the requirements. In particular, the research done in this paper is to assess which are the algorithm performances with multiple GNSS constellations (GPS, Galileo and GLONASS) The objective of this paper is to provide a detailed view of the IBPL family of algorithms to be used in autonomous transport, especially focused in autonomous vessels, and how they could fulfil the stringent requirements for autonomous transport applications.