According to the European Commission, passenger transport is projected to increase 42% by 2050, and freight transport up to 60%. Needless to say, this puts an enormous burden on transport networks and our environment. Compared to other modes of transport – which often face congestion and capacity problems – inland waterway transport is characterised by reliability, energy efficiency and a capacity for increased use. More than 37,000 km of waterways connect hundreds of cities and industrial regions in Europe. In the EU, 13 countries share an interconnected waterway network, highlighting the potential for increasing the modal share of inland waterway transport. This will not happen unless we can make inland waterways economically competitive. However, with crew costs accounting for 60% of the total cost, autonomous inland vessels represent an exciting disruptive technology.
AUTOBarge seized this opportunity by unlocking the innovation potential of Europe’s inland waterways through advanced research and high-level training. Europe’s rivers and canals constitute a valuable transport infrastructure that has long been underutilised. With recent developments in automation and digital technologies, these waterways can be exploited more intensively without the environmental impact associated with constructing new roads or airport infrastructure. The 15 early-stage researchers trained within AUTOBarge have taken important steps towards enabling this transformation.
AUTOBarge offered the first-ever training programme for the application of unmanned or autonomous vessels for smart inland shipping and their role in the overall multi-modal transport activity in Europe and had three scientific/technical objectives:
Objective 1 (WP1): Maximize the situational awareness (Sense and Understand) of an unmanned or autonomous inland vessel by covering the state and manoeuvrability of the vessel itself, the location and motion of other vessels, other relevant static and moving objects in the vicinity, features like buoys or traffic signs, as well as the wireless communication of information between the different waterway actors.
Objective 2 (WP2): Exploit the above situational awareness (Decide and Act) obtained for a safe, robust and energy-efficient path planning and motion control of the autonomous inland vessel with a focus on model predictive control, control methods supported by real-time machine learning, energy-efficiency, and fault identification and isolation schemes such that those do not affect the operation of autonomous vessels in a negative way.
Objective 3 (WP3): In-depth analysis of the socio-technical, economic and legal aspects that are needed to make autonomous inland shipping a success in the near future, including safety assurance, collaborative decision making for maximized performance, logistics, economic benefits, and the required changes to the regulatory framework.
