2. Equipment Test Inland Vessel

2.2 Actuator

2.2 Actuator

The Niedersachsen 22 has the usual propulsion and maneuvering elements used in inland navigation; the main engine, the rudder and the bow thruster. For the Autobin project, these will be addressed via modern interfaces and bus systems such as controller area network (CAN bus) or programmable logic controller (PLC) and connected to a 10 Gigabit Ethernet network using suitable converters. Even before the artificial intelligence developed in WP 1.2 takes control of the ship, the actuator data is recorded, so that the automatic and human control can be compared later and situations can be identified in which the artificial intelligence still needs to be improved or retrained. 

A switch will be installed on the bridge to allow the ship’s commanders to switch between automatic and manual control. If automatic steering is active, the artificial intelligence is to steer the ship based on the sensor data from AP 2.1. To do this, it provides the setpoints for propeller rotation rate and direction, rudder angle, and bow thruster rotation rate and direction. The artificial intelligence also operates other control functions, such as raising and lowering the bridge, setting the blue board and controlling the searchlights. For scheduled switching to manual operation, the setpoints are also transferred to the bridge’s control panels to enable a smooth transition. In emergency or safety-critical situations, the ship’s commanders can activate an additionally installed emergency switch to immediately regain control of the ship. In this case, the automaton is galvanically isolated from the system to prevent any last control commands from being executed or signals from blocking the bus systems. 

Work packages

The simulation environment as a virtual image of the real world is the central development environment for all control and monitoring algorithms. A digital twin of the test vessel is implemented in the simulation environment.


The development of the automated control of the inland vessel will initially take place in a simulator. In the first work package, the existing simulator will therefore be extended so that sensor readings can be generated virtually. The artificial intelligence (AI) developed in parallel in a modular fashion for ship control and for implementing the driving behavior functions will then be integrated in a simulation model in such a way that a later parallel porting to a real inland waterway vessel will be possible. Furthermore, the behavior of other road users (vessels in the vicinity of the automated barge) will be modeled and integrated into the simulation environment. The development of the AI for the implementation of the driving behavior functions for different tasks is initially carried out in parallel and then tested in the simulator. Fundamental questions about the choice and structure of the module are efficiently addressed in this way.

1.1 Simulator

The virtual home of the digital twin

1.2 AI / Behavior Control

The central algorithms: ship guidance and driving behavior functions

1.3 Behavior of other Road Users

Prerequisite for accident-free traffic: understanding the traffic situation

To test the test vessel, test scenarios are first defined. Subsequently, the automated vessel control is integrated and iteratively adapted. Test runs are absolutely necessary for this. 

2.1 Sensors

The senses of AI

2.2 Actuator

Artificial intelligence takes the control

2.3 Human-Machine Interface

Development of the human-machine interface

The realization of the automation of the test vessel requires a fine conception and coordination of the algorithms. Furthermore, the automation functions must be tested in advance in the simulation environment. This is followed by validation on the real system.

3.1 Fine-Tuning and Tuning of the Algorithms

Fine conception and tuning of the algorithms for the automation of the inland vessel.

3.2 Implementation

Technical implementation of the automation functions

3.3 Integration of Autom. Vessel Guidance in the Simulation Environment

Integration of automated ship guidance in the simulation environment

3.4 Validation ML/KI and Vessel Control

Validation of the AI

Sensors and actuators will be used to equip the test vessel. A human-machine interface is also being developed.

4.1 Definition of Test Scenarios

Testing of the developments

4.2 Integration and Adaptation of Control in Test Vessel

Integration and Adaptation of Control in Test Vessel

4.3 Test Drives and Demonstration

From theory to practice

The simulation environment as a virtual image of the real world is the central development environment for all control and monitoring algorithms. A digital twin of the test vessel is implemented in the simulation environment.

5.1 Profitability Analysis

Economic efficiency analysis

5.2 Rating

Final evaluation of automation