2. Equipment Test Inland Vessel

2.1 Sensors

2.1 Sensors

In the “Sensor Technology” work package, the Niedersachsen 22 of the HGK Logistic Group will be equipped with additional sensor technology. This will record the ship’s surroundings during the voyage. This allows obstacles and hazards to be identified. The sensor concept fulfills the requirements defined in WP 1.2. Within the concept, the direction of travel is detected by a lidar, a monocamera and a stereo camera. The rear area is detected by a lidar and a monocamera. The side areas are captured by a total of four mono cameras. The position and orientation of the barge are determined by a combined sensor module equipped with a dGPS module and inertial sensors. The sensor concept is rounded off by the ship’s existing internal radar.

The work package also includes the commissioning and integration of the sensor system on board the inland vessel. On the one hand, mounting options will be developed and implemented. On the other hand, the commissioning includes the implementation of a routine, which makes it possible to selectively record sensor data, pre-process it and save it in a database. 

The sensor data obtained in this way can then be used to train AI-based methods. Thus, the recorded real data is made usable in the simulator in this way.

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05.10.2021

The GMS Niedersachsen 22 is a typical dry cargo vessel with 100 m length and 10.5 m width. It is being operated by HGK Shipping GmbH and is mainly in service in the western german canal network between the Rhine and the Elbe. In the current video "AutoBin Niedersachsen 22" you will be taken on board of the test vessel.

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