Automodal - Efficient automation of container terminals

The aim of the Automodal project was to drive forward the automation of container terminals in inland ports. These terminals are open work areas in which employees move around freely. A key challenge was therefore to safely monitor the work areas in order to enable the seamless integration of automated processes.

Motivation

Combined transport depends on reliable processes in bi- or trimodal transhipment terminals, as this is where the transition between different modes of transport such as truck, rail and barge takes place. Manual processes in these terminals often lead to delays and inefficient use of resources along the entire transport chain. These inefficiencies need to be reduced in order to strengthen low-carbon intermodal transport, create capacity and shift more transport from road to rail and inland waterway.

Project objective

The project examined the end-to-end automation of the handling terminal. A key component was the automation of a gantry crane, which was converted into a prototype in order to be able to carry out independent automated processes. The open source approach in the development of the control software enabled a high level of technology transfer to various application scenarios. This should increase the overall reliability and efficiency of combined transport.

Solution approach

The work focused on the prototypical implementation of crane automation in a reference terminal. The following measures were implemented:

• Additional sensors on the gantry crane for safe and reliable automation
• Evaluation and testing of suitable sensor solutions on a test model
• Development of control software for automated crane processes
• Harmonization of interfaces for smooth integration
• Integration of hardware components for operations

The necessary components were then installed on the gantry crane, including the monitoring environment. Automated operation was tested as a prototype for around six months. The accompanying evaluation looked at system reliability and performance in various application scenarios, among other things. This was supplemented by a roadmap for the end-to-end automation of the handling terminal and an analysis of the potential of the individual terminal processes.

Services in the project

The team undertook the following tasks as part of the project:

• Selection and integration of suitable sensors to detect the work areas
• Development of machine learning models for recognizing people and objects
• Analysis and optimization of sensor data processing for reliable automation
• Prototypical automation of a gantry crane for autonomous work processes

Practical solutions for the future

The intelligent linking of sensor data and AI has enabled new standards to be set for the secure automation of inland port terminals. The findings from Automodal can be transferred to other areas of application in logistics and the port industry in the future.