The on-board hydrogen storage of mobile applications is a key area of global industrial transformation to hydrogen technology. The research work provides an overview about the principle of hydrogen fuel cell vehicles, with a focus on the widespread on-board hydrogen storage technologies. In this work, type IV composite pressure vessels in particular are reviewed. The key challenges of polymeric liners are deeply investigated, and liner collapse was identified as a critical failure of type IV vessels. Different factors of liner collapse were categorized and relevant material properties - such as permeability, physical characteristics, and surface properties - were explained in more detail to lay the foundation for further research on high barrier, durable polymeric liner materials.

The Automated Driving Data Analyzer (ADDA) is a modular application written in Python for the synchronized acquisition and analysis of physiological, vehicle, and interface data. It provides a managed data acquisition process and one-click data analysis. It also provides raw data storage and systematic archiving of data sets. ADDA integrates real-time data from a BeamNG vehicle simulation, Pupil Labs eye-tracking system, hand-tracking, and cardiac data. This integration allows the simultaneous recording and analysis of multiple data streams, which can be visualized and controlled through a graphical user interface (GUI) built with Tkinter. The application is designed to help researchers and engineers analyze driving behavior under different conditions, enabling a deeper understanding of the interactions between the driver and automated driving functions.