Highly accurate digital traffic recording as a basis for future mobility research: Methods and concepts of the research project HDV-Mess
This project addresses a crucial gap for researchers and developers in mobility and automated driving by providing a basis for validation, though it is incremental as it builds on existing traffic recording methods.
The research project HDV-Mess tackles the problem of missing high-accuracy traffic data for connected and automated driving by developing a mobile modular system for recording traffic events at various locations, with the result being a concept for data acquisition, processing, and validation to support sensor technology and driving function development.
The research project HDV-Mess aims at a currently missing, but very crucial component for addressing important challenges in the field of connected and automated driving on public roads. The goal is to record traffic events at various relevant locations with high accuracy and to collect real traffic data as a basis for the development and validation of current and future sensor technologies as well as automated driving functions. For this purpose, it is necessary to develop a concept for a mobile modular system of measuring stations for highly accurate traffic data acquisition, which enables a temporary installation of a sensor and communication infrastructure at different locations. Within this paper, we first discuss the project goals before we present our traffic detection concept using mobile modular intelligent transport systems stations (ITS-Ss). We then explain the approaches for data processing of sensor raw data to refined trajectories, data communication, and data validation.