Traffic Engineering - Research VisionsCopyright: © ISAC
In Traffic Engineering, we focus on digitalization of traffic and traffic infrastructure, road asset management, and traffic control. Our future research focuses on fundamental further development and adaptation of traffic infrastructure, incorporating the latest technologies such as digitalization, the use of AI approaches, and automated or autonomous driving.
In traffic digitalization, we will accompany the increasingly present paradigm shift towards microscopic data collection. Therefore, the focus will be on the individual data of each vehicle, independent of the vehicle itself and captured using sensors as part of the infrastructure.
With regard to traffic modeling, we intend to create the basis for analytical modeling, which has been lacking so far, in order to enable simulation-based estimation of accident risk in the future. To realize this, it is necessary to extend existing traffic flow models to include inhomogeneous, dynamic traffic conditions. In this context, the development of new data sources - also thanks to the growing opportunities arising from advances in traffic digitization - is of great benefit.
In Digital Road Asset Management, we will enable a lifecycle view of infrastructure. For this purpose, data-based model will be simulated and optimized as a linkage of all data assets. The model takes into account, for example, material and structure data, paving parameters, terrain models and cross-sections, traffic loads, and environmental data.
Ultimately, the assistance systems in the field of automated driving will also benefit from the progress made in all of the above-mentioned research fields.
FeGiS+ - Early detection of dangerous areas in traffic
InTraSens - Intelligent Traffic Sensors
DROVA - Development of a drone-based traffic analysis to optimize the use of existing infrastructure by federal highways with evaluation of the suitability for online traffic monitoring
MeBeSafe - Measures for Behaving Safely in Traffic