Loading
Real-world data is the foundation of the SCM enabling implementation, parametrisation and validation of realistic driver behaviour.
Real-world data is necessary for the implementation of new features in the Stochastic Cognitive Model, the parametrisation of the SCM and the validation of traffic and driver behaviour in the simulation. A wide range of real-world data sources is drawn on to meet this need.
Four distinct real-world data sources are used to implement, parametrise and validate the Stochastic Cognitive Model.
Field Operational Tests are conducted to collect detailed real-world traffic data. Participants are provided with test vehicles for a limited period under defined study conditions, typically with compensation. Data handling follows stringent data protection standards and may include multimodal recordings such as vehicle signals, environmental perception and in-cabin observations.
The collected data enables analysis of driver behavior, including gaze patterns, reaction times and control actions across diverse real-world scenarios. These insights support both the development of new functions and the validation of existing models.
Drone technology captures high-resolution images and video, providing exceptional detail in traffic data collection — well beyond conventional in-vehicle methods.
Drone data is used to analyse microscopic and macroscopic traffic patterns, especially to validate the Stochastic Cognitive Model across diverse traffic scenarios.
Simulator studies provide a safe, controlled environment for analysing driver behaviour. Reactions to stimuli such as sudden braking and lane changes reveal how drivers respond in critical traffic scenarios.
Simulator data is used to determine precise driver behaviour parameters for implementation in the Stochastic Cognitive Model.
In-depth accident databases such as GIDAS (German In-Depth Accident Study) provide revealing information about the occurrence and outcome of real-world traffic accidents.
Accident data is used to validate the Stochastic Cognitive Model with regard to the realistic representation of accidents in simulation.