MeaSURe DriVe: Methods and Sensors to Understand and Regard Driver Attentiveness in Autonomous Vehicles

As a precursor to fully autonomous mobility, more and more partially and conditionally automated vehicles (SAE-Level 2 and 3) will penetrate the market. These vehicles are equipped with systems that support the driver and can even take over driving functions in certain situations. Nevertheless, these systems still require a driver to be present as a safety layer, who is ultimately responsible for driving safety and takes back the driving task if necessary.
The aim of our project is to link technical, psychological and physiological parameters in order to gain information about the driver's attention and performance in (partially) autonomous driving.

While various studies already deal with the detection of the driver’s attention or distraction in the context of automated driving, neither standardized test procedures nor ground truth data concerning psychophysiological parameters indicating different driver states are available today [1-5]. Hence, the main research question regards the core methodical approach with includes the development of a requirements-oriented simulation environment as well as the coupling and synchronization of test bench, user inputs, simulation and measurement equipment. Due to the complexity of human behavior and its manifestation in psychophysiological parameters, several measurement techniques such as EEG, fNIRS, ECG and EDA  are utilized simultaneously. Furthermore, behavioral data is collected using camera data and user inputs. Considering the physical test environment, it is intended to implement different degrees of realism with increasing interaction requirements for the subjects. This ranges from simple video presentations without physical interaction to real-time driving tasks within a vehicle-in-the-loop test bench (VEL). In an intermediate state, another specially designed test bench comprising a driving seat, pedals for acceleration and braking, a steering wheel and HD monitors will be used.

Regarding the virtual environment, CarMaker is used to create a simulation which can be used for both active driving and autonomous driving modes while maintaining the same set of environmental parameters. This enables the comparison of both modes for different driving scenarios. The design of the simulation incorporates different types of surroundings throughout the drive. Additionally, different sources of distractions are used which can further be modified in frequency and trigger position.

The experimental setup at the VEL is also intended to be used for a project topic, which deals with handover situations relevant for SAE-Levels 3 and 4. Approaches will be developed to model human behavior in these situations. The analysis of human behavior in handover situations requires a realistic simulation of the vehicle environment and the driving situations, which will be performed in CarMaker.