Collaborative Research: Adaptive Intelligence for Cyber-Physical Automotive Active Safety- System Design and Evaluation

To improve the current capabilities of automotive active safety control systems (ASCS) one needs to take into account the interactions between driver/vehicle/ASCS/environment. To achieve this goal, we are proposing a novel approach to collect data from a sensor-equipped vehicle. Motion Sensors (Inertial Measurement Units) are placed on various locations in the car, particularly around the driver's operational environment and moving car components, such as steering wheel, seat, pedals, as well as critical car components (e.g. motor, suspensions). The collected sensor data will be used for safety monitoring and helps distinguishing between normal vs. abnormal driving behavior. Based on the driver's classified mood state, a smart management system for vehicles can activate and deactivate car functionalities to lower the risk of a potential traffic hazard. Road safety will be increased by e.g. showing warning signals, limiting the maximum speed, or lower music volume. In addition, the sensor data allows us to identify a unique inertial driver signature in a non-obtrusive manner and does not require a face recognition camera or a fingerprint sensor.