Understanding driver behavior and state is crucial for enhancing road safety, yet traditional assessment methods often lack the granularity of real-world dynamics. This paper introduces the Automated Driving Data Analyzer II (ADDA II), an onboard system evolving from a simulator-based tool to a comprehensive platform for real-world driving data acquisition and analysis. Interfacing via the OBD-II port and offering ECU (Engine Control Unit) compatibility (initially validated with Volkswagen Group vehicles), ADDA II is designed for both scientific research and as an accessible end-user product. The system integrates multimodal data streams, including detailed vehicle dynamics, driver physiological responses (e.g., heart rate), and eye-tracking metrics (blinks, fixations), all synchronized to provide a holistic view of the driving task. This paper demonstrates ADDA II’s architecture and analytical capabilities using a representative real-world dataset from a multi-stage driving task. The analysis showcases the system’s ability to characterize driving styles (identifying, for instance, a ‘Conservative’ profile based on smooth control and adaptive behaviors) and reveal patterns indicative of driver state. Key insights are derived from correlating vehicle speed with heart rate to infer variations in physiological arousal and cognitive load across different environments, and by linking heart rate with ocular fixation patterns to understand visual attention strategies under varying demands. Furthermore, ADDA II incorporates functionalities for real-time feedback and warnings, aiming to promote safer, more sustainable driving practices and enhance driver self-awareness. The presented findings underscore ADDA II’s significant potential as a tool for advancing research in driver state monitoring and developing effective driver support applications.