Presentation
Developing a Driver Monitoring System Driver Experience (DMSDX) Scale Using Insights from Developmental Psychology
SessionLBR2: Late-Breaking Results
DescriptionThis paper investigates the critical role in enhancing the effectiveness and user acceptance of Driver Monitoring Systems (DMS) often paired with Partially Automated Driving Systems (PADS). By drawing parallels with established parenting styles and developmental psychology frameworks, we develop an acceptability scale so that automakers can better evaluate how different monitoring approaches can influence driver behavior and system trust and acceptability. Utilizing insights from Erikson’s psychosocial theory, Bowlby and Ainsworth's attachment theory, and Baumrind’s parenting styles, we propose a novel DMS Driver Experience (DMSDX) scale designed to evaluate the balance support and control, much like authoritative parenting, to foster driver compliance and engagement.
To validate the DMSDX scale, we conducted an online validation study using vignettes of DMS experience, including surveys to measure the perceived effectiveness and other driver perceptions of different DMS approaches. Through exploratory and confirmatory factor analyses, the study established a clear factor structure. In addition, our proposed DMS scale demonstrated significant correlations with established measures of driving style and behavior with automated systems, particularly the Multidimensional Driving Style Inventory (MDSI) and the Automation-Induced Complacency Potential Revised (AICP-R) scale.
The study provides an evaluation framework for designing robust, adaptable, and culturally sensitive DMS using well-established concepts from developmental psychology. By aligning monitoring strategies with drivers' psychological profiles and driving styles, automakers can enhance the user experience and safety of PADS technologies, ensuring their commercial success and broader acceptance in the market.
To validate the DMSDX scale, we conducted an online validation study using vignettes of DMS experience, including surveys to measure the perceived effectiveness and other driver perceptions of different DMS approaches. Through exploratory and confirmatory factor analyses, the study established a clear factor structure. In addition, our proposed DMS scale demonstrated significant correlations with established measures of driving style and behavior with automated systems, particularly the Multidimensional Driving Style Inventory (MDSI) and the Automation-Induced Complacency Potential Revised (AICP-R) scale.
The study provides an evaluation framework for designing robust, adaptable, and culturally sensitive DMS using well-established concepts from developmental psychology. By aligning monitoring strategies with drivers' psychological profiles and driving styles, automakers can enhance the user experience and safety of PADS technologies, ensuring their commercial success and broader acceptance in the market.
Event Type
Late Breaking Results
TimeWednesday, September 11th3:50pm - 4pm MST
LocationFLW Salon B