# Physiological Evaluation of User Experience in Unstable Automated Driving: A Comparative Study
###### Abstract
Thus, despite technological advances, failure to ensure user safety and comfort may fundamentally hinder widespread adoption. Physiological measurements provide quantitative data about how emotions in specific situations affect the body. Electromyography (EMG), which records muscle contraction signals and resting currents, has applications across kinesiology, rehabilitation medicine, and human engineering [32; 33; 34; 35]. In driving research, EMG serves as an indicator of physiological changes [36; 37; 38; 39], with values increasing when drivers experience negative emotions or higher mental workload [37; 38; 39]. Negative emotions, such as frustration or startle responses, alter motor neuron activation patterns, producing measurable changes in muscle activity that EMG can detect [34; 37; 38; 37]. Changes in pupil diameter represent a key physiological response to startle and have been extensively studied. Pupil dilation occurs due to increased sympathetic nervous system activity and intensifies in response to emotional stimuli or stress [40; 41; 42]. Researchers have utilized these pupillary changes as physiological indicators to measure drivers' cognitive load and evaluate their level of startle response in various situations [43; 44; 45]. In this context, the importance of technological development that considers the user experience in addition to the technical performance of automated-driving vehicles is becoming increasingly important [46; 47; 48]. Ride comfort, driving stability, and user interaction are key elements for the successful introduction and diffusion of automated-driving services. In particular, the response technology in traffic obstruction situations and securing user trust will be critical challenges for the future development of automated-driving technology. [PERSON] et al. (2019) emphasized the need for systematic research on users' psychobiological responses to automated driving. Studies in simulated environments have shown increased heart rate and electromyography responses during automated-driving scenarios [49]. [PERSON] et al. (2022) analyzed changes in users' risk perception and confidence during sudden braking and lane changes through simulator experiments. Using pre- and post-experiment surveys and physiological measurements like heart rate and pupil diameter, they found that higher perceived risk correlated with lower confidence and increased physiological responses, such as pupil dilation [50]. Similarly, [PERSON] et al. (2019) evaluated physiological responses to six potentially uncomfortable traffic situations in automated driving, including intersection hazards, evasive maneuvers, and highway entry [29]. Their findings revealed that more unexpected situations triggered greater physiological changes. While early research relied primarily on simulations, recent studies have expanded to real automated-driving vehicles and real-world ride quality evaluation. One study evaluated passenger comfort and anxiety through physiological signals during actual automated driving [30]. The research implemented various driving events, such as overtaking, stopping, and sharp turns, finding that participant stress levels peaked during stopped states. In-vehicle evaluation provides valuable insights, as users can fully experience and evaluate automated-driving behaviors. However, these real-world studies face limitations: they are restricted to specific road environments for safety, require experimenter presence, and cannot control weather conditions. This study experimentally verifies the importance of user experience in automated driving-technology development. Specifically, we analyzed users' psychological responses when automated driving deviates from expectations, using both qualitative evaluation and physiological indicators (EMG and pupil diameter). We defined potential traffic interference situations during unstable automated driving and measured participants' psychological changes using a driving simulator in a virtual road environment.