Exploring Physiological Markers of Driver Workload in Response to Road Geometry: A Preliminary Investigation

Medium- and long-term international road safety goals require continued advancement of scientific research, especially with regard to the human component. Recent technological advances in sensor technology offer new opportunities to more accurately characterize driving behavior, helping to reduce the uncertainty associated with driver reactions. This study evaluated the effectiveness of specific physiological variables, detected by low-cost wearable sensors, to obtain reliable indicators of the driver’s workload. Heart rate and skin conductivity were analyzed in a real driving environment, in the absence of evident emotional stresses, to test their sensitivity to an ordinary level of physical and mental engagement. An experiment was conducted on a sample of users (10 drivers) along a rural road in Sicily, Italy. Data analysis, carried out through ANOVA and generalized linear models on three distinct curves, produced preliminary results indicating that subtle road geometry changes can be detected by physiological sensors, validating their potential for integration into driver monitoring systems. Statistically significant mean differences were found for speed (for all curves, p < 0.001), heart rate (R1 vs. R2, p = 0.009), and tonic GSR (R1 vs. R2, p = 0.006; R2 vs. R3, p = 0.013; A vs. B, p = 0.013; A vs. C, p = 0.006) as a function of different radius (R1, R2, R3) and deviation angle values (A, B, C). Future developments will require a significant increase in the sample size and the number of scenarios to achieve results of general utility.