Classifying experienced male drivers' mental workload on freeway ramps based on heart rate and speed measurements: A...

Freeway ramps are recognized as high-risk segments of the road network due to their geometric complexity and dynamic traffic demands. This study investigates drivers' mental workload in ramp areas by integrating psycho-physiological responses, specifically heart rate growth (HRG), with vehicle kinematic data, including speed and acceleration. Data were collected through real-world driving experiments from 32 experienced male drivers (aged 30-50 years) under both daytime and nighttime conditions. The findings revealed that HRG values were significantly higher at night, indicating increased cognitive stress in low-light conditions. In addition, the study identified a strong linear relationship between HRG and speed across all scenarios, indicating that increased speed is closely associated with higher mental workload. The relationship between HRG and acceleration followed a three-phase pattern, with sharp HRG changes at both low and high acceleration levels, and more stable responses within the mid-range. Based on these relationships, a classification framework was developed to categorize experienced male drivers' mental workload into three workload categories (Class 1, Class 2, and Class 3) using joint thresholds of HRG, speed, and acceleration. These findings provide a data-driven basis for identifying cognitively demanding ramp segments and inform the design of adaptive speed guidance systems, real-time driver monitoring technologies, and ramp infrastructure improvements.