Are Electrodermal Activity-Based Indicators of Driver Cognitive Distraction Robust to Varying Traffic Conditions and Adaptive Cruise Control Use?

TL;DR

This study examines how electrodermal activity indicators reflect driver cognitive distraction across different traffic scenarios and adaptive cruise control use, revealing their sensitivity to mental workload and automation.

Contribution

It demonstrates that EDA indicators are affected by cognitive distraction, traffic complexity, and ACC use, highlighting their robustness and limitations in diverse driving conditions.

Findings

All EDA indicators were influenced by cognitive distraction and ACC use.

Environment complexity affected SCL and SCR amplitude but not SCR rate.

EDA indicators reflect mental workload variations due to distraction, environment, and automation.

Abstract

In this simulator study, we investigate whether and how electrodermal activity (EDA) reflects driver cognitive distraction under varying traffic conditions and adaptive cruise control (ACC) use. Participants drove in six scenarios, combining two levels of cognitive distraction (presence/absence of a mental calculation task) and three levels of driving environment complexity (different traffic conditions). Throughout the experiment, they were free to activate or deactivate ACC (ACC use, two levels). We analyzed three EDA-based indicators of cognitive distraction: SCL (mean skin conductance level), SCR amplitude (mean amplitude of skin conductance responses), and SCR rate (rate of skin conductance responses). Results indicate that all three indicators were significantly influenced by cognitive distraction and ACC use, while environment complexity influenced SCL and SCR amplitude, but not SCR rate. These findings suggest that EDA-based indicators reflect variations in drivers' mental workload due not only to cognitive distraction, but also to driving environment and automation use.