Driver behavior

Abstract

This chapter examines driver behavior within automated driving systems from a human-centered perspective, emphasizing the integration of cognitive, behavioral, and decision-making processes into the design and evaluation of vehicle automation. First, it outlines the theoretical foundations of human–automation interaction (HAI), highlighting the limitations of purely technology-driven approaches and the need to conceptualize the driver as an integral and active component of the control loop. Particular attention is given to intermediate levels of automation, where drivers are required to supervise the system and resume control under time-critical conditions.The chapter focuses on the assessment of driver state within HAI models, identifying key dimensions influenced by automation, including mental workload, situational awareness, automation complacency, and skill degradation. It analyzes how automated driving may induce both cognitive underload and overload, leading to reduced vigilance and impaired takeover performance during transitions of control. A comprehensive review of subjective, behavioral, and physiological assessment methods is provided, underscoring the advantages of multimodal and non-intrusive approaches for real-time driver monitoring. Overall, the chapter argues that safe and effective automated driving requires adaptive systems capable of continuously evaluating driver state and supporting robust human–vehicle cooperation to mitigate automation-related performance degradation.