Human Performance in Vehicle Driving

Abendroth, Bettina; Joisten, Philip · 2026 · Crossref

DOI: 10.1007/978-3-658-45276-6_1

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Summary

This chapter, titled "Human Performance in Vehicle Driving," addresses the critical role of human factors in the driver–vehicle–environment system, particularly within the context of manual driving and advanced driver assistance systems (ADAS). The authors argue that understanding human performance is essential for ensuring safety and designing effective automation transitions. Human performance is defined as the interaction between the driver’s "offer of performance" (comprising general capacity and current willingness) and the specific requirements imposed by the driving task. As automation levels increase (SAE Levels 1–2), tasks shift from the driver to the vehicle, necessitating that drivers maintain situational awareness (knowledge of the environment) and mode awareness (understanding of responsibility distribution) to safely take over control when required. The paper analyzes human information processing through a combined sequential and resource model, detailing three stages: information intake, processing, and output. Information intake relies on sensory organs, with visual perception being the primary source for traffic-relevant data. The text distinguishes between foveal vision, which provides distinct detail for central objects, and peripheral vision, which detects movement and brightness changes to guide attention shifts. Attention is described as a limited resource managed through selective and intensity dimensions, influenced by top-down (expectation-based) and bottom-up (stimulus-driven) processes. The authors highlight risks such as cognitive tunneling and inattentional blindness, where drivers may ignore relevant information due to poor attention distribution or overload. Information processing is categorized into three behavioral levels: skill-based, rule-based, and knowledge-based. Skill-based behavior involves automated, sensorimotor actions requiring minimal attention, suitable for routine situations. Rule-based behavior relies on stored empirical rules for more cognitively demanding tasks, while knowledge-based behavior involves conscious analysis and planning for novel or complex scenarios. This processing depends heavily on memory systems, including sensory registers, short-term memory, and long-term memory. The chapter also identifies determinants of performance capacity, such as age, personality, driving experience, and fatigue, which influence the driver’s ability to meet task demands. The significance of this work lies in its comprehensive framework for evaluating human capabilities against driving requirements. By mapping the physiological and psychological limits of drivers—such as visual field constraints and attentional bottlenecks—the authors provide a foundation for designing ADAS that align with human information processing limits. The analysis underscores that safe interaction with automated systems requires maintaining driver awareness and understanding the cognitive resources needed for various driving subtasks, thereby informing the design of safer vehicle interfaces and automation strategies.

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

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• cognitive capacity variation
• mental demand

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• Theoretical Contribution: theory or model, computational model