A comprehensive review of the evolution, methods, and emerging directions of automotive ergonomics in human vehicle systems

Automotive ergonomics has evolved from a predominantly anthropometry-driven discipline into a complex, systems-oriented field integrating physical, cognitive, and data-driven human vehicle interactions. This review critically synthesizes both foundational and recent literature across key domains, including occupant packaging, seating biomechanics, whole-body vibration, digital human modeling (DHM), and human–automation interaction. Particular emphasis is placed on emerging challenges associated with electric and automated vehicles, where traditional ergonomic frameworks are increasingly insufficient to address dynamic, adaptive, and context-aware user requirements. Recent advances highlight the growing role of artificial intelligence, biomechanical modeling, and real-time sensing in enabling predictive and personalized ergonomics. However, this review identifies significant methodological limitations, including reliance on static anthropometric models, limited real-world validation of DHM tools, fragmented human centered datasets, and insufficient longitudinal evidence in automation research. The integration of human body dynamics into vehicle system models, along with the development of hybrid simulation–data-driven frameworks, is shown to be critical for improving predictive accuracy and design robustness. By bridging classical ergonomics with emerging technologies and interdisciplinary approaches, this paper proposes a future research agenda focused on multi-dimensional comfort modeling, inclusive population-specific design, and human–automation teaming. The findings contribute to advancing human centered vehicle design in increasingly automated, connected, and intelligent mobility systems.