Integrating Generative Design and Ergonomics: A Data-Driven Approach with Digital Manikins

Modern artificial intelligence (AI)-assisted design methods, such as generative design (GD), have expanded concept generation and evaluation far beyond traditional approaches. This chapter presents a comprehensive product concept generation and evaluation framework that integrates HFE and mechanical performance across both the divergent and convergent stages of conceptual design. It aims to eliminate infeasible concepts that fail to meet human-centered design requirements and identify preferred alternatives using AI algorithms early in the process. One of the major challenges of applying data-driven GD approaches to the early design stages is the pursuit of creativity. The chapter describes the proposed methodology for iteratively refining design concepts to satisfy ergonomic requirements alongside users' preferences. It employs an occupant packaging evaluation template that uses 3D digital manikin models to assess geometric factors affecting driver ergonomics, such as the impact of roof height on headroom.