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This paper proposes a method for analyzing the ingress motions for different driver's seats. Because of the multiplicity of possible ingress strategies, a unique motion calculated by minimization of energy consumption is not sufficient for understanding the variety of motions. In addition, during ingress the human body is supported by the hand placed on the steering wheel, the legs move without collision with the side sill, and the head avoids the roof rail. Consequently, difficulty is expected in constructing a computational dynamics model for this complex motion that is sufficiently precise to predict human behavior. In order to understand ingress behavior without a detailed physical model of human motion, we utilize a motion distribution map based on the degree of similarity between motions.

This paper proposes a method for visualizing and classifying the variation in the motions of a person when entering a passenger vehicle. Entering behaviors vary greatly between individuals, especially if the vehicle door is designed to have large clearance. The present study was conducted with the aim of supporting the design process of seats and front doors by visualizing possible variations of entering motions using a motion database, rather than calculating a single representative movement. The motion database is consist of different motions caused by various seats, and the motions are classified by mapping them into two-dimensional plane according to the similarities between them. A representative entering motion for a clustered motion strategy group is synthesized and visualized on the 2D distribution plane by interpolating existing motions in the database.