On the progress of knowledge-based motion simulation techniques in ergonomic vehicle design

Abstract

Applying DHMs in the ergonomic design of vehicle interiors has been established for many years. Most use cases focus on various aspects of static driving configurations, but several dynamic occupant tasks must be evaluated as well for new vehicle concepts. Because of the task complexity, these tests are still performed in physical mock-ups. Over the past years, new DHM technologies have supported evaluating dynamic ergonomics of interior designs in digital mock-ups more efficiently. Nevertheless, there are still simulation aspects to be improved for proper industrial applications. This paper presents the recent development progress on knowledge-based motion simulation techniques using motion capture data and DHM prediction methods. The focus is on a large variability of motions in the database, more user control on the simulated motions, and functions for collision avoidance. Based on adjustable mock-ups, a range of ingress and egress motions into a truck and a passenger car were systematically measured, taking various positions of vehicle components like steps, doors, pillars, and roofs into account. These motion takes were reconstructed and annotated by DHMs and stored in a database. A new simulation tool was developed which uses the database to predict motions in virtual environments. The GUI provides a range of motion components subjected to various motion data and simulation methods. These components can be combined to create a cumulative motion. <br> In addition, the intersection frames of consecutive components can be controlled by user-defined postures or tasks. Smooth transitions are supported by specific truncating and sewing up consecutive motions.In addition, the tool got new functions to consider collision avoidance during simulation. First, characteristic parameters (door angle) are extracted from the environment and used to find corresponding collision-free motions in the database. Second, specific geometric constraints avoid collisions at key frames. Applying both functions supports qualitative motion strategy changes and quantitative body positions to cope with collision situations. The tool development is accompanied by user evaluations with respect to usability and prediction capabilities. These identified open issues to be solved and pushed the tool further forward to a productive level.