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

Abstract

Applying DHMs in ergonomic design of vehicle interiors has been established for many years. Most use cases focus on various aspects of static driving configurations. But several dynamical occupant tasks must be evaluated for new vehicle concepts in addition. 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 efficient. 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 was put 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 use 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. 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.

Proceedings of the 7th International Digital Human Modeling Symposium, Aug. 29-31, 2022, Iowa City, Iowa, USA

“…A more pragmatic approach for simulating motions is the direct use of captured motions in a database which showed promising results with respect to usability and functionality (Wirsching et al 2013(Wirsching et al , 2016.…”

“…The results can be separated in a structured motion data pool and a DHM simulation tool making use of that pool. The motion data is transferred from the DHM Dynamicus to the DHM RAMSIS following the principal process in Wirsching et al (2016).…”

Energy transfer in reactive movements as a function of individual stretch load

“…Kinematic data was processed by VICON motion analysis software (Nexus 11.0, VICON Motion Systems Ltd., Oxford, UK). External joint moments were calculated in the distal segment coordinate system with a standard inverse dynamic approach integrating kinematic and kinetic data using the Golem model ( Wirsching, 2013 ). Ankle and knee joint power normalized to body mass were calculated as the product of net joint moment and joint angular velocity.…”