| 1. |
- Carlsson, Stina, 1967, et al.
(författare)
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Volunteer occupant kinematics during driver initiated and autonomous braking when driving in real traffic environments
- 2011
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Ingår i: 2011 IRCOBI Conference Proceedings - International Research Council on the Biomechanics of Injury IRCOBI, 14 - 16 September 2011, Krakow, Polen. ; 2011, s. 125-136
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Konferensbidrag (refereegranskat)abstract
- When a vehicle is braking, the occupants are subjected to longitudinal forces which may influence their positions. The aim of this paper is to quantify the driver and passenger kinematics during medium harsh braking while driving in real traffic and to identify the influencing parameters.The overall motions were relatively small during braking and the effect of seat belt locking was obvious. Mean forward motions were 55 ±26 mm for the chest and 97 ±47 mm for the head. This study indicates that several properties influence forward motion. Taller volunteers had a larger forward motion; females had a larger forward motion than males of the same sitting height. Passengers exhibited larger motions than drivers for most of the volunteers.The result provides a deeper understanding of pre-impact conditions and adds knowledge to further improve the interaction of active and passive safety systems. It also provides valuable validation data for low-g occupant models, which can be used in studies of the effect of pre-impact braking on restraint interaction.
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| 2. |
- Östh, Jonas, 1983, et al.
(författare)
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The Occupant Response to Autonomous Braking: A Modelling Approach That Accounts for Active Musculature
- 2012
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Ingår i: Traffic Injury Prevention. - : Informa UK Limited. - 1538-957X .- 1538-9588. ; 13:3, s. 265-277
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Tidskriftsartikel (refereegranskat)abstract
- Objective: The aim of this study is to model occupant kinematics in an autonomous braking event by using a Finite Element (FE) Human Body Model (HBM) with active muscles, as a step towards HBMs that can be used for injury prediction in integrated pre-crash and crash simulations.Methods: Trunk and neck musculature was added to an existing FE HBM. Active muscle responses were achieved using a simplified implementation of three feedback controllers for: the head angle, the neck angle, and the angle of the lumbar spine. The HBM was compared with volunteer responses in sled tests with 10 ms−2 deceleration over 0.2 s and in 1.4 s autonomous braking interventions with a peak deceleration of 6.7 ms−2.Results: The HBM captures the characteristics of the kinematics of volunteers in sled tests. Peak forward displacements have the same timing as for the volunteers, and lumbar muscle activation timing matches data from one of the volunteers. The responses of volunteers in autonomous braking interventions are mainly small head rotations and translational motions. This is captured by the HBM controller objective, which is to maintain the initial angular positions. The HBM response with active muscles is within +/- 1 standard deviation of the average volunteer response with respect to head displacements and angular rotation.Conclusions: With the implementation of feedback control of active musculature in an FE HBM, it is possible to model the occupant response to autonomous braking interventions. The lumbar controller is important for the simulations of lap-belt restrained occupants; it is less important for the kinematics of occupants with a modern three point seat belt. Increasing head and neck controller gains gives a better correlation for head rotation, while it reduces the vertical head displacement and introduces oscillations.
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| 3. |
- Nosratinia, Mohsen, 1979, et al.
(författare)
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A holistic decision-making framework for integrated safety
- 2010
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Ingår i: Proceedings of the 2010 IEEE Intelligent Vehicles Symposium, IV 2010, San Diego, 21-24 June 2010. - 1931-0587. - 9781424478668 ; , s. 1028-1035
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Konferensbidrag (refereegranskat)abstract
- A Bayesian decision-theoretic decision-making framework for integrated vehicle safety systems is introduced. The framework tries to address the increasing need for introduction of optimal decision-making to integrated vehicle safety. The framework tries to capture all the interdependencies between systems in one optimisation problem by designing appropriate risk functions. This is achieved by incorporating driver behavior model and pre-crash occupant position tracking. New software methods and tools should also be developed to efficiently accommodate this. The framework, in general, leads to higher design flexibility and scalability.
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