Search Results

Human-driven vehicles are going to be replaced by highly automated vehicles as one of the future mobility trends. Even though highly automated vehicles’ active safety systems can protect against vehicle-to-vehicle accidents, the traffic mix between human-driven vehicles and highly automated vehicles is still a potential source of vehicle collisions. Additionally, occupants in highly automated vehicles will be passengers not necessarily dealing with driving anymore, so there will be a considerable number of non-standard seating configurations. Those configurations are not able to be assessed for safety by hardware testing due to their number, variability and complexity. The objective of the paper is the development of a fast virtual approach to identify the passengers’ injury risk in non-standard seating configurations under multi-directional impact scenarios and severity.

The paper addresses the safety of a pregnant passenger from an injury risk point of view regarding to the position of the seatbelt’s lap part. The finite element based-pregnant abdomen model is incorporated into the simplified rigid body-based female body model. The study was done in two steps. Firstly, a female model was validated in the frontal sled test to ensure its biofidelity for this particular purpose. Secondly, a fully deformable abdomen was added to create a pregnant female model. Such model was positioned in a deformable frontal seat and restrained by a safety system such as a three-point seat belt and airbag to simulate the frontal sled test scenario. A deceleration pulse corresponding to a frontal impact related to two impact velocities (30 km/h and 50 km/h) is applied and the restraint system performance is assessed with the focus on the fetus and female injury risk.

Powered two-wheeler (PTW) riders and passengers are among the group of vulnerable road users (VRU). This group uses the road transportation system together with other better-protected users such as passenger cars and truck drivers. The main vulnerability of PTW rider lies in their unequal position during the crash, due to the inability of application of the crashworthiness concept during the PTW vehicle design. This inequality could be somehow mitigated by the design of personal protective equipment (PPE). Mostly the design of the PPE’s is led by the standards which often are obsolete and takes into account only simple drop-tests (ECE 22.05). Those tests did not take into account complicated kinematics of the motorcycle accidents and biomechanics of the human body (the assessment is based only on the linear acceleration of the headform center of gravity).

Road traffic accidents cause one of the highest numbers of severe injuries. Approximately 1.25 million people die each year as a result of road traffic crashes and between 20 and 50 million more people suffer non-fatal injuries, with many incurring a disability. Nearly half of those dying on the roads are so-called vulnerable road users, namely pedestrians, cyclists and two-wheeler riders including motorcyclists. Those vulnerable road users usually undergo complex kinematics and complex loading caused by the other vehicle impact. Virtual human body biomechanical models play an important role to assess the injuries during the impact loading especially for scenarios, where complex dynamical loading is taken into account. An additional benefit of some virtual human models is their scalability, so that they can assess the injury risk for the particular subject taking into account a wide spectrum of the whole population.

In this paper a novel approach in developing a simplified model of a vehicle front-end is presented. Its surface is segmented to form an MBS model with hundreds of rigid bodies connected via translational joints to a base body. Local stiffness of each joint is calibrated using a headform or a legform impactor corresponding to the EuroNCAP mapping. Hence, the distribution of stiffness of the front-end is taken into account. The model of the front-end is embedded in a whole model of a small car in a simulation of a real accident. The VIRTHUMAN model is scaled in height, weight and age to represent precisely the pedestrian involved. Injury risk predicted by simulation is in correlation with data from real accident. Namely, injuries of head, chest and lower extremities are confirmed. Finally, mechanical response of developed vehicle model is compared to an FE model of the same vehicle in a pedestrian impact scenario.

In this work we present the VIRTHUMAN model as a tool for injury risk assessment in pedestrian crash scenarios. It is a virtual human body model formed of a multibody structure and deformable segments to account for the mechanical response of soft tissues. Extensive validation has been performed to ensure its biofidelity. Due to the scaling algorithm implemented, variations in the human population in terms of height, weight, gender and age can be considered. Assessment of the injury risk is done via automatic evaluation software developed. Injury criteria for individual body parts are evaluated using accelerations, forces and displacements of certain points. Injury risk is indicated by the colour of particular body parts in accordance with NCAP rating. A real accident is investigated in this work. A 60-year-old female was hit laterally by a passenger vehicle with the impact velocity of 40 km/h. The accident is reconstructed using VIRTHUMAN as pedestrian representative.

The paper contributes to the field of vehicle safety technology by the virtual approach using biomechanical virtual human body models. The goal of the paper is to exploit the previously developed scaling algorithm to create several virtual human models of a given age and body proportions and to assess the impact analysis using the sensitivity approach. Based on a validated reference model, the previously developed scaling algorithm develops virtual human body models for given height, mass, age and gender. Particular body segments are scaled based on the anthropometrical database concerning the body dimensions taking also percentiles into account. The body stiffness is driven by age dependent flexindex. Several virtual models of human bodies representing particular cadavers were generated via the automatic scaling algorithm. The frontal sled test response of three models was successfully compared to the available experimental data previously.

The paper concerns the development of a new scalable virtual human body model. The model has been developed to assess safety risk during various complex crash scenarios including impacts from different directions. The novel approach described couples the basic multi-body structure with deformable segments, resulting in short calculation time. Each multi-body structure segment carries the particular surface parts that are linked to the segment with non-linear springs representing the behavior of related soft tissues. The response of particular body segments (head, thorax, pelvis, lower extremities) is validated in known impact scenarios and the response of the model is tuned to the experimental corridors obtained from literature. The tuning process involved the adjustment of both model material and numerical parameters in order to get the correct response for all the tests.

Traffic accidents cause one of the highest numbers of severe injuries in the whole population. The numbers of deaths or seriously injured citizens prove that traffic accidents and their consequences are still a serious problem to be solved. A lot of effort is devoted to both passive and active safety systems development. The transportation standards usually define safety requirements by regulations (e.g. ECE-R94, 96/79/EC and ECE-R95, 96/27/EC in Europe) with specific dummies for children to be used. The dummies include hardware sensors for monitoring accelerations, loads and other signals and each dummy is developed for a specific scenario, but there are limitations of these dummies, such as only a specific age or calibration just for a specific test.

The paper contributes to the development of virtual biomechanical human models as a support for design and optimization of both passive and active safety systems used in various modes of transportation. The paper shows the scaling methodology as simply as possible to creating models based on a reference model regarding anthropology and flexibility. The paper describes the methodology for the scaling of hybrid human models based on a multi-body structure carrying deformable parts. The idea is to have a reference model and to create other models automatically based on the least possible number of parameters. The developed method takes into account the height, age, mass and flexibility of joints. The scaling process starts by scaling the reference model to the target height for given age (including correct height for each major segment of the human body) based on the available anthropometrical data. The scaling coefficient for each segment is also used to scale the segment mass.