Numerical Approaches to Pedestrian Impact Simulation with Human Body Models: A Review

Wdowicz, Daniel; Ptak, Mariusz

doi:10.1007/s11831-023-09949-2

Cited by 8 publications

(5 citation statements)

References 137 publications

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“…Li et al [ 15 ] proposed a data-driven design method to optimize the engine hood through a machine learning model in order to achieve the lightweighting of the engine hood and to improve pedestrian safety. Mizuno et al [ 16 ] conducted a multi-body simulation analysis of different vehicle types and pedestrian body sizes and found that the decrease in pedestrian–vehicle re-contact was essential to reduce ground contact injury. The severity of pedestrian injury was not only related to vehicle speed but also to pedestrian sign, vehicle front parameter, and each participant motion involved in the collision [ 17 , 18 , 19 , 20 , 21 , 22 ].…”

Section: Introductionmentioning

confidence: 99%

A Hierarchical Prediction Method for Pedestrian Head Injury in Intelligent Vehicle with Combined Active and Passive Safety System

Shi,

Zhang,

et al. 2024

Biomimetics

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With the development of intelligent vehicle technology, the probability of road traffic accidents occurring has been effectively reduced to a certain extent. However, there is still insufficient research on head injuries in human vehicle collisions, making it impossible to effectively predict pedestrian head injuries in accidents. To study the efficacy of a combined active and passive safety system on pedestrian head protection through the combined effect of the exterior airbag and the braking control systems of an intelligent vehicle, a “vehicle–pedestrian” interaction system is constructed in this study and is verified by real collision cases. On this basis, a combined active and passive system database is developed to analyze the cross-influence of the engine hood airbag and the vehicle braking curve parameters on pedestrian HIC (head injury criterion). Meanwhile, a hierarchy design strategy for a combined active and passive system is proposed, and a rapid prediction of HIC is achieved via the establishment of a fitting equation for each grading. The results show that the exterior airbag can effectively protect the pedestrian’s head, prevent the collision between the pedestrian’s head and the vehicle front structure, and reduce the HIC. The braking parameter H2 is significantly correlated with head injury, and when H2 is less than 1.8, the HIC value is less than 1000 in nearly 90% of cases. The hierarchy design strategy and HIC prediction method of the combined active and passive system proposed in this paper can provide a theoretical basis for rapid selection and parameter design.

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Section: Introductionmentioning

confidence: 99%

A Hierarchical Prediction Method for Pedestrian Head Injury in Intelligent Vehicle with Combined Active and Passive Safety System

Shi,

Zhang,

et al. 2024

Biomimetics

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“…The scene is recreated in the software using detailed scale sketches, with geometry, infrastructure elements, braking traces, collision point, and final position of the subjects after impact. The pedestrian model in PCCrash© uses a validated multibody (MB) system [20,21], which is based on anthropometric studies [22,23] that represent the male and female Spanish population. The parameters of the MB model of the pedestrian are adjusted (according to height, weight, age, and gender).…”

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confidence: 99%

Effectiveness of the Autonomous Braking and Evasive Steering System OPREVU-AES in Simulated Vehicle-to-Pedestrian Collisions

Losada,

Páez,

Luque

et al. 2023

Vehicles

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This paper proposes a combined system (OPREVU-AES) that integrates optimized AEB and Automatic Emergency Steering (AES) to generate evasive maneuvers, and it provides an assessment of its effectiveness when compared to a commercial AEB system. The optimized AEB system regulates the braking response through a collision prediction model. OPREVU is a research project in which INSIA-UPM and CEDINT-UPM cooperate to improve driving assistance systems and to characterize pedestrians’ behavior through virtual reality (VR) techniques. The kinematic and dynamic analysis of OPREVU-AES is conducted using CarSim© software v2020.1. The avoidance trajectories are predefined for speeds above 40 km/h, which controls the speed and lateral stability during the overtaking and lane re-entry process. In addition, the decision algorithm integrates information from the lane and the blind spot detectors. The effectiveness evaluation is based on the reconstruction of a sample of vehicle-to-pedestrian crashes (INSIA-UPM database), using PCCrash© software v. 2013, and it considers the probability of head injury severity (ISP) as an indicator. The incorporation of AEB can avoid 53.8% of accidents, with an additional 2.5–3.5% avoided by incorporating automatic steering. By increasing the lateral activation range, the total avoidance rate is increased to 61.8–69.8%. The average ISP reduction is 65%, with significant reductions achieved in most cases where avoidance is not possible.

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“…We analyzed real accidents with pedestrian dummies with images captured with high-speed cameras and simulations performed in PC-Crash. PC-CRASH, multibody solvers, utilizes a contact algorithm similar to MADYMO, i.e., an algorithm based on the calculation of the depth of penetration [21].…”

mentioning

confidence: 99%

“…PC-CRASH, multibody solvers, utilizes a contact algorithm similar to MADYMO, i.e., an algorithm based on the calculation of the depth of penetration [21].…”

mentioning

confidence: 99%

“…For the roof, one quarter of the specified stiffness is used. Multibody forensic models available in reconstruction software were often validated by comparing body motion with video data either from dummy crash tests or CCTV recordings [21]. In [24,25], the authors used camera images from real accidents involving pedestrians as a technique for accident analysis.…”

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confidence: 99%

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The Contact Phase in Vehicle–Pedestrian Accident Reconstruction

Benea,

Soica

2023

Applied Sciences

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The need for continuous research to refine the models used in forensic accident reconstruction appears with the development of new car models that satisfy consumer complaints. This paper analyzed a sub-sequence of car and pedestrian accidents from the perspective of the distance traveled by them in the contact phase with the aim of improving the information regarding the reconstruction of road accidents. This research included the analysis of some real tests with pedestrian dummies, as well as simulations of the impact between different classes of vehicles and pedestrians in two different walking positions. Specialized software was used with complex multibody models of pedestrians, modifying the speed and deceleration parameters of the car at the time of the collision. For pedestrian characteristics, the friction coefficients of the ground, car and its mass were modified. The research results highlight the differences between the bilinear models used in accident reconstruction and the proposed study. They can also be used to determine the distance traveled by the vehicle in the first phase of a collision with pedestrians.

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Numerical Approaches to Pedestrian Impact Simulation with Human Body Models: A Review

Cited by 8 publications

References 137 publications

A Hierarchical Prediction Method for Pedestrian Head Injury in Intelligent Vehicle with Combined Active and Passive Safety System

A Hierarchical Prediction Method for Pedestrian Head Injury in Intelligent Vehicle with Combined Active and Passive Safety System

Effectiveness of the Autonomous Braking and Evasive Steering System OPREVU-AES in Simulated Vehicle-to-Pedestrian Collisions

The Contact Phase in Vehicle–Pedestrian Accident Reconstruction

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