Pedestrian Head Research Articles

A computational study on the basis for a safe speed limit for bicycles on shared paths considering the severity of pedestrian head injuries in bicyclist-pedestrian collisions

Bicyclists and pedestrians are two large vulnerable groups of road users. Many cities have allowed cyclists to share space with pedestrians on footpaths and off-road paths to reduce conflict with motor vehicles. The risk of bicyclist-pedestrian accidents is also increasing accordingly. Therefore, there is a need to understand the factors that affect the risk of injury in such accidents, especially to pedestrians who are considered more vulnerable. This paper presents a detailed investigation of bicyclist-pedestrian collisions and possible injury outcomes. The study has considered five levels of collision speed ranging from 10 km/h to 30 km/h, three pedestrian profiles (adult, child, and elderly) differentiated by their weight and height, three bicycles with different masses, and five impact directions. The bicyclist-pedestrian collision simulations have been analyzed based on four metrics: throw distance, peak head velocity on impact with the ground, head injury criterion (HIC) value, and the probability of severe head injury. For each simulation, the throw distance and peak head velocity on impact with the ground are extracted. Following that, the HIC and the probability of severe head injury to pedestrians are computed. The results show a significant effect of collision speed (p < 0.05) on all four metrics. The analysis has been further extended to study the effect of height and weight profile, bicycle mass, and impact directions on bicyclist-pedestrian collisions. According to the results, the impact directions largely influence the outcome of bicycle-pedestrian collisions. In general, direct impacts on pedestrian body center have been found to yield higher HIC values and probability of severe head injury to pedestrians than off-center impacts. Also, video analysis of simulated collisions has suggested that the accident mechanism depends on weight and height profiles (correlated with different age groups) and impact directions. Finally, recommendations have been proposed based on the study, including a speed limit of not more than 12 km/h for bicyclists on narrow shared paths and footpaths where risks of collisions with pedestrians are high. The results and analysis presented could be helpful for developing legislation to minimize conflicts between bicyclists and pedestrians on shared paths and to reduce potential injury to pedestrians.

Should anthropometric differences between the commonly used pedestrian computational biomechanics models and Chinese population be taken into account when predicting pedestrian head kinematics and injury in vehicle collisions in China?

Computational biomechanics models play a key role in predicting/evaluating pedestrian head kinematics and injury risk in car-to-pedestrian collisions. The human multibody models most commonly used in car-to-pedestrian collision reconstruction, such as pedestrian model by The Netherlands Organisation for Applied Scientific Research TNO, are built using the anthropometry of Western European population as defined in TNO (2013) human multibody model database. In this study, we investigate the effects of the anthropometric differences between the Western European and Chinese populations on the pedestrian head kinematics and injury responses predicted using multibody models. The comparison was conducted through car-to-pedestrian collision simulations using pedestrian multibody models representing anthropometric characteristics of Western European and Chinese populations, three typical vehicle shapes (sedan, SUV and minivan), five initial vehicle impact speeds (30, 35, 40, 45, 50 km/h), and six pedestrian walking postures. The results indicate that the change of pedestrian model anthropometry (from Western European to Chinese) exerts appreciable effects on both the predicted initial boundary conditions of the head-to-windscreen impact (in particular the head-to-windscreen impact angle) and the head injury indices in the impact with the road surface (secondary impact).

Pedestrian Head Impact Analysis on a Vehicle and Measures to Reduce HIC Value

Throughout the world numerous people are killed in vehicle collisions. Different innovations for expanding the energy-engrossing characteristics of the vehicle body are being considered. This paper worked out on the analysis of pedestrian head impact behavior on a vehicle and technique to reduce HIC (Head Impact Criteria) value. Objectives of this research work are: (a) to reduce the HIC (Head injury Criteria) less than 1000 without affecting the outer design and aesthetics of the vehicle, and (b) to find out the best and economical technologies among “rear-rising hood” and “airbag system for controlling pedestrian collision kinematics” to suit Indian requirements. The pedestrian air bag system along with the rear rising hood system is the best possible solution to protect the pedestrian from fatal injuries. The air bag covers the critical areas of the car for better safety.

Pedestrian head direction estimation using weight generation function for fusion of visible and thermal feature vectors

Head direction contains useful information to analyse the behaviour of pedestrian in a traffic environment and to estimate the risk of an accident. Pedestrian head direction estimation is harder at night, since the quality of visible image decreases significantly. Likewise, in thermal images, the resolution and texture of images are limited. In this study, a multispectral pedestrian head direction estimation method is proposed to circumvent the problem. Feature vectors are extracted from the visible and thermal images of pedestrian head at night. Multiple scenarios of series and parallel feature fusion methods with identical constant weights are tested. Experiments performed on a group of low-quality images justify the weighted fusion due to various discrimination ability of each feature vector in different situations. Consequently, this study proposes a sigmoid weight generation function for weighted fusion of feature vectors that improves the performance significantly. This function generates the weight coefficients which depend on these feature vectors. The genetic algorithm is also used to adjust the corresponding parameters. The experiments are performed on pedestrian head images from KAIST multispectral database. The experimental results show the significant improvement in performance of the proposed method in increasing the accuracy of the pedestrian head direction estimation system at night.

Realistic Reference for Evaluation of Vehicle Safety Focusing on Pedestrian Head Protection Observed From Kinematic Reconstruction of Real-World Collisions.

Head-to-vehicle contact boundary condition and criteria and corresponding thresholds of head injuries are crucial in evaluation of vehicle safety performance for pedestrian protection, which need a constantly updated understanding of pedestrian head kinematic response and injury risk in real-world collisions. Thus, the purpose of the current study is to investigate the characteristics of pedestrian head-to-vehicle contact boundary condition and pedestrian AIS3+ (Abbreviated Injury Scale) head injury risk as functions of kinematic-based criteria, including HIC (Head Injury Criterion), HIP (Head Impact Power), GAMBIT (Generalized Acceleration Model for Brain Injury Threshold), RIC (Rotational Injury Criterion), and BrIC (Brain Injury Criteria), in real-world collisions. To achieve this, 57 vehicle-to-pedestrian collision cases were employed, and a multi-body modeling approach was applied to reconstruct pedestrian kinematics in these real-world collisions. The results show that head-to-windscreen contacts are dominant in pedestrian collisions of the analysis sample and that head WAD (Wrap Around Distance) floats from 1.5 to 2.3 m, with a mean value of 1.84 m; 80% of cases have a head linear contact velocity below 45 km/h or an angular contact velocity less than 40 rad/s; pedestrian head linear contact velocity is on average 83 ± 23% of the vehicle impact velocity, while the head angular contact velocity (in rad/s) is on average 75 ± 25% of the vehicle impact velocity in km/h; 77% of cases have a head contact time in the range 50–140 ms, and negative and positive linear correlations are observed for the relationships between pedestrian head contact time and WAD/height ratio and vehicle impact velocity, respectively; 70% of cases have a head contact angle floating from 40° to 70°, with an average value of 53°; the pedestrian head contact angles on windscreens (average = 48°) are significantly lower than those on bonnets (average = 60°); the predicted thresholds of HIC, HIP, GAMBIT, RIC, BrIC2011, and BrIC2013 for a 50% probability of AIS3+ head injury risk are 1,300, 60 kW, 0.74, 1,470 × 104, 0.56, and 0.57, respectively. The findings of the current work could provide realistic reference for evaluation of vehicle safety performance focusing on pedestrian protection.

A context-aware pedestrian trajectory prediction framework for automated vehicles

With the unprecedented shift towards automated urban environments in recent years, a new paradigm is required to study pedestrian behaviour. Studying pedestrian behaviour in futuristic scenarios requires modern data sources that consider both the Automated Vehicle (AV) and pedestrian perspectives. Current open datasets on AVs predominantly fail to account for the latter, as they do not include an adequate number of events and associated details that involve pedestrian and vehicle interactions. To address this issue, we propose using Virtual Reality (VR) data as a complementary resource to current datasets, which can be designed to measure pedestrian behaviour under specific conditions. In this research, we focus on the context-aware pedestrian trajectory prediction framework for automated vehicles at mid-block unsignalized crossings. For this purpose, we develop a novel multi-input network of Long Short-Term Memory (LSTM) and fully connected dense layers. In addition to past trajectories, the proposed framework incorporates pedestrian head orientations and distance to the upcoming vehicles as sequential input data. By merging the sequential data with contextual information of the environment, we train a model to predict the future pedestrian trajectory. Our results show that the prediction error is reduced by considering contextual information extracted from the crossing environment, as well as the addition of time-series behavioural information to the model. To analyse the application of the methods to real AV data, the proposed framework is trained and applied to pedestrian trajectories extracted from an open-access video dataset. Finally, by implementing a game theory-based model interpretability method, we provide detailed insights and propose recommendations to improve the current automated vehicle sensing systems from a pedestrian-oriented point of view.

Analysis of Pedestrian Fractures in Collisions Between Small Cars and Pedestrians Based on Surveillance Videos.

To discuss the collision relationship and the cause of the fracture caused by traffic accidents in which the front of a small car collides with the side of a pedestrian while braking. The surveillance videos of 42 traffic accidents involving the front of a small car colliding with the side of a pedestrian while braking were collected. By analyzing the surveillance videos and the paths, the speed of the collision, the relationship between the vehicle and the pedestrian upon collision, and the movement trajectory of the human body were clearly identified. The type and severity of the injuries were also determined through autopsy. The characteristics of the human injuries and vehicle paths were analyzed according to the collision speed (<40 km/h, 40-60 km/h, 60-90 km/h), and the correlations between the fracture and the height of the pedestrian, the height of the hood and the length of the hood were discussed. When a small car hits the side of a pedestrian, the front bumper first hits the lower limbs of the pedestrian, and then, the human body falls to the side of the vehicle, causing a secondary collision with the hood and front windshield; thus, the pedestrian is thrown at a speed similar to the speed of the vehicle, finally falling to the ground and sliding forward a certain distance. (1) When V is less than 40 km/h (n = 10), the pedestrian's head did not collide with the windshield, and the fatal injuries were caused by the individual striking the ground. (2) When V is greater than 40 km/h (n = 32), the majority (97%) of cases showed collision with the windshield. (3) When 40 to 60 km/h (n = 16), the pedestrian's head collided with the windshield, which can cause fatal injuries, and pelvic fractures and rib fractures occurred in 56.25% of patients. (4) When V is less than 60 km/h (n = 26), the ratio of the height of the pedestrian to the height of the hood was significantly smaller in the pelvic fracture group than in the nonpelvic fracture group (P < 0.01). (5) When 60 to 90 km/h (n = 16), there were holes in the windshield, and the pedestrians experienced severe head injuries, with cervical spine fracture occurring in 37.5% of patients, pelvic fractures occurring in 43.75% of patients, and rib fractures occurring in 31.25% of patients. When V is less than 40 km/h, the vehicle does not cause severe injuries in pedestrians; when V is greater than 40 km/h, the collisions of the pedestrian's head with the windshield lead to severe head injuries and the accident can cause severe pelvic and rib fractures; when V is greater than 60 km/h, the collisions of the pedestrian's head with the windshield can cause cervical spine fracture in addition to head injuries. The occurrence of human injuries is related to not only the vehicle speed but also factors such as the height of the pedestrian, the height of the hood and the length of the hood.

Pedestrian Heading Estimation Methods Based on Multiple Phone Carrying Modes

The development of smartphone Micro-Electro-Mechanical Systems (MEMS) inertial sensors has provided opportunities to improve indoor navigation and positioning for location-based services. One area of indoor navigation research uses pedestrian dead reckoning (PDR) technology, in which the mobile phone must typically be held to the pedestrian’s chest. In this paper, we consider navigation in three other mobile phone carrying modes: “calling,” “pocket,” and “swinging.” For the calling mode, in which the pedestrian holds the phone to their face, the rotation matrix method is used to convert the phone’s gyroscope data from the calling state to the holding state, allowing calculation of the stable pedestrian forward direction. For a phone carried in a pedestrian’s trouser pocket, a heading complementary equation is established based on principal component analysis and rotation approach methods. In this case, the pedestrian heading is calculated by determining a subset of data that avoid 180° directional ambiguity and improve the heading accuracy. For the swinging mode, a heading capture method is used to obtain the heading of the lowest point of the pedestrian’s arm swing as they hold the phone. The direction of travel is then determined by successively adding the heading offsets each time the arm droops. Experimental analysis shows that 95% of the heading errors of the above three methods are less than 5.81°, 10.73°, and 9.22°, respectively. These results present better heading accuracy and reliability.

Design of a New Engine Hood based on Lattice Structure for Pedestrian Protection

This paper designs four kinds of three-dimensional negative Poisson’s ratio lattice structures, based on the two-dimensional concave hexagonal negative Poisson’s ratio honeycomb structure. Different parameters are designed for simulation analysis and experimental research, and the influence of different parameters on Poisson’s ratio is studied respectively. The main contents are as follows: Firstly, the three-dimensional solid model of lattice structure is established by modeling software, and the different structural parameters are determined, and the equivalent mechanical model is established. And according to the relevant structural parameters to establish the test scheme. Then, the finite element software is used to simulate the test core material with different parameters. According to the simulation results, the influence of different parameters on Poisson’s ratio is found out. Then the crashworthiness of the test board with different parameters is simulated and analyzed. According to the results, the most suitable structure is selected and applied to the engine hood. Finally, the simulation experiment of collision between pedestrian head and engine hood is carried out. The results of this paper compare the performance of lattice sandwich panels with different parameter structures in different tests and select the optimal combination of structural parameters. The adjustment and optimization direction of the structure is put forward according to the test results.

Methods, upper limit and reason for reducing pedestrian ground contact injury by controlling vehicle braking

In order to access the maximum benefits of controlled vehicle braking in reducing ground related injury, based on a basic simulation test sample, which include 24 simulations with three velocities, four pedestrian sizes and two pedestrian gaits, 10176 simulations were conducted by Madymo. After comparative study, we found that the vehicle caused injury will not increase if the vehicle braking is starting to reduce at the time the pedestrian head first contact the vehicle and the ground related WIC/HIC can be maximally reduced 88.9% and 75.6% respectively by controlling the vehicle braking efficiently. Through a further analysis we found that the optimal time at which the vehicle was to fully brake again (t2) is not hard to obtain because the optimal t2 is not an isolated point and hence it is easy to obtain a simple controlling method for a specific car shape but it may be impossible to find one way to control the braking of vehicles with different shapes. And the possible reason that the ground related injury can be reduced is the change of the landing mechanism. Not all ground related injury can be reduced because in some fully braked cases the WIC/HIC is already equal or close to 0; and two danger situations for controlling the vehicle braking were found, which are the pedestrian fall to the ground from the vehicle side and the controlled vehicle cannot contact the pedestrian’s main body in the controlling braking process. Research results will enhance our confidence.

Image-Based Crowd Stability Analysis Using Improved Multi-Column Convolutional Neural Network

Crowd stability analysis is an important yet challenging task, as it is difficult to obtain the quantitative information regarding a crowd in motion, for instance, the crowd count and crowd density in a pedestrian merging area. This paper proposes a novel model that can be used to accurately analyze the crowd stability based on images obtained from a real-time video surveillance system (VSS) in dense crowd scenarios. To enhance the accuracy of the human head recognition for the crowd counting and crowd density estimation, we improve the conventional convolution-neural-network (CNN) model with more columns and merged features, obtaining a four-column convolutional neural network (4C-CNN). Using more columns with receptive fields of deferent sizes, more merged features can be learned, to be adaptive to variations in pedestrian head size due to image resolution. Furthermore, the crowd density of different areas is calculated with image rectification against the perspective distortion. By utilizing the stability criterion based on crowd density, we propose a crowd stability analysis model (CSAM) with the capability of quantitative computation dynamically. The results of extensive experiments performed on public datasets indicate that this improved CNN model exhibits a better performance for crowd counting than the typical multi-column CNN models. In addition, the experiment results pertaining to Shanghai Hongqiao Railway Station demonstrate the effectiveness of the crowd stability analysis model. Thus, this integrated approach can simultaneously conduct the processes of crowd counting, image rectification, density map calculation and crowd stability analysis by using dense crowd images from a VSS.

Two-Channel SSD Pedestrian Head Detection Algorithm Based on Multi-Scale Feature fusion

Two-Channel SSD Pedestrian Head Detection Algorithm Based on Multi-Scale Feature fusion

Analysis of craniocerebral injury in facial collision accidents.

Considering that the Pc-Crash multibody dynamics software can reproduce the accident process accurately and obtain the collision parameters of pedestrian heads at the moment of head landing, the finite element analysis method can accurately analyze the injury of the pedestrian head when the boundary conditions are known. This paper combines the accident reconstruction method with the finite element analysis method to study the injury mechanism of pedestrian head impact on the ground in vehicle pedestrian collision accidents to provide a theoretical basis for pedestrian protection and the improvement of vehicle shapes. First, a real-life vehicle pedestrian collision is reproduced by Pc-Crash. The simulation results show that the rigid multibody model can accurately simulate the scene of the accident, then the speed and angle of the pedestrian head landing moment can be obtained at the same time. Second, the finite element model of human heads with a detailed facial structure is established and verified. Finally, the collision parameters obtained from the accident reconstruction are used as the boundary conditions to analyze the collision between the pedestrian head and the ground, and the biomechanical parameters, such as intracranial pressure, von Mises stress, shear stress and strain, can be determined. The results show that the stress wave will propagate inside and outside the skull and cause stress concentration in the skull and the brain tissue to varying degrees after the pedestrian head strikes the ground. When the stress exceeds a certain limit, it will cause different degrees of brain tissue injury.

Prediction of vehicle impact speed based on the post-cracking behavior of automotive PVB laminated glass: Analytical modeling and numerical cohesive zone modeling

Targeted investigation of the impact fracture performance of PVB laminated glass, which is a combined analytical and numerical method for impact dynamics prediction, is presented. In this method, the relationship between the impact force and the post-cracking response of laminated glass is developed in the framework of impact dynamics to present a prediction formulation. The formulation is utilized to be applied to predict vehicle impact speed based on the crack patterns propagated on the automotive laminated glass due to the pedestrian head impact. To prepare a numerical set-up, an automotive laminated glass finite element model is proposed by inserting cohesive elements on all common surfaces of glass layers and glass-PVB interfacial. The prediction model is validated well by comparison with numerical crash patterns and ten real vehicle–pedestrian accident cases.

Real-Time Height Measurement for Moving Pedestrians

Height measurement for moving pedestrians is quite significant in many scenarios, such as pedestrian positioning, criminal suspect tracking, and virtual reality. Although some existing height measurement methods can detect the height of the static people, it is hard to measure height accurately for moving pedestrians. Considering the height fluctuations in dynamic situation, this paper proposes a real-time height measurement based on the Time-of-Flight (TOF) camera. Depth images in a continuous sequence are addressed to obtain the real-time height of the pedestrian with moving. Firstly, a normalization equation is presented to convert the depth image into the grey image for a lower time cost and better performance. Secondly, a difference-particle swarm optimization (D-PSO) algorithm is proposed to remove the complex background and reduce the noises. Thirdly, a segmentation algorithm based on the maximally stable extremal regions (MSERs) is introduced to extract the pedestrian head region. Then, a novel multilayer iterative average algorithm (MLIA) is developed for obtaining the height of dynamic pedestrians. Finally, Kalman filtering is used to improve the measurement accuracy by combining the current measurement and the height at the last moment. In addition, the VICON system is adopted as the ground truth to verify the proposed method, and the result shows that our method can accurately measure the real-time height of moving pedestrians.

Heading Estimation for Multimode Pedestrian Dead Reckoning

The flexible carrying mode of smartphone brings challenge for Pedestrian Dead Reckoning (PDR) especially for heading estimation with build-in sensors. This paper focuses on POCKET mode and SWING mode and analyzes the correlation between smartphone's rotational motion and pedestrian's walking cycle states and walking direction. Based on the analysis, we propose to use the rotation vector sensor data of smartphone within one walking step to estimate the pedestrian's heading. For POCKET mode, heading is estimated by an improved rotational approach (IRA). A jitter detection algorithm is proposed to extract leg flexion interval. Stable walking direction without 180° ambiguity is obtained from the averaged rotation axis. For SWING mode, a single-point (SP) method is proposed. Heading is estimated from the direction of smartphone's y-axis when it is closest to the horizontal plane. The algorithms are validated with data collected by HUAWEI mate 10 smartphone. The RMS errors are less than 4.37° and 3.38° for POCKET and SWING mode respectively. Superior to previous heading estimation algorithms, our method can converge within one single walking step for both carrying modes without 180° ambiguity.

A METHOD TO CALCULATE THE AIS TRAUMA SCORE FROM A FINITE ELEMENT MODEL

In the real world, traumatic injuries are measured using the Abbreviated Injury Scale (AIS), however, such a scale cannot be computed to date or the injury precisely located by using human computer models. These models use stresses and strains to evaluate whether serious or fatal injuries are reached, which unfortunately bear no direct relation to AIS. This paper proposes to overcome this deficiency and suggests a unique Organ Trauma Model (OTM) able to calculate the risk to life of any organ injury, focussing in this case on real-life pedestrian head injuries. The OTM uses a power method, named Peak Virtual Power (PVP), and defines a brain white and gray matters trauma response as a function of impact direction and impact speed. The OTM was tested against four real-life pedestrian accidents and proved to predict the head trauma severity and location. In some cases, the method did however under-estimate the trauma by 1 AIS level because of post-impact haemorrhage which cannot be captured with Lagrangian Finite Element solvers. The OTM has the potential to create an important advance in vehicle safety by adding more information on the risk of head trauma.

Numerical investigation of the impact fracture performance of a composite laminated windshield considering the Park-Paulinho-Roesler cohesive zone model

The fracturing performance of the windshield glazing, as a simple sandwiched composite structure manufactured by bonding glass layers with polyvinyl butyral (PVB) interlayers, is indispensable to investigate the vehicle–pedestrian accidents. This paper presents an application of the simplified form of the Park–Paulino–Roesler (S-PPR) cohesive law along with fracture mechanics to the analysis of the mechanical behavior of the windshield under the pedestrian head impact, considering glass fracture and interfacial debonding. The S-PPR model calculates the damage variables in various mode-mixity cases to predict all separation paths, which yields to capturing more realistic crack patterns. A windshield finite element model is designed by embedding cohesive elements into the joint interfaces between the glass and PVB layers. The cracking mechanism of a windshield impacted by a headform impactor is simulated with a commercial explicit finite element code. Numerical simulation outcomes are validated by comparison with similar empirical observations. Furthermore, the difference between the S-PPR model and the commonly used bilinear model is investigated, in which simulation outcomes confirm that the S-PPR cohesive zone model (CZM) is more proper to capture the windshield cracking mechanisms. Ultimately, the effects of the impact locations and impact angles on the impact fracture performance of the windshield are investigated.

Intelligent video analysis: A Pedestrian trajectory extraction method for the whole indoor space without blind areas

Pedestrian trajectory extraction is an important part of intelligent monitoring, which is of great significance to many fields such as statistics on pedestrian flow and density, population behavior analysis, abnormal behavior detection, etc. However, it is quite challenging to extract pedestrian trajectory without blind areas in the whole space due to the limited view angle of ordinary cameras. So far, no efficient method has been proposed to deal with this problem. In this paper, we propose a pedestrian trajectory extraction method based on a single fisheye camera, which can realize no blind areas pedestrian trajectory extraction in the whole interior space. First, the fisheye camera with a perspective of 180∘ is adopted in our work which can realize the entire space monitoring without blind areas and avoid object matching among multiple cameras. Then, the deep convolutional neural network, the Kalman Filter algorithm, and the Hungarian algorithm are combined for pedestrian head detection and tracking. In order to calculate the coordinates of the trajectory points according to the obtained head position, we propose a novel pedestrian height estimation method for fisheye cameras. Finally, the pedestrian trajectory points are calculated based on the detected head position and the estimated height. The performance of the proposed pedestrian trajectory extraction method has been evaluated by a variety of experiments. The experimental results show that the trajectories of multiple pedestrians can be extracted simultaneously through the method proposed in this paper, and the average error of the trajectory points is less than 5.07 pixels in the 512×512 images.

Kinematics and dynamics of pedestrian head ground contact: A cadaver study

Pedestrians struck by vehicles are generally injured by the primary vehicle contact but also the secondary ground contact. However, experimental evidence for ground contact injuries is limited. Here we report on six staged cadaver tests at 20–30 km/h with passenger cars/vans in which we recorded the whole process from first pedestrian contact until after the end of the ground contact is complete using high-speed video and accelerometers mounted in the cadavers. Results show distinct phases for pedestrian flight and ground contact in addition to the already established vehicle contact phases. No skull fractures were observed in any of the tests. However, for the speed range tested, the linear and angular head injury risk (evaluated using HIC/3ms & BrIC respectively) is generally higher from the ground contact compared to the vehicle contact. Although not yet clearly understood, angular head injury risk during ground contact is higher for the 20 km/h tests compared to the 30 km/h tests. A good comparison was observed with respect to previously predicted ground contact mechanisms and head impact speeds from multibody modelling. These results emphasize the importance of ground related injuries to pedestrians when struck by vehicles at speeds of 20–30 km/h and provide a unique dataset for computational model validation of pedestrian ground contact.