Are electric self-balancing scooters safe in vehicle crash accidents?

Trajectory planning framework for autonomous vehicles based on collision injury prediction for vulnerable road users

Due to the escalating occurrence and high casualty rates of accidents involving Electric Two-Wheelers (E2Ws), it has become a major safety concern on the roads. Additionally, with the widespread adoption of current autonomous driving technology, a greater challenge has arisen for the safety of vulnerable road participants. Most existing trajectory planning methods primarily focus on the safety, comfort, and dynamics of autonomous vehicles themselves, often overlooking the protection of vulnerable road users (VRUs), typically E2W riders. This paper aims to investigate the kinematic response of E2Ws in vehicle collisions, including the 15 ms Head Injury Criterion (HIC15). It analyzes the impact of key collision parameters on head injuries, establishes injury prediction models for anticipated scenarios, and proposes a trajectory planning framework for autonomous vehicles based on predicting head injuries of VRUs. Firstly, a multi-rigid-body model of two-wheeler-vehicle collision was established based on a real accident database, incorporating four critical collision parameters (initial collision velocity, initial collision position, and collision angle). The accuracy of the multi-rigid-body model was validated through verifications with real fatal accidents to parameterize the collision scenario. Secondly, a large-scale effective crash dataset has been established by the multi-parameterized crash simulation automation framework combined with Monte Carlo sampling algorithm. The training and testing of the injury prediction model were implemented based on the MLP + XGBoost regression algorithm on this dataset to explore the potential relationship between the head injuries of the E2W riders and the crash variables. Finally, based on the proposed injury prediction model, this paper generated a trajectory planning framework for autonomous vehicles based on head collision injury prediction for VRUs, aiming to achieve a fair distribution of collision risks among road users. The accident reconstruction results show that the maximum error in the final relative positions of the E2W, the car, and the E2W rider compared to the real accident scene is 11 %, demonstrating the reliability of the reconstructed model. The injury prediction results indicate that the MLP + XGBoost regression prediction model used in this article achieved an R2 of 0.92 on the test set. Additionally, the effectiveness and feasibility of the proposed trajectory planning algorithm were validated in a manually designed autonomous driving traffic flow scenario.

Analysis of the consequences of car to micromobility user side impact crashes

INTRODUCTION

The strong rise in modes of travel commonly referred to as micromobility has changed the mobility patterns and lifestyles in cities worldwide, especially after the COVID-19 pandemic. It has led to a significant increase in the number of crashes involving these types of vehicles, especially bicycles and stand-up e-scooters. The risk of crashes is higher at intersections where motor-vehicles perform a turning maneuver crossing a bike lane.

METHOD

The consequences of a passenger car-to-micromobility vehicle side-impact crashes, considering both bicycle and e-scooter, were studied based on the results of the simulation of several scenarios with PC-Crash software. Two injury criteria were applied: Head Injury Criterion (HIC15) and 3 ms chest acceleration criterion.

RESULTS

When motor-vehicle speed is lower than 50 km/h, the 3 ms chest acceleration never exceeds the 60 g threshold. However, at 50 km/h, it is close to 50 g in the case of e-scooter rides. At this speed, HIC15 is considerably greater than 1000, both for bicycles and for e-scooters, and the safety margin of 700 is exceeded at 45 km/h for e-scooters.

CONCLUSIONS

In case of motor vehicle-to-micromobility vehicle side-impact crash, riding a bicycle is safer than riding an e-scooter since the observed HIC15 experienced by the cyclists is lower than that experienced by the e-scooter rider when motor vehicle speed is greater than 30 km/h.

PRACTICAL APPLICATIONS

To reduce micromobility users injury risk at intersections, motor vehicle speed limit should be equal or lower than 40 km/h. At this impact speed, the activation of hood or bumper airbags could be justified.

Kinematic responses of child as second rider of electric-two-wheelers under lateral impact with vehicle

Electric-two-wheeler (E2W) related accidents have become a major safety concern on road due to the growing prevalence and the high casualty rate. Most existing studies focus on drivers of the E2W, while ignore the second rider (usually a child) as passenger. This study aims at investigating the kinematic response of the child rider upon vehicle impact and analyzing how motion patterns are influenced by the geometric parameters of the vehicle and E2W. A computational framework was established for the intended task. We modeled the E2W-rider system in Madymo, including an E2W with parametric geometry and two riders, one adult and one child respectively. This study focuses on lateral impact in terms of the accident scenarios, as the case dominates in the field data reports. Vehicle types, seating height of the E2W and sitting position of the child rider were considered as variables in the simulation matrix. Results show that the relative height between child's sitting and vehicle hood front-edge, and the sitting position (back-seated or front-seated) are two main influencing parameters on kinematic responses of child rider. The child rider tends to bounce higher on hood upon impact when sitting above the hood front-edge, while might be laterally pushed away by the car-front when sitting below the hood front-edge. Meanwhile, back-seated child rider is more likely to rise higher and rotate faster upon impact compared to a front-seated one. These findings may guide safe riding and safety countermeasure development for child riders of E2W.

Head impact kinematics and injury risks during E-scooter collisions against a curb

E-scooters as a mode of transportation is rapidly growing in popularity. This study evaluates head impact conditions and injury risk associated with E-scooter crashes. A multibody model of E-scooter falls induced by wheel-curb collision was built and compared with an experimental E-scooter crash test. A total of 162 crash scenarios were simulated to assess the effect of fall conditions (E-scooter initial speed and inclination, obstacle orientation, and user size) on the head impact kinematics. The forehead hit the ground first in 44% of simulations. The average tangential and normal impact speeds were 3.5 m/s and 4.8 m/s respectively. Nearly 100% of simulations identified a risk of concussion (linear acceleration peak >82 g and rotational acceleration peak >6383 rad/s2) and 90% of simulations suggested a risk of severe head injuries (HIC>700). This work provides preliminary data useful for the assessment and design of protective gears.

Mapping the knowledge of traffic collision Reconstruction: A scientometric analysis in CiteSpace, VOSviewer, and SciMAT

Traffic collisions are incidents with high fatality rate which generate billions of US dollars of loss worldwide each year. Post-collision scene reconstruction, which involves knowledge of multiple disciplines, is an important approach to restore the traffic collision and infer the cause of it. This paper uses software CiteSpace, VOSviewer, and SciMAT to conduct a visualization study of knowledge mapping on the literature of traffic collision scene reconstruction from 2001 to 2021 based on the Web of Science database. Knowledge mapping is a cutting-edge research method in scientometric, which has been widely applied in medicine and informatics. Compared with traditional literature review, knowledge mapping with visual techniques identifies hot keywords and key literature in the field more scientifically, and displays them in schematic diagrams intuitively which allows to further predict potential hotspots. A total of 803 original papers are retrieved to analyze and discuss the evolution of the field in the past 20 years, from macro to micro, in term of background information, popular themes, and knowledge structure. Results indicate the number of publications in this field is limited, and collaborations among authors and among institutions are insufficient. In the meantime, mappings imply the top three hot themes being scene reconstruction, computer technology, and injuries. The introduction of AI related technologies, such as neural networks and genetic algorithms, into collision reconstruction would be a potential research direction.

Characterizing the effects of contributing factors on crash severity involving e-bicycles: a study based on police-reported data

Mitigating e-bicycle crash occurrence has become a great challenge across the world. It is of paramount importance for improving traffic safety to characterize the relationship between e-bicycle crash injury severities and contributing factors. This study positions itself at clarifying the roles of the factors in e-bicycle crashes from time, space, road, environment, rider and object characteristics. The partial proportional odds (PPOs) model as well as its elasticity analysis was employed to identify the influences based on 15,138 police-reported e-bicycle crashes in Shangyu District of Shaoxin City, China. The results evidenced that there were 12 factors having significant effects. Especially, the results emphasized the greater influences of rider gender, age, object hit and road type. Their maximum of the absolutes of elasticities was greater than 24%. Increased crash severity was associated with females, younger riders, and higher speed collisions. However, the remaining significant variables had minor effects (no more than 10%). The findings provide meaningful insights for advancing e-bicycle development, when making related policies and prioritizing safety countermeasures.

Numerical investigation of the rider's head injury in typical single-electric self-balancing scooter accident scenarios

As the use of electric self-balancing scooters (ESSs) increases, so does the number of related traffic accidents. Because of the special control method, mechanical structure and driving posture, ESSs are prone to various single-vehicle accidents, such as collisions with fixed obstacles and falls due to mechanical failures. In various ESS accident scenarios, the rider's head injury is the most frequent injury type. In this study, several typical single-ESS accident scenarios are reconstructed via computational methods, and the risk of riders' head/brain injury is assessed in depth using various injury criteria. Results showed that two types of ESSs (solo- and two-wheeler) do not have clear differences in head kinematics and head injury risks; the head kinematics (or falling posture) and ESS accident scenario exhibit a distinct effect on the head injury responses; half of the analysed ESS riders have a 50% probability of skull fracture, a few riders have a 50% risk of abbreviated injury scale (AIS) 4+ brain injury, and none has a diffuse axonal injury; the ESS speed plays an important role in producing the head/brain injury in ESS riders, and generally, higher ESS speed generates higher level of predicted head injury parameters. These findings will provide theoretical support for preventing head injury among ESS riders and data support for developing and legislating ESSs.

Computational prediction of head-ground impact kinematics in e-scooter falls

E-scooters are the fastest growing mode of micro-mobility with important environmental benefits. However, there are serious concerns about injuries caused by e-scooter accidents. Falls due to poor road surface conditions are a common cause of injury in e-scooter riders, and head injuries are one of the most common and concerning injuries in e-scooter falls. However, the head-ground impact biomechanics in e-scooter falls and its relationship with e-scooter speed and design, road surface conditions and wearing helmets remain poorly understood. To address some of these key questions, we predicted the head-ground impact force and velocity of e-scooter riders in different falls caused by potholes. We used multi-body dynamics approach to model a commercially available e-scooter and simulate 180 falls using human body models. We modelled different pothole sizes to test whether the pothole width and depth influences the onset of falls and head-ground impact velocity and force. We also tested whether the e-scooter travelling speed has an influence on the head-ground impact velocity and force. The simulations were carried out with three human body models to ensure that the results of the study are inclusive of a wide range of rider sizes. For our 10 in. diameter e-scooter wheels, we found a sudden increase in the occurrence of falls when the pothole depth was increased from 3 cm (no falls) to 6 cm (41 falls out of 60 cases). When the falls occurred, we found a head-ground impact force of 13.2 ± 3.4kN, which is larger than skull fracture thresholds. The head-ground impact speed was 6.3 ± 1.4 m/s, which is the same as the impact speed prescribed in bicycle helmet standards. All e-scooter falls resulted in oblique head impacts, with an impact angle of 65 ± 10° (measured from the ground). Decreasing the e-scooter speed reduced the head impact speed. For instance, reducing the e-scooter speed from 30 km/h to 20 km/h led to a 14% reduction in the mean impact speed and 12% reduction in the mean impact force, as predicted by the models. The models also showed that the median male riders were sustaining higher head-ground impact force and speed compared with the small female and large male riders. The findings of this study can assist authorities and e-scooter hiring companies to take more informed actions about road surface conditions and speed limits. These results can also help define representative impact test conditions for assessing the performance of helmets used by e-scooter riders in order to reduce head and brain injuries in e-scooter falls.

Assessment of standing passenger traumatic brain injury caused by ground impact in subway collisions

Human head is the most vulnerable region in subway collisions. To design a safer subway, the head impact biomechanical response should be studied first. This paper aims to investigate the standing passenger head-ground impact dynamic response and traumatic brain injury (TBI) in subway collisions. A standing passenger-subway interior dynamic model was numerically developed by using our previous validated finite element (FE)-multibody (MB) coupled human body model, which was integrated by the Total Human Model for Safety (THUMS) head-neck FE model and the extracted remaining body segments pedestrian MB model of TNO. A parametric study considering the handrail type, standing angle, and friction coefficient between the shoes and ground was performed. Results show that the passenger dynamic response could be divided into two categories according to whether the passenger hit handrails. Passenger TBIs severity could be efficiently alleviated by the passenger body (excluding the head) hitting the handrail first before head-ground impact. The probabilities of DAI in the cerebellum and brain stem were low. A statistical analysis of TBIs demonstrated that the risks of TBIs were sensitive to the handrail type in subway collisions, but did not to the standing angle and friction coefficient. This study provides practical help for improving the interior crashworthiness performance of subways.

Analysis of electric scooter user kinematics after a crash against SUV

The article presents the results of the analysis of electric scooter user kinematics after a crash against a vehicle. The share of electric scooters (e-scooters) in urban traffic has been growing in recent years. The number of road accidents involving e-scooters is also increasing. However, the safety situation of electric scooter users is insufficiently researched in terms of kinematics and injury outcomes. The article presents the importance of this problem based on an in-depth literature analysis of e-scooter-related types of accidents, injuries percentages, and helmet use. Subsequently, four accident scenarios were designed and simulated using two numerical codes–LS-DYNA for handling finite element (FE) code (the vehicle and scooter model) and MADYMO for multibody code (dummy model). Scenario one is a side bonnet crash that simulates an accident when the scooter drives into the side-front of the vehicle. The second and the third simulation is a side B-pillar crash, which was divided into two dummy’s positions: the squat and up-right. The fourth simulation is a frontal impact. For each scenario, subsequent frames describing the dummy movement are presented. The after-impact kinematics for various scenarios were analyzed and discussed. The plots of the dummy’s head linear acceleration and its magnitude for the analyzed scenarios were provided. As the study is devoted to increasing riders safety in this means of transportation, the potential directions for further research were indicated.

Electric Scooter-Related Injuries: A New Epidemic in Orthopedics

Background: The use of electric scooters has increased considerably as they are an accessible means of transportation. The number of injuries from falls and collisions has risen significantly. Therefore, the aim of the study was to describe demographics injury patterns of electric scooter accidents produced over one year. Methods: A prospective observational study of electric scooter- related injuries presented in the emergency room from May 2019 until May 2020. The inclusion criteria was based on the direct cause of injury produced while an electric scooter was in use. Demographic data, the use of a helmet or the lack thereof, accident mechanism, injury time, type of injury produced, and the treatment applied were collected. Results: Over the study period, 397 patients were identified with a total of 422 injuries. The mean age was 30.8 years, with 12.6% of patients being minors. The patients mainly presented in evening hours and in summertime at the emergency department. Of the total injuries seen, 46.9% were fractures. Some 25% of the total cases required surgery. Only 19% of the riders wore a helmet at the time of the accident. Most of the fractures were to the upper limbs (62.6%). There was a greater incidence of radius fractures. Conclusion: Injuries incurred while using electric scooters are an emerging phenomenon, despite existing regulations. In this study, most injuries occurred in young men and were due to falls from the vehicle. Nearly half of those injuries were fractures to the upper limbs. Surprisingly, 50% of the fractures required surgery.

Assessing the Willingness to Use Personal e-Transporters (PeTs): Results from a Cross-National Survey in Nine European Cities

In the last few years, there has been a strong increase in the interest in and usage of so-called “Personal e-Transporters” (PeTs), also referred to as micro-mobility devices. Empirical research on the usage of PeTs as a transport mode is virtually non-existent, especially within Europe. This paper aims to fill this gap by investigating people’s motivations and barriers to the use of PeTs. To this end, a behavioural survey was conducted in nine European cities. A representative sample of approximately 250 respondents per city was collected, resulting in a dataset, after data cleaning, of 2159 observations. Generally, respondents’ perceptions of PeTs are not (yet) very favourable. Respondents’ perceptions related to cost and safety received the lowest scores. The results from the transtheoretical model of behavioural change show that a variety of factors influence the stage of behavioural change in which the respondents can be situated. These factors include cycling norms, current walking behaviour, walking attitudes, pro-environmental orientation, gender, PeTs possession, cycling obstacles and subscription to a bicycle sharing service. An important strength of this study lies in the international nature and the size of the data collection, ensuring the reliability and transferability of the results to other cities. To the best of our knowledge, it is the first large-scale survey to investigate people’s travel behaviour related to the usage of PeTs and possibly the only large-scale investigation that took place before the deployment of shared e-scooters in many European cities. Furthermore, an explicit link is made with other modes of active transport (walking and cycling).

Survey on e-Powered Micro Personal Mobility Vehicles: Exploring Current Issues towards Future Developments

Nowadays, the diffusion of electric-powered micro Personal Mobility Vehicles (e-PMVs) worldwide—i.e., e-bikes, e-scooters, and self-balancing vehicles—has disrupted the urban transport sector. Furthermore, this topic has captured many scholars and practitioners’ interest due to multiple issues related to their use. Over the past five years, there has been strong growth in the publication of e-PMV studies. This paper reviews the existing literature by identifying several issues on the impact that e-PMVs produce from different perspectives. More precisely, by using the PRIMA’s methodological approach and well-known scientific repositories (i.e., Scopus, Web of Science, and Google Scholar), 90 studies between 2014 and 2020 were retrieved and analyzed. An overview and classification into endogenous issues (e.g., impact on transport and urban planning) and exogenous issues (e.g., impact on safety and the environment) are provided. While several issues are deeply investigated, the findings suggest that some others need many improvements. Therefore, the status quo of these studies is being assessed to support possible future developments.

Characterization of electric scooter injuries over 27 months at an urban level 1 trauma center

BACKGROUND

Electric scooters (e-scooters) have become a widespread method of transportation. The purpose of this study is to provide risk stratification tools for modifiable risk factors associated with e-scooter injury morbidity.

METHODS

Patients at an urban Level 1 Trauma center sustaining e-scooter injuries between November 2017 through March 2020 were identified. Primary outcomes of interest were major trauma, as defined by an Injury Severity Score (ISS) >15, or hospital admission.

RESULTS

A total of 442 patients sustained orthopaedic (51%), facial (31%), cranial (13%), and chest/abdominal injuries (4.5%). Rate of helmet use was 2.5%, hospital admission was 40.7%, and intensive care was 3%. Patients with facial injuries were half as likely to sustain major trauma as compared to orthopaedic injuries (p < 0.05). Factors with higher likelihood of hospital admission included age > 40 years (OR 4.20, p < 0.01), alcohol or other substance intoxication (OR 4.14 and 9.87, p < 0.001), loss of consciousness (OR 2.72, p < 0.003), or transport to the hospital by ambulance (OR 4.47, p < 0.001).

CONCLUSIONS

There is a substantial proportion of major trauma within e-scooter injuries. Modifiable risk factors for hospital admission include use of head protection and substance use while riding e-scooters.

Financial impact of electric scooters: a review of injuries over 27 months at an urban level 1 trauma center (cost of e-scooter injuries at an urban level 1 trauma center)

BACKGROUND

Electric scooters (e-scooters) have become a widespread method of transportation due to convenience and affordability. However, the financial impact of medical care for sustained injuries is currently unknown. The purpose of this study is to characterize total billing charges associated with medical care of e-scooter injuries.

METHODS

A retrospective review of patients with e-scooter injuries presenting to the trauma bay, emergency department or outpatient clinics at an urban level 1 trauma center was conducted from November 2017 to March 2020. Demographic and clinical data were collected. Primary outcomes of interest were total billing charges and billing to insurance (hospital and professional). Multivariable models were used to identify preventable risk factors associated with higher total billing charges.

RESULTS

A total of 63 patients were identified consisting of 42 (66.7%) males, average age 40.19 (SD 13.29) years and 3.2% rate of helmet use. Patients sustained orthopedic (29%, n=18), facial (48%, n=30) and cranial (23%, n=15) injuries. The average total billing charges for e-scooter clinical encounters was $95 710 (SD $138 215). Average billing to insurance was $86 376 (SD $125 438) for hospital charges and $9 334 (SD $14 711) for professional charges. There were no significant differences in charges between injury categories. On multivariable regression, modifiable risk factors independently associated with higher total billing charges included any intoxication prior to injury ($231 377 increase, p=0.02), intracranial bleeds ($75 528, p=0.04) and TBI ($360 898, p=0.006).

DISCUSSION

Many patients sustain high-energy injuries during e-scooter accidents with significant medical and financial consequences. Further studies may continue expanding the financial impact of e-scooter injuries on both patients and the healthcare system.

LEVEL OF EVIDENCE

III.

The predictive capacity of the MADYMO ellipsoid pedestrian model for pedestrian ground contact kinematics and injury evaluation

Pedestrian injuries occur in both the primary vehicle contact and the subsequent ground contact. Currently, no ground contact countermeasures have been implemented and no pedestrian model has been validated for ground contact, though this is needed for developing future ground contact injury countermeasures. In this paper, we assess the predictive capacity of the MADYMO ellipsoid pedestrian model in reconstructing six recent pedestrian cadaver ground contact experiments. Whole-body kinematics as well as vehicle and ground contact related aHIC (approximate HIC) and BrIC scores were evaluated. Reasonable results were generally achieved for the timings of the principal collision events, and for the overall ground contact mechanisms. However, the resulting head injury predictions based on the ground contact HIC and BrIC scores showed limited capacity of the model to replicate individual experiments. Sensitivity studies showed substantial influences of the vehicle-pedestrian contact characteristic and certain initial pedestrian joint angles on the subsequent ground contact kinematics and injury predictions. Further work is needed to improve the predictive capacity of the MADYMO pedestrian model for ground contact injury predictions.

The Orthopedic Injury Burden of Personal Mobility Devices in Singapore - Our Experience in the East Coast

PURPOSE

Personal mobility devices (PMDs) have become increasingly popular as a modality of transport worldwide. Starting out as novelty toys, PMDs are gradually being adopted as the mainstream mode of travel. There is an increasing number of accidents involving both PMD riders and other road users since its introduction, leading to a concomitant increase in demand for healthcare resources to manage the injuries. The main objective of this study was to evaluate the inpatient cost and the orthopedic injury pattern due to PMD accidents.

METHODS

All patients admitted to the Department of Orthopedic Surgery between December 2016 to February 2018 with injuries due to PMD accidents were recruited. Data collection was performed retrospectively on the demographic profiles, injury patterns, admission related outcomes and expenditures of these patients.

RESULTS

43 patients were included in this study. The mean duration of admission was 7.81 days and the median cost of admission was S$7835.01 (approximately US$5620). These were comparable to accidents arising from other modes of transport, such as motorcycles and bicycles. In addition, more than 80% of patients were not wearing protective gear at time of accident. These patients had a slightly higher median cost payable per patient as compared to those who donned protective gear, with a difference of S$1669.78 (approximately US$1221).

CONCLUSION

There is a significant health and financial cost to the individual and society from PMD injuries and admission. This can be reduced with strict regulations on PMD use, advocating protective gear use, and promoting awareness on safety measures and the consequences of PMD accidents. The most common injury mechanism and orthopedic injury type for PMD accidents are different from motorcycle accidents.

Methods for fusing uncertain results obtained from different models in accident reconstruction

Considering that almost all existing solutions of fusing different reconstructed results require experts’ opinions and the issue of how to fuse probabilistic results and mixed results has not been discussed. Two solutions are proposed. The first is based on the Monte Carlo Method (FMCM), while the second is based on the Sub-Interval Technique (FSIT). The method based on FMCM generates sample points according to the distribution of each uncertain result firstly, and then gives out the cumulative distribution function of the final fused result by statistical analysis. The method based on FSIT gets the result fusion interval set according to lower and upper bounds of all interval results and a given length d of each sub-interval firstly, and then calculate the weighted matrix of the result fusion interval. As a result, the cumulative distribution function of the final fused result can also be given out by statistical analysis. Finally, three real accidents are given to demonstrate the methods of FMCM and FSIT, the results of which show that both work well in practice.

Determination of Electricity Demand by Personal Light Electric Vehicles (PLEVs): An Example of e-Motor Scooters in the Context of Large City Management in Poland

Personal light electric vehicles (PLEVs) are a phenomenon that can currently be observed in cities, intended to be an ecological form of transport. The authors of the paper make an attempt to determine electricity consumption by PLEVs in the context of managing a large city in accordance with the concept of sustainable development. The article is of a cognitive nature. Research questions posed against the background of the goal formulated are as follows: how strong will the demand for PLEVs be (in the example of e-motor scooters, taking into consideration the number of vehicles) and for the electricity consumed by PLEVs. The method used is a simulation model. The conducted analyses demonstrate that a dynamic growth of PLEVs will result in an increased energy demand, which must be taken into account by the cities, developing according to the sustainable development conception.

An Investigation of Dynamic Responses and Head Injuries of Standing Subway Passengers during Collisions

With the development of the subway and the pressing demand of environmentally friendly transportation, more and more people travel by subway. In recent decades, the issues about passenger passive safety on the train have received extensive attention. In this research, the head injury of a standing passenger in the subway is investigated. Three MADYMO models of the different standing passenger postures, defined as baseline scenarios, are numerically set up. HIC₁₅ values of passengers with different postures are gained by systematic parametric studies. The injury numerical simulation results of various scenarios with different friction coefficients, collision acceleration, standing angle, horizontal handrail height, and ring handrail height are analyzed. Results show that the horizontal handrail provides better protection in the three different standing passenger postures. Different friction coefficients and the standing angle have great impact on the head injuries of passengers in three different scenarios. The handrail height also has some effects on head injury of passengers with different standing postures, so it is necessary to be considered when designing the interior layout of the subway. This study may provide guidance for the safety design of the subway and some advices for standing subway passengers.

A STUDY ON MOTORCYCLISTS HEAD INJURIES IN CAR–MOTORCYCLE ACCIDENTS BASED ON REAL-WORLD DATA AND ACCIDENT RECONSTRUCTION

Accident data had shown that as one of the most vulnerable road users, the risk of motorcyclist casualties due to head injuries is extremely high in motorcycle accidents. The objective of this study was to analyze motorcyclist head injury based on epidemiological statistical analysis and car–motorcycle accident reconstruction using real world accident data, and obtain a comprehensive understanding about safety effects of helmets on motorcyclists head injury. In epidemiological data analysis of this study, odds ratios (ORs) was applied to identify differences in injuries between helmeted and unhelmeted motorcyclists. Two vehicle–motorcycle collisions with detailed information were reconstructed by using PC-Crash simulation and MADYMO reconstruction. Furthermore, the head injury reconstruction using MADYMO outputs as boundary conditions was accomplished and analyzed with respect to 1st principal strain, Von Mises stress, coup pressure, countercoup pressure at the cerebrum. The results indicated that unhelmeted motorcyclists were more likely to suffer head injury, serious and fatal injury, and tend to take equal responsibility or more. 1st principal strain was reduced from 0.44 to 0.25 for Case 1, and from 0.16 to 0.10 for case 2 when including a helmet. Von Mises stress were reduced from 30.37[Formula: see text]kpa to 19.51[Formula: see text]kpa for Case 1 and from 3.42[Formula: see text]kpa to 3.03[Formula: see text]kpa for case when including a helmet, which meant a reduction of the risk of concussion. But the motorcyclist in Case 2 experienced a lower percentage increase in coup pressure and countercoup pressure. This study provided comprehensive knowledge on motorcyclists head injuries and the effectiveness of helmets as well as contributing to develop the injury prevention measures and protection devices of motorcyclists.

Numerical Investigation on Head and Brain Injuries Caused by Windshield Impact on Riders Using Electric Self-Balancing Scooters

To investigate head-brain injuries caused by windshield impact on riders using electric self-balancing scooters (ESS). Numerical vehicle ESS crash scenarios are constructed by combining the finite element (FE) vehicle model and multibody scooter/rider models. Impact kinematic postures of the head-windshield contact under various impact conditions are captured. Then, the processes during head-windshield contact are reconstructed using validated FE head/laminated windshield models to assess the severity of brain injury caused by the head-windshield contact. Governing factors, such as vehicle speed, ESS speed, and the initial orientation of ESS rider, have nontrivial influences over the severity of a rider's brain injuries. Results also show positive correlations between vehicle speed and head-windshield impact speeds (linear and angular). Meanwhile, the time of head-windshield contact happens earlier when the vehicle speed is faster. According to the intensive study, windshield-head contact speed (linear and angular), impact location on the windshield, and head collision area are found to be direct factors on ESS riders' brain injuries during an impact. The von Mises stress and shear stress rise when relative contact speed of head-windshield increases. Brain injury indices vary widely when the head impacting the windshield from center to the edge or impacting with different areas.

Comparative analyses of bicyclists and motorcyclists in vehicle collisions focusing on head impact responses

To investigate the differences of the head impact responses between bicyclists and motorcyclists in vehicle collisions. A series of vehicle–bicycle and vehicle–motorcycle lateral impact simulations on four vehicle types at seven vehicle speeds (30, 35, 40, 45, 50, 55 and 60 km/h) and three two-wheeler moving speeds (5, 7.5 and 10 km/h for bicycle, 10, 12.5 and 15 km/h for motorcycle) were established based on PC-Crash software. To further comprehensively explore the differences, additional impact scenes with other initial conditions, such as impact angle (0, π/3, 2π/3 and π) and impact position (left, middle and right part of vehicle front-end), also were supplemented. And then, extensive comparisons were accomplished with regard to average head peak linear acceleration, average head impact speed, average head peak angular acceleration, average head peak angular speed and head injury severity. The results showed there were prominent differences of kinematics and body postures for bicyclists and motorcyclists even under same impact conditions. The variations of bicyclist head impact responses with the changing of impact conditions were a far cry from that of motorcyclists. The average head peak linear acceleration, average head impact speed and average head peak angular acceleration values were higher for motorcyclists than for bicyclists in most cases, while the bicyclists received greater average head peak angular speed values. And the head injuries of motorcyclists worsened faster with increased vehicle speed. The results may provide even deeper understanding of two-wheeler safety and contribute to improve the public health affected by road traffic accidents.

Exploring the mechanisms of vehicle front-end shape on pedestrian head injuries caused by ground impact

In pedestrian-vehicle accidents, pedestrians typically suffer from secondary impact with the ground after the primary contact with vehicles. However, information about the fundamental mechanism of pedestrian head injury from ground impact remains minimal, thereby hindering further improvement in pedestrian safety. This study addresses this issue by using multi-body modeling and computation to investigate the influence of vehicle front-end shape on pedestrian safety. Accordingly, a simulation matrix is constructed to vary bonnet leading-edge height, bonnet length, bonnet angle, and windshield angle. Subsequently, a set of 315 pedestrian-vehicle crash simulations are conducted using the multi-body simulation software MADYMO. Three vehicle velocities, i.e., 20, 30, and 40km/h, are set as the scenarios. Results show that the top governing factor is bonnet leading-edge height. The posture and head injury at the instant of head ground impact vary dramatically with increasing height because of the significant rise of the body bending point and the movement of the collision point. The bonnet angle is the second dominant factor that affects head-ground injury, followed by bonnet length and windshield angle. The results may elucidate one of the critical barriers to understanding head injury caused by ground impact and provide a solid theoretical guideline for considering pedestrian safety in vehicle design.

Simulative investigation on head injuries of electric self-balancing scooter riders subject to ground impact

The safety performance of an electric self-balancing scooter (ESS) has recently become a main concern in preventing its further wide application as a major candidate for green transportation. Scooter riders may suffer severe brain injuries in possible vehicle crash accidents not only from contact with a windshield or bonnet but also from secondary contact with the ground. In this paper, virtual vehicle-ESS crash scenarios combined with finite element (FE) car models and multi-body scooter/human models are set up. Post-impact kinematic gestures of scooter riders under various contact conditions, such as different vehicle impact speeds, ESS moving speeds, impact angles or positions, and different human sizes, are classified and analyzed. Furthermore, head-ground impact processes are reconstructed using validated FE head models, and important parameters of contusion and laceration (e.g., coup or contrecoup pressures and Von Mises stress and the maximum shear stress) are extracted and analyzed to assess the severity of regional contusion from head-ground contact. Results show that the brain injury risk increases with vehicle speeds and ESS moving speeds and may provide fundamental knowledge to popularize the use of a helmet and the vehicle-fitted safety systems, and lay a strong foundation for the reconstruction of ESS-involved accidents. There is scope to improve safety for the use of ESS in public roads according to the analysis and conclusions.