Estimated crash injury risk and crash characteristics for motorsport drivers

Integrating biomechanics with stakeholder perspectives to inform safety in grassroots dirt track racing

Grassroots dirt track racing is a foundational part of motorsports with a high risk of severe injury. This study aimed to gather perspectives and experiences of motorsports drivers surrounding safety and head acceleration events experienced during grassroots dirt track racing to inform strategies to improve driver safety. Thirteen drivers (n=9 who primarily race on dirt tracks; n=4 who primarily race on pavement tracks) with prior dirt track racing experience participated in separate, group-specific focus groups and/or one-on-one interviews where video, simulations of head motion, and head acceleration data were shared. Peak kinematics of laps and crash contact scenarios were recorded, and head perturbations (i.e., deviations in head motion relative to its moving-average trajectory) were quantified for each lap and presented through guided discussion. Responses were summarized using Rapid Assessment Process. Audio recordings and field notes were collected from focus groups and interviews and analyzed across 25 domains. Drivers described dirt track racing as short, fast bursts of racing. Benefits of dirt track racing for driver development were described, including learning car control. Drivers acknowledged risks of racing and expressed confidence in safety equipment but identified areas for improvement. Drivers observed lateral bouncing of the head in video and simulations but recognized that such motions were not noticed while racing. Track conditions and track type were identified as factors influencing head perturbations. Mean PLA (5.5 g) and PRV (3.07 rad/s) of perturbations experienced during racing laps and perturbation frequencies of 5 and 7 perturbations per second were reported. Generally, drivers accurately estimated the head acceleration magnitudes but were surprised by the frequency and maximum magnitude of perturbations. Maximum perturbation magnitudes (26.8 g and 19.0 rad/s) were attributed to hitting a "rut" in the dirt. Drivers described sudden stops, vertical loads due to landing from a large height, and impacts to the vehicle frame as crash events they physically feel the most. Summary statistics for crashes (medians = 7.30 g, 6.94 rad/s) were reported. Typical impact magnitudes measured in other sports (e.g., football) were provided for context. Upon reviewing the biomechanics, drivers were surprised that crash accelerations were relatively low compared to other contact/collision sports. Pavement drivers noted limited safety features in dirt track racing compared to pavement, including rigidity of vehicle frames, seat structure, seatbelt integration, and lack of oversight from sanctioning bodies. Most drivers felt seat inserts and head and neck restraints are important for injury prevention; however, usage of seat inserts and preferred head and neck restraint system differed among drivers. Drivers described their perspectives and experiences related to safety and identified strategies to improve safety in grassroots dirt track racing. Drivers expressed support for future safety research.

Driver head kinematics in grassroots dirt track racing crashes: A pilot analysis

Motorsport athletes experience head acceleration loading during crashes; however, there is limited literature quantifying the frequency and magnitude of these loads, particularly at the grassroots level of the sport. Understanding head motion experienced during crash events in motorsport is necessary to inform interventions to improve driver safety. This study aimed to quantify and characterize driver head and vehicle kinematics during crashes in open-wheel grassroots dirt track racing. Seven drivers (ages 16-22, n = 2 female) competing in a national midget car series were enrolled in this study over two racing seasons and were instrumented with custom mouthpiece sensors. Drivers' vehicles were outfitted with an incident data recorder (IDR) to measure vehicle acceleration. Forty-one crash events were verified and segmented into 139 individual contact scenarios via film review. Peak resultant linear acceleration (PLA) of the vehicle and PLA, peak rotational acceleration (PRA), and peak rotational velocity (PRV) of the head were quantified and compared across the part of the vehicle contacted (i.e., tires or chassis), the vehicle location contacted (e.g., front, left, bottom), the external object contacted (i.e., another vehicle, wall, or the track), and the principal direction of force (PDOF). The median (95th percentile) PLA, PRA, and PRV of the head and PLA of the vehicle were 12.3 (37.3) g, 626 (1799) rad/s2, 8.92 (18.6) rad/s, and 23.2 (88.1) g, respectively. Contacts with a non-horizontal PDOF (n = 98, 71%) and contact with the track (n = 96, 70%) were common in the data set. Contact to the left side of the vehicle, with the track, and with a non-horizontal PDOF tended to have the greatest head kinematics compared to other factors in each sub-analysis. Results from this pilot study can inform larger studies of head acceleration exposure during crashes in the grassroots motorsports environment and may ultimately support evidence-based driver safety interventions.

Longitudinal Outcomes of Cumulative Impact Exposure on Oculomotor Functioning in Professional Motorsport Drivers

Importance

Professional motorsport drivers are regularly exposed to biomechanical forces comparable with those experienced by contact and collision sport athletes, and little is known about the potential short-term and long-term neurologic sequelae.

Objective

To determine whether cumulative impact exposure is associated with oculomotor functioning in motorsport drivers from the INDYCAR professional open-wheel automobile racing series.

Design, Setting, and Participants

This is a longitudinal retrospective cohort study conducted across 3 racing seasons (2017-2019). Statistical analyses were conducted in November 2021. Data were retrieved from a secondary care setting associated with the INDYCAR series. INDYCAR series drivers who participated in 3 professional level racing seasons and were involved in at least 1 contact incident (ie, crash) in 2 of the 3 seasons were included in the study.

Exposure

Cumulative acceleration and deceleration forces and total contact incidents (ie, crashes) measured via accident data recorder third generation chassis and ear accelerometers.

Main Outcomes and Measures

Postseries oculomotor performance, including predictive saccades, vergence smooth pursuit, and optokinetic nystagmus, was measured annually with a head-mounted, clinical eye tracking system (Neurolign Dx 100).

Results

Thirteen drivers (mean [SD] age, 29.36 [7.82] years; all men) sustained median resultant acceleration forces of 38.15 g (observed range, 12.01-93.05 g; 95% CI, 30.62-65.81 g) across 81 crashes. A 2-way multivariate analysis of variance did not reveal a statistically significant association between ear and chassis average resultant g forces, total number of contact incidents, and racing season assessed (F9,12 = 0.955; P = .54; Wilks Λ = 0.44).

Conclusions and Relevance

In this cohort study of professional drivers from the INDYCAR series, there were no statistically significant associations among cumulative impact exposure, racing season assessed, and oculomotor performance. Longitudinal studies across racing seasons using multidimensional examination modalities (eg, neurocognitive testing, advanced imaging, biomarkers, and physical examination) are critical to understand potential neurological and neurobehavioral sequelae and long-term consequences of cumulative impact exposure.

Effect of body size and enhanced helmet systems on risk for motorsport drivers

OBJECTIVE

Computational modeling has been shown to be a useful tool for simulating representative motorsport impacts and analyzing data for relative injury risk assessment. Previous studies have used computational modeling to analyze the probability of injury in specific regions of a 50th percentile male driver. However, NASCAR drivers can represent a large range in terms of size and female drivers are becoming increasingly more common in the sport. Additionally, motorsport helmets can be outfitted with external attachments, or enhanced helmet systems (EHS), whose effect is unknown relative to head and neck kinematics. The current study expands on this previous work by incorporating the F05-OS and M95-OS into the motorsport environment in order to determine correlations between metrics and factors such as PDOF, resultant ΔV occupant size, and EHS.

METHODS

A multi-step computational process was used to integrate the Global Human Body Models Consortium family of simplified occupant models into a motorsport environment. This family included the 5th percentile female (F05-OS), 50th percentile male (M50-OS), and 95th percentile male (M95-OS), which provide a representative range for the size and sex of drivers seen in NASCAR's racing series'. A series of 45 representative impacts, developed from real-world crash data, and set of observed on-track severe impacts were conducted with these models. These impacts were run in triplicate for three helmet configurations: bare helmet, helmet with visor, helmet with visor and camera. This resulted in 450 total simulations. A paired t-test was initially performed as an exploratory analysis to study the effect of helmet configuration on 10 head and neck injury metrics. A mixed-effects model with unstructured covariance matrix was then utilized to correlate the effect between five independent variables (resultant ΔV, body size, helmet configuration, impact quadrant, and steering wheel position) and a selection of 25 metrics. All simulations were conducted in LS-Dyna R. 9.1.

RESULTS

Risk estimates from the M50-OS with bare helmet were used as reference values to determine the effect of body size and helmet configuration. The paired t-test found significance for helmet configuration in select head-neck metrics, but the relative increase in these metrics was low and not likely to increase injury risk. The mixed-effects model analyzed statistical relationships across multiple types of variables. Within the mixed-effects model, no significance was found between helmet configuration and metrics. The greatest effect was found from resultant ΔV, body size, and impact quadrant.

CONCLUSIONS

Overall, smaller drivers showed statistically significant reductions in injury metrics, while larger drivers showed statistically significant increases. Lateral impacts showed the greatest effect on neck metrics and, on average, showed decreases for head metrics related to linear acceleration and increases for head metrics related to angular velocity. HBM parametric studies such as this may provide an avenue to assist injury detection for motorsport incidents, improve triage effectiveness, and assist in the development of safety standards.

Deriving a joint risk estimate from dynamic data collected at motorcycle rides

Making motorcycle rides safer by advanced technology is an ongoing challenge in the context of developing driving assistant systems and safety infrastructure. Determining which section of a road and which driving behaviour is "safe" or "unsafe" is rarely possible due to the individual differences in driving experience, driving style, fitness and potentially available assistant systems. This study investigates the feasibility of a new approach to quantify motorcycle riding risk for an experimental sample of bikers by collecting motorcycle-specific dynamic data of several riders on selected road sections. Comparing clustered dynamics with the observed dynamic data at known risk spots, we provide a method to represent individual risk estimates in a single risk map for the investigated road section. This yields a map of potential risk spots, based on an aggregation of individual risk estimates. The risk map is optimized to include most of the previous accident sites, while keeping the overall area classified as risky small. As such, with data collected on a large scale, the presented methodology could guide safety inspections at the highlighted areas of a risk map and be the basis of further studies into the safety relevant differences in driving styles.

An Improved Method for Developing Injury Risk Curves Using the Brier Metric Score

Many injury metrics are routinely proposed from measured or derived quantities from biomechanical experiments using post mortem human subjects (PMHS). The existing literature did not provide guidance on deciding between parameters collected in an experiment that would be best to use for the development of human injury probability curves (HIPC). The objective of this study was to use the Brier Metric Score (BMS) to identify the most appropriate metric from an experiment that predicts injury outcomes. The Brier Metric Score assesses how well a metric predicts the outcome for a censored data point (a lower BMS is better). Survival analysis was then conducted with the selected metric and the best distribution was selected using Akaike information criterion (AIC). Confidence intervals (CIs) and the normalized confidence interval width (NCIS) were calculated for the injury probability curve. The testing and validation of the methods described were performed using biomechanics data in the open literature. The methods for the HIPC development procedure detailed herein have been rigorously tested and used in the generation of WIAMan HIPCs and Injury Assessment Reference Curves (IARCs) for the WIAMan ATD, but can also be used in other ATD or PMHS injury risk curve development.

Simulation-based assessment of injury risk for an average male motorsport driver

OBJECTIVE

While well-protected through a variety of safety countermeasures, motorsports drivers can be exposed to a large variety of crash modes and severities. Computational human body models (HBMs) are currently used to assess occupant safety for the general driving public in production vehicles. The purpose of this study was to incorporate a HBM into a motorsport environment using a simulation-based approach and provide quantitative data on relative risk for on-track motorsport crashes.

METHODS

Unlike a traditional automotive seat, the NASCAR driver environment is driver-customized and form-fitting. A multi-step process was developed to integrate the Global Human Body Models Consortium (GHBMC) 50th percentile male simplified occupant into a representative motorsport environment which includes a donned helmet, a 7-point safety belt system, head and neck restraint (HNR), poured-foam seat, steering wheel, and leg enclosure. A series of 45 representative impacts, developed from real-world crash data, of varying severity (10 kph ≤ ΔV ≤ 100 kph) and impact direction (∼290° ≤ PDOF ≤ 20°) were conducted with the GHBMC 50th percentile male simplified occupant (M50-OS v2.2). Kinematic and kinetic data, and a variety of injury criteria, were output from each of the simulations and used to calculate AIS 1+, 2+, and 3+ injury risk. All simulations were conducted in LS-Dyna R. 9.1.

RESULTS

Injury risk of the occupant using the previously mentioned injury criteria was calculated for the head, neck, thorax, and lower extremity, and the probability of injury for each region was plotted. Of the simulated impacts, five had a maximum AIS 1+ injury risk >20%, six had a maximum AIS 2+ injury risk >10%, and no cases had a maximum AIS 3+ injury >1%. Overall, injury risk estimates were reasonable compared to on-track data reported from Patalak et al. (2020).

CONCLUSIONS

Beyond injury risk, the study is the first of its kind to provide mechanical loading values likely experienced during motorsports crash incidents with crash pulses developed from real-world data. Given the severity of the crash pulses, the simulated environments reinforce the need for the robust safety environment implemented by NASCAR.