On the road to retirement: Predicting nighttime driving difficulty and cessation using self-reported health factors.

Introduction: Older drivers now expect to drive longer than previous cohorts and will make up about 25% of licensed U.S. drivers by 2050. Identifying early predictors of nighttime driving difficulty, a precursor to driving retirement, can inform screening procedures and timely linkage to interventions supporting driving or transitioning to driving cessation. Methods: We examined self-reported physical and mental health baseline predictors of greater nighttime driving difficulty in five and ten years using weighted multivariate logistic analyses of 2261 drivers, aged 57 to 85, from the National Social Life, Health, and Aging Project (NSHAP). Transition matrix models describe probabilities of having greater, lesser, or the same nighttime driving difficulty after five years based on baseline driving conditions and the significant logistic model factors. We built a transition matrix tool that offers users the ability to calculate expected probabilities of change in nighttime driving difficulty based on the identified salient factors. Results: Five-year predictors of greater nighttime driving difficulty included perceived poor physical health (OR = 3.75), limitations to activities of daily living (ADLs; OR = 1.97), and clinical levels of depressive and anxiety symptoms (OR = 1.63; OR = 1.71). Excellent physical health (OR = 0.52), mental health (OR = 0.60), and any frequency of physical activity compared to 'never' were protective (OR = 0.37-0.51). Physical health, walking pain, and limitations to ADLs were predictive at ten-years. Transition models showed physical health and anxiety were most indicative of greater nighttime driving difficulty at 5-years for those reporting no difficulty at baseline, but limitations to ADLs were more predictive otherwise. Conclusions: Lay practitioners could capitalize on the use of self-report screening measures to identify older adults who may experience near-term nighttime driving difficulty. Earlier identification may better guide long-term driving retirement planning or engagement in appropriate health interventions. The transition matrix modeling tool is freely available to facilitate development and validation of related measures.

Understanding the new trends in pedestrian injury distribution and mechanism through data linkage and modeling.

The objectives of this study were to 1) collect and analyze recent pedestrian crash cases for better understanding of the pedestrian injury distribution and mechanism, 2) use computational simulations to reconstruct pedestrian cases and estimate potential benefit of pedestrian automatic emergency braking (PedAEB) in reducing pedestrian injury risks, and 3) estimate how future pedestrian crash distribution might influence priorities for pedestrian protection. Analyses of national crash-injury dataset showed that the overall number of pedestrians in crashes as well as the serious and fatal pedestrian injuries in the U.S. have been increasing in recent years. Striking vehicle type has changed (i.e., decreased proportion of passenger cars and increase of SUVs and pickup trucks) from 20 years ago mirroring changes in the fleet distribution of vehicle sales. A total of 432 pedestrian injury cases were generated by linking the Michigan trauma data and police-reported crash data from 2013 to 2018. Among the linked cases, pickup trucks and SUVs were involved in crashes with more injuries across body regions. Notably, AIS 3+ chest injuries occur at almost the same rate as lower extremity injuries. A method, combining MADYMO simulations (n = 3,500), response surface model, and data mining, was developed to reconstruct 25 linked pedestrian crash cases to estimate the effectiveness of PedAEB. Based on national field data and MADYMO simulations, PedAEB was estimated to be effective in reducing the risk of head and lower extremity injuries but is relatively less effective in reducing the risk of chest injuries. The increased proportions of SUVs and pickup trucks in the vehicle fleet and the higher penetration of PedAEB may highlight the importance of future research into chest injury risk for pedestrian protection.

U.S. vehicle occupancy trends relevant to future automated vehicles and mobility services.

OBJECTIVE: Identifying current occupant travel patterns can inform decision making regarding the design, regulation, and occupant protection systems helpful for automated vehicle systems and mobility services. METHODS: Two travel data sets were analyzed to quantify travel patterns: the 2017 National Household Travel Survey (NHTS), which provides data on household trips logged for a 24-h period, and the 2011-2015 National Automotive Sampling System-General Estimates System (NASS-GES), which contains data sampled from police-reported crashes. Analysis identified trends with driver age and gender, occupant age and gender, time of day, day of week, trip purpose, trip duration, vehicle type, as well as occupant role as solo driver, driver of others, single passenger, or multiple passengers. RESULTS: In NHTS, the median trip duration is 15 min; only 10% of trips last longer than 40 min. Trip duration does not vary with occupant role or vehicle type. Variations with trip time of day and day of week show a unimodal pattern for weekends, as well as weekday trips for those aged 55 years and older and non-solo occupants aged 18 to 29 years. Other occupant groups have a bimodal weekday travel pattern with peak trips corresponding to morning and evening rush hours.In GES, approximately half of occupants are solo drivers. Female drivers aged 55 and older travel alone 60% of the time, and drivers under age 18 and female drivers aged 30 to 54 drive alone on less than 45% of trips. Approximately 13% of occupants are single passengers, and 16% travel with a driver and at least 1 other passenger. About 16% of occupants are front seat passengers. CONCLUSIONS: This analysis of vehicle occupancy provides insights on what ridership of future automated vehicles and expanded ride-hailing services may look like. Because half of occupants are solo drivers, only 16% are multiple passengers, and median trip length is just 15 min, proposed alternative seating arrangements intended to promote comfort and passenger interaction may not represent the typical future vehicle use case in the United States. Knowledge of current occupancy patterns can help automated vehicle designers and regulators develop safe seating scenarios that meet customer needs.

Making a few talk for the many - Modeling driver behavior using synthetic populations generated from experimental data.

Understanding driver behavior is the basis for the development of many advanced driver assistance systems, and experimental studies are indispensable tools for constructing appropriate driver models. However, the high cost associated with testing is a serious obstacle in collecting large amounts of experimental data. This paper presents a methodology that can improve the reliability of results from experimental studies with a limited number of participants by creating a virtual population. Specifically, a methodology based on Bayesian inference has been developed, that generates synthetic cases that adhere to various real-world constraints and represent possible variations of the observed experimental data. The application of the framework is illustrated using data collected during a test-track experiment where truck drivers performed a right turn maneuver, with and without a cyclist crossing the intersection. The results show that, based on the speed profiles of the dataset and physical constraints, the methodology can produce synthetic speed profiles during braking that mimic the original curves but extend to other realistic braking patterns that were not directly observed. The models obtained from the proposed methodology have applications for the design of active safety systems and automated driving, demonstrating thereby that the developed framework has great promise for the automotive industry.

Field effectiveness of general motors advanced driver assistance and headlighting systems.

This study examined the field effectiveness of General Motors advanced driver assistance and headlighting systems. A total of 8,311,707 Model Year 2013-2019 vehicles were matched to police-reported crashes from 12 states. The quasi-induced exposure method was used to compare system-relevant and system-irrelevant (control) crash counts for equipped and unequipped vehicles. Logistic regression was used to adjust for ten covariates. Results indicated fusion/radar Automatic Emergency Braking, camera Automatic Emergency Braking, and Forward Collision Alert systems reduced rear-end striking crashes by 45%, 38%, and 20%, respectively. When restricting data to crashes in which someone in the General Motors striking vehicle was injured, these reductions were elevated to 59%, 54%, and 31%, respectively, providing evidence of additional crash mitigation benefits. Similarly, the Lane Keep Assist with Lane Departure Warning and Lane Departure Warning (alone) systems provided 12% and 10% reductions in lane departure crashes, respectively, with corresponding benefits in the injury analysis increasing to 19% and 18%, respectively. The Lane Change Alert with Side Blind Zone Alert system reduced lane change crashes by 16%. Reverse Automatic Braking, Rear Cross Traffic Alert, Rear Park Assist, and Rear Vision Camera (where each of these systems generally included all of the preceding systems) produced, respectively, an 82%, 55%, 36%, and 24% reduction in backing crashes. For Front Pedestrian Braking, a non-significant 14% reduction was observed for the limited set of available pedestrian crash cases. Intellibeam (auto high beam headlighting), High-Intensity Discharge headlights, and the combination of these two systems provided 26%, 11%, and 32% reductions (relative to halogen headlights) in a combined set of (unlighted) nighttime animal, pedestrian, and bicyclist crashes, respectively. These results provide widespread evidence of the substantial crash avoidance and injury reduction opportunities afforded by the production systems evaluated, as well as identify untapped system opportunities for moving toward a zero crashes vision.

Accounting for selection bias due to death in estimating the effect of wealth shock on cognition for the Health and Retirement Study.

The Health and Retirement Study (HRS) is a longitudinal study of U.S. adults enrolled at age 50 and older. We were interested in investigating the effect of a sudden large decline in wealth on the cognitive ability of subjects measured using a dataset provided composite score. However, our analysis was complicated by the lack of randomization, time-dependent confounding, and a substantial fraction of the sample and population will die during follow-up leading to some of our outcomes being censored. The common method to handle this type of problem is marginal structural models (MSM). Although MSM produces valid estimates, this may not be the most appropriate method to reflect a useful real-world situation because MSM upweights subjects who are more likely to die to obtain a hypothetical population that over time, resembles that would have been obtained in the absence of death. A more refined and practical framework, principal stratification (PS), would be to restrict analysis to the strata of the population that would survive regardless of negative wealth shock experience. In this work, we propose a new algorithm for the estimation of the treatment effect under PS by imputing the counterfactual survival status and outcomes. Simulation studies suggest that our algorithm works well in various scenarios. We found no evidence that a negative wealth shock experience would affect the cognitive score of HRS subjects.

Michigan system for opioid overdose surveillance.

Community rapid response may reduce opioid overdose harms, but is hindered by the lack of timely data. To address this need, we created and evaluated the Michigan system for opioid overdose surveillance (SOS). SOS integrates suspected fatal overdose data from Medical Examiners (MEs), and suspected non-fatal overdoses (proxied by naloxone administration) from the Michigan Emergency Medical Services (EMS) into a web-based dashboard that was developed with stakeholder feedback. Authorised stakeholders can view approximate incident locations and automated spatiotemporal data summaries, while the general public can view county-level summaries. Following Centers for Disease Control and Prevention (CDC) surveillance system evaluation guidelines, we assessed simplicity, flexibility, data quality, acceptability, sensitivity, positive value positive (PVP), representativeness, timeliness and stability of SOS. Data are usually integrated into SOS 1-day postincident, and the interface is updated weekly for debugging and new feature addition, suggesting high timeliness, stability and flexibility. Regarding representativeness, SOS data cover 100% of EMS-based naloxone adminstrations in Michigan, and receives suspected fatal overdoses from MEs covering 79.1% of Michigan's population, but misses those receiving naloxone from non-EMS. PVP of the suspected fatal overdose indicator is nearly 80% across MEs. Because SOS uses pre-existing data, added burden on MEs/EMS is minimal, leading to high acceptability; there are over 300 authorised SOS stakeholders (~6 new registrations/week) as of this writing, suggesting high user acceptability. Using a collaborative, cross-sector approach we created a timely opioid overdose surveillance system that is flexible, acceptable, and is reasonably accurate and complete. Lessons learnt can aid other jurisdictions in creating analogous systems.

The influence of environmental reliability in the marshmallow task: An extension study.

This study is an extension of an experiment where the reliability of children's environment was manipulated before children completed the Marshmallow Task (Cognition, 2013, Vol. 126, pp. 109-114). In that experiment, Kidd, Palmeri, and Aslin found a significant difference in waiting time between two conditions in which the experimenter demonstrated reliability (by returning with promised reward) or unreliability (by not returning with rewardP). Children who had an unreliable experimenter did not wait as long during the Marshmallow Task, suggesting that delay gratification performance may be, in part, based on a rational decision. Due to the important theoretical and practical implications of this finding, we repeated the procedure of this experiment with 60 3- to 5-year-old children (twice as many as in the original study), but in a more familiar context (e.g., children's school instead of a lab). Using Bayesian analyses, we found an effect (albeit smaller than in the original study) of experimenter reliability as well as a significant gender by condition interaction effect.

Multitasking additional-to-driving: Prevalence, structure, and associated risk in SHRP2 naturalistic driving data.

OBJECTIVE: This paper 1) analyzes the extent to which drivers engage in multitasking additional-to-driving (MAD) under various conditions, 2) specifies odds ratios (ORs) of crashing associated with MAD, and 3) explores the structure of MAD. METHODS: Data from the Second Strategic Highway Research Program Naturalistic Driving Study (SHRP2 NDS) was analyzed to quantify the prevalence of MAD in normal driving as well as in safety-critical events of various severity level and compute point estimates and confidence intervals for the corresponding odds ratios estimating the risk associated with MAD compared to no task engagement. Sensitivity analysis in which secondary tasks were re-defined by grouping similar tasks was performed to investigate the extent to which ORs are affected by the specific task definitions in SHRP2. A novel visual representation of multitasking was developed to show which secondary tasks co-occur frequently and which ones do not. RESULTS: MAD occurs in 11 % of control driving segments, 22 % of crashes and near-crashes (CNC), 26 % of Level 1-3 crashes and 39 % of rear-end striking crashes, and 9 %, 16 %, 17 % and 28 % respectively for the same event types if MAD is defined in terms of general task groups. The most common co-occurrences of secondary tasks vary substantially among event types; for example, "Passenger in adjacent seat - interaction" and "Other non-specific internal eye glance" tend to co-occur in CNC but tend not to co-occur in control driving segments. The odds ratios of MAD using SHRP2 task definitions compared to driving without any secondary task and the corresponding 95 % confidence intervals are 2.38 (2.17-2.61) for CNC, 3.72 (3.11-4.45) for Level 1-3 crashes and 8.48 (5.11-14.07) for rear-end striking crashes. The corresponding ORs using general task groups to define MAD are slightly lower at 2.00 (1.80-2.21) for CNC, 3.03 (2.48-3.69) for Level 1-3 crashes and 6.94 (4.04-11.94) for rear-end striking crashes. CONCLUSIONS: The number of secondary tasks that the drivers were engaged in differs substantially for different event types. A graphical representation was presented that allows mapping task prevalence and co-occurrence within an event type as well as a comparison between different event types. The ORs of MAD indicate an elevated risk for all safety-critical events, with the greatest increase in the risk of rear-end striking crashes. The results are similar independently of whether secondary tasks are defined according to SHRP2 or general task groups. The results confirm that the reduction of driving performance from MAD observed in simulator studies is manifested in real-world crashes as well.

Effects of child restraint misuse on dynamic performance.

Objective: Estimates of child restraint misuse rates in the United States range from 49% to 95%, but not all misuse modes have similar consequences in terms of restraint effectiveness. A series of laboratory sled tests was conducted to determine the effects of common misuses and combinations of misuses, including loose harness, loose installation, incorrect installation angle, incorrect belt path, loose/no tether, and incorrect harness clip usage.Methods: Three commercial convertible child restraint models were loaded with the Hybrid III 3-year-old anthropomorphic test device (ATD) and secured by either LATCH or seat belt on a modified FMVSS No. 213 bench. Tests were conducted in forward-facing (FF) and rear-facing (RF) modes. The response variables included ATD accelerations, excursions, and restraint kinematics. Belt/LATCH loads, tether loads, ATD kinematics, and restraint structural response data were also documented. A fractional factorial test design on 8 factors was used to define an initial series of 32 tests. The first series also included 4 tests of correct CRS, 2 forward facing and 2 rearward facing. The analysis of those data determined the selection of conditions for the remaining 20 tests to focus on factors and interactions of high interest and significance.Results: In the RF condition, misrouting the LATCH belt or seat belt through the incorrect belt path was the only misuse that significantly affected outcomes of interest and was associated with high levels of undesirable CRS rotation. In FF tests, loose installation and tether misuse had large adverse effects on 3 of 4 key response variables.Conclusion: The study provides strong evidence for prioritizing tight restraint installation and proper tether use for FF restraints. In particular, use of the tether helped offset the adverse effects of loose installation or loose harness. Because the results show that performance of a RF child restraint system (CRS) installation is less affected by user error, they also provide support for extended RF restraint use. In addition, packaging convertible child restraints with the LATCH belt routed through the RF belt path could help prevent the most consequential RF CRS misuse.

Factors Affecting Child Injury Risk in Motor-Vehicle Crashes.

Current recommendations for restraining child occupants are based on biomechanical testing and data from national and international field studies primarily conducted prior to 2011. We hypothesized that analysis to identify factors associated with pediatric injury in motor-vehicle crashes using a national database of more recent police-reported crashes in the United States involving children under age 13 where type of child restraint system (CRS) is recorded would support previous recommendations. Weighted data were extracted from the National Automotive Sampling System General Estimates System (NASS-GES) for crash years 2010 to 2015. Injury outcomes were grouped as CO (possible and no injury) or KAB (killed, incapacitating injury, nonincapacitating injury). Restraint was characterized as optimal, suboptimal, or unrestrained based on current best practice recommendations. Analysis used survey methods to identify factors associated with injury. Factors with significant effect on pediatric injury risk include restraint type, child age, driver injury, driver alcohol use, seating position, and crash direction. Compared to children using optimal restraint, unrestrained children have 4.9 (13-year-old) to 5.6 (< 1-year-old) times higher odds of injury, while suboptimally restrained children have 1.1 (13-year-old) to 1.9 (< 1-year-old) times higher odds of injury. As indicated by the differences in odds ratios, effects of restraint type attenuate with age. Results support current best practice recommendations to use each stage of child restraint (rear-facing CRS, forward-facing harnessed CRS, belt-positioning booster seat, lap and shoulder belt) as long as possible before switching to the next step.

Comparing motor-vehicle crash risk of EU and US vehicles.

OBJECTIVE: This study examined the hypotheses that passenger vehicles meeting European Union (EU) safety standards have similar crashworthiness to United States (US) -regulated vehicles in the US driving environment, and vice versa. METHODS: The first step involved identifying appropriate databases of US and EU crashes that include in-depth crash information, such as estimation of crash severity using Delta-V and injury outcome based on medical records. The next step was to harmonize variable definitions and sampling criteria so that the EU data could be combined and compared to the US data using the same or equivalent parameters. Logistic regression models of the risk of a Maximum injury according to the Abbreviated Injury Scale of 3 or greater, or fatality (MAIS3+F) in EU-regulated and US-regulated vehicles were constructed. The injury risk predictions of the EU model and the US model were each applied to both the US and EU standard crash populations. Frontal, near-side, and far-side crashes were analyzed together (termed "front/side crashes") and a separate model was developed for rollover crashes. RESULTS: For the front/side model applied to the US standard population, the mean estimated risk for the US-vehicle model is 0.035 (sd = 0.012), and the mean estimated risk for the EU-vehicle model is 0.023 (sd = 0.016). When applied to the EU front/side population, the US model predicted a 0.065 risk (sd = 0.027), and the EU model predicted a 0.052 risk (sd = 0.025). For the rollover model applied to the US standard population, the US model predicted a risk of 0.071 (sd = 0.024), and the EU model predicted 0.128 risk (sd = 0.057). When applied to the EU rollover standard population, the US model predicted a 0.067 risk (sd = 0.024), and the EU model predicted 0.103 risk (sd = 0.040). CONCLUSIONS: The results based on these methods indicate that EU vehicles most likely have a lower risk of MAIS3+F injury in front/side impacts, while US vehicles most likely have a lower risk of MAIS3+F injury in llroovers. These results should be interpreted with an understanding of the uncertainty of the estimates, the study limitations, and our recommendations for further study detailed in the report.

Assessing tether anchor labeling and usability in pickup trucks.

OBJECTIVE: The objective of this study was to investigate vehicle factors associated with child restraint tether use and misuse in pickup trucks and evaluate 4 labeling interventions designed to educate consumers on proper tether use. METHODS: Volunteer testing was performed with 24 subjects and 4 different pickup trucks. Each subject performed 8 child restraint installations among the 4 pickups using 2 forward-facing restraints: a Britax Marathon G4.1 and an Evenflo Triumph. Vehicles were selected to represent 4 different implementations of tether anchors among pickups: plastic loop routers (Chevrolet Silverado), webbing routers (Ram), back wall anchors (Nissan Frontier), and webbing routers plus metal anchors (Toyota Tundra). Interventions included a diagram label, Quick Response (QR) Code linked to video instruction, coordinating text label, and contrasting text tag. RESULTS: Subjects used the child restraint tether in 93% of trials. However, tether use was completely correct in only 9% of trials. An installation was considered functional if the subject attached the tether to a tether anchor and had a tight installation (ignoring routing and head restraint position); 28% of subjects achieved a functional installation. The most common installation error was attaching the tether hook to the anchor/router directly behind the child restraint (near the top of the seatback) rather than placing the tether through the router and attaching it to the anchor in the adjacent seating position. The Nissan Frontier, with the anchor located on the back wall of the cab, had the highest rate of correct installations but also had the highest rate of attaching the tether to components other than the tether anchor (seat adjustor, child restraint storage hook, around head restraint). None of the labeling interventions had a significant effect on correct installation; not a single subject scanned the QR Code to access the video instruction. Subjects with the most successful installations spent extensive time reviewing the vehicle manuals. CONCLUSION: Current implementations of tether anchors among pickup trucks are not intuitive for child restraint installations, and alternate designs should be explored. Several different labeling interventions were ineffective at achieving correct tether use in pickup trucks.

Development of a real-time prediction model of driver behavior at intersections using kinematic time series data.

As connected autonomous vehicles (CAVs) enter the fleet, there will be a long period when these vehicles will have to interact with human drivers. One of the challenges for CAVs is that human drivers do not communicate their decisions well. Fortunately, the kinematic behavior of a human-driven vehicle may be a good predictor of driver intent within a short time frame. We analyzed the kinematic time series data (e.g., speed) for a set of drivers making left turns at intersections to predict whether the driver would stop before executing the turn. We used principal components analysis (PCA) to generate independent dimensions that explain the variation in vehicle speed before a turn. These dimensions remained relatively consistent throughout the maneuver, allowing us to compute independent scores on these dimensions for different time windows throughout the approach to the intersection. We then linked these PCA scores to whether a driver would stop before executing a left turn using the random intercept Bayesian additive regression trees. Five more road and observable vehicle characteristics were included to enhance prediction. Our model achieved an area under the receiver operating characteristic curve (AUC) of 0.84 at 94m away from the center of an intersection and steadily increased to 0.90 by 46m away from the center of an intersection.

Can vehicle longitudinal jerk be used to identify aggressive drivers? An examination using naturalistic driving data.

This paper investigated the characteristics of vehicle longitudinal jerk (change rate of acceleration with respect to time) by using vehicle sensor data from an existing naturalistic driving study. The main objective was to examine whether vehicle jerk contains useful information that could be potentially used to identify aggressive drivers. Initial investigation showed that there are unique characteristics of vehicle jerk in drivers' gas and brake pedal operations. Thus two jerk-based metrics were examined: (1) driver's frequency of using large positive jerk when pressing the gas pedal, and (2) driver's frequency of using large negative jerk when pressing the brake pedal. To validate the performance of the two metrics, drivers were firstly divided into an aggressive group and a normal group using three classification methods (1) traveling at excessive speed (speeding), (2) following too closely to a front vehicle (tailgating), and (3) their association with crashes or near-crashes in the dataset. The results show that those aggressive drivers defined using any of the three methods above were associated with significantly higher values of the two jerk-based metrics. Between the two metrics the frequency of using large negative jerk seems to have better performance in identifying aggressive drivers. A sensitivity analysis shows the findings were largely consistent with varying parameters in the analysis. The potential applications of this work include developing quantitative surrogate safety measures to identify aggressive drivers and aggressive driving, which could be potentially used to, for example, provide real-time or post-ride performance feedback to the drivers, or warn the surrounding drivers or vehicles using the connected vehicle technologies.

Predictors of restraint use among child occupants.

OBJECTIVES: The objective of this study was to identify factors that predict restraint use and optimal restraint use among children aged 0 to 13 years. METHODS: The data set is a national sample of police-reported crashes for years 2010-2014 in which type of child restraint is recorded. The data set was supplemented with demographic census data linked by driver ZIP code, as well as a score for the state child restraint law during the year of the crash relative to best practice recommendations for protecting child occupants. Analysis used linear regression techniques. RESULTS: The main predictor of unrestrained child occupants was the presence of an unrestrained driver. Among restrained children, children had 1.66 (95% confidence interval, 1.27, 2.17) times higher odds of using the recommended type of restraint system if the state law at the time of the crash included requirements based on best practice recommendations. CONCLUSIONS: Children are more likely to ride in the recommended type of child restraint when their state's child restraint law includes wording that follows best practice recommendations for child occupant protection. However, state child restraint law requirements do not influence when caregivers fail to use an occupant restraint for their child passengers.

Does unbelted safety requirement affect protection for belted occupants?

OBJECTIVE: Federal regulations in the United States require vehicles to meet occupant performance requirements with unbelted test dummies. Removing the test requirements with unbelted occupants might encourage the deployment of seat belt interlocks and allow restraint optimization to focus on belted occupants. The objective of this study is to compare the performance of restraint systems optimized for belted-only occupants with those optimized for both belted and unbelted occupants using computer simulations and field crash data analyses. METHODS: In this study, 2 validated finite element (FE) vehicle/occupant models (a midsize sedan and a midsize SUV) were selected. Restraint design optimizations under standardized crash conditions (U.S.-NCAP and FMVSS 208) with and without unbelted requirements were conducted using Hybrid III (HIII) small female and midsize male anthropomorphic test devices (ATDs) in both vehicles on both driver and right front passenger positions. A total of 10 to 12 design parameters were varied in each optimization using a combination of response surface method (RSM) and genetic algorithm. To evaluate the field performance of restraints optimized with and without unbelted requirements, 55 frontal crash conditions covering a greater variety of crash types than those in the standardized crashes were selected. A total of 1,760 FE simulations were conducted for the field performance evaluation. Frontal crashes in the NASS-CDS database from 2002 to 2012 were used to develop injury risk curves and to provide the baseline performance of current restraint system and estimate the injury risk change by removing the unbelted requirement. RESULTS: Unbelted requirements do not affect the optimal seat belt and airbag design parameters in 3 out of 4 vehicle/occupant position conditions, except for the SUV passenger side. Overall, compared to the optimal designs with unbelted requirements, optimal designs without unbelted requirements generated the same or lower total injury risks for belted occupants depending on statistical methods used for the analysis, but they could also increase the total injury risks for unbelted occupants. CONCLUSIONS: This study demonstrated potential for reducing injury risks to belted occupants if the unbelted requirements are eliminated. Further investigations are necessary to confirm these findings.

Rating child passenger safety laws relative to best practice recommendations for occupant protection.

BACKGROUND: State laws regarding child passenger protection vary substantially. OBJECTIVES: The objective of this study was to develop a scoring system to rate child passenger safety laws relative to best practice recommendations for each age of child. METHODS: State child passenger safety and seat belt laws were retrieved from the LexisNexis database for the years 2002-2015. Text of the laws was reviewed and compared to current best practice recommendations for child occupant protection for each age of child. RESULTS: A 0-4 scale was developed to rate the strength of the state law relative to current best practice recommendations. A rating of 3 corresponds to a law that requires a restraint that is sufficient to meet best practice, and a rating of 4 is given to a law that specifies several options that would meet best practice. Scores of 0, 1, or 2 are given to laws requiring less than best practice to different degrees. The same scale is used for each age of child despite different restraint recommendations for each age. Legislation that receives a score of 3 requires rear-facing child restraints for children under age 2, forward-facing harnessed child restraints for children aged 2 to 4, booster seats for children 5 to 10, and primary enforcement of seat belt use in all positions for children aged 11-13. Legislation requiring use of a "child restraint system according to instructions" would receive a score of 1 for children under age 2 and a 2 for children aged 2-4 because it would allow premature use of a booster for children weighing more than 13.6 kg (30 lb). CONCLUSIONS: The scoring system developed in this study can be used in mathematical models to predict how child passenger safety legislation affects child restraint practices.

The Impact of Michigan's Partial Repeal of the Universal Motorcycle Helmet Law on Helmet Use, Fatalities, and Head Injuries.

OBJECTIVES: To evaluate the impact of the partial repeal of Michigan's universal motorcycle helmet law on helmet use, fatalities, and head injuries. METHODS: We compared helmet use rates and motorcycle crash fatality risk for the 12 months before and after the April 13, 2012, repeal with a statewide police-reported crash data set. We linked police-reported crashes to injured riders in a statewide trauma registry. We compared head injury before and after the repeal. Regression examined the effect of helmet use on fatality and head injury risk. RESULTS: Helmet use decreased in crash (93.2% vs 70.8%; P < .001) and trauma data (91.1% vs 66.2%; P < .001) after the repeal. Although fatalities did not change overall (3.3% vs 3.2%; P = .87), head injuries (43.4% vs 49.6%; P < .05) and neurosurgical intervention increased (3.7% vs 6.5%; P < .05). Male gender (adjusted odds ratio [AOR] = 1.65), helmet nonuse (AOR = 1.84), alcohol intoxication (AOR = 11.31), intersection crashes (AOR = 1.62), and crashes at higher speed limits (AOR = 1.04) increased fatality risk. Helmet nonuse (AOR = 2.31) and alcohol intoxication (AOR = 2.81) increased odds of head injury. CONCLUSIONS: Michigan's helmet law repeal resulted in a 24% to 27% helmet use decline among riders in crashes and a 14% increase in head injury.