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Background: Polypharmacy (i.e., simultaneous use of two or more medications) poses a serious safety concern for older drivers. This study assesses the association between polypharmacy and hard braking events in older adult drivers., Methods: Data for this study came from a naturalistic driving study of 2990 older adults. Information about medications was collected through the "brown-bag review" method. Primary vehicles of the study participants were instrumented with data recording devices for up to 44 months. Multivariable negative binomial model was used to estimate the adjusted incidence rate ratios (aIRRs) and 95 % confidence intervals (CIs) of hard-braking events (i.e., maneuvers with linear deceleration rates ≥0.4 g) associated with polypharmacy., Results: Of the 2990 participants, 2872 (96.1 %) were eligible for this analysis. At the time of enrollment, 157 (5.5 %) drivers were taking fewer than two medications, 904 (31.5 %) were taking 2-5 medications, 895 (31.2 %) were taking 6-9 medications, 571 (19.9 %) were taking 10-13 medications, and 345 (12.0 %) were taking 14 or more medications. Compared to drivers using fewer than two medications, the risk of hard-braking events increased 8 % (aIRR 1.08, 95 % CI 1.04, 1.13) for users of 2-5 medications, 12 % (aIRR 1.12, 95 % CI 1.08, 1.16) for users of 6-9 medications, 19 % (aIRR 1.19, 95 % CI 1.15, 1.24) for users of 10-13 medications, and 34 % (aIRR 1.34, 95 % CI 1.29, 1.40) for users of 14 or more medications., Conclusions: Polypharmacy in older adult drivers is associated with significantly increased incidence of hard-braking events in a dose-response fashion. Effective interventions to reduce polypharmacy use may help improve driving safety in older adults., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Objective: The advent of automated vehicles (AVs) provides an opportunity to design integrated wheelchair seating stations that provide an equivalent level of safety for occupants using wheelchairs as those using vehicle seating. This study designed a frontal occupant protection system for an integrated second-row wheelchair seating station that includes optimized airbags and seatbelt systems., Methods: MADYMO models were used to optimize belt geometry for a midsized male ATD seated in a surrogate wheelchair fixture, with and without inclusion of a Self Conforming Rearseat Air Bag (SCaRAB). Sled tests were performed to confirm the benefits of airbag use and optimized belt geometry. Additional modeling was performed with commercial manual and power wheelchairs, to identify the effects of wheelchair design and forward clear space on occupant kinematics and injury measures. Additional sled tests were performed with manual and power wheelchairs to demonstrate effectiveness of the restraint system with commercial products., Results: Simulations and tests both showed improved kinematics using an optimized seatbelt system geometry compared to a commonly used suboptimal D-ring location that places the shoulder belt at a more outboard location. Use of the SCaRAB helped compensate for suboptimal geometry. Results include specific recommendations for belt geometry relative to the wheelchair seating station and airbag parameters suitable for protecting occupants seated in wheelchairs. Restraint systems initially optimized using the surrogate wheelchair also performed well with the two commercial wheelchairs. The clear space required for maneuvering a wheelchair will likely prevent injurious head contact in frontal crashes., Conclusions: This study is the first to design a frontal optimal occupant protection system for an integrated second-row wheelchair seating station, demonstrating that it should be feasible once integrated wheelchair seating stations are included in AVs., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The objective of this study was to use computational models to study how unconventional seating positions and orientations in vehicles with Automated Driving System (ADS) may affect occupant response metrics of children with various restraint conditions. A literature review was first conducted to frame a simulation plan, including selections of surrogate ADS-equipped vehicles, potential seating arrangements, impact scenarios, anthropomorphic test device (ATD) models, and child restraint system (CRS) models that are relevant to the selected ATD models. Due to the lack of impact tests with child ATDs and CRS in farside, oblique, and rear impacts, 17 sled tests were conducted with CRS harness-restrained ATDs and vehicle belt-restrained ATDs in frontal, farside, oblique, and rear impact conditions. The sled tests were then used to validate a set of MADYMO (MAthematical DYnamic MOdels) v7.7 models. A total of 550 simulations were then conducted with four child ATDs and various CRS conditions across a range of conventional and unconventional seating locations and orientations under five impact directions. We did not find major safety concerns with ATDs restrained by harnessed CRSs based on the nature of ATD contacts. Compared with frontal and rear impacts, CRSs may rotate laterally in farside and oblique impacts, which could result in higher head and chest injury measures than frontal due to inertial loading to the CRS, and the larger lateral rotation of the CRS may lead to a contact between the CRS and vehicle interior. The major safety concern for vehicle belt-restrained ATDs (with and without booster) is that they have the potential to contact the seat next to them or the instrument panel behind them in a farside or oblique impact. Unconventional seating does not necessarily create additional safety concerns beyond what we know with the conventional seating. However, due to the orientation of the unconventional seats, the occupants on those seats may be involved in a higher percentage of oblique and rear-oblique impacts relative to their seating orientations than conventional seats, which may be considered in the future safety design process. This is the first study using different child ATDs and CRSs to investigate child occupant responses in a wide range of impact directions and seating orientations. Results from the sled tests and simulations provide a better understanding of child occupant responses in those crash conditions, but also identified several limitations of using frontal ATDs in other crash directions., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Illegal running into the opposite lane (IROL) on curve sections of two-lane rural roads is a frequently hazardous behavior and highly prone to fatal crashes. Although driving behaviors are always determined by the information from drivers' visual perceptions, current studies do not consider visual perceptions in predicting the occurrence of IROL. In addition, most machine learning methods belong to black-box algorithms and lack the interpretation of prediction results. Therefore, this study aims to propose an interpretable prediction model of IROL on curve sections of two-lane rural roads from drivers' visual perceptions. A new visual road environment model, consisting of five different visual layers, was established to better quantify drivers' visual perceptions by using deep neural networks. In this study, naturalistic driving data was collected on curve sections of typical two-lane rural roads in Tibet, China. There were 25 input variables extracted from the visual road environment, vehicle kinematics, and driver characteristics. Then, XGBoost (eXtreme Gradient Boosting) and SHAP (SHapley Additive exPlanation) methods were combined to build a prediction model. The results showed that our prediction model performed well, with an accuracy of 86.2% and an AUC value of 0.921. The average lead time of this prediction model was 4.4 s, sufficient for drivers to respond. Due to the advantages of SHAP, this study interpreted the impacting factors on this illegal behavior from three aspects, including relative importance, specific impacts, and variable dependency. After offering more quantitative information on the visual road environment, the findings of this study could improve the current prediction model and optimize road environment design, thereby reducing IROL on curve sections of two-lane rural roads., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Collision warning systems can improve traffic safety, while their safety benefit may be lessened due to improper risk compensation or system misuse. There are limited studies of advanced safety systems increasing unexpected risky driving behavior, especially with adolescent drivers. This study is designed to address this research gap in two main areas: 1) it seeks to examine whether and how the introduction of advanced driver-assistance systems influences drivers' risk compensation behavior (e.g., increase of hard braking frequency), and 2) it investigates key factors (e.g., distraction) that contribute to changes in hard braking frequency during driving for both teen and adult drivers. Naturalistic driving data from two previous studies were analyzed in this study with two methods: a hierarchical logistic regression model was used to evaluate the effects of an integrated collision warning system on hard braking behavior, while a Random forests algorithm was applied to model hard braking behavior and to rank the contributing factors by calculating the importance scores. No statistical evidence was observed that the integrated collision warning system significantly changed the likelihood of hard braking for teen or adult drivers. Other factors like distraction, especially visual-manual distraction, had the largest impact on the hard braking behavior, followed by speeding and roadway segments (i.e., at intersections or not). Short time-headways and driving in high-density traffic significantly increased the likelihood of hard braking. Furthermore, the rate of hard braking behavior on surface roads was much higher than on highways, as expected. Compared with straight road segments, hard braking behavior was less likely to occur on curve roads. This study applied an analytical strategy by using both machine learning and statistical analysis methods to achieve high model accuracy and facilitate inference concerning the relationships among variables. Findings in this study can help to improve the design of integrated collision warning systems and the use of autonomous braking systems, and to apply appropriate analysis methods in understanding teen drivers' behavior changes with those safety systems., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

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., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

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., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Seat belt use can significantly reduce fatalities in motor vehicle crashes (Kahane, 2000). Nevertheless, the current U.S. seat belt use rate of 89.6% (Enriquez & Pickrell, 2019) indicates that a relatively small but pervasive portion of the population does not wear seat belts on a full-time basis. Whereas much is known about the demographic predictors of seat belt use, far less is understood about psychological factors that predict individual proclivities toward using or not using a seat belt. In this study, we examined some of these potential psychological predictors. A probability-based web survey was conducted with 6,038 U.S. residents aged 16 or older who reported having driven or ridden in a car in the past year. We measured self-reported seat belt use and 18 psychological constructs and found that delay of gratification, life satisfaction, risk aversion, risk perception, and resistance to peer influence were positively associated with belt use. Impulsivity and social resistance orientation were negatively associated with belt use. Prior research has shown that psychological factors like delay of gratification, risk aversion/perception, and impulsivity predict other health behaviors (e.g., cigarette smoking, sunscreen use); our results extend this literature to seat belts and can aid the development of traffic safety programs targeted at non-users who-due to such factors-may be resistant to more traditional countermeasures such as legislation and enforcement., (Copyright © 2020. Published by Elsevier Ltd.)

Teen drivers are overrepresented in motor vehicle crashes, and most studies concluded it was mainly due to their lack of experiences and tendencies of risk-taking. The design of advanced driving assistance systems (ADAS) aims to provide assistance in multiple stages in human information processing during driving, including environmental sensing, information processing, decision making, and vehicle controlling, in order to improve driving safety. It is expected that novice drivers may benefit more from using ADAS than adult drivers as such technologies can compensate for their frequent errors. This study examined whether and how an integrated crash warning system impacted on drivers' following behavior, and what were the corresponding age-related differences through an analysis of two unique naturalistic driving study datasets. Significant age-related differences in car-following behavior were found. Results showed potential negative effects of ADAS on teen drivers' following behavior that teen drivers tended to have less controlled pedal use during treatment weeks with ADAS than during baseline weeks without ADAS, while such behavior was not observed in adult drivers. All adult drivers tended to keep longer headways when driving at night than during daytime to compensate for poor vision conditions, but no such compensation behavior was observed in the teens. In addition, teen and young-adult drivers had more aggressive following behavior (with shorter mean time headway) than middle-aged and older drivers. One limitation of this study is that the findings of this study are only addressing the short-term effect of ADAS exposure, and future studies are needed to examine the longitudinal effect. The findings of this study suggest that the design of future ADAS should consider minimizing potential negative impacts on teen driver behavior., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Among the three major safety assessment methods (i.e., simulation, test track, and on-road test) for highly automated driving systems (ADS), test tracks provide high fidelity and a safe and controllable testing environment. However, due to the lack of realistic background traffic, scenarios that can be tested in test tracks are usually static and limited. To address this limitation, a new safety assessment framework is proposed in this paper, which integrates an augmented reality (AR) testing platform and a testing scenario library generation (TSLG) method. The AR testing platform generates simulated background traffic in test tracks, which interact with subject ADS under test, to create a realistic traffic environment. The TSLG method can systematically generate a set of critical scenarios under each operational design domain (ODD) and the critical scenarios generated from the TSLG method can be imported into the AR testing platform. The proposed framework has been implemented in the Mcity test track at the University of Michigan with a Level 4 ADS. Field test results show that the proposed framework can accurately and efficiently evaluate the safety performance of highly ADS in a cost-effective fashion. In the cut-in case study, the proposed framework is estimated to accelerate the assessment process by 9.87×10 4 times comparing to the on-road test approach., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing for financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

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., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Recent field data analyses have shown that lumbar spine fractures occurred more frequently in late model vehicles than the early ones in frontal crashes. Therefore, the objective of this study was to investigate risk factors associated with lumbar spine fractures in frontal crashes. Parametric simulations were conducted using a set of validated vehicle driver compartment model, restraint system model, and a HIII mid-size male crash test dummy model. Risk factors considered in the study included occupant seating posture, crash pulse, vehicle pitch angle, seat design, anchor pre-tensioner, dynamic locking tongue, and shoulder belt load limiter. ANOVA and ANCOVA were used to test the statistical significance (p < 0.05). Simulation results showed that all the factors that reduced the risk of submarining increased the lumbar spine forces, indicating a direct conflict between submarining and lumbar spine fractures. Among all the factors selected, seat structure is the most significant factor in determining the lumbar spine force (p < 0.001). Crash pulse severity, time at which the peak crash deceleration reached, and pitch angle are also crucial for lumbar spine force. Specifically, increase in vehicle pitch angle increased lumbar spine force, but reduced injury measures to other body regions; while a crash pulse with early peak produced greater lumbar spine force than that with a late peak. On average, more reclined posture increased the lumbar spine force compared to upright posture, and decreases in the coefficient of friction between the pelvis and the seat cushion reduced the lumbar spine force. However, they are not statistically significant. This study provided better understanding of effects from design countermeasures to reduce occupant lumbar spine injuries in new generation of vehicle models., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

This study examined cannabis use and driving outcomes among older drivers in Colorado, which has legalized medical and recreational use. The associations of self-reported past-year cannabis use with diverse driving outcomes were assessed in 598 drivers aged 65-79 (51% female, 70% with postsecondary education), using regression analysis to adjust for health and sociodemographic characteristics. Two hundred forty four (40.8%) drivers reported ever using cannabis. Fifty-four drivers (9.0%) reported past-year use, ranging from more than once a day (13.0%) to less than once a month (50.0%). Of past-year users, 9.3% reported cannabis use within 1 h of driving in the past year. Past-year users were younger, less highly educated, lower income, and reported significantly worse mental, emotional, social and cognitive health status than drivers without past-year use. Past-year users were four times as likely to report having driven when they may have been over the legal blood-alcohol limit (adjusted OR [aOR] = 4.18; 95% CI: 2.11, 8.25) but were not more likely to report having had a crash or citation (aOR = 1.36; 95% CI: 0.70, 2.66) in the past year. Users and non-users had similar scores on self-rated abilities for safe driving (adjusted beta=-0.04; 95% CI: -0.23, 0.15) and on driving-related lapses, errors and violations in the past year (adjusted beta = 0.04; 95% CI: -0.04, 0.12). Further study is needed to establish driving risks and behaviours related to cannabis use, independent of other associated risk factors, among older adults., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Speeding is one of the major contributors to traffic crashes. To solve this problem, speeding prediction is recognized as a critical step in a pre-warning system. While previous studies have shown that speeding is affected by road environmental design, research in predicting speeding behavior through road environment features has not yet been conducted. Furthermore, there is a large discrepancy between actual and perceived road environmental information given that a driver's visual perception plays a crucial role as the dominant source of information in determining driver's behavior. Thus, this paper aims to establish a speeding prediction model based on quantifying the visual road environment to improve the design of pre-waring systems, which can predict whether drivers are going to speed and provide them with visual or/and audio warnings about their current driving speed and the speed limit prior to the occurrence of speeding behavior. Twenty input variables derived from three categories including visual road environment parameters, vehicle kinematic features, and driver characteristics were considered in the proposed speeding prediction model. Especially, the road environmental design factors consisting of the visual road geometry and visual roadside environment as perceived by the driver's eyes were quantified using a visual road environment model. Field experiments were conducted to collect naturalistic driving data concerning speeding behavior on the typical two-lane mountainous rural highways in five provinces of China. Random Forests, an ensemble learning method for regression and classification, were applied to build the speeding prediction model and variable importance was calculated. Additionally, logistic regression was used as a supplement to further investigate factors impacting on speeding behavior. A speeding criterion was defined with two levels in this study: a lower level (exceeding the posted speed limit) and a higher level (10% above the posted speed limit). Under both levels of the speeding criterion, the speeding prediction model performed well with high accuracy (over 85%). This model could use the value of the variables obtained from the current position to predict drivers' speeding behavior at the future position located a sighting distance away. This interval was sufficient for a pre-warning system to give a speeding warning that a driver with normal perception-reaction time (around 2.5 s) could respond to. Findings in this study can be used to effectively predict speeding in advance and help to reduce speeding-related traffic accidents., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

This article summarizes the recommendations on data and methodology issues for studying commercial motor vehicle driver fatigue of a National Academies of Sciences, Engineering, and Medicine study. A framework is provided that identifies the various factors affecting driver fatigue and relating driver fatigue to crash risk and long-term driver health. The relevant factors include characteristics of the driver, vehicle, carrier and environment. Limitations of existing data are considered and potential sources of additional data described. Statistical methods that can be used to improve understanding of the relevant relationships from observational data are also described. The recommendations for enhanced data collection and the use of modern statistical methods for causal inference have the potential to enhance our understanding of the relationship of fatigue to highway safety and to long-term driver health., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Motor vehicle crashes are a leading cause of injury, and teen drivers contribute disproportionately to that burden. Graduated Driver Licensing (GDL) programs are effective at reducing teen crash risk, but teen crash rates remain high. Between-state variation in the teen crash rate reduction following GDL implementation has been documented, but this is the first study to examine small-area variation in such a reduction. Fusing together crash data from the Michigan State Police, census data, and organizational data (alcohol outlet, movie theatre, and school locations), we analyzed spatial correlates of teen injury crash, and place-based features that modified the injury crash rate difference following GDL implementation. Specifically, using census-based units, we estimated changes in injury crash rates among teens using negative binomial regression controlling for spatial autocorrelation, and tested whether any measured spatial characteristics modified the crash rate change in the pre versus post GDL periods. There was a substantial reduction in teen crashes after GDL implementation (RR = 0.66, 95%CI: [0.65, 0.67]), and this effect was robust across gender and time-of-day (light/dark). We found evidence that this reduction varied across space; areas with more alcohol outlets corresponded to a larger daytime crash rate reduction post-GDL, while areas near schools corresponded to a smaller daytime crash rate reduction. Concentrations of movie theatres corresponded to larger post-GDL crash rate reductions after dark. Maximizing the substantial successes of GDL programs requires understanding why crash rate reductions were larger in some areas following GDL implementation, and harnessing that understanding to improve its effectiveness across a state, focusing on identifying priorities for improving driver training (e.g., by parents and driver educators), law enforcement, and future policy changes to current GDL laws., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

This study aims to classify the injury severity in motor-vehicle crashes with both high accuracy and sensitivity rates. The dataset used in this study contains 297,113 vehicle crashes, obtained from the Michigan Traffic Crash Facts (MTCF) dataset, from 2016-2017. Similar to any other crash dataset, different accident severity classes are not equally represented in MTCF. To account for the imbalanced classes, several techniques have been used, including under-sampling and over-sampling. Using five classification learning models (i.e., Logistic regression, Decision tree, Neural network, Gradient boosting model, and Naïve Bayes classifier), we classify the levels of injury severity and attempt to improve the classification performance by two training-testing methods including Bootstrap aggregation (or bagging) and majority voting. Furthermore, due to the imbalance present in the dataset, we use the geometric mean (G-mean) to evaluate the classification performance. We show that the classification performance is the highest when bagging is used with decision trees, with over-sampling treatment for imbalanced data. The effect of treatments for the imbalanced data is maximized when under-sampling is combined with bagging. In addition to the original five classes of injury severity in the MTCF dataset, we consider two additional classification problems, one with two classes and the other with three classes, to (1) investigate the impact of the number of classes on the performance of classification models, and (2) enable comparing our results with the literature., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Owing to constrained topography and road geometry, mountainous highways are subjected to frequent traffic accidents, and these crashes have relatively high mortality rates. In middle and high mountains, most roads are two-lane highways. Most two-lane mountain highways are located in rural areas in China, where traffic volume is relatively small; namely, traffic accidents are mainly related to the design of roads, rather than the impact of traffic flow. Previous studies primarily focused on the relationship between actual road geometry and traffic safety. However, some scholars put forward that there was a significant discrepancy between actual and visual perceived information. Drivers greatly depend on what they perceived by their vision to determine driving behavior. Thus, in this paper drivers' visual lane model was established to quantify drivers' visual perception. To further explore drivers' perception of horizontal and vertical alignments, the visual lane model was projected onto horizontal and vertical planes in drivers' vision respectively. The length and curvature of the visual curve were extracted as shape parameters of drivers' visual lane models. Real vehicle driving tests were conducted on typical two-lane mountain highway sections of G318 in Tibet, China. Then the differences of visual perception at black spots and accident-free locations were analyzed and compared. In horizontal and vertical projections of visual lane model, there were 9 shape parameters have significant differences between accident-prone and accident-free locations. A probabilistic neural network (PNN) was formed to identify accident-prone locations on two-lane mountain highways. This study will lay a foundation for the improvement of traffic safety on mountain highways based on the quantification of drivers' visual perception, during the phase of both road design and reconstruction, and can also make a contribution to the automatic driving technique., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

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., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)

This study applied the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM) to assess drivers' intended use of automated vehicles (AVs) after undertaking a simulated driving task. In addition, this study explored the potential for trust to account for additional variance to the psychosocial factors in TPB and TAM. Seventy-four participants (51% female) aged between 25 and 64 years (M = 42.8, SD = 12.9) undertook a 20 min simulated experimental drive in which participants experienced periods of automated driving and manual control. A survey task followed. A hierarchical regression analysis revealed that TPB constructs; attitude toward the behavior, subjective norms, and perceived behavioral control, were significant predictors of intentions to use AV. In addition, there was partial support for the test of TAM, with ease of use (but not usefulness) predicting intended use of AV (SAE Level 3). Trust contributed variance to both models beyond TPB or TAM constructs. The findings provide an important insight into factors that might reflect intended use of vehicles that are primarily automated (longitudinal, lateral, and manoeuvre controls) but require and allow drivers to have periods of manual control., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

This paper demonstrates a unique and promising approach to study driver-bicyclist interactions from a driver's perspective by using in-vehicle sensory data from naturalistic driving studies. A total of 4789 events of drivers overtaking bicyclists were extracted from an existing naturalistic driving study in Michigan, United States. The vehicle lateral placement at the time of passing bicyclists was used as a surrogate safety measure. A number of factors were examined, including the lane marking type, the presence of a bike lane or paved shoulder, the presence of traffic, lane width, and driver distraction. Some notable findings include that (1) when a bike lane or paved shoulder was present, a dashed non-center line (i.e., a dashed line separating two lanes in the same direction) was associated with significantly less vehicle lane-crossing and closer distance to the bike lane/shoulder compared to a solid centerline; (2) an alarming 7.8% of the overtaking occurred when the drivers were distracted within five seconds prior to passing bicyclists. From a bicyclist's perspective, that translates to one overtaken by a distracted driver for every thirteen times they are overtaken. In addition, drivers manipulating a cell phone were associated with significantly less vehicle lane-crossing when overtaking bicyclists. The results of this work could be potentially used by traffic engineers, policymakers and legislators to support the designs of better road infrastructures, education programs, policies, and traffic laws that aim to improve the safety of all road users. The quantitative results could also be potentially used as a baseline to develop and benchmark automated vehicle technologies on how to interact with bicyclists on the road., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

The purpose of the present study was to gain a better understanding of the types of in-vehicle technologies being used by older drivers as well as older drivers' use, learning, and perceptions of safety related to these technologies among a large cohort of older drivers at multiple sites in the United States. A secondary purpose was to explore the prevalence of aftermarket vehicle adaptations and how older adults go about making adaptations and how they learn to use them. The study utilized baseline questionnaire data from 2990 participants from the Longitudinal Research on Aging Drivers (LongROAD) study. Fifteen in-vehicle technologies and 12 aftermarket vehicle adaptations were investigated. Overall, 57.2% of participants had at least one advanced technology in their primary vehicle. The number of technologies in a vehicle was significantly related to being male, having a higher income, and having a higher education level. The majority of respondents learned to use these technologies on their own, with "figured-it-out-myself" being reported by 25%-75% of respondents across the technologies. Overall, technologies were always used about 43% of the time, with wide variability among the technologies. Across all technologies, nearly 70% of respondents who had these technologies believed that they made them a safer driver. With regard to vehicle adaptations, less than 9% of respondents had at least one vehicle adaptation present, with the number of adaptations per vehicle ranging from 0 to 4. A large majority did not work with a professional to make or learn about the aftermarket vehicle adaptation., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

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., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Advances are being made in vehicle technologies that may help older adults compensate for some of the declines in abilities associated with aging. These advances hold promise for increasing vehicle safety, reducing injuries, and making the driving task more comfortable. However, important research gaps remain with regard to how various advanced technologies impact the safety of older drivers, as well as older drivers' perceptions about these technologies. This special issue contains seven original contributions that address these issues. Specific topics include the: congruence of design guidelines with the needs and abilities of older drivers, transfer of control between automated and manual driving, use of in-vehicle monitoring technology, motivations for technology use and assigned meanings, technology valuation, and effects on driving behavior., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

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., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Yellow signal indications at intersections are well-known to be a contributor to traffic crashes. This study examined drivers' behavior during yellow signal indication (i.e., indecision zone) maneuvers. Data from a driving simulator study was used, which included drivers' performance data when they encountered a yellow signal indication at intersections under different secondary-task conditions. This study calculated drivers' likelihood to go through a yellow signal indication and examined factors that are related to drivers' decision making on intersection traversing. The results showed that drivers' decision on stopping or not at a yellow signal indication was associated with different variables including age, distraction, pedal conditions, and time to stop line. Distracted drivers' insensitive behavior was also captured from the significant interaction effect between time to stop line and distraction conditions, which implied that intersection related crash risk may increase when drivers were distracted., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Motorcycle crashes result in a significant health burden, including many fatal injuries and serious non-fatal head injuries. Helmets are highly effective in preventing such trauma, and jurisdictions that require helmet use of all motorcyclists have higher rates of helmet use and lower rates of head injuries among motorcyclists. The current study examines helmet use and characteristics of helmeted operators and their riding conditions in Michigan, following a weakening of the state's universal motorcycle helmet use law in April 2012. Data on police-reported crashes occurring during 2012-14 and from a stratified roadside observational survey undertaken in Southeast Michigan during May-September 2014 were used to estimate statewide helmet use rates. Observed helmet use was more common among operators of sports motorcycles, on freeways, and in the morning, and least common among operators of cruisers, on minor arterials, and in the afternoon. The rate of helmet use across the state was estimated at 75%, adjusted for roadway type, motorcycle class, and time of day. Similarly, the helmet use rate found from examination of crash records was 73%. In the observation survey, 47% of operators wore jackets, 94% wore long pants, 54% wore boots, and 80% wore gloves. Protective clothing of jackets and gloves was most often worn by sport motorcycle operators and long pants and boots most often by riders of touring motorcycles. Findings highlight the much lower rate of helmet use in Michigan compared with states that have a universal helmet use law, although the rate is higher than observed in many states with partial helmet laws. Targeted interventions aimed at specific groups of motorcyclists and situations where helmet use rates are particularly low should be considered to increase helmet use., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Adolescents value protecting friends from harm and report that they do intervene as bystanders in friends' risky and dangerous behavior. Moreover intervention can be effective in reducing such behaviors. The Protection-Risk Framework was used to explain bystander intervention. There were 962 students from 13 Australian high schools (mean age at time 1=13.44 years) surveyed in their 9th grade and again 1-year later when students were in 10th grade. We found that protective factors of self-efficacy, support, prosocial models, social control, and ease of opportunity related to greater intervening behavior after 12-months. Among those who reported that they had intervened in a 3-month period, a cumulative measure of protective factors was associated with their reports of intervening. Risk factors were non-significant predictors after accounting for earlier, time 1, bystander intervening behavior and demographic factors. The findings highlight potential mechanisms to promote adolescents' looking out for their friends and provide an assessment over time of bystander behavior. The theory-guided inquiry into such behavior provides a foundation on which to better develop our understanding of benefits to adolescent friendship in the injury field., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

The purpose of this study was to determine whether a driver's use of turn signals is sufficiently reliable to forecast a vehicle's future path around an intersection, when detailed information about the intersection is unavailable. Naturalistic observations of turn signal use among 108 drivers on surface streets were extracted from the baseline portion of a field operational test of a safety system. Left and right turns that resulted in heading changes of between 70 and 110° and turn radii between 18 and 90 m were selected from the dataset. The odds that a driver would signal a turn were modeled as a function of road type, turn direction, presence of a forward vehicle, whether the vehicle stopped before the turn, and driver age and gender. Overall, 25 percent of left turns and 29 percent of right turns were not signaled. Road type, turn direction, and presence of a forward vehicle were found to influence the odds that a turn is signaled, while gender and age of the driver did not. The results suggest that situational factors like road type and turn direction are more powerful predictors of whether a turn will be signaled than either age or gender. Signaling on major and minor surface roads was about 5 times more likely than on local roads and 1.5 times more likely when a forward vehicle was present, suggesting a possible effect of traffic volume. It was concluded that turn signal activation alone may be insufficiently reliable to forecast a driver's path., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Based on existing literature, a system thinking approach was used to set up a conceptual model on the interrelationships among the components influencing adolescent road mortality, distinguishing between components at the individual level and at the system level. At the individual level the role of risk behaviour (sometimes deliberate and sometimes from inexperience or other non-deliberate causes) in adolescent road mortality is well documented. However, little is known about the extent to which the 'road system' itself may also have an impact on younger adolescents' road mortality. This, by providing a safe or unsafe road environment for all road users (System-induced exposure) and by allowing access to high-risk vehicles at a young or older age through the legal licensing age. This study seeks to explore these relationships by analysing the extent to which the road mortality of 10 to 17 year olds in various jurisdictions can be predicted from the System-induced Exposure (SiE) in a jurisdiction and from its legal licensing age to drive motor vehicles. SiE was operationalized as the number of road fatalities per 10(5) inhabitants/all ages together, but excluding the 10 to 17 year olds. Data on road fatalities during the years 2001 through 2008 were obtained from the OECD International Road Traffic Accident Database (IRTAD) and from the USA NHTSA's Fatality Analysis Reporting System (FARS) database for 29 early and 10 late licensing jurisdictions. Linear mixed models were fitted with annual 'Adolescent road mortality per capita' for 2001 through 2008 as the dependent variable, and time-dependent 'SiE' and time-independent 'Licensing system' as predictor variables. To control for different levels of motorisation, the time-dependent variable 'Annual per capita vehicle distance travelled' was used as a covariate. Licensing system of a jurisdiction was entered as a categorical predictor variable with late licensing countries as a baseline group. The study found support for the protective effects of SiE on adolescent safety. If SiE increased by one unit, the mortality rate of 10 to 17 year olds increased by 0.487 units. No support was found for a protective effect of late licensing for this age group. Thus, compared to young adolescents who are allowed to drive motor vehicles in early licensing jurisdictions, late licensing does not provide extra protection for pre-license adolescents. This finding is probably the result of the high risks associated with alternative transport modes, such as moped riding and bicycling. Also, the fact that the study only included risks to young adolescents themselves and did not include the risks they might pose to other road users and passengers may have contributed to this finding, because such risks are greater when driving a motor vehicle than riding a moped or a bicycle. Therefore, to advance our understanding of the impact of licensing systems, more study is needed into the benefits of early or late licensing, thereby considering these wider effects as well., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Background: The effects of age, body mass index (BMI) and gender on motor vehicle crash (MVC) injuries are not well understood and current prevention efforts do not effectively address variability in occupant characteristics., Objectives: (1) Characterize the effects of age, BMI and gender on serious-to-fatal MVC injury. (2) Identify the crash modes and body regions where the effects of occupant characteristics on the numbers of occupants with injury is largest, and thereby aid in prioritizing the need for human surrogates that represent different types of occupant characteristics and adaptive restraint systems that consider these characteristics., Methods: Multivariate logistic regression was used to model the effects of occupant characteristics (age, BMI, gender), vehicle and crash characteristics on serious-to-fatal injuries (AIS 3+) by body region and crash mode using the 2000-2010 National Automotive Sampling System (NASS-CDS) dataset. Logistic regression models were applied to weighted crash data to estimate the change in the number of annual injured occupants with AIS 3+ injury that would occur if occupant characteristics were limited to their 5th percentiles (age≤17 years old, BMI≤19kg/m(2)) or male gender., Results: Limiting age was associated with a decrease in the total number of occupants with head [8396, 95% CI 6871-9070] and thorax injuries [17,961, 95% CI 15,960-18,859] across all crash modes, decreased occupants with spine [3843, 95% CI 3065-4242] and upper extremity [3578, 95% CI 1402-4439] injuries in frontal and rollover crashes and decreased abdominal [1368, 95% CI 1062-1417] and lower extremity [4584, 95% CI 4012-4995] injuries in frontal impacts. The age effect was modulated by gender with older females more likely to have thorax and upper extremity injuries than older males. Limiting BMI was associated with 2069 [95% CI 1107-2775] fewer thorax injuries in nearside crashes, and 5304 [95% CI 4279-5688] fewer lower extremity injuries in frontal crashes. Setting gender to male resulted in fewer occupants with head injuries in farside crashes [1999, 95% CI 844-2685] and fewer thorax [5618, 95% CI 4212-6272], upper [3804, 95% CI 1781-4803] and lower extremity [2791, 95% CI 2216-3256] injuries in frontal crashes. Results indicate that age provides the greater relative contribution to injury when compared to gender and BMI, especially for thorax and head injuries., Conclusions: Restraint systems that account for the differential injury risks associated with age, BMI and gender could have a meaningful effect on injury in motor-vehicle crashes. Computational models of humans that represent older, high BMI, and female occupants are needed for use in simulations of particular types of crashes to develop these restraint systems., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

A practical approach was developed to assess and compare the effects of five short road safety education (RSE) programmes for young adolescents that does not rely on injury or crash data but uses self reported behaviour. Questionnaires were administered just before and about one month after participation in the RSE programmes, both to youngsters who had participated in a RSE programme, the intervention group, and to a comparable reference group of youngsters who had not, the reference group. For each RSE programme, the answers to the questionnaires in the pre- and post-test were checked for internal consistency and then condensed into a single safety score using categorical principal components analysis. Next, an analysis of covariance was performed on the obtained safety scores in order to compare the post-test scores of the intervention and reference groups, corrected for their corresponding pre-test scores. It was found that three out of five RSE programmes resulted in significantly improved self-reported safety behaviour. However, the proportions of participants that changed their behaviour relative to the reference group were small, ranging from 3% to 20%. Comparisons among programme types showed cognitive approaches not to differ in effect from programmes that used fear-appeal approaches. The method used provides a useful tool to assess and compare the effects of different education programmes on self-reported behaviour., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Self-regulation shows promise as a means by which older adults can continue to drive at some level without having to stop altogether. Self-regulation is generally described as the process of modifying or adjusting one's driving patterns by driving less or intentionally avoiding driving situations considered to be challenging, typically in response to an awareness that driving skills have declined. However, most studies asking older adults whether they avoid certain driving situations or have reduced the amount of driving they do under certain circumstances have not delved deeper into the motivations for such avoidance or driving reduction. There are many reasons for modifying driving that have nothing to do with self-regulation, such as no longer needing to take trips at certain times of day because of changes in preferences or lifestyles. The purpose of this study was to examine self-regulatory practices among older adults at multiple levels of driver performance and decision making, taking into account the specific motivations for avoiding particular driving situations or engaging in other driving practices. Study participants completed a computer-based questionnaire on driving self-regulation. Results suggest that self-regulation is a complex process that cannot be defined simply by the reported driving modifications made by drivers. Understanding the motivations for these behaviors is necessary and the study showed that they are varied and differ considerably across driving situations. Reasons for driving avoidance or other practices were often more closely related to lifestyle or preferences than to self-regulation. Based on these findings, three distinct groups were identified with regard to whether and for what reasons participants modified their driving., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Background: Most studies evaluating the effectiveness of Graduated Driver Licensing (GDL) have focused on the overall system. Studies examining individual components have rarely accounted for the confounding of multiple, simultaneously implemented components. The purpose of this paper is to quantify the effects of a required learner license duration and required hours of supervised driving on teen driver fatal crashes., Methods: States that introduced a single GDL component independent of any other during the period 1990-2009 were identified. Monthly and quarterly fatal crash rates per 100,000 population of 16- and 17-year-old drivers were analyzed using single-state time series analysis, adjusting for adult crash rates and gasoline prices. Using the parameter estimates from each state's time series model, the pooled effect of each GDL component on 16- and 17-year-old drivers' fatal crashes was estimated using a random effects meta-analytic model to combine findings across states., Results: In three states, a six-month minimum learner license duration was associated with a significant decline in combined 16- and 17-year-old drivers' fatal crash rates. The pooled effect of the minimum learner license duration across all states in the sample was associated with a significant change in combined 16- and 17-year-old driver fatal crash rates of -.07 (95% Confidence Interval [CI] -.11, -.03). Following the introduction of 30 h of required supervised driving in one state, novice drivers' fatal crash rates increased 35%. The pooled effect across all states in the study sample of having a supervised driving hour requirement was not significantly different from zero (.04, 95% CI -.15, .22)., Conclusion: These findings suggest that a learner license duration of at least six-months may be necessary to achieve a significant decline in teen drivers' fatal crash rates. Evidence of the effect of required hours of supervised driving on teen drivers' fatal crash rates was mixed., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Self-regulation shows promise as a means by which older adults can continue to drive at some level without having to stop altogether. Self-regulation is generally described as the process of modifying or adjusting one's driving patterns by driving less or intentionally avoiding driving situations considered to be challenging, typically in response to an awareness that driving skills have declined. However, most studies asking older adults whether they avoid certain driving situations or have reduced the amount of driving they do under certain circumstances have not delved deeper into the motivations for such avoidance or driving reduction. There are many reasons for modifying driving that have nothing to do with self-regulation, such as no longer needing to take trips at certain times of day because of changes in preferences or lifestyles. The purpose of this study was to examine self-regulatory practices among older adults at multiple levels of driver performance and decision making, taking into account the specific motivations for avoiding particular driving situations or engaging in other driving practices. Study participants completed a computer-based questionnaire on driving self-regulation. Results suggest that self-regulation is a complex process that cannot be defined simply by the reported driving modifications made by drivers. Understanding the motivations for these behaviors is necessary and the study showed that they are varied and differ considerably across driving situations. Reasons for driving avoidance or other practices were often more closely related to lifestyle or preferences than to self-regulation. Based on these findings, three distinct groups were identified with regard to whether and for what reasons participants modified their driving., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

A laboratory study was conducted to quantify the effects of belt-positioning boosters on lap and shoulder belt fit. Postures and belt fit were measured for forty-four boys and girls ages 5-12 in four highback boosters, one backless booster, and on a vehicle seat without a booster. Belt anchorage locations were varied over a wide range. Seat cushion angle, seat back angle, and seat cushion length were varied in the no-booster conditions. All boosters produced better mean lap belt fit than was observed in the no-booster condition, but the differences among boosters were relatively large. With one midrange belt configuration, the lap belt was not fully below the anterior-superior iliac spine (ASIS) landmark on the front of the pelvis for 89% of children in one booster, and 75% of children failed to achieve that level of belt fit in another. In contrast, the lap belt was fully below the ASIS for all but two children in the best-performing booster. Child body size had a statistically significant but relatively small effect on lap belt fit. The largest children sitting without a booster had approximately the same lap belt fit as the smallest children experienced in the worst-performing booster. Increasing lap belt angle relative to horizontal produced significantly better lap belt fit in the no-booster condition, but the boosters isolated the children from the effects of lap belt angles. Reducing seat cushion length in the no-booster condition improved lap belt fit but changing cushion angle did not. Belt upper anchorage (D-ring) location had a strong effect on shoulder belt fit in conditions without shoulder belt routing from the booster. Unexpectedly, the worst average shoulder belt fit was observed in one highback booster with a poorly positioned shoulder belt routing clip. The shoulder belt was routed more outboard, on average, with a backless booster than without a booster, but raising the child also amplified the effect of D-ring location, such that children were more likely to experience poor shoulder belt fit due to outboard and forward D-ring locations when sitting on the booster. Taller children experienced more-outboard shoulder belt fit in conditions without shoulder belt routing by the booster and in the one booster with poor shoulder belt routing. Adjustable shoulder belt routing on three of the highback boosters effectively eliminated stature effects, providing approximately the same shoulder belt fit for all children. Seat back angle did not have a significant effect on shoulder belt fit. The results of this study have broad applicability toward the improvement of occupant restraints for children The data show substantial effects of booster design on belt fit, particularly the effects of alternative lap and torso belt routing approaches. The data quantify the critical importance of belt anchorage location for child belt fit, providing an important foundation for efforts to optimize belt geometry for children., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

According to the Alzheimer's Association (2011), (1) in 8 people age 65 and older, and about one-half of people age 85 and older, have Alzheimer's disease in the United States (US). There is evidence that drivers with Alzheimer's disease and related dementias are at an increased risk for unsafe driving. Recent advances in sensor, computer, and telecommunication technologies provide a method for automatically collecting detailed, objective information about the driving performance of drivers, including those with early stage dementia. The objective of this project was to use in-vehicle technology to describe a set of driving behaviors that may be common in individuals with early stage dementia (i.e., a diagnosis of memory loss) and compare these behaviors to a group of drivers without cognitive impairment. Seventeen drivers with a diagnosis of early stage dementia, who had completed a comprehensive driving assessment and were cleared to drive, participated in the study. Participants had their vehicles instrumented with a suite of sensors and a data acquisition system, and drove 1-2 months as they would under normal circumstances. Data from the in-vehicle instrumentation were reduced and analyzed, using a set of algorithms/heuristics developed by the research team. Data from the early stage dementia group were compared to similar data from an existing dataset of 26 older drivers without dementia. The early stage dementia group was found to have significantly restricted driving space relative to the comparison group. At the same time, the early stage dementia group (which had been previously cleared by an occupational therapist as safe to drive) drove as safely as the comparison group. Few safety-related behavioral errors were found for either group. Wayfinding problems were rare among both groups, but the early stage dementia group was significantly more likely to get lost., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

There is considerable variation in seat belt use within the United States despite extensive evidence that the use of seat belts saves lives. Previous studies have identified some important factors that affect belt use rates, including gender, age, race, vehicle type, seat-belt enforcement laws, and amount of fine for belt-use law violation. In this study, we examined the influence of additional socio-demographic factors on state-level use rates: education (percentage of high school educated population), racial composition (percentage White), median household income, political leaning (percentage Democrat), and a measure of religiosity. These variables, which collectively characterize the 'culture' of a state, have received little attention in seat-belt studies. The paper reports results from a multiple regression analysis of data from the 2008 Fatality Analysis Reporting System (FARS). Many of the use rate patterns in FARS data were consistent with those found in other data sets, suggesting that conclusions based on FARS data are likely to hold for the population-at-large. Of the five cultural factors considered in the study, three were identified as important in explaining the differences in seat belt use at the state level: religiosity, race (percentage White), and political leaning (percentage Democrat). The other two variables - income and education - were not significant. Hold-out analyses confirmed that this conclusion was consistent across different subsets of data. The findings from this study are preliminary and have to be confirmed on other data sets. Nevertheless, they demonstrate the potential usefulness of cultural factors in explaining state-to-state variation in seat belt use rates. If factors such as religiosity are indeed important, they can be used to develop culturally appropriate programs for increasing belt use., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Older occupants in motor-vehicle crashes are more likely to experience injury than younger occupants. One possible reason for this is that increasing age is associated with increased prevalence of osteoporosis, which decreases bone strength. Crash-injury data were used with Bayes' Theorem to estimate the conditional probability of AIS 3+ skeletal injury given that an occupant is osteoporotic for the injury to the head, spine, thorax, lower extremities, and upper extremities. This requires the conditional probabilities of osteoporosis given AIS 3+ injury for each of the body regions, which were determined from analysis of the Crash Injury Research and Engineering Network database. It also requires information on probability of osteoporosis in the crash-involved population and the probabilities of AIS 3+ skeletal injury to different body regions in crashes. The latter probabilities were obtained from the National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) database. The former was obtained by modeling the probability of osteoporosis in the US populations using data from the 2006 National Health Examination Nutrition Survey and applying this model to the estimate of the crash-involved population in NASS-CDS. To attempt to account for the effects of age on injury outcome that are independent of osteoporosis, only data from occupants who were 60 years of age or older were used in all analyses. Results indicate that the only body region that experiences a statistically significant change in fracture injury risk with osteoporosis is the spine, for which osteoporosis increases the risk of AIS 3+ fracture by 3.28 times, or from 0.41% to 1.34% (p<0.0001). This finding suggests that the increase in AIS 3+ injury risk with age for non-spine injuries is likely influenced by factors other than osteoporosis., (2010 Elsevier Ltd. All rights reserved.)

Injury risk curves for the skeletal knee-thigh-hip (KTH) relate peak force applied to the anterior aspect of the flexed knee, the primary source of KTH injury in frontal motor-vehicle crashes, to the probability of skeletal KTH injury. Previous KTH injury risk curves have been developed from analyses of peak knee-impact force data from studies where knees of whole cadavers were impacted. However, these risk curves either neglect the effects of occupant gender, stature, and mass on KTH fracture force, or account for them using scaling factors derived from dimensional analysis without empirical support. A large amount of experimental data on the knee-impact forces associated with KTH fracture are now available, making it possible to estimate the effects of subject characteristics on skeletal KTH injury risk by statistically analyzing empirical data. Eleven studies were identified in the biomechanical literature in which the flexed knees of whole cadavers were impacted. From these, peak knee-impact force data and the associated subject characteristics were reanalyzed using survival analysis with a lognormal distribution. Results of this analysis indicate that the relationship between peak knee-impact force and the probability of KTH fracture is a function of age, total body mass, and whether the surface that loads the knee is rigid. Comparisons between injury risk curves for the midsize adult male and small adult female crash test dummies defined in previous studies and new risk curves for these sizes of occupants developed in this study suggest that previous injury risk curves generally overestimate the likelihood of KTH fracture at a given peak knee-impact force. Future work should focus on defining the relationships between impact force at the human knee and peak axial compressive forces measured by load cells in the crash test dummy KTH complex so that these new risk curves can be used with ATDs.

Belt-positioning booster seats are recommended for children who use vehicle seat belts as primary restraints but who are too small to obtain good belt fit. Previous research has shown that belt-positioning boosters reduce injury risk, but the belt fit produced by the wide range of boosters in the US market has not previously been assessed. The present study describes the development of a method for quantifying static belt fit with a Hybrid-III 6-year-old test dummy. The measurement method was applied in a laboratory seat mockup to 31 boosters (10 in both backless and highback modes) across a range of belt geometries obtained from in-vehicle measurements. Belt fit varied widely across boosters. Backless boosters generally produced better lap belt fit than highback boosters, largely because adding the back component moved the dummy forward with respect to the lap belt routing guides. However, highback boosters produced more consistent shoulder belt fit because of the presence of belt routing guides near the shoulder. Some boosters performed well on both lap belt and shoulder belt fit. Lap belt fit in dedicated boosters was generally better than in combination restraints that also can be used with an integrated harness. Results demonstrate that certain booster design features produce better belt fit across a wide range of belt geometries. Lap belt guides that hold the belt down, rather than up, and shoulder belt guides integrated into the booster backrest provided better belt fit.

This study examined the association between psychosocial maturation and problem driving behavior in young adulthood. Psychosocial maturation is the process of adopting adult roles, attitudes and behaviors and completing developmental tasks associated with becoming an adult. Past research has demonstrated that individuals' participation in health-risk behaviors decreases as psychosocial maturity increases. Not surprisingly, decreases in driving risk that occur over the first years of driving have often been assumed to result in large degree from general maturation; however, no research has tested this assumption. This study used data from a telephone survey of young adults to begin addressing this gap in the literature by testing three hypotheses: (1) indicators of higher psychosocial maturity are associated with lower problem driving behavior; (2) the association between the level of psychosocial maturity and problem driving behavior is cumulative; and, (3) these associations are moderated by sex. Problem driving behavior was evaluated by assessing three measures: high-risk driving, drink/driving, and drug/driving. Results supported all three hypotheses. Participants with greater psychosocial maturity had lower levels of problem driving behavior than participants who were less psychosocially mature. Second, problem driving behavior was lower with higher psychosocial maturity. Third, these associations between psychosocial maturity and problem driving behavior were moderated by sex. The primary contributions of this study are: (1) initial evidence that psychosocial maturation may play a role in improvements in the safety of young drivers; and (2) the generation of questions and hypotheses that provide direction for future research on the role of maturation in observed declines in risk among young drivers.

The purpose of this study was to better understand how older adults self-regulate driving, and to identify differences by age, sex, and health-related functioning. Michigan drivers over age 64 were surveyed by telephone (n=961, age [mu=74.2, sigma=5.8], 56% female) about their driving-related behaviors, physical functioning, and health. Respondents were presented with scenarios involving driving to an important appointment under adverse conditions (rainy stormy weather, on alternate route in heavy freeway traffic, 200-mile trip on unfamiliar roads). Generalized logit models examined outcomes for each scenario: driving as usual, driving with modifications, and not driving. Results indicate that the effect of sex on self-regulation was significant and greater than that of age and physical functioning. Women were more likely to self-regulate by not driving. Odds ratios and 95% confidence limits for each scenario for women vs. men are 6.8 (3.8-2.0), 6.5 (3.6-12.0), and 17.7 (11.0-28.6). The effect of sex on self-regulation by modifying driving was smaller and significant only in scenarios 2 and 3. Women were more likely then men to modify driving for scenario 2 (odds ratio, 3.0 (2.0-4.5)) and scenario 3 (odds ratio 4.4 (3.1-0.1)). Overall, the study finds the relative effect of sex on self-regulation greater than that of age and physical functioning for conditions examined.

This manuscript reports the results of an evaluation of two community-based booster seat promotion programs in Michigan; one program focused on a low-income community, while the other focused on a Hispanic community. Each community received funding to develop and implement a booster seat intervention program specific to their community. To determine the effectiveness of each program, direct observation surveys of booster seat use were conducted in each community, as well as in similarly composed comparison communities, before and after program implementation. A process evaluation documented activities and provided additional information for interpreting the results of the direct observation survey. Target age children (4-8 years) were observed traveling in cars, vans/minivans, sport-utility vehicles, and pickup trucks in each community. Baseline booster seat use was 19.0+/-5.3% and 9.7+/-2.5% for the low-income and Hispanic program communities, respectively. Post program results showed no significant change for the low-income program community, and a significant increase within the Hispanic program community. The process evaluation revealed challenges for each program and suggestions to overcome those challenges. Findings from the study can be useful to other communities interested in implementing programs to increase the use of booster seats.

The influence of light level was determined for three pedestrian crash scenarios associated with three adaptive headlighting solutions-curve lighting, motorway lighting, and cornering light. These results were coupled to corresponding prevalence data for each scenario to derive measures of annual lifesaving potential. For each scenario, the risk associated with light level was determined using daylight saving time (DST) transitions to produce a dark/light interval risk ratio; prevalence was determined using the corresponding annual crash rate in darkness for each scenario. For curve lighting, pedestrian crashes on curved roadways were examined; for motorway lighting, crashes associated with high speed roadways were examined; and for cornering light, crashes involving turning vehicles at intersections were examined. In the curve analysis, lower dark/light crash ratios were observed for curved sections of roadway compared to straight roads. In the motorway analysis, posted speed limit was the dominant predictor of this ratio for the fatal crash dataset; road function class was the dominant predictor of the ratio for the fatal/nonfatal dataset. Finally, in the intersection crash analysis, the dark/light ratio for turning vehicles was lower than for nonturning vehicles; and the ratio at intersections was lower than at non-intersections. Relative safety need was determined by combining the dark/light ratio with prevalence data to produce an idealized measure of lifesaving potential. While all three scenarios suggested a potential for safety improvement, scenarios related to high speed roadway environments showed the greatest potential.

This study used telephone interview data on booster seat use from a state-wide probability sample of parents with children ages 4-8-years-old who were living in Michigan. Interviews were completed with parents of children in 350 households. Analyses examined the entire sample, and three sub-groups: always users, part-time booster seat users, and booster seat non-users. Results indicated that booster seat legislation was a key determinant of the level of use and the motivation to use booster seats. Nearly 70% of part-time users said that they used booster seats because they believed it was the law. Similarly, 60% of part-time and non-booster seat users said that they would be more likely to use booster seats if use were mandated by law, with non-users being 3.5 times more likely than part-time users to agree that a law would increase their booster seat use. Finally, over 90% of part-time and non-booster seat users said it would be easier for them to use booster seats if a law required it, and non-users were almost six times more likely than part-time users to agree that a law would make use easier. The need for booster seat laws, issues of social equity, and implications for intervention were discussed.

The influence of lateral visibility from the vehicle cabin on safety was evaluated by examining the differences in lane-change crashes of four-door and two-door body styles of the same vehicle models. These two vehicle styles were used because B-pillars (the pillars between the front and rear seats) on four-door models are farther forward, and thus nearer the fore-aft position of the driver. (Furthermore, the B-pillars on two-door models can be narrower, and some two-door models have no B-pillars at all.) To control for driver differences between these two body styles, going-straight-ahead crashes were used for comparison. The analysis used 2000-2003 North Carolina crash data, and considered the crash experience of four-door and two-door body styles for the same 10 vehicles for model years 1995 and newer. The main finding is that four-door body styles are more likely to be involved in lane-change crashes than are two-door body styles of the same vehicle models. This finding suggests that lateral visibility out of the vehicle cabin affects safety.

This study reports the results of a statewide survey of restraint use by 4-8-year-old children in Michigan conducted between July 13 and 29, 2004. In this study, 3420 4-8-year-old children were observed traveling in passenger cars, vans/minivans, sport-utility vehicles, and pickup trucks. Restraint use was estimated for children traveling in all vehicles combined, as well as for each vehicle type separately. Children's restraint use was also calculated by the sex, age, and belt use of the driver. Separate estimates were also made of the restraint use of 4-8-year-old children by the combination of sex and belt use of the driver. Overall, 8.6 +/- 5.9% of 4-8-year-old children were seated in a booster seat, 48.8 +/- 10.3% were wearing a safety belt, 5.1 +/- 3.4% were seated in a child safety seat, and the remaining 37.5 +/- 11.5% were traveling completely unrestrained. When examining the rates by vehicle type, booster seat use was highest among children riding in sport-utility vehicles and lowest for those in pickup trucks. Surprisingly, children riding in passenger cars were more likely to be completely unrestrained than those in any other type of vehicle. While the sex of the driver did not seem to influence the restraint use of target-aged children, the driver's age did seem to have an effect. Booster seat use was quite low (0.6%) for children traveling with a driver over the age of 60, compared to 7.0 and 9.1% for those riding with drivers 16-29 and 30-59 years of age, respectively. The safety belt use of the driver also had a substantial influence on children's restraint use. Irrespective of driver sex, children riding with belted drivers were traveling in booster seats about 10% of the time, while those riding with unbelted drivers were only in booster seats 1-2% of the time.

The purpose of the study was to identify daytime differences in safety belt use by race. Safety belt use was investigated in a direct observation survey of drivers and front-outboard passengers throughout Michigan. Data were weighted to calculate statewide safety belt use rates by race. Race was assessed visually by trained observers. The study showed that motor vehicle occupants identified as Black had significantly lower safety belt use than those occupants identified as White or Other.