Transporting Children in Autonomous Vehicles: An Exploratory Study.

OBJECTIVE: Identify factors that impact parents' decisions about allowing an unaccompanied child to ride in an autonomous vehicle (AV). BACKGROUND: AVs are being tested in several U.S. cities and on highways in multiple states. Meanwhile, suburban parents are using ridesharing services to shuttle children from school to extracurricular activities. Parents may soon be able to hire AVs to transport children. METHOD: Nineteen parents of 8- to 16-year-old children, and some of their children, rode in a driving simulator in autonomous mode, then were interviewed. Parents also participated in focus groups. Topics included minimum age for solo child passengers, types of trips unaccompanied children might take, and vehicle features needed to support child passengers. RESULTS: Parents would require two-way audio communication and prefer video feeds of vehicle interiors, seatbelt checks, automatic locking, secure passenger identification, and remote access to vehicle information. Parents cited convenience as the greatest benefit and fear that AVs could not protect passengers during unplanned trip interruptions as their greatest concern. CONCLUSION: Manufacturers have an opportunity to design family-friendly AVs from the outset, rather than retrofit them to be safe for child passengers. More research, especially usability studies where families interact with technology prototypes, is needed to understand how AV design impacts child passengers. APPLICATION: Potential applications of this research include not only designing vehicles that can be used to safely transport children, seniors who no longer drive, and individuals with disabilities but also developing regulations, policies, and societal infrastructure to support safe child transport via AVs.

Simulated Driving Assessment (SDA) for teen drivers: results from a validation study.

BACKGROUND: Driver error and inadequate skill are common critical reasons for novice teen driver crashes, yet few validated, standardised assessments of teen driving skills exist. The purpose of this study is to evaluate the construct and criterion validity of a newly developed Simulated Driving Assessment (SDA) for novice teen drivers. METHODS: The SDA's 35 min simulated drive incorporates 22 variations of the most common teen driver crash configurations. Driving performance was compared for 21 inexperienced teens (age 16-17 years, provisional license ≤90 days) and 17 experienced adults (age 25-50 years, license ≥5 years, drove ≥100 miles per week, no collisions or moving violations ≤3 years). SDA driving performance (Error Score) was based on driving safety measures derived from simulator and eye-tracking data. Negative driving outcomes included simulated collisions or run-off-the-road incidents. A professional driving evaluator/instructor (DEI Score) reviewed videos of SDA performance. RESULTS: The SDA demonstrated construct validity: (1) teens had a higher Error Score than adults (30 vs. 13, p=0.02); (2) For each additional error committed, the RR of a participant's propensity for a simulated negative driving outcome increased by 8% (95% CI 1.05 to 1.10, p<0.01). The SDA-demonstrated criterion validity: Error Score was correlated with DEI Score (r=-0.66, p<0.001). CONCLUSIONS: This study supports the concept of validated simulated driving tests like the SDA to assess novice driver skill in complex and hazardous driving scenarios. The SDA, as a standard protocol to evaluate teen driver performance, has the potential to facilitate screening and assessment of teen driving readiness and could be used to guide targeted skill training.

EMERGENCY BRAKING IN ADULTS VERSUS NOVICE TEEN DRIVERS: RESPONSE TO SIMULATED SUDDEN DRIVING EVENTS.

Motor vehicle crashes remain the leading cause of death in teens in the United States. Newly licensed drivers are the group most at risk for crashes. Their driving skills are very new, still very often untested, so that their ability to properly react in an emergency situation remains a research question. Since it is impossible to expose human subjects to critical life threatening driving scenarios, researchers have been increasingly using driving simulators to assess driving skills. This paper summarizes the results of a driving scenario in a study comparing the driving performance of novice teen drivers (n=21) 16-17 year olds with 90 days of provisional licensure with that of experienced adult drivers (n=17) 25-50 year olds with at least 5 years of PA licensure, at least 100 miles driven per week and no self-reported collisions in the previous 3 years. As part of a 30 to 35 simulated drive that encompassed the most common scenarios that result in serious crashes, participants were exposed to a sudden car event. As the participant drove on a suburban road, a car surged from a driveway hidden by a fence on the right side of the road. To avoid the crash, participants must hard brake, exhibiting dynamic control over both attentional and motor resources. The results showed strong differences between the experienced adult and novice teen drivers in the brake pressure applied. When placed in the same situation, the novice teens decelerated on average 50% less than the experienced adults (p<0.01).

Evaluation of a Risk Awareness Perception Training Program on Novice Teen Driver Behavior at Left-Turn Intersections.

Collisions at left turn intersections are among the most prevalent types of teen driver serious crashes, with inadequate surveillance as a key factor. Risk awareness perception training (RAPT) has shown effectiveness in improving hazard anticipation for latent hazards. The goal of this study was to determine if RAPT version 3 (RAPT-3) improved intersection turning behaviors among novice teen drivers when the hazards were not latent and frequent glancing to multiple locations at the intersection was needed. Teens aged 16-18 with ≤180 days of licensure were randomly assigned to: 1) an intervention group (n=18) that received RAPT-3 (Trained); or 2) a control group (n=19) that received no training (Untrained). Both groups completed RAPT-3 Baseline Assessment and the Trained group completed RAPT-3 Training and RAPT-3 Post Assessment. Training effects were evaluated on a driving simulator. Simulator (gap selection errors and collisions) and eye tracker (traffic check errors) metrics from six left-turn stop sign controlled intersections in the Simulated Driving Assessment (SDA) were analyzed. The Trained group scored significantly higher in RAPT-3 Post Assessment than RAPT-3 Baseline Assessment (p< 0.0001). There were no significant differences in either traffic check and gap selection errors or collisions among Trained and Untrained teens in the SDA. Though Trained teens learned about hazard anticipation related to latent hazards, learning did not translate to performance differences in left-turn stop sign controlled intersections where the hazards were not latent. Our findings point to further research to better understand the challenges teens have with left turn intersections.

In-depth analysis of crash contributing factors and potential ADAS interventions among at-risk drivers using the SHRP 2 naturalistic driving study.

OBJECTIVE: Motor vehicle crashes remain a significant problem. Advanced driver assistance systems (ADAS) have the potential to reduce crash incidence and severity, but their optimization requires a comprehensive understanding of driver-specific errors and environmental hazards in real-world crash scenarios. Therefore, the objectives of this study were to quantify contributing factors using the Strategic Highway Research Program 2 (SHRP 2) Naturalistic Driving Study (NDS), identify potential ADAS interventions, and make suggestions to optimize ADAS for real-world crash scenarios. METHODS: A subset of the SHRP 2 NDS consisting of at-fault crashes (n = 369) among teens (16-19 yrs), young adults (20-24 yrs), adults (35-54 yrs) and older adults (70+ yrs) were reviewed to identify contributing factors and potential ADAS interventions. Contributing factors were classified according to National Motor Vehicle Crash Causation Survey pre-crash assessment variable elements. A single critical factor was selected among the contributing factors for each crash. Case reviews with a multidisciplinary panel of industry experts were conducted to develop suggestions for ADAS optimization. Critical factors were compared across at-risk driving groups, gender, and incident type using chi-square statistics and multinomial logistic regression. RESULTS: Driver error was the critical factor in 94% of crashes. Recognition error (56%), including internal distraction and inadequate surveillance, was the most common driver error sub-type. Teens and young adults exhibited greater decision errors compared to older adults (p < 0.01). Older adults exhibited greater performance errors (p < 0.05) compared to teens and young adults. Automatic emergency braking (AEB) had the greatest potential to mitigate crashes (48%), followed by vehicle-to-vehicle communication (38%) and driver monitoring (24%). ADAS suggestions for optimization included (1) implementing adaptive forward collision warning, AEB, high-speed warning, and curve-speed warning to account for road surface conditions (2) ensuring detection of nonstandard road objects, (3) vehicle-to-vehicle communication alerting drivers to cross-traffic, (4) vehicle-to-infrastructure communication alerting drivers to the presence of pedestrians in crosswalks, and (5) optimizing lane keeping assist for end-departures and pedal confusion. CONCLUSIONS: These data provide stakeholders with a comprehensive understanding of critical factors among at-risk drivers as well as suggestions for ADAS improvements based on naturalistic data. Such data can be used to optimize ADAS for driver-specific errors and help develop more robust vehicle test procedures.

The Impact of driver distraction and secondary tasks with and without other co-occurring driving behaviors on the level of road traffic crashes.

Driving safety is typically affected by concurrent non-driving tasks. These activities might negatively impact the trips' outcome and cause near-crash or crash incidents and accidents. The crashes impose a tremendous social and economic cost to society and might affect the involving individuals' quality of life. As it stands, road injuries are ranked among top-ten leading causes of death by the World Health Organization. Distracted driving is defined as an attention diversion of the driver toward a competing activity. It was shown in numerous studies that distracted driving increase the probability of near-crash or crash events. By leveraging the statistical power of the large SHRP2 naturalistic data, we are able to quantify the preponderance of specific distractions during daily trips and confirm the causality factor of an ubiquitous non-driving task in the crash event. We show that, except for phone usage which happens more frequently in near-crash and crash categories than in baseline trips, both distracted driving and secondary tasks occur almost uniformly in different types of trips. In this study, we investigate the impact of the co-occurrence of distracted driving with other driving behaviors and secondary tasks. It is found that the co-occurrence of distracted driving with other driving behaviors or secondary tasks increase the chance of near-crash and crash events. This study's findings can inform the design and development of more precise and reliable driving assistance and warning systems.

Near crash characteristics among risky drivers using the SHRP2 naturalistic driving study.

PROBLEM: Previous research have focused extensively on crashes, however near crashes provide additional data on driver errors leading to critical events as well as evasive maneuvers employed to avoid crashes. The Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study contains extensive data on real world driving and offers a reliable methodology to study near crashes. The current study utilized the SHRP2 database to compare the rate and characteristics associated with near crashes among risky drivers. METHODS: A subset from the SHRP2 database consisting of 4,818 near crashes for teen (16-19 yrs), young adult (20-24 yrs), adult (35-54 yrs), and older (70+ yrs) drivers was used. Near crashes were classified into seven incident types: rear-end, road departure, intersection, head-on, side-swipe, pedestrian/cyclist, and animal. Near crash rates, incident type, secondary tasks, and evasive maneuvers were compared across age groups. For rear-end near crashes, near crash severity, max deceleration, and time-to-collision at braking were compared across age. RESULTS: Near crash rates significantly decreased with increasing age (p < 0.05). Young drivers exhibited greater rear-end (p < 0.05) and road departure (p < 0.05) near crashes compared to adult and older drivers. Intersection near crashes were the most common incident type among older drivers. Evasive maneuver type did not significantly vary across age groups. Near crashes exhibited a longer time-to-collision at braking (p < 0.01) compared to crashes. SUMMARY: These data demonstrate increased total near crash rates among young drivers relative to adult and older drivers. Prevalence of specific near crash types also differed across age groups. Timely execution of evasive maneuvers was a distinguishing factor between crashes or near crashes. Practical Applications: These data can be used to develop more targeted driver training programs and help OEMs optimize ADAS to address the most common errors exhibited by risky drivers.

Computer Vision to Automatically Assess Infant Neuromotor Risk.

An infant's risk of developing neuromotor impairment is primarily assessed through visual examination by specialized clinicians. Therefore, many infants at risk for impairment go undetected, particularly in under-resourced environments. There is thus a need to develop automated, clinical assessments based on quantitative measures from widely-available sources, such as videos recorded on a mobile device. Here, we automatically extract body poses and movement kinematics from the videos of at-risk infants (N = 19). For each infant, we calculate how much they deviate from a group of healthy infants (N = 85 online videos) using a Naïve Gaussian Bayesian Surprise metric. After pre-registering our Bayesian Surprise calculations, we find that infants who are at high risk for impairments deviate considerably from the healthy group. Our simple method, provided as an open-source toolkit, thus shows promise as the basis for an automated and low-cost assessment of risk based on video recordings.

Age and gender differences in emergency takeover from automated to manual driving on simulator.

Objective: The objective of this study was to explore how age and sex impact the ability to respond to an emergency when in a self-driving vehicle.Methods: For this study, 60 drivers (male: 48%, female: 52%) of different age groups (teens: aged 16-19, 32%, adults: aged 35-54, 37%, seniors: aged 65+, 32%) were recruited to share their perspectives on self-driving technology. They were invited to ride in a driving simulator that mimicked a vehicle in autopilot mode (longitudinal and lateral control).Results: In a scenario where the automated vehicle unexpectedly drives toward a closed highway exit, 21% of drivers did not react at all. For this event, where drivers had 6.2 s to avoid a crash, 40% of drivers crashed. Adults aged 35-54 crashed less than other age groups (33% crash rate), whereas teens crashed more (47% crash rate). Seniors had the highest crash rate (50% crash rate). Males (38% crash rate) crashed less than females (43% crash rate). All participants with a reaction time less than 4 s were able to avoid the crash.Conclusions: The results from the simulation drives show that humans lose focus when they do not actively drive so that their response in an emergency does not allow them to reclaim control quickly enough to avoid a crash.

Frontal and oblique crash tests of HIII 6-year-old child ATD using real-world, observed child passenger postures.

OBJECTIVE: The aim of this study was to evaluate the consequences of frontal and oblique crashes when positioning a Hybrid III (HIII) 6-year-old child anthropometric test device (ATD) using observed child passenger postures from a naturalistic driving study (NDS). METHODS: Five positions for booster-seated children aged 4-7 years were selected, including one reference position according to the FMVSS 213 ATD seating protocol and 4 based on real-world observed child passenger postures from an NDS including 2 user positions with forward tilting torso and 2 that combined both forward and lateral inboard tilting of the torso. Seventeen sled tests were conducted in a mid-sized vehicle body at 64 km/h (European New Car Assessment Programme [Euro NCAP] Offset Deformable Barrier [ODB] pulse), in full frontal and oblique (15°) crash directions. The rear-seated HIII 6-year-old child ATD was restrained on a high-back booster seat. In 10 tests, the booster seat was also attached with a top tether. In the oblique tests, the ATD was positioned on the far side. Three camera views and ATD responses (head, neck, and chest) were analyzed. RESULTS: The shoulder belt slipped off the shoulder in all ATD positions in the oblique test configuration. In full frontal tests, the shoulder belt stayed on the shoulder in 3 out of 9 tests. Head acceleration and neck tension were decreased in the forward leaning positions; however, the total head excursion increased up to 210 mm compared to te reference position, due to belt slip-off and initial forward leaning position. CONCLUSIONS: These results suggest that real-world child passenger postures may contribute to shoulder belt slip-off and increased head excursion, thus increasing the risk of head injury. Restraint system development needs to include a wider range of sitting postures that children may choose, in addition to the specified postures of ATDs in seating test protocols, to ensure robust performance across diverse use cases. In addition, these tests revealed that the child ATD is limited in its ability to mimic real-world child passenger postures. There is a need to develop child human body models that may offer greater flexibility for these types of crash evaluations.

Analysis of near crashes among teen, young adult, and experienced adult drivers using the SHRP2 naturalistic driving study.

OBJECTIVE: Motor vehicle crashes are the leading cause of death among young drivers. Though previous research has focused on crash events, near crashes offer additional data to help identify driver errors that could potentially lead to crashes as well as evasive maneuvers used to avoid them. The Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study (NDS) contains extensive data on real-world driving and offers a reliable methodology to quantify and study near crashes. This article presents findings on near crashes and how they compare to crash events among teen, young adult, and experienced adult drivers. METHODS: A subset from the SHRP2 database consisting of 1,653 near crashes for teen (16-19 years, n = 550), young adult (20-24 years, n = 748), and experienced adult (35-54 years, n = 591) drivers was used. Onboard instrumentation including scene cameras, accelerometers, and Global Positioning System logged time series data at 10 Hz. Scene videos were reviewed for all events to classify near crashes based on 7 types: rear-end, road departure, intersection, head-on, side-swipe, pedestrian/cyclist, and animal. Near crash rates, incident type, secondary tasks, and evasive maneuvers were compared across age groups and between crashes and near crashes. For rear-end near crashes, vehicle dynamic variables including near crash severity, headway distance, time headway, and time to collision at the time of braking were compared across age groups. Crashes and near crashes were combined to compare the frequency of critical events across age. RESULTS: Teen drivers exhibited a significantly higher (P <.01) near crash rate than young adult and experienced adult drivers. The near crash rates were 81.6, 56.6, and 37.3 near crashes per million miles for teens, young adults, and experienced adults, respectively. Teens were also involved in significantly more rear-end (P <.01), road departure (P <.01), side-swipe (P <.01), and animal (P <.05) near crashes compared to young and experienced adults. Teens exhibited a significantly greater (P <.01) critical event rate of 102.2 critical events per million miles compared to 72.4 and 40.0 critical events per million miles for young adults and experienced adults, respectively; the critical event rate ratio was 2.6 and 1.8 for teens and young adults, respectively. CONCLUSIONS: To our knowledge, this is the first study to examine near crashes among teen, young adult, and experienced adult drivers using SHRP2 naturalistic data. Near crash and critical event rates significantly decreased with increasing age and driver experience. Overall, teens were more than twice as likely to be involved in critical events compared to experienced adults. These data can be used to develop more targeted driver training programs and help manufacturers design active safety systems based on the most common driving errors for vulnerable road users.

Stereo 3D tracking of infants in natural play conditions.

This paper describes the design and implementation of a multiple view stereoscopic 3D vision system and a supporting infant tracker pipeline to track limb movement in natural play environments and identify potential metrics to quantify movement behavior. So far, human pose estimation and tracking with 3D cameras has been focused primarily on adults and cannot be directly extended to infants because of differences in visual features such as shapes, sizes and appearance. With rehabilitation in mind, we propose a portable, compact, markerless, low cost and high resolution 3D vision system and a tracking algorithm that exploits infant appearance attributes and depth information. This approach achieved a mean 3D tracking error of 8.21cm and a standard deviation of 8.75cm. We also identify two potential metrics for movement behavior analysis - approximate entropy and interaction events.

Automated recognition of rear seat occupants' head position using Kinect™ 3D point cloud.

INTRODUCTION: Child occupant safety in motor-vehicle crashes is evaluated using Anthropomorphic Test Devices (ATD) seated in optimal positions. However, child occupants often assume suboptimal positions during real-world driving trips. Head impact to the seat back has been identified as one important injury causation scenario for seat belt restrained, head-injured children (Bohman et al., 2011). There is therefore a need to understand the interaction of children with the Child Restraint System to optimize protection. METHOD: Naturalistic driving studies (NDS) will improve understanding of out-of-position (OOP) trends. To quantify OOP positions, an NDS was conducted. Families used a study vehicle for two weeks during their everyday driving trips. The positions of rear-seated child occupants, representing 22 families, were evaluated. The study vehicle - instrumented with data acquisition systems, including Microsoft Kinect™ V1 - recorded rear seat occupants in 1120 driving 26 trips. Three novel analytical methods were used to analyze data. To assess skeletal tracking accuracy, analysts recorded occurrences where Kinect™ exhibited invalid head recognition among a randomly-selected subset (81 trips). Errors included incorrect target detection (e.g., vehicle headrest) or environmental interference (e.g., sunlight). When head data was present, Kinect™ was correct 41% of the time; two other algorithms - filtering for extreme motion, and background subtraction/head-based depth detection are described in this paper and preliminary results are presented. Accuracy estimates were not possible because of their experimental nature and the difficulty to use a ground truth for this large database. This NDS tested methods to quantify the frequency and magnitude of head positions for rear-seated child occupants utilizing Kinect™ motion-tracking. RESULTS: This study's results informed recent ATD sled tests that replicated observed positions (most common and most extreme), and assessed the validity of child occupant protection on these typical CRS uses. SUMMARY: Optimal protection in vehicles requires an understanding of how child occupants use the rear seat space. This study explored the feasibility of using Kinect™ to log positions of rear seated child occupants. Initial analysis used the Kinect™ system's skeleton recognition and two novel analytical algorithms to log head location. PRACTICAL APPLICATIONS: This research will lead to further analysis leveraging Kinect™ raw data - and other NDS data - to quantify the frequency/magnitude of OOP situations, ATD sled tests that replicate observed positions, and advances in the design and testing of child occupant protection technology.

Comparison of crash rates and rear-end striking crashes among novice teens and experienced adults using the SHRP2 Naturalistic Driving Study.

OBJECTIVE: Motor vehicle crashes are the leading cause of death for teens. Previous teen and adult crash rates have been based upon fatal crashes, police-reported crashes, and estimated miles driven. Large-scale naturalistic driving studies offer the opportunity to compute crash rates using a reliable methodology to capture crashes and driving exposure. The Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study contains extensive real-world data on teen and adult driving. This article presents findings on the crash rates of novice teen and experienced adult drivers in naturalistic crashes. METHODS: A subset from the SHRP2 database consisting of 539 crash events for novice teens (16-19 years, n = 549) and experienced adults (35-54 years, n = 591) was used. Onboard instrumentation such as scene cameras, accelerometers, and Global Positioning System logged time series data at 10 Hz. Scene videos were reviewed for all events to identify rear-end striking crashes. Dynamic variables such as acceleration and velocity were analyzed for rear-end striking events. Number of crashes, crash rates, rear-end striking crash severity, and rear-end striking impact velocity were compared between novice teens and experienced adults. RESULTS: Video review of the SHRP2 crashes identified significantly more crashes (P < 0.01) and rear-end striking crashes (P < 0.01) among the teen group than among the adult group. This yielded crash rates of 30.0 crashes per million miles driven for novice teens compared to 5.3 crashes per million miles driven for experienced adults. The crash rate ratio for teens vs. adults was 5.7. The rear-end striking crash rate was 13.5 and 1.8 per million miles driven for novice teens and experienced adults, respectively. The rear-end striking crash rate ratio for teens vs. adults was 7.5. The rear-end striking crash severity measured by the accelerometers was greater (P < 0.05) for the teen group (1.8 ± 0.9 g; median = 1.6 g) than for the adult group (1.1 ± 0.4 g; median = 1.0 g), suggesting that teen crashes tend to be more serious than adult crashes. Increased rear-end striking impact velocity (P < 0.01) was also observed for novice teens (18.8 ± 13.2 mph; median = 18.9 mph) compared to experienced adults (3.3 ± 1.2 mph; median = 2.8 mph). CONCLUSION: To our knowledge, this is the first study to compare crash rates between teens and adults using a large-scale naturalistic driving database. Unlike previous crash rates, the reported rates reliably control for crash type and driving exposure. These results conform to previous findings that novice teens exhibit increased crash rates compared to experienced adults.

Naturalistic driving study of rear seat child occupants: Quantification of head position using a Kinect™ sensor.

OBJECTIVE: Restraint performance is evaluated using anthropomorphic test devices (ATDs) positioned in prescribed, optimal seating positions. Anecdotally, humans-children in particular-assume a variety of positions that may affect restraint performance. Naturalistic driving studies (NDSs), where cameras and other data acquisition systems are placed in a vehicle used by participants during their regular transportation, offer means to collect these data. To date, these studies have used conventional video and analysis methods and, thus, analyses have largely been qualitative. This article describes a recently completed NDS of child occupants in which their position was monitored using a Kinect sensor to quantify their head position throughout normal, everyday driving trips. METHODS: A study vehicle was instrumented with a data acquisition system to measure vehicle dynamics, a set of video cameras, and a Kinect sensor providing 3D motion capture at 1 Hz of the rear seat occupants. Participant families used the vehicle for all driving trips over 2 weeks. The child occupants' head position was manually identified via custom software from each Kinect color image. The 3D head position was then extracted and its distribution summarized by seat position (left, rear, center) and restraint type (forward-facing child restraint system [FFCRS], booster seat, seat belt). RESULTS: Data from 18 families (37 child occupants) resulted in 582 trips (with children) for analysis. The average age of the child occupants was 45.6 months and 51% were male. Twenty-five child occupants were restrained in FFCRS, 9 in booster seats, and 3 in seat belts. As restraint type moved from more to less restraint (FFCRS to booster seat to seat belt), the range of fore-aft head position increased: 218, 244, and 340 mm on average, respectively. This observation was also true for left-right movement for every seat position. In general, those in the center seat position demonstrated a smaller range of head positions. CONCLUSIONS: For the first time in a naturalistic setting, the range of head positions for child occupants was quantified. More variability was observed for those restrained in booster seats and seat belts than for those in FFCRS. The role of activities, in particular interactions with electronic devices, on head position was notable; this will be the subject of further analysis in other components of the broader study. These data can lead to solutions for optimal protection for occupants who assume positions that differ from prescribed, optimal testing positions.

HEADWAY TIME AND CRASHES AMONG NOVICE TEENS AND EXPERIENCED ADULT DRIVERS IN A SIMULATED LEAD TRUCK BRAKING SCENARIO.

Driving simulators can be used to evaluate driving performance under controlled, safe conditions. Teen drivers are at particular risk for motor vehicle crashes and simulated driving can provide important information on performance. We developed a new simulator protocol, the Simulated Driving Assessment (SDA), with the goal of providing a new tool for driver assessment and a common outcome measure for evaluation of training programs. As an initial effort to examine the validity of the SDA to differentiate performance according to experience, this analysis compared driving behaviors and crashes between novice teens (n=20) and experienced adults (n=17) on a high fidelity simulator for one common crash scenario, a rear-end crash. We examined headway time and crashes during a lead truck with sudden braking event in our SDA. We found that 35% of the novice teens crashed and none of the experienced adults crashed in this lead truck braking event; 50% of the teens versus 25% of the adults had a headway time <3 seconds at the time of truck braking. Among the 10 teens with <3 seconds headway time, 70% crashed. Among all participants with a headway time of 2-3 seconds, further investigation revealed descriptive differences in throttle position and brake pedal force when comparing teens who crashed, teens who did not crash and adults (none of whom crashed). Even with a relatively small sample, we found statistically significant differences in headway time for adults and teens, providing preliminary construct validation for our new SDA.