Sheila G. Klauer

Distracted Driving and Risk of Road Crashes among Novice and Experienced Drivers

BACKGROUND Distracted driving attributable to the performance of secondary tasks is a major cause of motor vehicle crashes both among teenagers who are novice drivers and among adults who are experienced drivers. METHODS We conducted two studies on the relationship between the performance of secondary tasks, including cell-phone use, and the risk of crashes and near-crashes. To facilitate objective assessment, accelerometers, cameras, global positioning systems, and other sensors were installed in the vehicles of 42 newly licensed drivers (16.3 to 17.0 years of age) and 109 adults with more driving experience. RESULTS During the study periods, 167 crashes and near-crashes among novice drivers and 518 crashes and near-crashes among experienced drivers were identified. The risk of a crash or near-crash among novice drivers increased significantly if they were dialing a cell phone (odds ratio, 8.32; 95% confidence interval [CI], 2.83 to 24.42), reaching for a cell phone (odds ratio, 7.05; 95% CI, 2.64 to 18.83), sending or receiving text messages (odds ratio, 3.87; 95% CI, 1.62 to 9.25), reaching for an object other than a cell phone (odds ratio, 8.00; 95% CI, 3.67 to 17.50), looking at a roadside object (odds ratio, 3.90; 95% CI, 1.72 to 8.81), or eating (odds ratio, 2.99; 95% CI, 1.30 to 6.91). Among experienced drivers, dialing a cell phone was associated with a significantly increased risk of a crash or near-crash (odds ratio, 2.49; 95% CI, 1.38 to 4.54); the risk associated with texting or accessing the Internet was not assessed in this population. The prevalence of high-risk attention to secondary tasks increased over time among novice drivers but not among experienced drivers. CONCLUSIONS The risk of a crash or near-crash among novice drivers increased with the performance of many secondary tasks, including texting and dialing cell phones. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the National Highway Traffic Safety Administration.).

Near Crashes as Crash Surrogate for Naturalistic Driving Studies

Naturalistic driving is an innovative method for investigating driver behavior and traffic safety. However, as the number of crashes observed in naturalistic driving studies is typically small, crash surrogates are needed. A study evaluated the use of near crashes as a surrogate measure for assessment of the safety impact of driver behaviors and other risk factors. Two metrics, the precision and bias of risk estimation, were used to assess whether near crashes could be combined with crashes. The principles and exact conditions for improved precision and unbiased estimation were proposed and applied to data from the 100-Car Naturalistic Driving Study. The analyses indicated that a positive relationship exists between the frequencies of contributing factors for crashes and for near crashes. The study also indicated that analyses based on combined crash and near-crash data consistently underestimate the risk of contributing factors compared to use of crash data alone. At the same time, the precision of the estimation will increase. This consistent pattern allows investigators to identify true high-risk behaviors while qualitatively assessing potential bias. In summary, the study concluded that the use of near crashes as a crash surrogate provides definite benefit when naturalistic studies are not large enough to generate sufficient numbers of crashes for statistical analysis.

Keep your eyes on the road: young driver crash risk increases according to duration of distraction

PURPOSE Secondary task engagement that distracts the driver is a contributing factor to motor vehicle crashes among adults. However, the association between eye glance duration and crash risk with novice teenage drivers has not been determined. METHODS Vehicles of 42 newly licensed teenage drivers were instrumented with cameras, accelerometers, Global Positioning System(s) (GPS), and other devices. Data were collected continuously for 18 months. Crashes and near crashes (CNCs) were identified by examining highly elevated gravitational force events. Video footage of the 6 seconds prior to each CNC and randomly sampled non-CNC road segments were coded for the duration of eye glances off the forward roadway and the presence of secondary task engagement. The likelihood (odds ratios) of CNC due to eye glance behavior was calculated by comparing the prevalence of secondary task engagement and duration of eyes off road prior to CNC with the prevalence and duration of eyes off road during non-CNC road segments. RESULTS Crash risk increased with the duration of single longest glance during all secondary tasks (OR=3.8 for >2 s) and wireless secondary task engagement (OR=5.5 for >2 s). Single longest glance provided a more consistent estimate of crash risk than total time eyes off the forward roadway. CONCLUSIONS Those eye glances away from the forward roadway involving secondary tasks increased the likelihood of CNC. The longer the duration of eye glance away from the road the greater the risk, regardless of type of secondary task. Education and policy discouraging secondary task engagement, particularly for prolonged periods, is warranted.

DETECTION OF ROAD HAZARDS BY NOVICE TEEN AND EXPERIENCED ADULT DRIVERS.

Previous laboratory and simulator research has indicated that hazard detection skills and abilities are less developed among novice drivers compared with experienced adult drivers. Novices tend to miss some relevant cues and may be less able to process important elements in the environment while driving. It was hypothesized that novices would have lower hazard detection skills and would react less appropriately to hazards than older and more experienced drivers. Three hazard perception scenarios were simulated on a test track, and data were collected on newly licensed teen drivers (within 2 weeks of licensure) and a comparison group of adults. The scenarios included a hidden stop sign, hidden pedestrian, and hidden pedestrian with lane closure (this last included a text-messaging task). Discrete quantitative performance metrics were evaluated for this analysis, including the following: (a) Did the participant glance at the potential hazard (e.g., stop sign, pedestrian)? (b) Did the participant stop (for the stop sign scenario)? (c) Did the participant show signs of indecision, caution, or awareness (for all hazards)? Significant differences between teen drivers and more experienced adult drivers were found in a combined hazard detection analysis. Results indicated that the adult drivers observed hazards and demonstrated overt recognition of hazards more frequently than the teen drivers did. Results indicated that a large portion of teen drivers failed to disengage from peripheral task engagement in the presence of hazards. The results will be compared with naturalistic data for the same set of drivers to see whether these test track results are predictive of real-world behavior.

Novice Drivers’ Exposure to Known Risk Factors During the First 18 Months of Licensure: The Effect of Vehicle Ownership

Objective: Though there is ample research indicating that nighttime, teen passengers, and speeding increase the risk of crash involvement, there is little research about teen drivers’ exposure to these known risk factors. Three research questions were assessed in this article: (1) Does exposure to known risk factors change over time? (2) Do teenage drivers experience higher rates of exposure to known risk factors than adult drivers? (3) Do teenage drivers who own a vehicle experience higher rates of exposure to risk factors than those who share a family vehicle? Methods: Forty-one newly licensed teenage drivers and at least one parent (adult) were recruited at licensure. Driving data were recorded for 18 months. Results: Average vehicle miles traveled (VMT) or average nighttime VMT for teens did not increase over time. Teenagers consistently drove 24 percent of VMT at night, compared with 18 percent for adults. Teenagers drove 62 percent of VMT with no passengers, 29 percent of VMT with one passenger, and less than 10 percent of VMT with multiple passengers. Driving with no passengers increased with driving experience for these teens. Teenage drivers who owned their vehicles, relative to those who shared a vehicle, sped 4 times more frequently overall and more frequently at night and with multiple teen passengers. Conclusion: These findings are among the first objective data documenting the nature of teenage driving exposure to known risk factors. The findings provide evidence that vehicle access is related to risk and suggest the potential safety benefit of parental management of novice teenage driving exposure.

Estimating Crash Risk

Naturalistic driving research involves the instrumentation of vehicles, including video cameras, for the purpose of precisely recording participants as they normally drive as well as in the seconds leading up to crashes and near-crashes. The results provide new insight into driver behavior and performance that cannot be gained through traditional empirical approaches. Naturalistic driving studies provide context of the overall driving environment, information that is absent from other methods. This article highlights how results from naturalistic driving research have reshaped our understanding of driver behavior and crash risk, including the fact that some findings are contrary to results from other empirical approaches.

Naturalistic Teenage Driving Study: Findings and Lessons Learned

INTRODUCTION This paper summarizes the findings on novice teenage driving outcomes (e.g., crashes and risky driving behaviors) from the Naturalistic Teenage Driving Study. METHOD Survey and driving data from a data acquisition system (global positioning system, accelerometers, cameras) were collected from 42 newly licensed teenage drivers and their parents during the first 18 months of teenage licensure; stress responsivity was also measured in teenagers. RESULT Overall teenage crash and near-crash (CNC) rates declined over time, but were >4 times higher among teenagers than adults. Contributing factors to teenage CNC rates included secondary task engagement (e.g., distraction), kinematic risky driving, low stress responsivity, and risky social norms. CONCLUSIONS The data support the contention that the high novice teenage CNC risk is due both to inexperience and risky driving behavior, particularly kinematic risky driving and secondary task engagement. PRACTICAL APPLICATIONS Graduated driver licensing policy and other prevention efforts should focus on kinematic risky driving, secondary task engagement, and risky social norms.

Driver Inattention: A Contributing Factor to Crashes and Near-Crashes

Driver distraction, or inattention, has been receiving wide media attention recently as many state legislatures are considering various levels of restricting cell phone use. Research has been conducted using a variety of experimental methods to determine the level of risk associated with driving inattention. While most of this research suggests that inattention impairs driving, there have been no studies to directly link driving inattention to crashes. Data from the 100-Car Naturalistic Driving Study, an instrumented vehicle study for which data was collected on 100 drivers in the Washington, DC metropolitan area for 12 months, were used in the following analyses. Crashes and near-crashes were identified in the data using post-hoc triggers based upon driving performance metrics, (i.e. hard braking). Results suggest that inattention contributed to 78% of all crashes collected over the 12 month data collection period.

The effects of age on crash risk associated with driver distraction

Background Driver distraction is a major contributing factor to crashes, which are the leading cause of death for the US population under 35 years of age. The prevalence of secondary-task engagement and its impacts on distraction and crashes may vary substantially by driver age. Methods Driving performance and behaviour data were collected continuously using multiple cameras and sensors in situ for 3542 participant drivers recruited for up to 3 years for the Second Strategic Highway Research Program Naturalistic Driving Study. Secondary-task engagement at the onset of crashes and during normal driving segments was identified from videos. A case-cohort approach was used to estimate the crash odds ratios associated with, and the prevalence of, secondary tasks for four age groups: 16-20, 21-29, 30-64 and 65-98 years of age. Only severe crashes (property damage and higher severity) were included in the analysis. Results Secondary-task-induced distraction posed a consistently higher threat for drivers younger than 30 and above 65 when compared with middle-aged drivers, although senior drivers engaged in secondary tasks much less frequently than their younger counterparts. Secondary tasks with high visual-manual demand (e.g. visual-manual tasks performed on cell phones) affected drivers of all ages. Certain secondary tasks, such as operation of in-vehicle devices and talking/singing, increased the risk for only certain age groups. Conclusions Teenaged, young adult drivers and senior drivers are more adversely impacted by secondary-task engagement than middle-aged drivers. Visual-manual distractions impact drivers of all ages, whereas cognitive distraction may have a larger impact on young drivers.

Chapter 6 – Naturalistic Driving Studies and Data Coding and Analysis Techniques

Publisher Summary This chapter describes the traffic conflict technique and the theory behind the power of instrumented vehicle or naturalistic driving studies, the life cycle of naturalistic driving studies, and powerful analytic techniques that can and have been used with these data. Naturalistic driving data provide powerful tools for safety researchers that incorporate some characteristics of epidemiological data analysis techniques with empirical data analysis techniques. Although these characteristics are very beneficial, they also provide novel new data and analytic methods in which to explore and study driver safety, specifically driver behavior. The life cycle of naturalistic driving studies includes the following: study design and data collection, data preparation and storage, data coding, and data analysis. Each of these steps is complex primarily due to the size and the extent of the data being collected. Naturalistic driving studies typically collect 6–8 gigabytes of video per minute, which can easily result in thousands of hours of video collected, and 6–10 TB of data that must be prepared, stored, coded, and analyzed. Naturalistic driving studies are typically lengthy and resource-intensive but worth the rich, detailed data that can be collected. These types of studies are complex and require extensive planning both prior to data collection and through the entire life cycle of the study to ensure that the initial research objectives are appropriately evaluated. Detailed planning at every step in the life cycle will result in a much easier and efficient data analysis phase of the project.