Using naturalistic driving data to examine drivers' seatbelt use behavior: Comparison between teens and adults

ProblemTeens and young drivers are often reported as one driver group that has significantly lower seatbelt use rates than other age groups.ObjectiveThis study was designed to address the questions of whether and how seatbelt-use behavior of novice teen drivers is different from young adult drivers and other adult drivers when driving on real roads.MethodDriving data from 148 drivers who participated in two previous naturalistic driving studies were further analyzed. The combined dataset represents 313,500 miles, 37,695 valid trips, and about 9500 h of driving. Drivers did not wear their seatbelts at all during 1284 trips. Two dependent variables were calculated, whether and when drivers used seatbelts during a trip, and analyzed using logistic regression models.ResultsResults of this study found significant differences in the likelihood of seatbelt use between novice teen drivers and each of the three adult groups. Novice teen drivers who recently received their driver's licenses were the most likely to use a seatbelt, followed by older drivers, middle-aged drivers, and young drivers. Young drivers were the least likely to use a seatbelt. Older drivers were also more likely to use seatbelts than the other two adult groups. The results also showed that novice teen drivers were more likely to fasten their seatbelts at the beginning of a trip when compared to the other three adult groups.SummaryNovice teen drivers who were still in the first year after obtaining their driver's license were the most conservative seatbelt users, when compared to adult drivers.Practical applicationFindings from this study have practical application insights in both developing training programs for novice teen drivers and designing seatbelt reminder and interlock systems to promote seatbelt use in certain driver groups.     

A pedestrian's smile and drivers' behavior: When a smile increases careful driving

IntroductionResearch has reported that smiles facilitate social relationships. However, the effect of a smile on driving behavior has received less interest.MethodThis study attempts to evaluate how a pedestrian's smile influences an oncoming driver's behavior. In the first part of our study, male and female research assistants waiting at several pedestrian crossings were asked to smile or not at oncoming drivers.ResultsIt was found that a smile increases the number of drivers who stop. The same effect was observed when the pedestrian tries to cross outside the pedestrian crossing. Finally, this study shows that motorists drive slower after they see a pedestrian smile, suggesting that a smile can induce a positive mood.Practical ApplicationsThis leads to motorists stopping more readily and driving more carefully. These results also suggest that pedestrians may increase their own safety by using appropriate nonverbal signals toward drivers.     

Examination of drivers' cell phone use behavior at intersections by using naturalistic driving data

IntroductionMany driving simulator studies have shown that cell phone use while driving greatly degraded driving performance. In terms of safety analysis, many factors including drivers, vehicles, and driving situations need to be considered. Controlled or simulated studies cannot always account for the full effects of these factors, especially situational factors such as road condition, traffic density, and weather and lighting conditions. Naturalistic driving by its nature provides a natural and realistic way to examine drivers' behaviors and associated factors for cell phone use while driving.MethodIn this study, driving speed while using a cell phone (conversation or visual/manual tasks) was compared to two baselines (baseline 1: normal driving condition, which only excludes driving while using a cell phone, baseline 2: driving-only condition, which excludes all types of secondary tasks) when traversing an intersection.ResultsThe outcomes showed that drivers drove slower when using a cell for both conversation and visual/manual (VM) tasks compared to baseline conditions. With regard to cell phone conversations, drivers were more likely to drive faster during the day time compared to night time driving and drive slower under moderate traffic compared to under sparse traffic situations. With regard to VM tasks, there was a significant interaction between traffic and cell phone use conditions. The maximum speed with VM tasks was significantly lower than that with baseline conditions under sparse traffic conditions. In contrast, the maximum speed with VM tasks was slightly higher than that with baseline driving under dense traffic situations.Practical applicationsThis suggests that drivers might self-regulate their behavior based on the driving situations and demand for secondary tasks, which could provide insights on driver distraction guidelines. With the rapid development of in-vehicle technology, the findings in this research could lead the improvement of human-machine interface (HMI) design as well.     

Safe driving practices and factors associated with motor-vehicle collisions among people with insulin-treated diabetes mellitus: Results from the Diabetes and Driving (DAD) study

IntroductionThe aim of this study was to assess the prevalence of people with insulin-treated diabetes mellitus (ITDM) who have discussed issues related to diabetes and driving with their health care providers (HCPs). We also sought to determine the safe driving practices that are currently employed by this group. Finally, we investigated the factors that might increase the risk of motor-vehicle collisions (MVCs) among this group in Saudi Arabia.MethodThis cross-sectional study surveyed a representative sample of 429 current male drivers with ITDM using a structured questionnaire in Saudi Arabia.ResultsMost of the participants (76.5%) never discussed topics regarding diabetes and driving with their HCPs. The majority of the participants (61.8%) reported at least never doing one of the following: (a) carrying a blood glucose testing kit while driving, (b) testing their blood glucose level before driving or during a journey, or (c) having thought of a specific threshold of blood glucose level that would preclude driving. Three factors were associated with a higher risk of MVCs among participants with ITDM: (a) being on a basal/boluses regimen, (b) never having a discussion regarding diabetes and driving with their HCPs, and (c) having experienced hypoglycemia during driving.ConclusionsThe majority of people with ITDM had not had a discussion regarding diabetes and driving with their HCPs, which was reflected by a lack of safe driving practices. People with ITDM should be encouraged to take precautions while driving in order to prevent future MVCs.Practical applicationsThis research highlights the importance of investing more effort in educating drivers who have diabetes about safe driving practices by their health care providers. Also, it will attracts the attention of policymakers for an urgent need to establish clear policies and procedures for dealing with drivers who have diabetes.     

Learning to Drive: Learners’ Self-Reported Cognitive Failure Level Predicts Driving Instructor’s Observation Rating of Driving Performance

Objectives. Evidence increases that cognitive failure may be used to screen for drivers at risk. Until now, most studies have relied on driving learners. This exploratory pilot study examines self-report of cognitive failure in driving beginners and error during real driving as observed by driving instructors. Methods. Forty-two driving learners of 14 driving instructors filled out a work-related cognitive failure questionnaire. Driving instructors observed driving errors during the next driving lesson. In multiple linear regression analysis, driving errors were regressed on cognitive failure with the number of driving lessons as an estimator of driving experience controlled. Results. Higher cognitive failure predicted more driving errors(p < .01) when age, gender and driving experience were controlled in analysis. Conclusions. Cognitive failure was significantly associated with observed driving errors. Systematic research on cognitive failure in driving beginners is recommended.     

Drivers' visual behavior when using handheld and hands-free cell phones

ObjectiveThis study investigated driver distraction and how the use of handheld (HH), portable hands-free (PHF), and integrated hands-free (IHF) cell phones affected the visual behavior of motor vehicle drivers.MethodA naturalistic driving study recorded 204 participating drivers using video cameras and vehicle sensors for an average of 31 days. A total of 1564 cell phone calls made and 844 text messages sent while driving were sampled and underwent a video review. Baselines were established by recording epochs prior to the cell phone interactions. Total eyes-off-road time (TEORT) was examined to assess the visual demands of cell phone subtasks while driving. Percent TEORT was reported and compared against the baseline.ResultsVisual-manual subtasks performed on HH, PHF, and IHF cell phones were found to significantly increase drivers' mean percent TEORT. In contrast, conversing on an HH cell phone was found to significantly decrease drivers' mean percent TEORT, indicating that drivers looked at the forward roadway more often. No significant differences in percent TEORT were found for drivers conversing using PHF or IHF cell phones. The mean TEORT durations for visual-manual subtasks performed on an HH cell phone were significantly longer than the mean TEORT durations on either IHF or PHF cell phones.Practical applicationsThis research helps to further reinforce the distinction made between handheld and hands-free cell phone use in transportation distraction policy.     

What’s in a name? Drivers’ perceptions of the use of five SAE Level 2 driving automation systems

Introduction: Automobile manufacturers are developing increasingly sophisticated driving automation systems. Currently, the highest level of automation available on the market is SAE Level 2, which provides sustained assistance for both lateral and longitudinal vehicle control. The purpose of this study was to evaluate how drivers’ perceptions of what behaviors secondary to driving are safe while a Level 2 system is operating vary by system name. Methods: A nationally representative telephone survey of 2005 drivers was conducted in 2018 with questions about behaviors respondents perceived as safe while a Level 2 driving automation system is in operation. Each respondent was asked about two out of five system names at random for a balanced study design. Results: The name “Autopilot” was associated with the highest likelihood that drivers believed a behavior was safe while in operation, for every behavior measured. There was less variation observed among the other four SAE Level 2 system names when compared with each other. A limited proportion of drivers had experience with advanced driver assistance systems and fewer of these reported driving a vehicle in which Level 2 systems were available. Drivers reported that they would consult a variety of sources for information on how to use a Level 2 system. Conclusions: The names of SAE Level 2 driving automation systems influence drivers’ perceptions of how to use them, and the name “Autopilot” was associated with the strongest effect. While a name alone cannot properly instruct drivers on how to use a system, it is a piece of information and must be considered so that drivers are not misled about the correct usage of these systems. Practical Applications: Manufacturers, suppliers, and organizations regulating or evaluating SAE Level 2 automated driving systems should ensure that systems are named so as not to mislead drivers about their safe use.     

Identifying compensatory driving behavior among older adults using the situational avoidance questionnaire

IntroductionDriving self-regulation is considered a means through which older drivers can compensate for perceived declines in driving skill or more general feelings of discomfort on the road. One form of driving self-regulation is situational avoidance, the purposeful avoidance of situations perceived as challenging or potentially hazardous. This study aimed to validate the Situational Avoidance Questionnaire (SAQ, Davis, Conlon, Ownsworth, & Morrissey, 2016) and identify the point on the scale at which drivers practicing compensatory avoidance behavior could be distinguished from those whose driving is unrestricted, or who are avoiding situations for other, non-compensatory reasons (e.g., time or convenience).MethodSeventy-nine Australian drivers (M_age = 71.48, SD = 7.16, range: 55 to 86 years) completed the SAQ and were classified as a compensatory-restricted or a non-restricted driver based on a semi-structured interview designed to assess the motivations underlying avoidance behavior reported on the SAQ.ResultsUsing receiver-operator characteristic (ROC) analysis, the SAQ was found to have high diagnostic accuracy (sensitivity: 85%, specificity: 82%) in correctly classifying the driver groups. Group comparisons confirmed that compensatory-restricted drivers were self-regulating their driving behavior to reduce the perceived demands of the driving task. This group had, on average, slower hazard perception reaction times, and reported greater difficulty with driving, more discomfort when driving due to difficulty with hazard perception skills, and greater changes in cognition over the past five years.ConclusionsThe SAQ is a psychometrically sound measure of situational avoidance for drivers in baby boomer and older adult generations.Practical applicationsUse of validated measures of driving self-regulation that distinguish between compensatory and non-compensatory behavior, such as the SAQ, will advance our understanding of the driving self-regulation construct and its potential safety benefits for older road users.     

Comparison of self-report and objective measures of driving behavior and road safety: A systematic review

IntroductionThis research systematically reviewed the existing literature in regards to studies which have used both self-report and objective measures of driving behavior. The objective of the current review was to evaluate disparities or similarities between self-report and objective measures of driving behavior.MethodsSearches were undertaken in the following electronic databases, PsycINFO, PubMed, and Scopus, for peer-reviewed full-text articles that (1) focused on road safety, and (2) compared both subjective and objective measures of driving performance or driver safety. A total of 22,728 articles were identified, with 19 articles, comprising 20 studies, included as part of the review.ResultsThe research reported herein suggested that for some behaviors (e.g., driving in stressful situations) there were similarities between self-report and objective measures while for other behaviors (e.g., sleepiness and vigilance states) there were differences between these measurement techniques. In addition, findings from some studies suggested that in-vehicle devices may be a valid measurement tool to assess driving exposure in older drivers.ConclusionsFurther research is needed to examine the correspondence between self-report and objective measures of driving behavior. In particular, there is a need to increase the number of studies which compare “like with like” as it is difficult to draw comparisons when there are variations in measurement tools used.Practical applicationsIncorporating a range of objective and self-report measurements tools in research would help to ensure that the methods used offer the most reliable measures of assessing on-road behaviors.     

Effect of age and secondary task engagement on motor vehicle crashes in a naturalistic setting

ProblemAutomobile crashes are one of the leading causes of death in the United States, especially for younger and older drivers. Additionally, distracted driving is another leading factor in the likelihood of crashes. However, there is little understanding about the interaction between age and secondary task engagement and how that impacts crash likelihood and maneuver safety.MethodData from the Naturalistic Driving Study (NDS), which was part of the Second Strategic Highway Research Program (SHRP2), were used to investigate this issue.ResultsIt was found that the distribution of crashes per one million km driven during the NDS was similar to previous research, but with fewer crashes from older drivers. Additionally, it was found that older and middle-aged drivers engaged in distracted driving more frequently than was expected, and that crashes were significantly more likely if drivers of those age groups were engaged in secondary tasks. However, secondary task engagement did not predict judgment of safe/unsafe vehicle maneuvers.Practical ApplicationsMore research is needed to better understand the interaction of age and distraction on crash likelihood. However, this research could aid future researchers in understanding the likelihood of future use of new in-vehicle technologies for different age groups, as well as provide insight to the engagement patterns of distraction for different age groups.     

Real-world effects of using a phone while driving on lateral and longitudinal control of vehicles

IntroductionTechnologies able to augment human communication, such as smartphones, are increasingly present during all daily activities. Their use while driving, in particular, is of great potential concern, because of the high risk that distraction poses during this activity. Current countermeasures to distraction from phone use are considerably different across countries and not always widely accepted/adopted by the drivers.MethodsThis study utilized naturalistic driving data collected from 108 drivers in the Integrated Vehicle-Based Safety Systems (IVBSS) program in 2009 and 2010 to assess the extent to which using a phone changes lateral or longitudinal control of a vehicle. The IVBSS study included drivers from three age groups: 20–30 (younger), 40–50 (middle-aged), and 60–70 (older).ResultsResults from this study show that younger drivers are more likely to use a phone while driving than older and middle-aged drivers. Furthermore, younger drivers exhibited smaller safety margins while using a phone. Nevertheless, younger drivers did not experience more severe lateral/longitudinal threats than older and middle-aged drivers, probably because of faster reaction times. While manipulating the phone (i.e., dialing, texting), drivers exhibited larger lateral safety margins and experienced less severe lateral threats than while conversing on the phone. Finally, longitudinal threats were more critical soon after phone interaction, suggesting that drivers terminate phone interactions when driving becomes more demanding.ConclusionsThese findings suggest that drivers are aware of the potential negative effect of phone use on their safety. This awareness guides their decision to engage/disengage in phone use and to increase safety margins (self-regulation). This compensatory behavior may be a natural countermeasure to distraction that is hard to measure in controlled studies.Practical ApplicationsIntelligent systems able to amplify this natural compensatory behavior may become a widely accepted/adopted countermeasure to the potential distraction from phone operation while driving.     

Sleepy driving and risk of obstructive sleep apnea among truck drivers in Saudi Arabia

Objective: Truck drivers represent a group at a particularly higher risk of motor vehicle accidents (MVAs). Sleepy driving and obstructive sleep apnea (OSA) among truck drivers are major risk factors for MVAs. No study has assessed the prevalence of sleepy driving and risk of OSA among truck drivers in Saudi Arabia. Therefore, this study aimed to assess sleepy driving and risk of OSA among these truck drivers.

Methods: This study included 338 male truck drivers working in Saudi Arabia. A validated questionnaire regarding sleepy driving and OSA was used. The questionnaire included sociodemographic assessment, the Epworth Sleepiness Scale (ESS), the Berlin Questionnaire (BQ), and driving-related items.

Results: The drivers had a mean age of 42.9?±?9.7 years. The majority (94.7%) drove more than 5?h a day. A history of MVAs during the last 6 months was reported by 6.5%. Approximately 95% of the participants reported that they had accidentally fallen asleep at least once while driving over the past 6 months, and 49.7% stated that this had happened more than 5 times during the last 6 months. Based on the BQ score, a high risk of OSA was detected in 29% of the drivers. “Not getting good-quality sleep” (odds ratio [OR]?=?2.89; 95% confidence interval [CI], 1.08–7.75; P = .014) and driving experience from 6 to 10 years (OR = 3.37; 95% CI, 1.28–8.91; P = .034) were the only independent predictors of MVAs in the past 6 months.

Conclusions: Sleepy driving and a high risk of OSA was prevalent among the study population of male truck drivers in Saudi Arabia. Not getting good-quality sleep and driving experience from 6 to 10 years contributes to the accident risk among these truck drivers.     

Assessing the safety criticality of driver behavior toward cyclists at intersections

Abstract

Objective: Detailed analyses of car-to-cyclist accidents show that drivers intending to turn right at T-junctions collide more often with cyclists crossing from the right side on the bicycle lane than drivers intending to turn left. This fact has led to numerous studies examining the behavior of drivers turning left and right. However, the most essential question still has not been sufficiently answered: is the behavior of drivers intending to turn right generally more safety critical than the behavior of those intending to turn left? The purpose of this article is to provide a method that allows to determine whether a driver’s behavior toward cyclists can retrospectively be assessed as critical or non-critical.

Methods: Several theoretical considerations enriched by findings of experimental studies were employed to devise a multi-measure method. This method was applied to a dataset containing real-world approaching behavior of 48 drivers turning right and left at four T-junctions with different sight obstructions. For each driver a behavior-specific criticality was defined based on both, their driving and gaze behavior. Moreover, based on the behavior-specific criticality of each driver, the required field of view to see a cyclist from the right was defined and was set into relation with the available field of view of the T-junction.

Results: The results show that only a small portion of the drivers within the dataset would have posed an actual risk to cyclists crossing from the right side. Those situations with a higher safety criticality did not only arise when drivers intended to turn right, but also left.

Conclusion: Therefore, the analysis can only provide an explanation for the higher proportion of accidents between drivers turning right and cyclists crossing from the right side in certain situations. Further research, for example analyses of exposure data regarding the frequency of turning manoeuvers at T-junctions, is needed in order to explain the higher proportion of accidents between drivers turning right and cyclists crossing from the right side.     

Child passengers and driver culpability in fatal crashes by driver gender

Objective: Studies based on accident statistics generally suggest that the presence of a passenger reduces adult drivers' accident risk. However, passengers have been reported to be a source of distraction in a remarkable portion of distraction-related crashes. Although the effect of passengers on driving performance has been studied extensively, few studies have focused on how a child passenger affects the driver.

?A child in a car is a potential distractor for parents, especially for mothers of small children, who often suffer from sleep deficit. The aim of this study was to examine how the presence of child passengers of different ages is associated with a higher driver culpability, which was expected due to child-related distraction and fatigue.

Methods: The analysis was based on the comprehensive data of fatal crashes studied in-depth by multidisciplinary road accident investigation teams in Finland during 1988–2012. Teams determine the primary party who had the most crucial effect on the origin of the event. We define the primary party as culpable and the others involved as nonculpable drivers. The culpability rate was defined as the percentage of culpable drivers and rates were compared for drivers with a child/teen passenger aged 0–17 years (N = 348), with an adult passenger without children (N = 324), and when driving alone (N = 579), grouped by child age and driver gender.

?Drivers with specific risk-related behavior (substantial speeding, driving when intoxicated, unbelted, or without a license) were excluded from the analyses, in order to make the drivers with and without children comparable. Only drivers 26–47 years old were included, representing parents with children 0–9 years of age.

Results: Male drivers were less often culpable with 0- to 17-year-old passengers in the car than alone or with adults. This was not the case with female drivers. The gender difference in culpability was most marked with small children age 0–4 years. Female drivers' culpability rate with a 0- to 4-year-old child passenger was higher and male drivers' culpability rate was lower compared to drivers without passengers or with only adult passengers.

Conclusion: The results indicate that female drivers are at higher risk of crashes than male drivers when driving with small children. Further research is needed to replicate this finding and to determine causal mechanisms.     

Self-reported driving under the influence of alcohol and cannabis among Ontario students: Associations with graduated licensing,risk taking,and substance abuse

Objective: This article describes the patterns of self-reported driving under the influence of alcohol (DUIA) and driving under the influence of cannabis (DUIC) among licensed Ontario students in 2009 and examines their associations with graduated licensing, risk taking, and substance use problems for understanding DUIA and DUIC behaviors. Ontario's graduated licensing system requires new drivers to hold a G1 license for a minimum of 8 months and a G2 license for a minimum of 12 months before a full and unrestricted G license can be obtained. Among other restrictions, G1 drivers must maintain a 0 blood alcohol content (BAC), have an experienced driver in the passenger seat, not drive on any high-speed expressways, and not drive between the hours of midnight and 5 a.m. A G2 license is more similar to a G license, with fewer restrictions.

Method: This study analyzed data from the 2009 Ontario Student Drug Use and Health Survey (OSDUHS). The OSDUHS is a biennial population-based survey of students (grades 7 to 12) in Ontario, Canada.

Results: The results showed that 16.3% of licensed students in Ontario reported DUIC and 11.5% reported DUIA during the past year. After controlling for the effect of age, type of license emerged as a robust predictor for both DUIA and DUIC behavior, because students with a G2 and full license were significantly more likely to report DUIA and DUIC than drivers with a G1 license. Multivariate analyses suggested that risk-seeking behaviors were more important for understanding DUIA behavior than for DUIC behavior. Elevated problem indicators for alcohol and for cannabis were associated with DUIA and DUIC, respectively.

Conclusions: Though much attention has been paid to drinking and driving among adolescents, this research shows that more Ontario students now report driving after cannabis use than after drinking alcohol. The results identify important correlates of both behaviors that may be useful for prevention purposes.     

Teenage driver crash incidence and factors influencing crash injury by rurality

BackgroundPrevious research has identified teenage drivers as having an increased risk for motor-vehicle crash injury compared with older drivers, and rural roads as having increased crash severity compared with urban roads. Few studies have examined incidence and characteristics of teen driver-involved crashes on rural and urban roads.MethodsAll crashes involving a driver aged 10 through 18 were identified from the Iowa Department of Transportation crash data from 2002 through 2008. Rates of overall crashes and fatal or severe injury crashes were calculated for urban, suburban, rural, and remote rural areas. The distribution of driver and crash characteristics were compared between rural and urban crashes. Logistic regression was used to identify driver and crash characteristics associated with increased odds of fatal or severe injury among urban and rural crashes.ResultsFor younger teen drivers (age 10 through 15), overall crash rates were higher for more rural areas, although for older teen drivers (age 16 through 18) the overall crash rates were lower for rural areas. Rural teen crashes were nearly five times more likely to lead to a fatal or severe injury crash than urban teen crashes. Rural crashes were more likely to involve single vehicles, be late at night, involve a failure to yield the right-of-way and crossing the center divider.ConclusionsIntervention programs to increase safe teen driving in rural areas need to address specific risk factors associated with rural roadways.Impact on IndustryTeen crashes cause lost work time for teen workers as well as their parents. Industries such as safety, health care, and insurance have a vested interest in enhanced vehicle safety, and these efforts should address risks and injury differentials in urban and rural roadways.     

Identifying risky drivers with simulated driving

Objective: The present study aimed to examine whether high-risk drivers differ from low-risk drivers in driving behavior in a simulated environment.

Method: The 2 risk groups including 36 drivers (18 males and 18 females) performed driving tasks in a simulated environment. The simulated driving behaviors are compared between the 2 risk groups.

Results: The high-risk drivers drove much faster and exhibited larger offsets of the steering wheel than did the low-risk drivers in events without incidents. Additionally, the high-risk drivers used turn signals and horns less frequently than the low-risk drivers.

Conclusions: The present study revealed that the high-risk group differed from the low-risk group in driving behavior in a simulated environment. These results also suggest that simulated driving tasks might be useful tools for the evaluation of drivers’ potential risks.     

Adaptive response criteria in road hazard detection among older drivers

Objectives: The majority of existing investigations on attention, aging, and driving have focused on the negative impacts of age-related declines in attention on hazard detection and driver performance. However, driving skills and behavioral compensation may accommodate for the negative effects that age-related attentional decline places on driving performance. In this study, we examined an important question that had been largely neglected in the literature linking attention, aging, and driving: can top-down factors such as behavioral compensation, specifically adaptive response criteria, accommodate the negative impacts from age-related attention declines on hazard detection during driving?

Methods: In the experiment, we used the Drive Aware Task, a task combining the driving context with well-controlled laboratory procedures measuring attention. We compared younger (n = 16, age 21–30) and older (n = 21, age 65–79) drivers on their attentional processing of hazards in driving scenes, indexed by percentage of correct responses and reaction time of hazard detection, as well as sensitivity and response criteria using signal detection analysis.

Results: Older drivers, in general, were less accurate and slower on the task than younger drivers. However, results from this experiment revealed that older, but not younger, drivers adapted their response criteria when the traffic condition changed in the driving scenes. When there was more traffic in the driving scene, older drivers became more liberal in their responses, meaning that they were more likely to report that a driving hazard was detected.

Conclusions: Older drivers adopt compensatory strategies for hazard detection during driving. Our findings showed that, in the driving context, even at an older age our attentional functions are still adaptive according to environmental conditions. This leads to considerations on potential training methods to promote adaptive strategies that may help older drivers maintain performance in road hazard detection.     

Using SHRP 2 naturalistic driving data to assess drivers' speed choice while being engaged in different secondary tasks

IntroductionThe engagement in secondary tasks while driving has been found to result in considerable impairments of driving performance. Texting has especially been suspected to be associated with an increased crash risk. At the same time, there is evidence that drivers use various self-regulating strategies to compensate for the increased demands caused by secondary task engagement. One of the findings reported from multiple studies is a reduction in driving speed. However, most of these studies are of experimental nature and do not let the drivers decide for themselves to (not) engage in the secondary task, and therefore, eliminate other strategies of self-regulation (e.g., postponing the task). The goal of the present analysis was to investigate if secondary task engagement results in speed adjustment also under naturalistic conditions.MethodOur analysis relied on data of the SHRP 2 naturalistic driving study. To minimize the influence of potentially confounding factors on drivers' speed choice, we focused on episodes of free flow driving on interstates/highways. Driving speed was analyzed before, during, and after texting, smoking, eating, and adjusting/monitoring radio or climate control; in a total of 403 episodes.ResultsData show some indication for speed adjustment for texting, especially when driving with high speed. However, the effect sizes were small and behavioral patterns varied considerably between drivers. The engagement in the other tasks did not influence drivers' speed behavior significantly.Conclusions and practical applicationsWhile drivers might indeed reduce speed slightly to accommodate for secondary task engagement, other forms of adaptation (e.g., strategic decisions) might play a more important role in a natural driving environment. The use of naturalistic driving data to study drivers' self-regulatory behavior at an operational level has proven to be promising. Still, in order to obtain a comprehensive understanding about drivers' self-regulatory behavior, a mixed-method approach is required.     

Are cellular phone blocking applications effective for novice teen drivers?

ProblemDistracted driving is a significant concern for novice teen drivers. Although cellular phone bans are applied in many jurisdictions to restrict cellular phone use, teen drivers often report making calls and texts while driving.MethodThe Minnesota Teen Driver Study incorporated cellular phone blocking functions via a software application for 182 novice teen drivers in two treatment conditions. The first condition included 92 teens who ran a driver support application on a smartphone that also blocked phone usage. The second condition included 90 teens who ran the same application with phone blocking but which also reported back to parents about monitored risky behaviors (e.g., speeding). A third control group consisting of 92 novice teen drivers had the application and phone-based software installed on the phones to record cellular phone (but not block it) use while driving.ResultsThe two treatment groups made significantly fewer calls and texts per mile driven compared to the control group. The control group data also demonstrated a higher propensity to text while driving rather than making calls.DiscussionSoftware that blocks cellular phone use (except 911) while driving can be effective at mitigating calling and texting for novice teen drivers. However, subjective data indicates that some teens were motivated to find ways around the software, as well as to use another teen's phone while driving when they were unable to use theirs.Practical applicationsCellular phone bans for calling and texting are the first step to changing behaviors associated with texting and driving, particularly among novice teen drivers. Blocking software has the additional potential to reduce impulsive calling and texting while driving among novice teen drivers who might logically know the risks, but for whom it is difficult to ignore calling or texting while driving.