Injury prevention programs against distracted driving: Are they effective?

Introduction: Distracted driving (talking and/or texting) is a growing public safety problem, with increasing incidence among adult drivers. The aim of this study was to identify the incidence of distracted driving (DD) among health care providers and to create awareness against DD. We hypothesized that distracted driving is prevalent among health care providers and a preventive campaign against distracted driving would effectively decrease distracted driving among health care providers.

Methods: We performed a 4-phase prospective interventional study of all health care providers at our level 1 trauma center. Phase 1: one week of pre-intervention observation; phase 2: one week of intervention; phase 3: one week of postintervention observation; and phase 4: one week of 6 months of postintervention observation. Observations were performed outside employee parking garage at the following time intervals: 6:30–8:30 a.m., 4:40–5:30 p.m., and 6:30–7:30 p.m. Intervention included an e-mail survey, pamphlets and banners in the hospital cafeteria, and a postintervention survey. Hospital employees were identified with badges and scrubs, employees exiting through employee gate, and parking pass on the car. Outcome measure was incidence of DD pre, post, and 6 months postintervention.

Results: A total of 15,416 observations (pre: 6,639, post: 4,220, 6 months post: 4,557) and 520 survey responses were collected. The incident of DD was 11.8% among health care providers. There was a significant reduction in DD in each time interval of observation between pre- and postintervention. On subanalysis, there was a significant decrease in talking (P = .0001) and texting (P = .01) while driving postintervention compared to pre-intervention. In the survey, 35.5% of respondents admitted to DD and 4.5% respondents were involved in an accident due to DD. We found that 77% respondents felt more informed after the survey and 91% respondents supported a state legislation against DD. The reduction in the incidence of DD postintervention was sustained even at 6-month follow-up.

Conclusion: There was a 32% reduction in the incidence of distracted driving postintervention, which remained low even at 6-month follow-up. Implementation of an effective injury prevention campaign could reduce the incidence of distracted driving nationally.     

Teens' distracted driving behavior: Prevalence and predictors

IntroductionTeen drivers' over-involvement in crashes has been attributed to a variety of factors, including distracted driving. With the rapid development of in-vehicle systems and portable electronic devices, the burden associated with distracted driving is expected to increase. The current study identifies predictors of secondary task engagement among teenage drivers and provides basis for interventions to reduce distracted driving behavior. We described the prevalence of secondary tasks by type and driving conditions and evaluated the associations between the prevalence of secondary task engagement, driving conditions, and selected psychosocial factors.MethodsThe private vehicles of 83 newly-licensed teenage drivers were equipped with Data Acquisition Systems (DAS), which documented driving performance measures, including secondary task engagement and driving environment characteristics. Surveys administered at licensure provided psychosocial measures.ResultsOverall, teens engaged in a potentially distracting secondary task in 58% of sampled road clips. The most prevalent types of secondary tasks were interaction with a passenger, talking/singing (no passenger), external distraction, and texting/dialing the cell phone. Secondary task engagement was more prevalent among those with primary vehicle access and when driving alone. Social norms, friends' risky driving behaviors, and parental limitations were significantly associated with secondary task prevalence. In contrast, environmental attributes, including lighting and road surface conditions, were not associated with teens' engagement in secondary tasks.ConclusionsOur findings indicated that teens engaged in secondary tasks frequently and poorly regulate their driving behavior relative to environmental conditions. Practical applications: Peer and parent influences on secondary task engagement provide valuable objectives for countermeasures to reduce distracted driving among teenage drivers.     

Effects of cognitive distraction on speed control in curve negotiation

Objective: Maintaining a lower speed is recommended for curve negotiation and it has been shown that cognitive distraction may impair driving performance. This study examines the effects of different levels of cognitive distraction on the speed control of drivers negotiating a curve.

Methods: Experiments were conducted on a 6 degrees of freedom driving simulator with 28 participants. A comparison of the speed and acceleration from 300 m before to 100 m after the curve was performed for baseline driving (without distraction) and 3 levels of cognitive distractions using n-back tasks.

Results: The speed was significantly higher at the highest level of cognitive distraction (8%) than in baseline driving from the beginning of the curve to 50 m after it and the ratio of the highest level to the baseline was even greater throughout the range. The average acceleration was significantly higher than the baseline at the highest and the medium levels (80 and 70%, respectively) from 250 m before the curve to the one-quarter curve and from 250 to 150 m before the curve, respectively. It was also found that the point of deceleration was significantly delayed at the highest level of cognitive distraction and occurred only after the middle of the curve, whereas deceleration in baseline driving occurred just before entering the curve.

Conclusions: The impairment due to cognitive distraction was confirmed in this study but was only significant at a high level of cognitive distraction. The highly distracted drivers failed to perceive the curve in advance, resulting in a slower response to changes in the roadway. The findings indicate that acceleration may be an indicator of cognitive distraction while negotiating curves. A driver is prone to cognitive distraction and the driving performance is affected when driving requires excessive attention such as curve negotiation.     

Using naturalistic driving study data to investigate the impact of driver distraction on driver's brake reaction time in freeway rear-end events in car-following situation

IntroductionThe rear-end crash is one of the most common freeway crash types, and driver distraction is often cited as a leading cause of rear-end crashes. Previous research indicates that driver distraction could have negative effects on driving performance, but the specific association between driver distraction and crash risk is still not fully revealed. This study sought to understand the mechanism by which driver distraction, defined as secondary task distraction, could influence crash risk, as indicated by a driver's reaction time, in freeway car-following situations.MethodA statistical analysis, exploring the causal model structure regarding drivers’ distraction impacts on reaction times, was conducted. Distraction duration, distraction scenario, and secondary task type were chosen as distraction-related factors. Besides, exogenous factors including weather, visual obstruction, lighting condition, traffic density, and intersection presence and endogenous factors including driver age and gender were considered.ResultsThere was an association between driver distraction and reaction time in the sample freeway rear-end events from SHRP 2 NDS database. Distraction duration, the distracted status when a leader braked, and secondary task type were related to reaction time, while all other factors showed no significant effect on reaction time.ConclusionsThe analysis showed that driver distraction duration is the primary direct cause of the increase in reaction time, with other factors having indirect effects mediated by distraction duration. Longer distraction duration, the distracted status when a leader braked, and engaging in auditory-visual-manual secondary task tended to result in longer reaction times.Practical applicationsGiven drivers will be distracted occasionally, countermeasures which shorten distraction duration or avoid distraction presence while a leader vehicle brakes are worth considering. This study helps better understand the mechanism of freeway rear-end events in car-following situations, and provides a methodology that can be adopted to study the association between driver behavior and driving features.     

Prevalence and trends of distracted driving in Canada

Introduction: This study evaluates prevalence and trends in distracted driving in Canada based on multiple indicators collected from the Road Safety Monitor (RSM) and Canada’s National Fatality Database maintained by the Traffic Injury Research Foundation (TIRF). Method: Data from the RSM on self-reported distracted driving behaviors were analyzed using multivariate techniques including logistic regression analysis in various years spanning from 2004 to 2019. Data from TIRF’s National Fatality Database from 2000 to 2016 were also analyzed using piecewise regression analysis to evaluate trends and prevalence of driver distraction. Results: Significantly more Canadians reported talking on their phone hands-free or handheld phone while driving in 2019 compared to 2010. There was a 102% increase in the percentage that reported texting while driving in 2019 (9.7%) compared to 2010 (4.8%). For every 10-year increase in age, drivers were 44% less likely to text, 38% less likely to use a handheld phone, and 28% less likely to use a hands-free phone. Males were 62% more likely to use a handheld phone and 50% more likely to use a hands-free phone than females. Findings related to drivers’ perceived danger of distracted driving and attitudes are also presented. Although the number of distraction-related fatalities has not increased substantially from 2000 to 2016, the percentage of all fatalities where distraction was a contributing factor has increased. Unlike drinking drivers, distracted drivers more often kill other road users in crashes than kill themselves. Conclusions: In conclusion, while most Canadians appear to understand that one of the high-risk forms of distracted driving (i.e., texting while driving) is indeed dangerous, there is a minority who are unaware of, or resistant to, this fact. Practical Applications: Enforcement activities and education initiatives to combat distracted driving ought to be tailored to the target audience based on the patterns uncovered.     

Ticketing aggressive cars and trucks (TACT): How does it work on city streets?

Objective: The purpose of this study was to determine the feasibility of modifying the Ticking Aggressive Cars and Trucks (TACT) program, originally designed to work on state highways, within a metropolitan area to reduce unsafe interactions and their related crashes between drivers of large trucks and passenger vehicles.

Methods: Using crash data, the driving behaviors most commonly associated with large truck and passenger vehicle crashes were identified. A public awareness campaign using media messaging and increased law enforcement was created targeting these associated behaviors. The frequency of these behaviors both before and after the public awareness campaign was determined through observation of traffic at 3 specific locations within the city. Each location had a sufficient volume of large truck and passenger traffic to observe frequent interactions. Pre- and postintervention data were compared using negative binomial regression with generalized estimating equations to evaluate whether the campaign was associated with a reduction in the identified driving behaviors.

Results: A comparison between crash data from before, during, and after the campaign and crashes during the same time periods in previous years did not show a significant difference (P =.081). The number of large trucks observed in traffic remained the same during pre- and postintervention periods (P =.625). The rates of negative interactions per 100 large trucks decreased for both large trucks and passenger vehicles after the intervention, with calculated rate ratios of 0.58 (95% confidence interval [CI], 0.48, 0.70) and 0.31 (95% CI, 0.20, 0.47). The greatest reduction was seen in passenger vehicles following too close, with a rate ratio of 0.21 (95% CI, 0.15, 0.30).

Conclusions: Although designed for reducing crashes on highways, the TACT program can be an effective approach for improving driver behaviors on city streets.     

Examining drivers' eye glance patterns during distracted driving: Insights from scanning randomness and glance transition matrix

IntroductionVisual attention to the driving environment is of great importance for road safety. Eye glance behavior has been used as an indicator of distracted driving. This study examined and quantified drivers' glance patterns and features during distracted driving.MethodData from an existing naturalistic driving study were used. Entropy rate was calculated and used to assess the randomness associated with drivers' scanning patterns. A glance-transition proportion matrix was defined to quantity visual search patterns transitioning among four main eye glance locations while driving (i.e., forward on-road, phone, mirrors and others). All measurements were calculated within a 5 s time window under both cell phone and non-cell phone use conditions.ResultsResults of the glance data analyses showed different patterns between distracted and non-distracted driving, featured by a higher entropy rate value and highly biased attention transferring between forward and phone locations during distracted driving. Drivers in general had higher number of glance transitions, and their on-road glance duration was significantly shorter during distracted driving when compared to non-distracted driving.ConclusionsResults suggest that drivers have a higher scanning randomness/disorder level and shift their main attention from surrounding areas towards phone area when engaging in visual-manual tasks.Practical applicationsDrivers' visual search patterns during visual-manual distraction with a high scanning randomness and a high proportion of eye glance transitions towards the location of the phone provide insight into driver distraction detection. This will help to inform the design of in-vehicle human-machine interface/systems.     

The role of self-regulation in the context of driver distraction: A simulator study

Objective: There is considerable evidence for the negative effects of driver distraction on road safety. In many experimental studies, drivers have been primarily viewed as passive receivers of distraction. Thus, there is a lack of research on the mediating role of their self-regulatory behavior. The aim of the current study was to compare drivers' performance when engaged in a system-paced secondary task with a self-paced version of this task and how both differed from baseline driving performance without distraction.

Methods: Thirty-nine participants drove in a simulator while performing a secondary visual–manual task. One group of drivers had to work on this task in predefined situations under time pressure, whereas the other group was free to decide when to work on the secondary task (self-regulation group). Drivers' performance (e.g., lateral and longitudinal control, brake reaction times) was also compared with a baseline condition without any secondary task.

Results: For the system-paced secondary task, distraction was associated with high decrements in driving performance (especially in keeping the lateral position). No effects were found for the number of collisions, probably because of the lower driving speeds while distracted (compensatory behavior). For the self-regulation group, only small impairments in driving performance were found. Drivers engaged less in the secondary task during foreseeable demanding or critical driving situations.

Conclusions: Overall, drivers in the self-regulation group were able to anticipate the demands of different traffic situations and to adapt their engagement in the secondary task, so that only small impairments in driving performance occurred. Because in real traffic drivers are mostly free to decide when to engage in secondary tasks, it can be concluded that self-regulation should be considered in driver distraction research to ensure ecological validity.     

Driving concerns among older adults: Associations with driving skill,behaviors, and experiences

Objectives: The purpose of this investigation was to determine what older adults find most concerning about driving as they age and how these concerns are related to driving skill, behaviors, and experiences.

Methods: In partnership with the Maryland Motor Vehicle Administration, a sample of 751 older adults ages 65 and older completed an online survey between October 2017 and May 2018. A content analysis was used to code open-ended responses about driver concerns, and multivariate logistic regression models were used to analyze the associations between driving concerns and driving skill, behavior, and experiences.

Results: Eighty-four percent of participants reported at least one driving concern, with 44% concerned about others’ driving, 34% concerned about their own driving, and 24% concerned about driving conditions. The most frequently mentioned driving concerns were other drivers in general, driving at night, visual ability and awareness, and other drivers being aggressive or reckless. Being concerned with their own driving was significantly associated with decreased perceived driving skill and increased odds of experiencing negative driving experiences in the past year. Being concerned about others’ driving was associated with increased odds of wearing a seat belt (adjusted odds ratio [AOR]?=?2.67; 95% confidence interval [CI], 1.02, 7.00), having high perceived driving skills in emergency situations (AOR = 1.56; 95% CI, 1.14, 2.12), and getting in a near crash or collision in the past year (AOR = 1.50; 95% CI, 1.04, 2.18).

Conclusions: Older adult drivers are frequently concerned about their own driving as well as the driving of others. Implications for future research and health practice are discussed.     

How do significant others influence our driving? A descriptive study of ego–alter dyads in a college population

Objectives: The purpose of this investigation was to describe the mutual influences between drivers and their significant others in a sample of college students, using a social network perspective.

Methods: A web-based survey was made of 65 dyads of drivers and their significant others, in order to examine areas of mutual influence concerning driving. Measures were taken of their frequency of risky driving, including how often they drive, talk on the cell phone, or text with each other while driving. They were also asked whether they have influenced or been influenced by each other to drive safer or in a more risky manner.

Results: The dyads were very similar in how frequently they drive as well as talk to each other on the phone while driving. However, they were unlikely to feel that their driving was influenced by each other, with only 17% of the drivers and 19% of the significant others saying that they have been overtly influenced by (or have influenced) each other's driving behavior often or most of the time. Yet, most (67.7% and 72.1%) said they have ever encouraged or been encouraged by each other to drive more safely, mainly by being told to reduce their speed. In both sets of drivers in these dyads, talking to and texting their significant other while driving was related to risky driving.

Conclusions: These findings suggest that a similarity exits in the driving patterns of young drivers and their significant others, especially concerning talking to each other on the phone while driving. The largest degree of overt social influence appears to center around avoidance of behaviors perceived to be associated with getting a traffic citation. Implications for safety campaign development and future research are presented.     

Self-regulation of driving speed among distracted drivers: An application of driver behavioral adaptation theory

Objective: The adaptive behavior of mobile phone–distracted drivers has been a topic of much discussion in the recent literature. Both simulator and naturalistic studies suggest that distracted drivers generally select lower driving speeds; however, speed adaptation is not observed among all drivers, and the mechanisms of speed selection are not well understood. The aim of this research was to apply a driver behavioral adaptation model to investigate the speed adaptation of mobile phone–distracted drivers.

Methods: The speed selection behavior of drivers was observed in 3 phone conditions including baseline (no conversation) and hands-free and handheld phone conversations in a high-fidelity driving simulator. Speed adaptation in each phone condition was modeled as a function of secondary task demand and self-reported personal/psychological characteristics with a system of seemingly unrelated equations (SURE) accounting for potential correlations due to repeated measures experiment design.

Results: Speed adaptation is similar between hands-free and handheld phone conditions, but the predictors of speed adaptation vary across the phone conditions. Though perceived workload of secondary task demand, self-efficacy, attitude toward safety, and driver demographics were significant predictors of speed adaptation in the handheld condition, drivers' familiarity with the hands-free interface, attitude toward safety, and sensation seeking were significant predictors in the hands-free condition. Drivers who reported more positive safety attitudes selected lower driving speeds while using phones.

Conclusion: This research confirmed that behavioral adaptation models are suitable for explaining speed adaptation of mobile phone distracted drivers, and future research could be focused on further theoretical refinement.     

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.     

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.     

Vehicle choices for teenage drivers: A national survey of U.S. parents

IntroductionPrevious research has shown that many newly licensed teenagers in the United States are driving vehicles with inferior crash protection. The objective of this study was to update and extend previous research on U.S. parents' choices of vehicles for their teenagers.MethodTelephone surveys were conducted with parents in May 2014 using a random sample of U.S. households likely to include teenagers. Participation was restricted to parents or guardians of teenagers who lived in the household and held either an intermediate or full driver's license. Parents were interviewed about the vehicle their teenager drives, the reason they chose the vehicle for their teenager, and the cost of purchased vehicles.ResultsTeenagers most often were driving 2000–06 model year vehicles (41%), with 30% driving a more recent model year and 19% driving an older model year. Teenagers most often were driving midsize or large cars (27%), followed by SUVs (22%), mini or small cars (20%), and pickups (14%). Far fewer were driving minivans (6%) or sports cars (1%). Forty-three percent of the vehicles driven by teenagers were purchased when the teenager started driving or later. A large majority (83%) were used vehicles. The median cost of the vehicles purchased was $5300, and the mean purchase price was $9751.ConclusionsAlthough parents report that the majority of teenagers are driving midsize or larger vehicles, many of these vehicles likely do not have key safety features, such as electronic stability control, which would be especially beneficial for teenage drivers. Many teenagers were driving older model year vehicles or vehicle types or sizes that are not ideal for novice drivers.Practical applicationsParents, and their teenage drivers, may benefit from consumer information about optimal vehicle choices for teenagers.     

Changes in the sources of distracted driving among Northern Virginia drivers in 2014 and 2018: A comparison of results from two roadside observation surveys

Introduction: An increase in distracted driving has been suggested as a factor contributing to the 15% increase in fatal crashes from 2014 to 2016, but objective information about the prevalence of distracted driving in recent years is incomplete or lacking. The current study replicated a 2014 observation study conducted in Northern Virginia to examine whether the prevalence of distracted driving overall and of individual secondary behaviors has changed. Method: Drivers of moving or stopped vehicles were observed at 12 locations across 4 Northern Virginia communities during the daytime. The presence of 12 different secondary behaviors was recorded. Results: In 2018, about 23% of drivers were engaged in at least one secondary behavior, which was not significantly different from 2014. Overall phone use was not significantly different between 2014 and 2018. However, the likelihood of holding a cellphone significantly decreased while the likelihood of manipulating a cellphone significantly increased in 2018 relative to 2014. About 14% of drivers were engaged in noncellphone secondary behaviors in 2014 and 2018, which exceeded the proportion using phones in both years. Conclusions: There was no evidence that distracted driving has become more common in recent years, but the prevalence of some secondary behaviors has changed. Most concerning was the 57% increase in the likelihood of cellphone manipulation in 2018 relative to 2014, a behavior that has been consistently linked to increased crash risk; however, because the behavior is uncommon overall, the increased prevalence would be expected to only slightly increase crash rates. Practical applications: Although cellphone use was frequently observed in 2014 and 2018, collectively, other noncellphone secondary behaviors were more prevalent. Practitioners and policymakers should continue targeting cellphone use, but also must target other common secondary behaviors to fully address distracted driving.     

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.     

Understanding driver distractions in fatal crashes: An exploratory empirical analysis

Introduction: Driver distraction has become a significant problem in transportation safety. As more portable wireless devices and driver assistance and entertainment systems become available to drivers, the sources of distraction are increasing. Method: Based on the results of different studies in the literature review, this paper categorizes different distraction enablers into six subcategories according to their fundamental characteristics and how they would affect a driver's likelihood of engaging in non-driving related activities. The review also discusses the characteristics and influence of external and internal distractions. The objective of this study is to examine the effect of different distraction sources in fatal crashes with the consideration of a driver's age and sex. Tukey test, chi-square test of independence, Nemenyi post-hoc test, and Marascuilo procedure have been used to investigate the top distraction sources, the trend of distraction-affected fatal crashes, the effect of different distractions on drives in different age groups, and their influence on female and male drivers. Results: It was found that inner cognitive inferences accounted for the greatest proportion of driver engagement in distractions. Young drivers show a larger probability of being distracted by in-vehicle technology-related devices/objects. Within the group of young drivers, female drivers showed a higher probability than their male counterparts of engaging in distracted driving caused by in-vehicle technology-related devices. Among six subcategories of distractions, drivers older than 80 years old were found to be most likely affected by inner cognitive interferences.     

Passenger distractions among adolescent drivers

PROBLEM: Adolescents who drive with peers are known to have a higher risk of crashes. While passengers may distract drivers, little is known about the circumstances of these distractions among teen drivers. METHOD: This study used survey data on driving among 2,144 California high school seniors to examine distractions caused by passengers. RESULTS: Overall, 38.4% of youths who drove reported having been distracted by a passenger. Distractions were more commonly reported among girls and students attending moderate- to high-income schools. Talking or yelling was the most commonly reported type of distraction. About 7.5% of distractions reported were deliberate, such as hitting or tickling the driver or attempting to use the vehicle's controls. Driving after alcohol use and having had a crash as a driver were both significant predictors of reporting passenger-related distraction. CONCLUSION: Adolescents often experience distractions related to passengers, and in some cases these distractions are intentional. IMPACT ON INDUSTRY: These results provide information about teenage drivers who are distracted by passenger behaviors. In some cases, passengers attempted to use vehicle controls; however, it seems unlikely that this behavior is common enough to warrant redesign of controls to make them less accessible to passengers.     

A spectral power analysis of driving behavior changes during the transition from nondistraction to distraction

Objective: This article investigated and compared frequency domain and time domain characteristics of drivers' behaviors before and after the start of distracted driving.

Method: Data from an existing naturalistic driving study were used. Fast Fourier transform (FFT) was applied for the frequency domain analysis to explore drivers' behavior pattern changes between nondistracted (prestarting of visual–manual task) and distracted (poststarting of visual–manual task) driving periods. Average relative spectral power in a low frequency range (0–0.5 Hz) and the standard deviation in a 10-s time window of vehicle control variables (i.e., lane offset, yaw rate, and acceleration) were calculated and further compared. Sensitivity analyses were also applied to examine the reliability of the time and frequency domain analyses.

Results: Results of the mixed model analyses from the time and frequency domain analyses all showed significant degradation in lateral control performance after engaging in visual–manual tasks while driving. Results of the sensitivity analyses suggested that the frequency domain analysis was less sensitive to the frequency bandwidth, whereas the time domain analysis was more sensitive to the time intervals selected for variation calculations. Different time interval selections can result in significantly different standard deviation values, whereas average spectral power analysis on yaw rate in both low and high frequency bandwidths showed consistent results, that higher variation values were observed during distracted driving when compared to nondistracted driving.

Conclusions: This study suggests that driver state detection needs to consider the behavior changes during the prestarting periods, instead of only focusing on periods with physical presence of distraction, such as cell phone use. Lateral control measures can be a better indicator of distraction detection than longitudinal controls. In addition, frequency domain analyses proved to be a more robust and consistent method in assessing driving performance compared to time domain analyses.     

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.