The reaction times of drivers aged 20 to 80 during a divided attention driving

Objective: Many studies addressing age-related changes in driving performance focus on comparing young vs. older drivers, which might lead to the biased conclusion that driving performance decreases only after the age of 65. The main aim of the study was to show that changes in driving performance are progressive throughout the adult years.

Methods: A sample of 351 drivers aged 20 to 80 was assessed for their reaction times while driving between road cones. The drivers were exposed to 2 conditions varying according to task complexity. In single task conditions, the drivers performed a full stopping maneuver at a given signal; in dual task conditions, the drivers were distracted before the signal for stopping maneuver was triggered. Reaction times were compared across conditions and age groups.

Results: The results showed that both reaction times and variability of driving performance increased progressively between the ages of 20 and 80. The increase in both reaction times and variability was greater in the complex task condition. The high-performing quarter of elderly drivers performed equally well or better than younger drivers did.

Conclusions: The data clearly supported the claim that driving performance changes steadily across age groups: both mean reaction time and interindividual variability progressively increase with age. In addition, a significant group of older drivers was identified who did not show the expected age-related decrease in performance. The findings have important implications, suggesting that in relation to driving, aging is a progressive phenomenon and may lead to variety of driving performance; age-related studies of driving performance should put more emphasis on investigating changes across the whole driver age range rather than only comparing younger and older drivers.     

Driving safety improves after individualized training: An RCT involving older drivers in an urban area

Objective: This study aimed to reproduce the results of a previous investigation on the safety benefits of individualized training for older drivers. We modified our method to address validity and generalizability issues.

Methods: Older drivers were randomly assigned to one of the 3 arms: (1) education alone, (2) education?+?on road training, and (3) education?+?on road?+?simulator training. Older drivers were recruited from a larger urban community. At the pre- and posttests (separated by 4 to 8 weeks) participants followed driving directions using a Global Positioning System (GPS) navigation system.

Results: Our findings support the positive influence of individualized on-road training for urban-dwelling older drivers. Overall, driving safety improved among drivers who received on-road training over those who were only exposed to an education session, F(1, 40) = 11.66, P = .001 (26% reduction in total unsafe driving actions [UDAs]). Statistically significant improvements were observed on observation UDAs (e.g., scanning at intersections, etc.), compliance UDAs (e.g., incomplete stop), and procedural UDAs (e.g., position in lane).

Conclusion: This study adds to the growing evidence base in support of individualized older driver training to optimize older drivers’ safety and promote continued safe driving.     

Driver licensing,motor-vehicle crashes,and moving violations among older adults

IntroductionDriving is important for well-being among older adults, but age-related conditions are associated with driving reduction or cessation and increased crash risk for older drivers. Our objectives were to describe population-based rates of older drivers’ licensing and per-driver rates of crashes and moving violations.Methods: We examined individual-level statewide driver licensing, crash, and traffic citation data among all New Jersey drivers aged ≥ 65 and a 35- to 54-year-old comparison group during 2010–2014. Rate ratios (RR) of crashes and moving violations were estimated using Poisson regression.Results: Overall, 86% of males and 71% of females aged ≥ 65 held a valid driver’s license. Older drivers had 27% lower per-driver crash rates than middle-aged drivers (RR: 0.73, 95% CI: 0.73, 0.74)—with appreciable differences by sex—but 40% higher fatal crash rates (RR: 1.40 [1.24, 1.58]). Moving violation rates among older drivers were 72% lower than middle-aged drivers (RR: 0.28 [0.28, 0.28]).Conclusion: The majority of older adults are licensed, with substantial variation by age and sex. Older drivers have higher rates of fatal crashes but lower rates of moving violations compared with middle-aged drivers.Practical applications: Future research is needed to understand the extent to which older adults drive and to identify opportunities to further reduce risk of crashes and resultant injuries among older adults.     

Prevalence and concentrations of drugs in older suspected drugged drivers

Objective: Older drivers are somewhat more likely to be involved in car crashes than middle-aged drivers but less likely to be involved than younger drivers. This study aimed to assess the extent of drug use in older suspected drunk and drugged drivers, with respect to which drugs were detected and at which concentrations.

Methods: Blood samples from older suspected drunk and drugged drivers taken between February 1, 2012, and May 22, 2013, were identified from the database at the Norwegian Institute of Public Health and were retrospectively analyzed for a broad repertoire of drugs relevant for impairment. The prevalence of different drugs among the suspected drunk and drugged drivers was studied. Regarding drug concentrations, the findings in older drivers (>65 years) were compared to a reference group of apprehended drivers aged 20–40 years.

Results: Four hundred and ten older suspected drunk and drugged drivers were included. Any drug (including ethanol) was detected in 92% of blood samples, and ethanol was detected in 81%. Benzodiazepines were found in 15% of the older drivers and z-hypnotics (zopiclone or zolpidem) were detected in 13%. The most frequent single legal drugs found in blood samples taken from older impaired drivers were zopiclone (9.8%) and diazepam (9.3%). Regarding drug combinations, older drivers used a mean number of 1.4 drugs, and 20% of ethanol-positive cases showed at least one other drug. High drug concentrations of clonazepam and diazepam were more frequently seen in the younger group.

Conclusions: This study showed that drugs were detected in the vast majority of older drivers suspected for drunk or drugged driving. Ethanol was the most frequent drug detected, followed by zopiclone and diazepam. Older drivers combine drugs to a lesser degree than younger drivers, but their combination of ethanol and other drugs represents a considerable traffic risk. Lower concentrations of benzodiazepines are seen in older compared to younger drivers.     

Driving performance comparing older versus younger drivers

Objectives: A cross-sectional study was conducted at the Touro University California campus to compare differences in reaction times and driving performance of younger adult drivers (18–40 years) and older adult drivers (60 years and older). Each test group consisted of 38 participants.

Methods: A Simple Visual Reaction Test (SVRT) tool was used to measure reaction times. The STISIM Drive M100 driving simulator was used to assess driving parameters. Driving performance parameters included mean lane position, standard deviation of mean lane position measured, mean speed, standard deviation of mean speed, car-following delay, car-following modulus, car-following coherence, off-road accidents, collisions, pedestrians hit, and traffic light tickets.

Results: Compared to younger participants, older drivers experienced significantly slower reaction times (510.0 ± 208.8 vs. 372.4 ± 96.1 ms, P =.0004), had more collisions (0.18 ± 0.39 vs. none, P =.0044), drove slower (44.6 ± 6.6 vs. 54.9 ± 11.7 mph, P <.0001), deviated less in speed (12.6 ± 4.3 vs. 16.8 ± 6.3, P =.0011), and were less able to maintain a constant distance behind a pace car (0.42 ± 0.23 vs. 0.59 ± 0.24; P =.0025).

Conclusions: Differences exist in driving patterns of older and younger drivers as measured by reaction times and driving simulator outcomes. These results are the first to compare these 2 specific adult age groups' driving performance as measured by a standardized driving simulator scenario. Identifying these differences is essential in addressing them and preventing future traffic injuries.     

Risk and safety perception on urban and rural roads: Effects of environmental features,driver age and risk sensitivity

Objective: The ability to detect changing visual information is a vital component of safe driving. In addition to detecting changing visual information, drivers must also interpret its relevance to safety. Environmental changes considered to have high safety relevance will likely demand greater attention and more timely responses than those considered to have lower safety relevance. The aim of this study was to explore factors that are likely to influence perceptions of risk and safety regarding changing visual information in the driving environment. Factors explored were the environment in which the change occurs (i.e., urban vs. rural), the type of object that changes, and the driver's age, experience, and risk sensitivity.

Methods: Sixty-three licensed drivers aged 18–70 years completed a hazard rating task, which required them to rate the perceived hazardousness of changing specific elements within urban and rural driving environments. Three attributes of potential hazards were systematically manipulated: the environment (urban, rural); the type of object changed (road sign, car, motorcycle, pedestrian, traffic light, animal, tree); and its inherent safety risk (low risk, high risk). Inherent safety risk was manipulated by either varying the object's placement, on/near or away from the road, or altering an infrastructure element that would require a change to driver behavior. Participants also completed two driving-related risk perception tasks, rating their relative crash risk and perceived risk of aberrant driving behaviors.

Results: Driver age was not significantly associated with hazard ratings, but individual differences in perceived risk of aberrant driving behaviors predicted hazard ratings, suggesting that general driving-related risk sensitivity plays a strong role in safety perception. In both urban and rural scenes, there were significant associations between hazard ratings and inherent safety risk, with low-risk changes perceived as consistently less hazardous than high-risk impact changes; however, the effect was larger for urban environments. There were also effects of object type, with certain objects rated as consistently more safety relevant. In urban scenes, changes involving pedestrians were rated significantly more hazardous than all other objects, and in rural scenes, changes involving animals were rated as significantly more hazardous. Notably, hazard ratings were found to be higher in urban compared with rural driving environments, even when changes were matched between environments.

Conclusion: This study demonstrates that drivers perceive rural roads as less risky than urban roads, even when similar scenarios occur in both environments. Age did not affect hazard ratings. Instead, the findings suggest that the assessment of risk posed by hazards is influenced more by individual differences in risk sensitivity. This highlights the need for driver education to account for appraisal of hazards’ risk and relevance, in addition to hazard detection, when considering factors that promote road safety.     

Hazard perception of stroke drivers in a video-based Japanese hazard perception task

Objective: Hazard perception (HP) is the ability to identify a hazardous situation while driving. Though HP has been well studied among neurologically intact populations, little is known about the HP of neurologically impaired populations (in this study, stroke patients). The purpose of this study is, first, to investigate the HP of stroke patients and, second, to verify the effect of lesion side (right or left hemisphere) on HP, from the viewpoint of hazard types.

Methods: Sixty-seven neurologically intact age-matched older drivers and 63 stroke patients with valid driver’s licenses conducted a video-based Japanese HP task. Participants were asked to indicate the hazardous events in the driving scenario. These events were classified into 3 types: (1) behavioral prediction hazards (BP), which are those where the cause is visible before it becomes a hazard; (2) environmental prediction hazards (EP), which are those where the ultimate hazard may be hidden from view; and (3) dividing and focusing attention hazards (DF), which are those where there is more than one potential hazard to monitor on approach．Participants also took part in the Trail Making Test (TMT) to evaluate visual information processing speed.

Results: The results showed that the number of responses was significantly fewer for stroke patients than for age-matched drivers for all hazard types (P < .001), and this difference was not affected by lesion side (P > .05). It was also found that stroke patients showed a slower response time than age-matched drivers only for BP (P < .001). The lesion side did not affect response latency (P > .05). Results of the TMT revealed that age-matched drivers completed the task significantly faster than stroke patients (P < .001) and that neither TMT-A nor TMT-B differentiated between patients with left hemisphere damage and patients with right hemisphere damage (P > .05).

Conclusions: Firstly, HP in stroke patients is low compared to age-matched drivers. Secondly, even if stroke patients notice hazards, their response may be delayed in a BP situation, due to a slower visual information processing speed. Thirdly, the lesion side does not appear to affect HP.     

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.     

“Are you still driving?” Metasynthesis of patient preferences for communication with health care providers

Aim: The aim of this study was to synthesize published qualitative studies to identify older adults' preferences for communication about driving with health care providers.

Background: Health care providers play a key role in addressing driving safety and driving retirement with older adults, but conversations about driving can be difficult. Guides exist for family members and providers, but to date less is known about the types of communication and messages older drivers want from their health care providers.

Design: A qualitative metasynthesis of studies published on or before October 10, 2014, in databases (PubMed, CINAHL, PsycINFO, and Web of Science) and grey literature was performed.

Review Methods: Twenty-two published studies representing 518 older adult drivers met the following inclusion criteria: the study (1) was about driving; (2) involved older drivers; (3) was qualitative (rather than quantitative or mixed methods); and (4) contained information on older drivers' perspectives about communication with health care providers.

Results: We identified 5 major themes regarding older adults' communication preferences: (1) driving discussions are emotionally charged; (2) context matters; (3) providers are trusted and viewed as authority figures; (4) communication should occur over a period of time rather than suddenly; and (5) older adults desire agency in the decision to stop driving.

Conclusion: Various stakeholders involved in older driver safety should consider older drivers' perspectives regarding discussions about driving. Health care providers can respect and empower older drivers—and support their family members—through tactful communication about driving safety and mobility transitions during the life course.     

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.     

Age-related differences in effects of non-driving related tasks on takeover performance in automated driving

Introduction: During SAE level 3 automated driving, the driver’s role changes from active driver to fallback-ready driver. Drowsiness is one of the factors that may degrade driver’s takeover performance. This study aimed to investigate effects of non-driving related tasks (NDRTs) to counter driver’s drowsiness with a Level 3 system activated and to improve successive takeover performance in a critical situation. A special focus was placed on age-related differences in the effects. Method: Participants of three age groups (younger, middle-aged, older) drove the Level 3 system implemented in a high-fidelity motion-based driving simulator for about 30 min under three experiment conditions: without NDRT, while watching a video clip, and while switching between watching a video clip and playing a game. The Karolinska Sleepiness Scale and eyeblink duration measured driver drowsiness. At the end of the drive, the drivers had to take over control of the vehicle and manually change the lane to avoid a collision. Reaction time and steering angle variability were measured to evaluate the two aspects of driving performance. Results: For younger drivers, both single and multiple NDRT engagements countered the development of driver drowsiness during automated driving, and their takeover performance was equivalent to or better than their performance without NDRT engagement. For older drivers, NDRT engagement did not affect the development of drowsiness but degraded takeover performance especially under the multiple NDRT engagement condition. The results for middle-aged drivers fell at an intermediate level between those for younger and older drivers. Practical Applications: The present findings do not support general recommendations of NDRT engagement to counter drowsiness during automated driving. This study is especially relevant to the automotive industry’s search for options that will ensure the safest interfaces between human drivers and automation systems.     

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.     

Driving and alternatives: older drivers in Michigan

Method: A statewide telephone survey of Michigan drivers and former drivers aged 65 and older collected information on transportation mode choices, experience with alternatives to driving, and whether drivers planned for when they could no longer drive. Results: Results showed that most older adult households owned at least one automobile, and that the automobile was the primary mode of transportation. Most former drivers obtained rides from relatives and friends. Use of public transportation was low, and some seniors were not aware of available public transportation services. Older drivers did not plan for driving cessation. Over half the drivers who perceived a likelihood of driving problems within 5 years expected to keep driving beyond 5 years. Impact on industry: Because of their lifelong reliance on the automobile, their desire to drive themselves, and their lack of experience with public transportation, efforts to enhance the mobility of older people should consider this background while alternatives to the personal automobile are developed.     

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.     

Driving difficulties as reported by older drivers with mild cognitive impairment and without neurological impairment

Objective: Considerable evidence indicates that medical conditions prevalent among older individuals lead to impairments in visual, cognitive, or psychomotor functions needed to drive safely. The purpose of this study was to explore the factors determining driving difficulties as seen from the viewpoint of 30 older drivers with mild cognitive impairment (MCI) and 30 age-matched controls without cognitive impairment.

Methods: Perceptions of driving difficulties from both groups were examined using data from an extensive questionnaire. Samples of drivers diagnosed with MCI and age-matched controls were asked to report the frequency with which they experienced driving difficulties due to functional deficits and knowledge of new traffic rules and traffic signs.

Results: The analysis revealed that 2 factors underlie MCI perceptions of driving difficulties, representing (1) difficulties associated with late detection combined with slowed response to relevant targets in the peripheral field of view and (2) difficulties associated with divided attention between tasks requiring switching from automatic to conscious processing particularly of long duration. The analysis for healthy controls revealed 3 factors representing (1) difficulties in estimating speed and distance of approaching vehicles in complex (attention-dividing) high-information-load conditions; (2) difficulties in moving head, neck, and feet; and (3) difficulties in switching from automatic responses to needing to use cognitive processing in new or unexpected situations.

Conclusions: Though both group analyses show difficulties with switching from automatic to decision making, the difficulties are different. For the control group, the difficulty in switching involves switching in new or unexpected situations associated with high-information-load conditions, whereas this switching difficulty for the MCI group is associated with divided attention between easier tasks requiring switching. These findings underline the ability of older drivers (with MCI and without cognitive impairment) to indicate probable impairments in various driving skills. The patterns of difficulties perceived by the MCI group and the age-matched healthy control group are indicative of demanding driving situations that may merit special attention for road designers and road safety engineers. They may also be considered in the design of older drivers’ fitness to drive evaluations, training programs, and/or vehicle technologies that provide for older driver assistance.     

What can a hazard function teach us about drivers’ perception of hazards?

Objective: Hazard perception (HP) is typically defined as the ability to read the road and anticipate hazardous situations. Several studies have shown that HP is a driving skill that correlates with traffic crashes. Measuring HP differences between various groups of drivers typically involves a paradigm in which participants observe short videos of real-world traffic scenes taken from a driver’s or a pedestrian’s perspective and press a response button each time they identify a hazard. Young, inexperienced drivers are considered to have poor HP skills compared to experienced drivers, as evident by their slower response times (RTs) to road hazards. Nevertheless, though several studies report RT differences between young, inexperienced and experienced drivers, other studies did not find such differences. We have already suggested that these contradictory findings may be attributed to how cases of no response—that is, a situation where a participant did not respond to a hazard—are being treated. Specifically, we showed that though survival analysis handles cases of no response appropriately, common practices fail to do so. These methods often replace a case of no response with the mean RT of those who responded or any other central tendency parameters. The present work aims to show that treating cases of no response appropriately as well as selecting a distribution that fits the RT data is more than just a technical phase in the analysis.

Method: This work used simulation of predefined distributions and real-world data.

Results: It was demonstrated that selecting the appropriate distribution and treating nonresponse cases appropriately affect the shape and characteristics of the density, survival, and hazard functions.

Conclusions: The suggested process has the ability to provide researchers with additional information regarding the nature of the traffic scenes that enables differentiating between various hazardous situations and between various users with different characteristics such as age or experience.     

A novel driver hazard perception sensitivity model based on drivers’ characteristics: A simulator study

Objective: Considering the high annual number of fatal driving accidents in Iran, any approach for reducing the number or severity of driving accidents is a positive step toward decreasing accident-related losses. Accidents can often be avoided by a timely reaction of the driver. One of the steps before reacting to a hazard is perception. Some driver characteristics may affect road hazard perception. In this research, it was assumed that various driver characteristics, including demographic characteristics and cognitive characteristics, have an impact on driver perception.

Methods: The driving simulator used in this research provides various scenarios; for example, passing a pedestrian or animal across the road or placing fixed objects in a 2-lane separated rural road for 2 groups of experienced and inexperienced drivers under day and night lighting conditions. The go/no-go test was carried out in order to assess drivers’ attention to driving tasks and inhibitory control. A structural equation model (SEM) was used to estimate the relation between driver characteristics and sensitivity to road hazard perception. A new hazard perception index was proposed based on the time intervals in the hazard vulnerability.

Results: The results show that the most effective variables in the analysis of sensitivity to hazard perception are driving experience (in kilometers) during the last 3 years and road lighting conditions. Moreover, hazard perception sensitivity was improved by better inhibitory control, selective attention, and decision making, more carefulness, the average amount of daily sleep, and marital status.

Conclusion: The results of this research may be useful in educating and advertising programs. It also could enhance sensitivity to perception of hazards such as pedestrians, animals, and fixed obstacles among young and novice drivers.     

An awareness campaign decreases distracted driving among hospital employees at a rural trauma center

Abstract

Objective: To evaluate whether an educational campaign on distracted driving will have an impact in a given community.

Methods: Investigators were stationed in an employee parking lot of a 256-bed hospital to determine baseline distracted driving followed by a 4-week hospital-wide distracted-driving awareness campaign. The campaign included signs/posters in the hospital, a booth outside of the cafeteria with flyers, a large banner in the employee lot and an opportunity for people to sign a pledge form to drive distraction free. The same employee lot was observed at the same time of the day to re-assess distracted driving immediately following the campaign. The observations were repeated again one year later to evaluate the short and long-term impact of the campaign.

Results: A total of 485 vehicles were observed pre-campaign, identifying 170 (35%) distracted drivers at baseline. The awareness campaign resulted in 525 people pledging to drive distraction free. Following the campaign, 495 vehicles were observed and the number of distracted drivers was 64 (12.9%), showing a significant decrease in the number of distracted drivers by 22.1% (p?<?0.01). One year later, 530 drivers were observed with 150 (28%) displaying one form of distraction.

Conclusions: A local distracted driving educational campaign resulted in a significant decrease in the number of distracted drivers immediately following the campaign. However, one year after the campaign, there was an increase in distracted driving. The proportion of distracted drivers was still significantly lower than the initial rate of distracted-drivers.