Transport company safety climate—The impact on truck driver behavior and crash involvement

Objective: The present study investigated the relationships between safety climate and driving behavior and crash involvement.

Methods: A total of 339 company-employed truck drivers completed a questionnaire that measured their perceptions of safety climate, crash record, speed choice, and aberrant driving behaviors (errors, lapses, and violations).

Results: Although there was no direct relationship between the drivers' perceptions of safety climate and crash involvement, safety climate was a significant predictor of engagement in risky driving behaviors, which were in turn predictive of crash involvement.

Conclusions: This research shows that safety climate may offer an important starting point for interventions aimed at reducing risky driving behavior and thus fewer vehicle collisions.     

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.     

State all-driver distracted driving laws and high school students' texting while driving behavior

Objective: Texting while driving is highly prevalent among adolescents and young adults in the United States. Texting while driving can significantly increase the risk of road crashes and is associated with other risky driving behaviors. Most states have enacted distracted driving laws to prohibit texting while driving. This study examines effects of different all-driver distracted driving laws on texting while driving among high school students.

Methods: High school student data were extracted from the 2013 National Youth Risk Behavior Survey. Distracted driving law information was collected from the National Conference of State Legislatures. The final sample included 6,168 high school students above the restricted driving age in their states and with access to a vehicle. Logistic regression was applied to estimate odds ratios of laws on texting while driving.

Results: All-driver text messaging bans with primary enforcement were associated with a significant reduction in odds of texting while driving among high school students (odds ratio = 0.703; 95% confidence interval, 0.513–0.964), whereas all-driver phone use bans with primary enforcement did not have a significant association with texting while driving (odds ratio = 0.846; 95% confidence interval, 0.501–1.429).

Conclusions: The findings indicate that all-driver distracted driving laws that specifically target texting while driving as opposed to all types of phone use are effective in reducing the behavior among high school students.     

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.     

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.     

Driving in mild cognitive impairment: The role of depressive symptoms

Objectives: Previous studies indicate a negative association between depression and driving fitness in the general population. Our goal was to cover a gap in the literature and to explore the link between depressive symptoms and driving behavior in individuals with mild cognitive impairment (MCI) through the use of a driving simulator experiment.

Methods: Twenty-four individuals with MCI (mean age = 67.42, SD = 7.13) and 23 cognitively healthy individuals (mean age = 65.13, SD = 7.21) were introduced in the study. A valid driving license and regular car use served as main inclusion criteria. Data collection included a neurological/neuropsychological assessment and a driving simulator evaluation. Depressive symptomatology was assessed with the Patient Health Questionnaire (PHQ-9).

Results: Significant interaction effects indicating a greater negative impact of depressive symptoms in drivers with MCI than in cognitively healthy drivers were observed in the case of various driving indexes, namely, average speed, accident risk, side bar hits, headway distance, headway distance variation, and lateral position variation. The associations between depressive symptoms and driving behavior remained significant after controlling for daytime sleepiness and cognition.

Conclusions: Depressive symptoms could be a factor explaining why certain patients with MCI present altered driving skills. Therefore, interventions for treating the depressive symptoms of individuals with MCI could prove to be beneficial regarding their driving performance.     

Predictors of health care provider anticipatory guidance provision for older drivers

Objective: The objective of this study was to determine the frequency of health care provider (HCP) driving safety/cessation-related anticipatory guidance provision and predictors of driving safety-related anticipatory guidance provision by HCPs.

Methods: HCPs in several central/upper Midwest states were surveyed about frequency of anticipatory guidance provision (n = 265).

Results: More than half of HCPs stated that they frequently or always provide driving safety/cessation-related anticipatory guidance to patients aged 85 or older, 38.7% provided this guidance to patients aged 75 to 84, and 13.7% to patients aged 65 to 74. Predictors of driving safety/cessation-related anticipatory guidance provision differed by patient age. For patients aged 65–74, HCP personal experience with a motor vehicle crash (either the HCP themselves or a friend/family member) was significant in predicting anticipatory guidance provision. However, for patients aged 75 and older, significant predictors included HCP rural practice, HCP age, and percentage of HCP patients who were older adults.

Conclusion: HCP counseling provision related to driving issues differs by patient age and several HCP characteristics, including HCP rurality, age, and personal experience with motor vehicle crashes. Because aging results in physical and mental changes that affect driving and can be identified by HCPs, HCPs are in a position to counsel patients on the potential impacts of aging on the act of driving. Future research should examine the reasons for the differences in anticipatory guidance provision found in this study.     

Difficulties in emotion regulation and risky driving among Lithuanian drivers

Background: Risky driving is a common cause of traffic accidents and injuries. However, there is no clear evidence of how difficulties in emotion regulation contribute to risky driving behavior, particularly in small post-Soviet countries. The present study aimed to investigate the relationship between difficulties in emotion regulation and self-reported risky driving behavior in a sample of Lithuanian drivers.

Methods: A total of 246 nonprofessional Lithuanian drivers participated in a cross-sectional survey. Difficulties in emotion regulation were assessed using the Difficulties in Emotion Regulation Scale (DERS; Gratz and Roemer 2004), and risky driving behavior was assessed using the Manchester Driver Behaviour Questionnaire (DBQ; Lajunen et al. 2004).

Results: Males scored higher than females in aggressive violations and ordinary violations. Females scored higher for the nonacceptance of emotional responses, whereas males had more difficulties with emotional awareness than females. More difficulties in emotion regulation were positively correlated with driving errors, lapses, aggressive violations, and ordinary violations for both males and females. Structural equation modeling showed that difficulties in emotion regulation explained aggressive and ordinary violations more clearly than lapses and errors. When controlling for interactions among the distinct regulation difficulties, difficulties with impulse control and difficulties engaging in goal-directed behavior predicted risky driving. Furthermore, nonacceptance of emotional responses and limited access to emotion regulation strategies were related to less violations and more driving errors.

Conclusion: Emotion regulation difficulties were associated with the self-reported risky driving behaviors of Lithuanian drivers. This provides useful hints for improving driver training programs in order to prevent traffic injuries.     

Drink driving and risky behavior among university students in southwestern Nigeria—Implications for policy development

Background: Drink driving contributes significantly to road traffic injuries. Little is known about the relationship between drink driving and other high-risk behaviors in non-Western countries. The study aimed to assess the relationship between drink driving and other risky behaviors including making phone calls, sending text messages, nonuse of protective gear, and driving against traffic.

Methods: A cross-sectional survey of risky behavior among undergraduates was conducted. A stratified random sampling method was used to identify young undergraduates who had driven a motorized vehicle in the past year. The Alcohol Use Disorder Identification Test (AUDIT) and other tools developed by researchers were used to identify the risky behaviors.

Results: Of 431 respondents, 10.7% had engaged in drink driving in the past 12 months. The most common risky behavior was making phone calls (63.7%), followed by nonuse of helmets (54.7%), driving against traffic (49.2%), nonuse of seat belts (46.8%), and sending text messages (26.1%). Alcohol use was significantly associated with making phone calls (U = 1.148; P < .0001), sending text messages (U = 1.598; P = .021), nonuse of helmets (U = 1.147; P < .0001), driving against traffic (U = 1.234; P < .0001), and nonuse of seat belts (U = 3.233; P = .001). Drink driving was associated with all risky behaviors except nonuse of seat belts (U = 1.842; P = .065).

Conclusion: Alcohol use and drink driving were associated with multiple risky driving behaviors. This provides useful insight for policy development and presents additional challenges for traffic injury prevention.     

Risk factors for the severity of injury incurred in crashes involving on-duty police cars

Objective: This article explores the risk factors associated with police cars on routine patrol and/or on an emergency run and their effects on the severity of injuries in crashes.

Methods: The binary probit model is used to examine the effects of important factors on the risk of injuries sustained in crashes involving on-duty police cars.

Results: Several factors significantly increase the probability of crashes that cause severe injuries. Among those causes are police officers who drive at excessive speeds, traffic violations during emergency responses or pursuits, and driving during the evening (6 to 12 p.m.) or in rainy weather. Findings also indicate some potential issues associated with an increase in the probability of crashes that cause injuries. Younger police drivers were found to be more likely to be involved in crashes causing injuries than middle-aged drivers were. Distracted driving by on-duty police officers as well as civilian drivers who did not pull over to let a police car pass in emergency situations also caused serious crashes.

Conclusions: Police cars are exempted from certain traffic laws under emergency circumstances. However, to reduce the probability of being involved in a crash resulting in severe injuries, officers are still obligated to drive safely and follow safety procedures when responding to emergencies or pursuing a car. Enhancement of training techniques for emergency situations or driving in pursuit of an offender and following the safety procedures are essential for safety in driving during an emergency run by police.     

Analysis of naturalistic driving videos of fleet services drivers to estimate driver error and potentially distracting behaviors as risk factors for rear-end versus angle crashes

Objective: The objective of this study was to estimate the prevalence and odds of fleet driver errors and potentially distracting behaviors just prior to rear-end versus angle crashes.

Methods: Analysis of naturalistic driving videos among fleet services drivers for errors and potentially distracting behaviors occurring in the 6 s before crash impact. Categorical variables were examined using the Pearson's chi-square test, and continuous variables, such as eyes-off-road time, were compared using the Student's t-test. Multivariable logistic regression was used to estimate the odds of a driver error or potentially distracting behavior being present in the seconds before rear-end versus angle crashes.

Results: Of the 229 crashes analyzed, 101 (44%) were rear-end and 128 (56%) were angle crashes. Driver age, gender, and presence of passengers did not differ significantly by crash type. Over 95% of rear-end crashes involved inadequate surveillance compared to only 52% of angle crashes (P < .0001). Almost 65% of rear-end crashes involved a potentially distracting driver behavior, whereas less than 40% of angle crashes involved these behaviors (P < .01). On average, drivers spent 4.4 s with their eyes off the road while operating or manipulating their cell phone. Drivers in rear-end crashes were at 3.06 (95% confidence interval [CI], 1.73–5.44) times adjusted higher odds of being potentially distracted than those in angle crashes.

Conclusions: Fleet driver driving errors and potentially distracting behaviors are frequent. This analysis provides data to inform safe driving interventions for fleet services drivers. Further research is needed in effective interventions to reduce the likelihood of drivers' distracting behaviors and errors that may potentially reducing crashes.     

Evaluation of measures of impairment in real and simulated driving: Results from a randomized,placebo-controlled study

Objective: Standard deviation of lateral position (SDLP) is often the primary outcome in experimental studies on impaired driving. However, other measures may be easier and more practical to obtain and reflect a broader range of driving-related behaviors. We wanted to assess the validity and sensitivity of a range of measures in a driving simulator as well as during real driving and compare these to SDLP.

Methods: Twenty healthy male volunteers undertook 6 driving trials each, 3 in a regular car on a closed track resembling rural road conditions and 3 in a simulator with an identical driving scenario. Ethanol was used as impairing substance due to its well-characterized effects on driving. The subjects were tested sober and at blood alcohol concentrations (BAC) of approximately 0.5 and 0.9 g/L. We explored dose–response relationships between BAC and a range of driving-related measures, as well as their BAC-dependent effect sizes.

Results: In simulator driving, ethanol intake increased steering wheel reversal frequency, steering wheel movement measures, average speed, standard deviation of speed, and pedal use frequency. At the test track, only steering wheel movement and standard deviation of speed were significantly correlated to BAC. Likewise, reaction to unexpected incidents and observance of red traffic lights were adversely affected by ethanol in the simulator but not at the test track. Whereas SDLP showed a relatively large effect size that was similar in simulated and real driving, all other measures demonstrated smaller effect sizes, with less pronounced BAC effects on the test track than in the simulator.

Conclusions: The results suggest that the driving-related measures explored in this study are less sensitive to alcohol-mediated driving impairment than SDLP, especially during real (test track) driving. The discrepancy in effect sizes between simulated and real driving may imply low external validity of these measures in simulator studies.     

Examining motor vehicle crash involvement and readiness to change on drinking and driving behaviors among injured emergency department patients

Objective: To measure the effect of motor vehicle crash (MVC) involvement and readiness to change drinking and driving behaviors on subsequent driving and drinking behaviors among injured emergency department (ED) patients who use alcohol at harmful levels.

Methods: This was a secondary analysis of a randomized controlled trial of injured ED patients who screened positive for harmful alcohol use, who at recruitment reported driving in the past 12 months and received at least one of the intended intervention sessions (brief behavioral intervention versus attention placebo control; N = 407). Outcome variables were as follows: (1) change in 6 impaired driving behaviors and (2) report of MVCs and traffic violations in the 12 months following recruitment; predictor variables were as follows: (1) treatment assignment, (2) MVC involvement at recruitment, and (3) baseline readiness to change alcohol use and drinking and driving.

Results: Modeling of change in the 6 impaired driving variables indicated that neither the recruitment visits being MVC related nor baseline readiness to change alcohol use and drinking and driving behaviors predicted greater changes in impaired driving over time. Baseline reports of past moving traffic violations and the ED visit being MVC related predicted a greater likelihood of each behavior at 12 months following study recruitment.

Conclusions: This study and others have demonstrated that ED patients with harmful alcohol use are willing to engage in behavioral interventions directed at changing risky behaviors. However, this study did not demonstrate that patients considered having the potential to be more engaged with the intervention because their ED visit was MVC related and/or they had expressed intent to change their risky alcohol use and drinking and driving behaviors were more likely to change these risky behaviors.     

The characteristics of young Indigenous drink drivers in Queensland,Australia

Objective: This study investigates the prevalence and characteristics of first drink driving convictions among young Aboriginal and Torres Strait Islander (Indigenous) Australians (aged from 14 to 24) and considers some of the risk factors associated with recidivism.

Methods: Convictions recorded between 2006 and 2013 were extracted from the Queensland Department of Justice and Attorney General database. Convictions were regrouped by gender, age, Accessibility/Remoteness Index of Australia classification, and sentence severity. Chi-square analyses and logistic regression were conducted to identify group differences in offense characteristics for gender and recidivism (recidivists versus nonrecidivists).

Results: The sample consisted of 1,583 individuals (74.1% males) convicted in the 8-year period. Gender comparisons showed that there was no significant difference in age at time of first offense, blood alcohol concentration (BAC) level at apprehension, or type of penalty received between males and females. However, males received larger fines and longer periods of license disqualification. Comparisons for reoffending and non-reoffending revealed that males, drivers aged 14–17 years of age and 18 to 20 years of age, and inner regional drivers were more likely to reoffend.

Conclusions: There were limited differences between females and males or recidivists and nonrecidivists at first conviction. Convictions for drink driving may provide an opportunity for early alcohol intervention with Indigenous young drivers (<20 years) because it is likely to be an individual's first alcohol-related conviction.     

Representativity and univocity of traffic signs and their effect on trajectory movement in a driving simulation task: Warning signs

Objective: The effect of traffic signs on the behavior of drivers is not completely understood. Knowing about how humans process the meaning of signs (not just by learning but instinctively) will improve reaction time and decision making when traveling. The economic, social, and psychological consequences of car accidents are well known.

Methods: This study sounds out which traffic signs are more ergonomic for participants, from a cognitive point of view, and determines, at the same time, their effect in participants' movement trajectories in a driving simulation task.

Results: Results point out that the signs least representative of their meaning produce a greater deviation from the center of the road than the most representative ones.

Conclusions: This study encourages both an in-depth analysis of the effect on movement of roadside signs and the study of how this effect can be modified by the context in which these signs are presented (with the aim to move the research closer to and analyze the data in real contexts). The goal is to achieve clarity of meaning and lack of counterproductive effects on the trajectory of representative signs (those that provoke fewer mistakes in the decision task).     

The use and safety of medications known to affect driving in Jordan: A cross-sectional study

Objectives: The aim of this study was to estimate the main driving-impairing medications used by drivers in Jordan, the reported frequency of medication side effects, the frequency of motor vehicle crashes (MVCs) while using driving-impairing medicines, as well as factors associated with MVCs.

Methods: A cross-sectional study involving 1,049 individuals (age 18–75 years) who are actively driving vehicles and taking at least one medication known to affect driving (anxiolytics, antidepressants, hypnotics, antiepileptics, opioids, sedating antihistamines, hypoglycemic agents, antihypertensives, central nervous system [CNS] stimulants, and herbals with CNS-related effects) was conducted in Amman, Jordan, over a period of 8 months (September 2013–May 2014) using a structured validated questionnaire.

Results: Sixty-three percent of participants noticed a link between a medicine taken and feeling sleepy and 57% stated that they experience at least one adverse effect other than sleepiness from their medication. About 22% of the participants reported having a MVC while on medication. Multiple logistic regression analysis showed that among the participants who reported having a crash while taking a driving-impairing medication, the odds ratios were significantly higher for the use of inhalant substance (odds ratio [OR] = 2.787, P = .014), having chronic conditions (OR = 1.869, P = .001), and use of antiepileptic medications (OR = 2.348, P = .008) and significantly lower for the use of antihypertensives (OR = 0.533, P = .008).

Conclusion: The study results show high prevalence of adverse effects of medications with potential for driving impairment, including involvement in MVCs. Our findings highlight the types of patient-related and medication-related factors associated with MVCs in Jordan, such as inhalant use, presence of chronic conditions, and use of antiepileptics.     

Driving restrictions post-stroke: Physicians' compliance with regulations

Objective: Suffering a stroke might lead to permanent cognitive and/or physical impairment. It has been shown that these impairments could have an impact on an individual's fitness to drive. In Sweden, as in many other countries, there are regulations on driving cessation post-stroke. Information on driving cessation should be given to all patients and noted in the journal. The present study sought to determine physician's compliance to driving regulations post-stroke as well as follow-up and gender aspects.

Method: A retrospective study of medical records on stroke patients was carried out. The study covered all of the medical records on stroke incidents (n = 342) during a year at a typical medium to large-sized hospital in Sweden.

Results: A journal entry on driving cessation post-stroke was missing in 81% of the medical records. Only 2% of the patients were scheduled for a follow-up meeting specifically concerning fitness to drive. Significantly more men than women had an entry on driving in the journal.

Conclusions: We conclude that the Swedish regulations on driving cessation post-stroke were not followed at the participating hospital. It is crucial that all stroke patients receive information on driving cessation because their condition might affect fitness to drive. Analysis of follow-up records showed that there was no consistent method for assessment of a patient's fitness to drive. There was also a gender difference in the material, which warrants further investigation.     

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.     

Can variations in visual behavior measures be good predictors of driver sleepiness? A real driving test study

Objective: The primary purpose of this study was to examine the association between variations in visual behavior measures and subjective sleepiness levels across age groups over time to determine a quantitative method of measuring drivers' sleepiness levels.

Method: A total of 128 volunteer drivers in 4 age groups were asked to finish 2-, 3-, and 4-h continuous driving tasks on expressways, during which the driver's fixation, saccade, and blink measures were recorded by an eye-tracking system and the subjective sleepiness level was measured through the Stanford Sleepiness Scale. Two-way repeated measures analysis of variance was then used to examine the change in visual behavior measures across age groups over time and compare the interactive effects of these 2 factors on the dependent visual measures.

Results: Drivers' visual behavior measures and subjective sleepiness levels vary significantly over time but not across age groups. A statistically significant interaction between age group and driving duration was found in drivers' pupil diameter, deviation of search angle, saccade amplitude, blink frequency, blink duration, and closure duration. Additionally, change in a driver's subjective sleepiness level is positively or negatively associated with variation in visual behavior measures, and such relationships can be expressed in regression models for different period of driving duration.

Conclusions: Driving duration affects drivers' sleepiness significantly, so the amount of continuous driving time should be strictly controlled. Moreover, driving sleepiness can be quantified through the change rate of drivers' visual behavior measures to alert drivers of sleepiness risk and to encourage rest periods. These results provide insight into potential strategies for reducing and preventing traffic accidents and injuries.