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Objective: Driver sleepiness is a major crash risk factor but may be underrecognized as a risky driving behavior. Sleepy driving is usually rated as less of a road safety issue than more well-known risky driving behaviors, such as drink driving and speeding. The objective of this study was to compare perception of crash risk of sleepy driving, drink driving, and speeding.

Methods: Three hundred Australian drivers completed a questionnaire that assessed crash risk perceptions for sleepy driving, drink driving, and speeding. Additionally, the participants' perceptions of crash risk were assessed for 5 different contextual scenarios that included different levels of sleepiness (low, high), driving duration (short, long), and time of day/circadian influences (afternoon, nighttime) of driving.

Results: The analysis confirmed that sleepy driving was considered a risky driving behavior but not as risky as high levels of speeding (P < .05). Yet, the risk of crashing at 4 a.m. was considered as equally risky as low levels of speeding (10 km over the limit). The comparisons of the contextual scenarios revealed driving scenarios that would arguably be perceived as quite risky because time of day/circadian influences were not reported as high risk.

Conclusions: The results suggest a lack of awareness or appreciation of circadian rhythm functioning, particularly the descending phase of circadian rhythm that promotes increased sleepiness in the afternoon and during the early hours of the morning. Yet, the results suggested an appreciation of the danger associated with long-distance driving and driver sleepiness. Further efforts are required to improve the community's awareness of the impairing effects from sleepiness and, in particular, knowledge regarding the human circadian rhythm and the increased sleep propensity during the circadian nadir.  相似文献   


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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.  相似文献   


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This study aims to explore the effects of different road environments and their changes on driving behaviors and cognitive task performance of fatigued drivers. Twenty-four participants volunteered in a 2 (road environment) × 3 (fatigue level) within-subjects factorial design simulated driving experiment. Participants were asked to perform basic numerical calculation and distance estimation of traffic signs when driving normally, and provide answers to a questionnaire on fatigue rating. Results show that fatigued drivers faced greater attention demand, were less alert, and tended to overestimate the distance to roadside traffic signs. Fatigue caused by driving in complex road environment had the greatest negative impact on driving behavior and visual distance estimation, and the fatigue transfer effect worsened significantly but differently on both driving behavior and performance of fatigued drivers when switching from a complex to a monotonous road environment and vice versa. Notably, this study shows that fatigued drivers performed relatively better in arithmetic tasks than non-fatigued ones. In addition, when switching from a monotonous to a complex road environment, drivers’ performance in visual distance estimation and arithmetic tasks improved though their driving behavior deteriorated, revealing that the fatigue effect upon drivers might be explained to some extent by their alertness and arousal levels.  相似文献   

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Introduction: Intersections are the most dangerous locations in urban traffic. The present study aims to investigate drivers’ visual scanning behavior at signalized and unsignalized intersections. Method: Naturalistic driving data at 318 green phase signalized intersections and 300 unsignalized ones were collected. Drivers’ glance allocations were manually categorized into 10 areas of interest (AOIs), based on which three feature subsets were extracted including glance allocation frequencies, durations and AOI transition probabilities. The extracted features at signalized and unsignalized intersections were compared. Features with statistical significances were integrated to characterize drivers’ scanning patterns using the hierarchical clustering method. Andrews Curve was adopted to visually illustrate the clustering results of high-dimensional data. Results: Results showed that drivers going straight across signalized intersections had more often glances at the left view mirror and longer fixation on the near left area. When turning left, drivers near signalized intersections had more frequent glances at the left view mirror, fixated much longer on the forward and rearview mirror area, and had higher transition probabilities from near left to far left. Compared with drivers’ scanning patterns in left turning maneuver at signalized intersections, drivers with higher situation awareness levels would divide more attention to the forward and right areas than at unsignalized intersections. Conclusions: This study revealed that intersection types made differences on drivers’ scanning behavior. Practical applications: These findings suggest that future applications in advanced driver assistance systems and driver training programs should recommend different scanning strategies to drivers at different types of intersections.  相似文献   

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Objective: Research has found that mandatory motorcycle helmet laws increase helmet use and reduce motorcycle-related fatalities. However, the association between state moped helmet laws and helmet use in the United States has not been examined. This study investigated this association among a census of fatally injured moped riders in the United States.

Methods: A logistic regression model was constructed to analyze data extracted from the Fatality Analysis Reporting System (FARS) to examine risk factors for helmet nonuse among 572 moped riders fatally injured between 2011 and 2015.

Results: Fatally injured moped riders in states with universal helmet laws had 69 times the odds of wearing a helmet (P < .001).

Conclusions: Findings suggest that universal moped helmet laws increase helmet use. However, additional research is needed to examine helmet laws and use among nonfatally injured moped riders.  相似文献   


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