Introduction: One of the challenging tasks for drivers is the ability to change lanes around large commercial motor vehicles. Lane changing is often characterized by speed, and crashes that occur due to unsafe lane changes can have serious consequences. Considering the economic importance of commercial trucks, ensuring the safety, security, and resilience of freight transportation is of paramount concern to the United States Department of Transportation and other stakeholders. Method: In this study, a mixed (random parameters) logit model was developed to better understand the relationship between crash factors and associated injury severities of commercial vehicle crashes involving lane change on interstate highways. The study was based on 2009–2016 crash data from Alabama. Results: Preliminary data analysis showed that about 4% of the observed crashes were major injury crashes and drivers of commercial motor vehicles were at-fault in more than half of the crashes. Acknowledging potential crash data limitations, the model estimation results reveal that there is increased probability of major injury when lane change crashes occurred on dark unlit portions of interstates and involve older drivers, at-fault commercial vehicle drivers, and female drivers. The results further show that lane change crashes that occurred on interstates with higher number of travel lanes were less likely to have major injury outcomes. Practical Applications: These findings can help policy makers and state transportation agencies increase awareness on the hazards of changing lanes in the immediate vicinity and driving in the blind spots of large commercial motor vehicles. Additionally, law enforcement efforts may be intensified during times and locations of increased unsafe lane changing activities. These findings may also be useful in commercial vehicle driver training and driver licensing programs. 相似文献
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. 相似文献
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. 相似文献
Objective: To investigate the available evidence referring to the effectiveness of digital countdown timers (DCTs) in improving the safety and operational efficiency of signalized intersection.
Methods: A systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement guidelines. Relevant literature was searched from electronic databases using key terms. Based on study selection and methodological quality assessment, 14 studies were included in the review. Findings of the studies were synthesized in a narrative analysis.
Results: Three types of DCT had different effects on intersection safety and operational efficiency. Green signal countdown timers (GSCTs) reduced red light violations, type I dilemma zone distributions, and rear-end collision likelihood but increased crossing after yellow onset and had mixed impacts on type II dilemma zone distributions and intersection capacity. In contrast, red signal countdown timers (RSCTs) increased intersection capacity, although their effectiveness in reducing red light violations dissipated over time. Likewise, continuous countdown timers (CCTs) significantly enhanced intersection capacity but had mixed influences on red light violations and crossing after yellow onset.
Conclusions: Due to the limited and inconsistent evidence regarding DCTs' effects on intersection safety and efficiency, it is not sufficient to recommend any type of DCT to be installed at signalized intersections to improve safety and operational efficiency. Nevertheless, it is apparent that both RSCTs and CCTs enhance intersection capacity, though their impacts on intersection safety are unclear. Future studies need to further verify those anticipated safe and operational benefits of DCTs with enriched field observation data. 相似文献
Objective: The Useful Field of View (UFOV) assessment, a measure of visual speed of processing, has been shown to be a predictive measure of motor vehicle collision (MVC) involvement in an older adult population, but it remains unknown whether UFOV predicts commercial motor vehicle (CMV) driving safety during secondary task engagement. The purpose of this study is to determine whether the UFOV assessment predicts simulated MVCs in long-haul CMV drivers.
Method: Fifty licensed CMV drivers (Mage = 39.80, SD = 8.38, 98% male, 56% Caucasian) were administered the 3-subtest version of the UFOV assessment, where lower scores measured in milliseconds indicated better performance. CMV drivers completed 4 simulated drives, each spanning approximately a 22.50-mile distance. Four secondary tasks were presented to participants in a counterbalanced order during the drives: (a) no secondary task, (b) cell phone conversation, (c) text messaging interaction, and (d) e-mailing interaction with an on-board dispatch device.
Results: The selective attention subtest significantly predicted simulated MVCs regardless of secondary task. Each 20 ms slower on subtest 3 was associated with a 25% increase in the risk of an MVC in the simulated drive. The e-mail interaction secondary task significantly predicted simulated MVCs with a 4.14 times greater risk of an MVC compared to the no secondary task condition. Subtest 3, a measure of visual speed of processing, significantly predicted MVCs in the email interaction task. Each 20 ms slower on subtest 3 was associated with a 25% increase in the risk of an MVC during the email interaction task.
Conclusions: The UFOV subtest 3 may be a promising measure to identify CMV drivers who may be at risk for MVCs or in need of cognitive training aimed at improving speed of processing. Subtest 3 may also identify CMV drivers who are particularly at risk when engaged in secondary tasks while driving. 相似文献