Risk Factors For Traffic Accidents Research Articles

Drowsy Driver Detection System

Abstract: Drowsy driver detection system is a safety technology designed to identify the potential signs of fatigue or drowsiness of the driver to prevent accidents caused as a result of not being alert. It is a significant risk factor for traffic accidents which has led to thousands of accidents, injuries, and fatalities each year. In this system we have used some techniques to monitor the driver’s behavior or state. This involves tracking facial features, eye movements or blink patterns and yawning. The system identifies signs of fatigue, such as slow eyelid closure, increased blink duration and yawn which often indicate drowsiness. As technology advances, these systems are becoming more accurate, efficient and integrated with other vehicle safety features. The continued development of drowsy driver detection technology holds significant promise for reducing traffic accidents and improving overall road safety.

Trends in drivers testing positive for drugs of abuse in oral fluid from 2018 to 2021 in France

BackgroundDriving under the influence of drugs (DUID) is a risk factor for traffic accidents. The testing of oral fluid by roadside immunochromatography and laboratory-confirmed chromatography coupled to mass spectrometry (LC-MS/MS) analysis to detect drug abuse has increased in France. The aim of this study was to describe the trends observed in drivers testing positive for illicit drugs in oral fluid and to investigate the concordance between the two analytical methods used. MethodsWe received for confirmation 3051 oral fluid samples from drivers who had tested positive at the roadside with a Drugwipe-5S® device between 2018 and 2021 around Grenoble, France. Samples were collected with FLOQSwab® and analyzed by LC-MS/MS (THC, amphetamine, methamphetamine, MDMA and MDA, MDEA, cocaine and benzoylecgonine, morphine and 6-monoacetylmorphine) at Grenoble Alpes University Hospital, France. Binomial logistic regression was performed to evaluate consumption trends. ResultsMost of the drivers were men (93.2%), with a median age of 26 years (range: 14–66 years). Cannabis (94.6%) cocaine (17.5%) and MDMA (2.5%) were the drugs most frequently detected. Poly-drug use was observed in 17.3% of drivers and involved cannabis and cocaine in 85.3% of these drivers. Poly-drug use was more frequent among drivers over the age of 32 years (OR, 3.48; 95% CI, 2.59–4.68; p ≤ .001), as was cocaine use (OR, 5.15; 95% CI, 3.75–7.08; p ≤ .001). The frequency of positive tests for amphetamines was higher in women than in men (OR, 2.53; 95% CI, 1.50–4.27; p ≤ .001). The positive predictive value of Drugwipe-5S was 98.2% for cannabis, 22.6% for amphetamines, 75.4% for cocaine and 17.3% for opiates. At least one discrepancy between Drugwipe-5S® and LC-MS/MS results was observed for 22.3% of the samples tested. ConclusionWe report recent trends for drivers testing positive for illicit drugs in oral fluid in France. Cannabis was the most prevalent drug of abuse identified, suggesting that a general prevention program might be useful. Our results also highlight the need for LC-MS/MS confirmation when screening oral fluid for drugs of abuse.

Analyzing the Risk Factors of Traffic Accident Severity Using a Combination of Random Forest and Association Rules

This study explores risk factors influencing the at-fault party in traffic accidents and analyzes their impact on traffic accident severity. Based on the traffic accident data of Shenyang City, Liaoning Province, China, from 2018 to 2020, 19 attribute variables including road attributes, time attributes, environmental attributes, and characteristics of the at-fault parties with either full responsibility, primary responsibility, or equal responsibility of the traffic accidents were extracted and analyzed in conjunction with the built environment attributes, such as road network density and POI (points of interest) density at the sites of traffic accidents. Using the RF-SHAP method to determine the relative importance of risk factors influencing the severity of traffic accidents with either motor vehicles or vulnerable groups at-fault, the top ten risk factors influencing the severity of traffic accidents with vulnerable road users as the at-fault parties are: functional zone, density of shopping POI, density of services POI, cause of accident, travel mode, collision type, season, road type, age of driver, and physical isolation. Travel mode, season, and road speed limit are more important risk factors for traffic accidents, with motor vehicle drivers as the at-fault parties. The density of service POI and cause of the accident are less critical for traffic accidents with motor vehicle drivers than traffic accidents with vulnerable road users who are at-fault. Subsequently, the Apriori algorithm based on association rules is used to analyze the important causal factors of traffic accidents, so as to explore the influence mechanism of multiple causal factors and their implied strong association rules. Our results show that most combined factors are associated with the matched Service and Shopping POI features. This study provides valuable information on the perceived risk of fatal accidents and highlights the built environment’s significant influence on fatal traffic accidents. Management strategies targeting the most typical combinations of accident risk factors are proposed for preventing fatalities and injuries in serious traffic accidents.

A Systematic Review of Pattern and Prevalence of Cannabis Use among Transporters and Associated Road Traffic Accidents

Background: Cannabis (marijuana), while being prohibited in many countries, is the most commonly used illicit drug worldwide (WHO, 1997). "Cannabis-impaired driving" refers to the impairment brought on by 9-tetrahydrocannabinol's (THC) cognitive and psychomotor effects, which have a negative impact on a driver of a motor vehicle after THC ingestion. In contrast, a "cannabis-positive driver" is a person who operates a motor vehicle while exhibiting driving impairments due to any measurable THC concentration in blood, oral fluid, or urine. A driver is considered to be "driving under the influence of cannabis" (DUIC) if their cognitive or psychomotor abilities are significantly impaired and their blood, oral fluid, or urine contains a specific amount of THC.
 Aim: This study aimed at conducting a systematic review of pattern and prevalence of cannabis use among transporters and the associated road traffic accidents.
 Design: A systematic review.
 Data Sources: Systematic search for worldwide published literature from PubMed, PsycINFO, EMBASE, Google Scholar, Science Direct, Cochrane Library and Medline databases.
 Study eligibility criteria: These studies provided techniques and/or measurements of the frequency and pattern of cannabis use among transporters and the related traffic incidents.
 Data extraction: The first reviewer extracted the data, and the second reviewer verified it. Both reviewers individually critiqued each of the identified papers. Data was extracted from each eligible study (including author, title, year, and study setting) following the Preferred Reporting Items on Systematic Reviews and Meta-Analysis (PRISMA). These data abstraction forms were examined, and studies that satisfied the criteria were added to the meta-analysis.
 Findings: Only 10 studies met all of the inclusion criteria out of the 2,251 papers that were recovered after looking at the titles and abstracts (where an abstract was not available, the article was still counted).
 Conclusion: The study emphasizes the significance of education, law enforcement, and routine drug testing, reducing bribery among federal prosecutors, and influencing the accessibility of cannabis and other psychiatric substances as assessments for preventing substance cruising and restricting road traffic accidents. It also highlights areas where the study's findings and the scientific literature on risk factors for traffic accidents and preventative measures overlap. To increase acceptance and improve results, it is crucial to incorporate lay perspectives into road safety policies and initiatives.

The Bordeaux Sleepiness Scale (BOSS): a new questionnaire to measure sleep-related driving risk.

Sleepiness is a well-known risk factor for traffic accidents. Our study presents a new questionnaire, the Bordeaux Sleepiness Scale (BOSS), specifically designed to evaluate sleep-related driving risk in patients with sleep disorders. The BOSS was designed by gathering data on sociodemographics, sleepiness, driving items, and traffic accident exposure (kilometers driven) in the past year of 293 patients followed for sleep disorders at a French sleep clinic. It was then validated on data from a large population-based cohort of 7,296 highway drivers. Its performance was compared to the Epworth sleepiness scale and to self-reported episodes of severe sleepiness at the wheel. Receiver operating characteristic curves were computed. The sensitivity and specificity of the BOSS (cutoff = 3) to predict sleep-related near-misses or accidents was, respectively, 82% and 74%, with an area under the receiver operating characteristic curve of 0.83. In a cohort of patients and a large population-based cohort, the area under the curve of the BOSS was significantly larger than that of the Epworth sleepiness scale (P < .001). Although the areas under the curve were equivalent between the BOSS and sleepiness at the wheel, the specificity of the BOSS was higher. The BOSS scale combining exposure (kilometers driven) and self-perception of situational sleepiness provides a simple and reliable evaluation of sleep-related driving risk. This short, specific questionnaire should be promoted as a first-line tool to evaluate the risk of traffic accidents in sleepy patients. Philip P, Micoulaud-Franchi J-A, Taillard J, etal. The Bordeaux Sleepiness Scale (BOSS): a new questionnaire to measure sleep-related driving risk. J Clin Sleep Med. 2023;19(5):957-965.

A Retrospective, Single-Agency Analysis of Ambulance Crashes during a 3-Year Period: Association with EMS Driver Characteristics and a Telematics-Measured Safe Driving Score

Background Driver demographics and aggressive driving behavior are established risk factors for traffic accidents, yet their role in ambulance crashes remains poorly studied. We reviewed all ambulance crashes that occurred in our emergency medical services (EMS) agency during a 3-year period, and examined incidence rates (IR) by driver characteristics and telematics-measured driver behavior. Methods This retrospective study was conducted in a U.S. EMS agency that operates 75 Type III ambulances and requires personnel to document all ambulance collisions, regardless of severity. Crashes reported between September 2017 and August 2020 were reviewed, and established criteria were used to classify injury and vehicle damage severity. Serious crashes were defined as events with any injury and/or functional or disabling damage. A vehicle telematics system installed fleet-wide in 2017 continuously captures driver-specific data, including miles driven and indicators related to speeding, harsh cornering and braking, and seatbelt use. A composite score characterizes compliance with safe driving behaviors (1 = low compliance to 5 = high compliance). Crash IR per 100,000 miles, IR ratios (IRR), and Poisson regression were used in analysis. Driver sex, age, agency tenure, miles driven, and safe driving score were examined. Results Clinicians reported 214 crashes and the IR of any crash and serious crash were 2.1 and 0.63 per 100,000 miles, respectively. Injuries occurred in 8% of crashes and were all of low acuity. About one third of crashes produced functional (21%) or disabling (8%) vehicle damage, and the ambulance required towing in 10%. In a multivariate model, female sex (IRR = 1.50, 95%CI = 1.13–1.97), age 18–24 (IRR = 1.67, 95%CI = 1.06–2.66), and being in the lowest quartile of safe driving score (IRR = 1.51, 95%CI = 1.14–2.02) were EMS driver factors independently associated with an increased risk of any collision. Conclusion Most ambulance crashes are minor events, but the proportion that result in injury and/or functional or disabling vehicle damage may be as high as one-third. Poor driver compliance with objectively measured safe driving behaviors may increase risk for collisions independent of driver sex and age. The EMS industry would benefit from additional studies that examine the full spectrum of ambulance crashes and expand understanding of EMS driver-related risk factors.

Association of benzodiazepines, Z-drugs, pregabalin, and melatonin with traffic accidents: A nationwide cohort and case-crossover study in Danish adults.

Benzodiazepines, Z-drugs, pregabalin, and melatonin (BZPMs) have been associated with a higher risk of traffic accidents, but the evidence is inconsistent, and lacking for newer drugs. To examine the association of BZPMs with risk of traffic accidents. All Danish adults (n = 3,823,588) were followed for redeemed prescriptions of BZPM and for incident traffic accidents registered in Danish registers from 2002 through 2018. Associations were examined in cohort and case-crossover designs using Cox proportional hazard and conditional logistic regression with adjustment for co-variables. A total of 19.3% (n = 738,019) of all participants initiated treatment with BZPMs. During the mean follow-up of 10.3 years, 595,173(15.5%) of participants were involved in a traffic accident. In the cohort analysis, all BZPMs besides pregabalin were associated with a higher risk of traffic accidents in adults below 70 years, with chlordiazepoxide showing the strongest association (hazard ratio (HR)age 18-49 = 1.76, 95% confidence interval (CI): 1.67-1.86 and HRage 50-69 = 1.84, 95% CI: 1.70-2.00). In the older age groups, the specific BZPM medications were associated with lower or no risk of traffic accidents. However, in case-time-crossover analysis with inherited control for confounders, no BZPM medication was positively associated with traffic accidents, except for chlordiazepoxide, which had a higher odds ratio in middle-aged group (1.62, 95% CI: 1.15-2.29). This study does not fully support that BZPM use is a risk factor for traffic accidents. However, a positive association was found for chlordiazepoxide, which is approved for treatment of acute alcohol withdrawal.

Effect of Smartphone Dependency on Smartphone Use While Driving

Distracted driving is an important risk factor for traffic accidents. In particular, smartphone use while driving has become the leading cause of distraction in recent years, with the advent of smartphones and their extended functions. One noteworthy change is the addictiveness and dependency on smartphones. This study was conducted to investigate the effect of smartphone dependency on the use of smartphones while driving. A survey of 948 Korean drivers assessed smartphone dependency as well as driver experiences of calling and manipulating the smartphone while driving. Based on the survey, the relationship between smartphone dependency and the use of smartphones was examined using factor analysis and binary logistic regression. Results reveal that drivers who had high smartphone dependency were more likely to use their smartphones while driving, and the effect of smartphone dependency on manipulation was more influential than it was on calls. The results provide compelling evidence that patterns of dependent smartphone usage affect the use of smartphones while driving, especially regarding manipulation. These findings explore smartphone usage whilst driving and can provide a stepping stone toward the formulation of future policies for traffic safety.

Intelligent Traffic Accident Prediction Model for Internet of Vehicles With Deep Learning Approach

In this study, a high accident risk prediction model is developed to analyze traffic accident data, and identify priority intersections for improvement. A database of the traffic accidents was organized and analyzed, and an intersection accident risk prediction model based on different mechanical learning methods was created to estimate the possible high accident risk locations for traffic management departments to use in planning countermeasures to reduce accident risk. Using Bayes’ theorem to identify environmental variables at intersections that affect accident risk levels, this study found that road width, speed limit and roadside markings are the significant risk factors for traffic accidents. Meanwhile, Naïve Bayes, Decision tree C4.5, Bayesian Network, Multilayer perceptron (MLP), Deep Neural Networks (DNN), Deep Belief Network (DBN) and Convolutional Neural Network (CNN) were used to develop an accident risk prediction model. This model can also identify the key factors that affect the occurrence of high-risk intersections, and provide traffic management departments with a better basis for decision-making for intersection improvement. Using the same environmental characteristics as high-risk intersections for model inputs to estimate the degree of risk that may occur in the future, which can be used to prevent traffic accidents in the future. Moreover, it also can be used as a reference for future intersection design and environmental improvements.

Alcohol as a risk factor for accidents among bus drivers

Traffic safety is an important issue that needs to be taken into account in developing national policy. Several causes of accidents along the "diver-vehicle-road-environment" chain have been identified, although alcohol consumption seems to be the most important preventable cause. The aim of this paper is to describe the main activities to detect alcohol-related problems among bus drivers with the further going aim to develop public health strategies to decrease the number of traffic accidents. Methods. We analyzed normative documents, laws and edicts of the Russian Ministry of Health directed at reduction of traffic accidents associated with alcohol intoxication among drivers. Results. The main analytic approaches to study risk factors for traffic accidents including alcohol consumption practiced by intersectoral organizations are presented. Special emphasis is given to changes in legal limits of blood alcohol concentrations among the drivers in Russia. The analysis suggests that occupation as a drivers of public buses poses greater demands to physical and mental health. Psychological traits of bus drivers were summarized. Difficulties associated with detection of alcohol abuse and use of other substances among bus drivers were analyzed. The fact of driving a bus under the influence of alcohol should be treated as the use of psychoactive substances with health-related consequences. Data related to substance use obtained at medical checkup of drivers at the beginning of the shift can be transferred to narcological dispensaries (abuse clinics). Conclusions: the suggested algorithm of screening for substance abuse among bus drivers can become the basis for development of medical and psychological prevention directed at reduction of the number of traffic accidents associated with alcohol.

Prospective association between burnout and road traffic accidents in teachers.

We investigated whether burnout (emotional exhaustion, depersonalization and reduced professional efficacy) is a risk factor for traffic accidents. A prospective cohort study was conducted with 509 school teachers. The teachers were interviewed in 2012-2013, and the Maslach Burnout Inventory was applied. After 2 years, the teachers were interviewed again to determine the occurrence of traffic accidents. Poisson regression models with robust variance were used to adjust the analyses. Relative risks (RRs) and 95% confidence intervals (95%CIs) were calculated to assess changes in c-units in the scores of each Burnout dimension, with c equal to 1, 5 and 10 units. The incidence rate of road traffic accidents at follow-up was 10.8%. After adjustments for sex, age, high workload/exposure to the traffic environment, daily consumption of alcoholic beverages and the other dimensions of burnout, depersonalization was a risk factor for traffic accidents. For each 1- and 10-point increase in the depersonalization score, the risk increased by 8 and 119%, respectively. Emotional exhaustion was not associated with these accidents. Increases in the professional efficacy score increased the risk of traffic accidents. The association of depersonalization with future road traffic accidents reinforces the need for measures to improve teachers' work conditions to reduce burnout.

대구지역 교통사고 유형별 위험요인 분석

교통사고는 발생 규모와 관계없이 인명 및 재산에 큰 영향을 미치는 사회 주요 현안 중 하나이다. 최근 경찰청 교통사고 통계에 따르면 2016년 기준 자동차 등록 대수가 2천만 대를 넘어섰으며 운전면허 소지자가 전체 인구의 60%를 넘어가면서 교통혼잡 및 교통사고와 같은 부작용이 심각한 사회문제로 대두되고 있다. 기존의 교통사고를 줄이기 위한 노력은 교통 인프라를 늘리는 전통적인 방법에 집중되어 있어서 비용 대비 높은 효과를 기대하기 어렵다. 따라서 효율적인 교통안전시설을 확충을 위해 교통사고 위험요인을 파악할 수 있는 교통사고 유형별 위험요인 분석이 필요하다. 이를 위해, 교통사고 발생지점을 지도에 시각화하여 교통사고 발생 패턴을 확인하고 리플리의 K 함수를 이용하여 교통사고 패턴의 공간군집이 존재하는지 시공간 검정통계량을 통해 알아보았다. 또한, 최근 대구지역 교통사고 자료를 활용하여 교통사고 유형별 위험요인을 분석하였고, 교통사고에 영향을 미치는 각 요인과 기상자료의 영향도 분석을 통해 교통사고 발생 위험요인을 알아보았다.

RISK AND PREVENTIVE FACTORS FOR TRAFFIC ACCIDENTS: ANALYSIS OF CHILDREN'S PERCEPTION USING THE EDUTHERAPEUTIC METHOD.

ABSTRACTObjective: To describe children’s perception of risk and preventive factors related to traffic accidents using the Edutherapeutic Method.Methods: This is a qualitative descriptive study carried out with 173 students from public schools aged seven to 14 years in Lagarto, Sergipe, Brazil. Data were collected in the second half of 2014. The first stage consisted of an activity with drawing/writing sheets in all classes selected by the Nursing undergraduate students. Next, the children answered a questionnaire on sociodemographic data. The qualitative analysis of the expressive language of the children’s drawings generated two categories: positive and negative factors for the prevention of traffic accidents and their subcategories.Results: The children’s perception regarding preventive and risk factors for traffic accidents was considered adequate according to other studies found in the literature on the same subject. The drawings and descriptions were used later to provide the students with a better understanding of these factors.Conclusions: The study lends support to educational activities and interventions about prevention with schoolchildren. This is one of the main goals proposed by Brazil in the National Plan of Action for Road Traffic Safety for the decade 2011-2020.

Sleep and take-over in automated driving

Abstract The issue of driving performance after sleeping becomes highly interesting when introducing automated driving in Level 4 (SAE). It is known that fatigue as well as hypovigilance are severe risk factors for traffic accidents while an effective countermeasure is sleeping. In Level 4 automation sleeping while driving becomes a possible scenario, including the issues of transitions. Several seconds for take-over as known from distraction studies are not enough to adjust the seat, regain control and recover after sleeping. Furthermore, when analyzing human performance after sleeping, the phenomenon of sleep inertia may affect reaction time and quality of performance. Take-over time and the effect of sleep inertia are investigated in a driving simulator study with 44 participants. As independent variable, the time after waking-up until taking over is varied: The participants had to take-over the driving task one minute, seven minutes or 15 min after waking up. A control group completed the task without sleeping. Lane keeping, deviation of line during the lane change task, braking time and mental workload served as dependent variables. There were no significant differences in driving performance between the groups when looking at driving performance, safety aspects and mental workload, hence no effect of sleep inertia was measured here. Further studies should investigate individual performance of more outliers and apply even more controlled measures to understand better if and how sleep inertia can become a problem for driving and what countermeasures should be applied. The study also shows, that take-over time of one minute leads to successful, but hectic take-overs, whereas a take-over time of 15 min induces fatigue in some drivers. We conclude that powernaps have a good chance to become a safe reality in Level 4 automation with a suitable take-over time between one and seven minutes.

A paradox: Undergraduate's knowledge and exposure to risk factors for traffic accidents

A paradox: Undergraduate's knowledge and exposure to risk factors for traffic accidents

Daytime Sleepiness in Patients with Restless Legs Syndrome: A Risk Factor for Traffic Accidents?

Daytime Sleepiness in Patients with Restless Legs Syndrome: A Risk Factor for Traffic Accidents? Abstract. Restless legs syndrome (RLS) is a symptom complex of predominantly leg-focused paraesthesias and the associated increased urge to move. Since evening exacerbations are typical, many patients suffer from sleep disorders, which can lead to increased daytime fatigue in the long term. The present retrospective data analysis investigated a potentially relevant relationship between RLS and an increased incidence of traffic accidents due to daytime sleepiness in Swiss road traffic. A direct correlation between RLS and the occurrence of traffic accidents could not be found. Nevertheless, the question of increased daytime sleepiness should not be absent from any (traffic) medical discussion.

Patterns of Harmful Alcohol Consumption among Truck Drivers: Implications for Occupational Health and Work Safety from a Systematic Review and Meta-Analysis.

Alcohol consumption is one of the main causes of productivity losses arising from absenteeism, presenteeism, and workplace injuries. Among occupational categories most affected by the use of this substance, truck drivers are subject to risk factors and risky behaviors that can have a serious impact on their health, their work, and the general road safety. The use of alcohol during truck-driving activities is, indeed, an important risk factor for traffic accidents. The present systematic review and meta-analysis aims at synthesizing the literature regarding harmful alcohol consumption patterns among truck drivers in a rigorous way. A ‘binge drinking’ prevalence of 19.0%, 95% confidence interval or CI (13.1, 26.9) was present. An ‘everyday drinking’ pattern rate of 9.4%, 95% CI (7.0, 12.4) was found, while the rate of alcohol misuse according to the “Alcohol Use Disorders Identification Test” (AUDIT)—“Cut down-Annoyed-Guilty-Eye opener questionnaire” (CAGE) instruments was computed to be of 22.7%, 95% CI (14.8, 33.0). No evidence of publication bias could be found. However, there is the need to improve the quality of published research, utilizing standardized reliable instruments. The knowledge of these epidemiological data can be useful for decision makers in order to develop, design, and implement ad hoc adequate policies.

Profile and trend of risk factors for traffic accidents in schoolchildren in Brazilian capitals: PeNSE 2009, 2012 and 2015.

Land transport accidents (LTA) are the second cause of death in schoolchildren aged 13 to 17 years. The study aims to describe the risk factors for LTA in schoolchildren from the National School Health Survey (PeNSE) of 2015 and to evaluate the trend of selected indicators in the last three editions of PeNSE. A descriptive study on risk factors for LTA in 2015, with PeNSE data and time series trends analysis, with age-adjusted regression tests of the 2009, 2012 and 2015 editions, in Brazilian capitals. In 2015, 26.3% of ninth grade schoolchildren, mostly between 13 and 15 years of age, reported having been in a motor vehicle driven by someone who consumed alcohol and 32.4% had driven a motor vehicle; 30.7% of adolescents did not use seat belts in the back seat; and 16.8% of schoolchildren who ride motorcycles did not wear helmets. There was also a worsening of the indicators between 2009 and 2015, regarding driving a motor vehicle (1.0 percentage points) and having been driven by vehicle for consumption of alcoholic beverages (1.1 percentage points). The LTA occurrence results from the interaction between roads, vehicles and users, and has a strong correlation with behavior. The results show the need to invest in educational measures, associated with supervision, the improvement of road infrastructure, research and improvement of legislation. The monitoring of risk factors in schoolchildren substantially contributes to support intersectoral public policies interventions to reduce morbidity and mortality in traffic.

Falling asleep at the wheel and distracted driving. The High-Risk Professional Drivers study.

Background:Sleepiness at the wheel and driving while engaged in other activities are well known risk factors for traffic accidents. This article estimates the prevalence of these factors among Italian Professional Drivers (PDs) and their impact on reported driving mistakes.Methods:A cross-sectional study was conducted using anonymous questionnaires. PDs (n=497) were divided into two groups: high-risk PDs (HiRis_PDs) (those who self-reported more than one incident during the last 3 years and/or more than one mistake during the past year) and non-HiRis_PDs (subjects who did not meet the above-mentioned inclusion criteria). Logistic regression analyses were performed to assess the association of self-reported sleepiness and/or risky driving behaviour with the condition of being a high-risk driver.Results:161 (32.4%) subjects were defined as HiRis_PDs. Forty-one percent of the interviewees experienced at least one episode per month of sudden-onset sleep at the wheel. Twenty-eight point two percent reported a regular use of a hand-held cell phone. Predictive factors for being HiRis_PDs were: at least one self-reported episode per month of falling asleep at the wheel [odds ratio (OR) 5, 95% confidence interval (CI) 3.21-7.80, P<0.001], driving while regularly engaged in other activities (mainly hand-held cell phone use) (OR 6.11, 95% CI 2.90-12.84, P<0.001), and young age (OR 0.96, OR 1 year of age increase, 95% CI 0.94-0.98, P=0.001).Conclusions:Focusing prevention efforts on recognizing sleepiness at the wheel and on avoiding other distracting activities while driving can reduce the possibility of driving errors on the road by about 5-6 times.

MEASUREMENT OF HEART RATE TO DETERMINE CAR DRIVERS’ PERFORMANCE IMPAIRMENT IN SIMULATED DRIVING: AN OVERVIEW

Fatigue is a gradual process related with an effort to keep awake, eventually resulting in declination of human performance. It is one of the well-known risk factors for traffic accidents. The objective of this study is to understand the psychophysiological aspects of driver fatigue by using driving simulator. This study had focused on heart rate (HR) measures to determine drivers’ performance as this method can be measured in a less intrusive manner. Hence, in this study, 17 relevant studies were discussed, chosen from electronic databases. This study encompasses a range of subject areas, including concepts and theories of fatigue, driver fatigue, and psychophysiological indicators and countermeasures of driver fatigue. A variety of psychophysiological measures and parameters have been used in past research as indicators of fatigue. Based on this review, HR can assists researchers to determine performance according to a task demand, condition and its complexity. The review highlighted gaps in the literature and opportunities for future studies.