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Study Objective: To determine whether the objective level of alertness measured by the Maintenance of Wakefulness Test (MWT) is associated with the occurrence of self-reported sleepiness-related traffic near misses and accidents related to sleepiness in patients with sleep disorders.Methods: This case-control study was conducted over a three-year period in four French sleep centers during a 4∗40 min MWT in patients driving more than 5000 Km/year. Relationship between mean sleep latency on the MWT (MWT latency) and age, sex, driving, sleepiness-related near misses and accidents reported during the previous year, and sleep disorder characteristics was analyzed.Results: Of 377 patients suffering from OSAS, idiopathic hypersomnia, narcolepsy, restless leg syndrome or insufficient sleep syndrome, 176 were included. 74 cases reported an accident or near miss related to sleepiness at the wheel in the past year, and 102 reported no accident/near miss (control patients). Thirty-one (37.8 %) cases and 9 (8.8 %) controls reported being sleepy at the wheel more than once a week (p < 0.0001). After adjusted regression analyses, patients with MWT latency between 19 and 33 minutes had a 3.2- (CI 95%[1.5; 6.8], p < 0.0001) fold increase in risk of reporting a near miss/ accident and patients with MWT latency <19 min had a 5.5- (CI 95%[2.2; 13.8], p = 0.003) fold increase in this risk, compared to the referent group (MWT latency>33 min).Conclusions: MWT latency is associated with self-reported, sleepiness-related near misses and accidents related to sleepiness in the past year in patients routinely investigated in sleep clinics. The MWT could be used to assess driving risk together with clinical interviews assessing sleepiness at the wheel. [ABSTRACT FROM AUTHOR]

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Copyright of Journal of Changzhou University (Social Science Edition) is the property of Editorial Department of Journal of Changzhou University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The advent of autonomous vehicles (AVs) has complicated traffic flow and raised safety concerns, there is a pressing need to enhance traffic efficiency alongside ensuring robust safety. This paper proposes a dynamic longitudinal control strategy for AVs, based on real-time accident risk assessments. Data from traffic flow, road characteristics, and weather conditions are analyzed using a random forest algorithm, producing a real-time accident risk identification model through a support vector machine. In addition, the Perceived Risk Field Model (PRFM), a car-following model calibrated using the NGSIM dataset, considers vehicle distance, velocity, relative velocity, and acceleration. These models underpin our proposed longitudinal control strategies, tailored to variable accident risk levels. Under the normal risk control strategy, the PRFM outperforms the Intelligent Driver Model (IDM) and the Cooperative Adaptive Cruise Control Model (CACC) in stability and driving comfort. For high accident risk scenarios, our approach shows improved collision avoidance and traffic oscillation mitigation. Simulations indicate that the high accident risk control strategy offers better safety and stability than the normal risk strategy. Furthermore, traffic flow diagrams suggest an increase in road capacity as AV penetration rates rise, pointing to the promising efficiency of our proposed solution. This research provides a robust framework for AV operation, ensuring optimal traffic safety and efficiency. • A real-time accident risk identification model tailored for AVs using machine learning with high predictive accuracy. • Development of a car-following model based on safety potential field and validation using real-world datasets. • Adaptive longitudinal control strategies for AVs, capable of adjusting car-following spacing based on real-time risk. • Framework with risk identification, behavior modeling, and control strategy, providing an integrated approach to AV safety. [ABSTRACT FROM AUTHOR]

The article describes the models for assessing aircraft accident risk due to aircraft coordinate information errors at the controller’s air situation display. The models allow to justify safety requirements on aircraft coordinates display accuracy or to assess the current aircraft accident risk by analyzing observed intervals between aircraft and parameters of the surveillance system.

Human errors are one of the most significant contributory factors in ship accidents. This study aims to explore the quantitative relationship between the occurrence likelihood of human errors and external factors including the environmental characteristics, accident characteristics and ship characteristics. A multinomial logistic regression model has been developed to reflect the relationship between these factors and the occurrence likelihood of human errors using 14 years' ship accident records from Fujian water areas. Model results show that the season of spring, poor visibility and night are more likely to be associated with high occurrence likelihood of negligence and judgment/operation errors. One important finding is that mooring and no strong-wind condition are two circumstances that would highly increase occurrence likelihood of all kinds of human errors. Fishing boats and engineering ships/sand dredgers are the primary ship types which have relatively higher occurrence likelihood of negligence errors than other ship types. • This study explores the quantitative relationship between the occurrence likelihood of human errors and external factors. • A multinomial logistic regression model is developed to reflect the relationship using 14 years' ship accident records. • Negligence and judgment/operation errors are more likely to be associated with season of spring, poor visibility and night. • Mooring and no strong-wind condition will highly increase occurrence likelihood of all kinds of human errors. [ABSTRACT FROM AUTHOR]

• No compensatory measure adapted for eating and drinking tasks at intersections. • Crash risk at unsignalised intersections increased during eating and drinking tasks. • Texting resulted in reduced reaction distance at the intersection approach. • Drivers who drove regularly kept large safety margins while crossing intersections. The present study analysed and compared the impacts of distraction caused by eating, drinking and texting on risky driving behaviour at unsignalised intersections. For this purpose, 89 participants approached the simulated unsignalised intersections through the minor road and encountered a series of vehicles on the major road. Their driving performance data were analysed in terms of reaction distance and accident probability at approach and completion zones respectively. The results revealed that during the texting tasks, the drivers detected the major road traffic at a later stage compared to the baseline. Further, unlike the texting task, the eating and drinking tasks did not affect the driving performance negatively in the approach zone. However, the accident risk in the completion zone was increased significantly due to the presence of the eating and drinking tasks. Unexpectedly, the accident risk was as low as 76% for the texting task while crossing through the intersections, possibly because of the compensatory measures adapted by the drivers. The study suggested that everyday distractions could result in unsafe consequences particularly in complex driving situations because of the lower risk perceptions associated with these distractions. [ABSTRACT FROM AUTHOR]

Objective: To review systematically the published literature regarding the impact of treatment for OSA on monetized health economic outcomes.Methods: Customized structured searches were performed in PubMed, Embase (Embase.com), and the Cochrane Central Register of Controlled Trials (Wiley) databases. Reference lists of eligible studies were also analyzed. Titles and abstracts were examined, and articles were identified for full-text review. Studies that met inclusion criteria were evaluated in detail, and study characteristics were extracted using a standardized template. Quantitative characteristics of the studies were summarized, and a qualitative synthesis was performed.Results: Literature searches identified 2,017 nonredundant abstracts, and 196 full-text articles were selected for review. Seventeen studies met inclusion criteria and were included in the final synthesis. Seven studies included formal cost-effectiveness or cost-utility analyses. Ten studies employed cohort designs, and four studies employed randomized controlled trial or quasi-experimental designs. Positive airway pressure was the most common treatment modality, but oral appliances and surgical approaches were also included. The most common health economic outcomes were health-care use (HCU) and quality-adjusted life years (QALYs). Follow-ups ranged from 6 weeks to 5 years. Overall, 15 of 18 comparisons found that treatment of OSA resulted in a positive economic impact. Treatment adherence and OSA severity were positively associated with cost-effectiveness.Conclusions: Although study methodologies varied widely, evidence consistently suggested that treatment of OSA was associated with favorable economic outcomes, including QALYs, within accepted ranges of cost-effectiveness, reduced HCU, and reduced monetized costs. [ABSTRACT FROM AUTHOR]

Highlights • The factor structure of commonly given driving self-report measures is examined. • Within an undergraduate sample, a four-factor structure solution was identified. • Negative driving emotions represent a separate construct from driving behaviors. • Intentionality helps distinguish driving aggression from broader reckless behaviors. • Enacted and perceived driving aggressions map on to differing constructs. Abstract Objective A wide variety of driving self-report measures are purported to assess drivers' behaviors and emotions. However, little is known about the underlying factor structure of these measures. This study examined the factor structure of several self-report measures frequently utilized in the assessment of driving-related behaviors and emotions. Design Cohort survey in a large sample (n = 287) of young adults (mean age = 19.91 years, SD = 1.65). Results Exploratory factor analysis revealed a four-factor structure that included reckless driving behaviors, negative driving-related emotions, aggressive driving behaviors in response to perceived transgressions from other drivers, and perceived aggressive driving behaviors from other drivers. Aggressive driving behaviors not performed in response to other drivers loaded onto both aggressive driving-related factors. Conclusions The factor structure derived in the present study suggests considerable overlap in the content across commonly administered driving self-reports, while also suggesting four distinct dimensions of self-reported driving emotions and behaviors. Whereas some of these dimensions have been explored considerably in the literature (e.g., negative emotions), others deserve further exploration (e.g., perceived aggressive driving behaviors from other drivers). Implications for clinical practice and future investigations are discussed. [ABSTRACT FROM AUTHOR]

Abstract It has been argued that risk and performance-based approaches to licensing would be appropriate for Small Modular Reactors (SMRs) because their risk profiles differ from large-scale reactors. This is based on several factors including their limited electrical capacity of 300 MW, the below grade reactor vessel, and passive safety features. One design feature that can significantly reduce accident severity is the larger lateral surface area-to-volume (A/V) ratio of SMRs. Following a nuclear accident, this larger A/V ratio can increase the removal of radioactive particles due to natural phenomena compared to large light water reactors (LWRs). To quantify the improvements in safety, this work estimates the airborne radioactivity within containment and environmental dose exposure in a post-accident scenario for an advanced Generation III+ LWR (AP1000), a representative Generation II LWR (Surry), and an SMR. On average, the AP1000, Surry, and SMR produces 139, 153, and 104 curies/ft3 (182, 200, and 136 terabecquerels/m3) 75 min after a Loss-of-coolant-accident (LOCA). Using Monte Carlo simulations, the SMR produces less radioactivity per volume in containment than the AP1000 and Surry 84% and 96% of the time, respectively. On average, the AP1000, Surry, and SMR produces 84, 106, and 7 thousand curies/ MW th (3.1, 3.9, and 2.5 petabecquerels/ MW th ) 75 min after a LOCA. The larger A/V ratio of the SMR plays a substantial role in reducing the radioactivity. While it is expected that the SMR would have a lower levels of radioactivity compared to the AP1000 and Surry, the SMR produces less radioactivity after normalizing by thermal reactor power and containment volume. With respect to environmental dose exposure, the US Environmental Protection Agency 1–5 rem (0.01–0.05 sieverts) Protective Action Guide (PAG) limits for whole body exposure is not exceeded at the 10-mile (16.1-km) EPZ using the mean estimates for the AP1000 and Surry. The iPWR does not exceed the 1 rem (0.01 sieverts) lower PAG limit for whole body exposure at the 5-mile (8-km) EPZ using the mean value. These findings can be used in conjunction with the improved analytical methods, found in the SOARCA study, to provide accurate and realistic estimates for exposure. This will help create a pathway to develop a regulatory basis for technology-neutral, risk-based approach to EPZs for iPWRs. Highlights • New decontamination factors are used to estimate dose exposure post-LOCA for iPWRs. • Lower dose exposure rates are due to the higher sa/vol ratios and convective flows. • The AP1000, Surry, and iPWR yields 139, 153, and 104 ci/ft3 75 min post-LOCA. • The 5 rem PAG thyroid limit is never exceeded for the iPWR. • As much as $50 million in EPZ costs can be saved by reducing the EPZ to 5 miles. [ABSTRACT FROM AUTHOR]

Abstract This study was designed to investigate the relative accident risk of different road weather conditions and combinations of conditions. The study applied a recently developed method which is based on the notion of Palm probability, originating in the theory of random point processes, which in this case corresponds to picking a random vehicle from the traffic. The method consists of calculating the Palm distribution of different conditions and comparing it with the distribution of the same conditions as seen by the accidents. The condition affects the accident risk statistically, when these two distributions differ. The study included all police reported single- and multi-vehicle accidents (N = 10,646) occurring on 43 main roads in Finland during the years 2014–2016. A major contribution of this paper is the demonstration of the method on national scale by using estimated hourly traffic volumes on road segments instead of measured ones, which would have been available for few roads only. Accident risks are commonly examined in relation to traffic volume. This paper includes the speed of the traffic and thus, the paper examines accident risk in relation to the time spent on the road segment in certain conditions. The hour-level weather and road condition data per segment were obtained from nearby road weather stations. The relative accident risks were increased for poor road weather conditions; however, they were highest for icy rain and slippery and very slippery road conditions. When comparing the relative accident risk based on road type, the results showed that the risk in poor weather and road conditions was higher on motorways compared to two-lane and multiple-lane roads even though the overall risk was lower on motorways. Furthermore, the corresponding relative accident risks were generally higher for single-vehicle accidents compared to multi-vehicle accidents. [ABSTRACT FROM AUTHOR]

Objective: The present study aims to quantify the effects of texting and driver behavior on the accident risk associated with a sudden event. Further, the study attempts to compare the effects of driving behavior of inexperienced young and professional drivers on risk during predetection and postdetection phases of the event.Methods: Forty-nine drivers from 2 categories-inexperienced young drivers and experienced professional drivers-took part in simulated experiments. The participants drove in a free-flow road environment under 3 driving conditions: no distraction (baseline) and writing short and long texts while driving. The participants were exposed to a sudden hazardous event during each drive. Accident probability during the sudden event was modeled with a generalized linear mixed model (with a logit link function).Results: As expected, both texting tasks increased accident risk, and the risk was much higher for inexperienced young drivers than for professional drivers. Time lapsed in reducing speed increased the odds for accident risk significantly. A comparative analysis of the driver categories showed that impairment in driving behavior due to the texting tasks was similar for both groups during the predetection phase. However, the risk associated with the texting tasks was higher for young drivers during the postdetection phase. A possible reason could be that young drivers had 65% and 75% higher approach speeds (than the professional drivers) during the short and long text tasks, respectively.Conclusions: The results provide statistical evidence that increased speed is expressed as increased risk-taking behavior among young drivers, which subsequently is the main reason for their higher accident risk during texting tasks. Moreover, the results confirm that professional drivers are not able to mitigate the increased accident risk associated with texting tasks due to late detection of the event during the tasks. [ABSTRACT FROM AUTHOR]

The use of containers in the world is increasing every year in line with international trade flows. In very complex container terminal operations, the risk of work accidents is inevitable and can happen at any time. Therefore, this paper aimed to identify accidents and potential risks occurring in the container terminals. For the case study, the analysis was used the data of accidents during five years in one of the major container terminals in Indonesia. Risk assessment is carried out using the risk matrix method to get the level of risk. The risk that has the highest level is analyzed by using the Fault Tree Analysis method. From the results of the risk assessment shows the container fell to the berth when loading and unloading have the highest risk value. While the results of the Fault Tree Analysis show that traffic accidents are the biggest potential risk, which is 41.8% compared to other accidents. Moreover, human factors especially due to the negligence in operating vehicles or equipment as well as the damage of equipment were the highest common causes of accidents in the container terminal. Based on these results the contribution offered is the risk control options for terminal operators to reduce the possibility of safety failure in the container terminal.

Competing Interests: JW is founder and president of Novometrix Research Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

New ministerial decree restricts driving motorized vehicles for patients with Alzheimer's disease and related disorders. Reisberg stage 3, threshold used to contraindicate driving, appears to correspond to a mild stage of major neurocognitive impairment. A single scale gives an idea of the level of risk but does not provide a holistic assessment. The aim of this consensus is to put forward recommendations from several French learned societies for individualized cognitive assessments to minimize the risks associated with driving and its cessation. Fitness to drive should be raised at the earliest stages of the diagnostic process, and regularly throughout the follow-up. Consult a registered doctor is recommended to all patients wishing to continue driving. All documents must be given to the patient only. An alternative must always be offered to patients who are recommended a modal shift.

Interaction between adverse weather conditions and motor vehicle crashes is an important topic for traffic engineers and hydrometeorologists. With the recent availability of high resolution precipitation products (hourly, 4 × 4 km), it is possible to evaluate crash risk during rainfall events more accurately. Texas, the second largest state in the U.S., with a relatively high population density in its eastern part that receives significant rainfall from tropical events, experiences many hazardous traffic conditions every year. This study investigates temporal and spatial variability of the Relative Accident Risk (RAR) due to rainy conditions across Texas during the year 2015 using a Crash-Based Matched Pairs Analysis (CB-MPA) approach for every 4 × 4 km grid using an hourly time scale. The overall findings show that rainfall increases crash risk across the state by about 57%, while seasonal-based analysis confirms the role of precipitation patterns on crash rates. Although eastern and central counties (wetter and more urbanized) have remarkably higher rates of crash occurrence, the western counties (mainly rural and dry) show higher RAR values. Moreover, higher rainfall intensity can increase RAR up to three-fold while directly having an adverse effect on crash injury type. There is a relatively high correlation between rainfall intensity and RAR values (R 2  = 0.76). The analysis also shows higher RAR values on high-speed interstate highways and tollways compared to urban local streets. RAR values also vary according to the gender and age of drivers. The study findings shed light on future paths toward more detailed applications of high-resolution environmental data in crash risk analysis. [ABSTRACT FROM AUTHOR]

Vehicle routing is a daily activity to move people and goods from one point to another. Routing is subject to constraints, such as time, distance, and out-of-pocket cost. Traditionally, routing decisions were based mainly on efficiency considerations (i.e., finding shortest path in terms of distance or travel time). With rising global interest in traffic safety and green transportation, there is a need to consider other factors such as risk to humans and environment. In this study, a methodology was developed to provide a comprehensive, risk-based vehicle routing approach to account for various objectives (or risks), including: travel time, travel distance, travel cost, accident risk, air emissions risk, and noise risk. The methodology involves three major steps: first, estimation of the various risks for individual road links; second, integration of the individual risks into a single comprehensive risk measure using the Analytical Hierarchy Process (AHP); and finally, finding the preferred (i.e., least risky) route based on risk. The framework is implemented inside a Geographic Information System (GIS) environment. The proposed methodology was applied to a real-world setting: Sharjah City, United Arab Emirates. Outcomes are charted in the form of least-risky routes for a selected origin-destination pair taking into consideration each objective individually or in combinations, in addition to comprehensive risk. The proposed methodology provides a way to integrate environmental and safety related measures into vehicle routing, which is a step towards making the transportation system safer and greener. [ABSTRACT FROM AUTHOR]

Car insurance is quickly becoming a big data industry, with usage-based insurance (UBI) poised to potentially change the business of insurance. Telematics data, which are transmitted from wireless devices in car, are widely used in UBI to obtain individual-level travel and driving characteristics. While most existing studies have introduced telematics data into car insurance pricing, the telematics-related characteristics are directly obtained from the raw data. In this study, we propose to quantify drivers’ familiarity with their driving routes and develop models to quantify drivers’ accident risks using the telematics data. In addition, we build a latent class model to study the heterogeneity in travel and driving styles based on the telematics data, which has not been investigated in literature. Our main results include: (1) the improvement to the model fit is statistically significant by adding telematics-related characteristics; (2) drivers’ familiarity with their driving trips is critical to identify high risk drivers, and the relationship between drivers’ familiarity and accident risks is non-linear; (3) the drivers can be classified into two classes, where the first class is the low risk class with 0.54% of its drivers reporting accidents, and the second class is the high risk class with 20.66% of its drivers reporting accidents; and (4) for the low risk class, drivers with high probability of reporting accidents can be identified by travel-behavior-related characteristics, while for the high risk class, they can be identified by driving-behavior-related characteristics. The driver's familiarity will affect the probability of reporting accidents for both classes. [ABSTRACT FROM AUTHOR]

World-wide, alcohol is still a major cause of traffic accidents. The dose-related accident risk function has been found in a large number of risk studies. A plethora of laboratory studies has examined the effect of alcohol with regard to different information processing capabilities of drivers. Summarizing the results, alcohol effects occur at lower blood alcohol concentrations (BAC) the more complex the tasks get. However, in contrast, typical alcohol-related crashes are frequently single vehicle crashes but not so often crashes in complex situations like at intersections. It may be that the subjective assessment of the traffic situation and the adaptation of behavior under the influence of alcohol plays a major role in accident causation. In order to examine this hypothesis, two driving simulator studies were conducted at a target BAC of 0.5 g/l comparing two (alcohol vs. placebo; n = 48, Experiment 1) and three (sober, placebo and alcohol; n = 63, Experiment 2) groups of subjects in two critical scenarios. The first scenario was a seemingly easy traffic situation and was supposed to lead to a relaxed driving behavior under alcohol. The second scenario involved a complex intersection situation where especially drivers under the influence of alcohol should try to concentrate and compensate their experienced alcohol effects. In all scenarios, a critical object appeared suddenly and the driver had to react fast in order to prevent a (simulated) accident. Overall, the results support the hypothesis. Accidents were more frequent for alcohol drivers as compared to placebo/sober drivers in the easy scenario, but not the complex one. The initial speed of the driver when entering the scenario seems to play a major role in the accident causation. Drivers under the influence of alcohol seem to lower their speed in complex scenarios, possibly to thus counteract alcohol effects. In seemingly easy scenarios this does not seem necessary for them and the arousing effect of alcohol may contribute to driving faster. The results are summarized in a model of alcohol-related crashes. Further in-depth analyses of real crashes would be an interesting next step to further corroborate this model. [ABSTRACT FROM AUTHOR]

A comprehensive quality assessment method for civil engineering is described. The comprehensive assessment includes the indicators of the quality system level, absence of defects, stability of engineering procedures, and construction safety indexes. The quality system is considered broadly in terms of the project organization potential, suppliers of building materials and the construction company. Calculation formulas for statistical values considering the parameters distribution type are given. The estimated values of the indexes for two stages of control (with and without the use of process technology accuracy regulation) are proposed. The analysis of construction quality by the example of solid buildings construction is carried out. The impact of different defects on construction safety index is studied. The defects root causes are revealed. [ABSTRACT FROM AUTHOR]

• We examined the accuracy of on-road self-assessments in older drivers. • 75% of older drivers showed an accurate on-road self-assessment. • 25% of older drivers overestimated their on-road driving performance. • Overestimators showed an increased prospective accident risk. • Overestimators appear to represent a risk group. Older drivers often show less precise self-ratings with a tendency to overestimate themselves. It is unclear, however, how overestimators differ from underestimators or drivers with adequate self-ratings. 59 healthy older drivers participated in this on-road study. Besides standardized on-road driving assessment, the study protocol included the collection of neuropsychological and driving-related data as well as different self-ratings. Statistical analyses involved correlations between different subjective and objective ratings as well as statistical comparisons between drivers who overestimated and drivers who adequately rated their on-road driving performance (no drivers underestimated their performance). Despite positive correlations between different self- and expert ratings, our results revealed that 25 % of the participants overestimated their on-road driving skills. Among other things, overestimators showed poorer on-road driving performances, more prospective near and minor at-fault accidents, poorer cognitive performances in specific driving-related domains and reduced annual mileage. Our results suggest that older drivers who overestimate their driving skills show poorer performances within a broad range of skills that directly reflect or are closely related to driving safety. Against the background that an adequate self-assessment is required by German traffic regulations, our findings suggest that overestimators represent a risk group among the population of older drivers. [ABSTRACT FROM AUTHOR]