Exploring the challenges faced by Dutch truck drivers in the era of technological advancement.

Introduction: Despite their important role in the economy, truck drivers face several challenges, including adapting to advancing technology. The current study investigated the occupational experiences of Dutch truck drivers to detect common patterns. Methods: A questionnaire was distributed to professional drivers in order to collect data on public image, traffic safety, work pressure, transport crime, driver shortage, and sector improvements. Results: The findings based on 3,708 respondents revealed a general dissatisfaction with the image of the industry and reluctance to recommend the profession. A factor analysis of the questionnaire items identified two primary factors: 'Work Pressure', more common among national drivers, and 'Safety & Security Concerns', more common among international drivers. A ChatGPT-assisted analysis of textbox comments indicated that vehicle technology received mixed feedback, with praise for safety and fuel-efficiency improvements, but concerns about reliability and intrusiveness. Discussion: In conclusion, Dutch professional truck drivers indicate a need for industry improvements. While the work pressure for truck drivers in general may not be high relative to certain other occupational groups, truck drivers appear to face a deficit of support and respect.

The development of a road safety policy index and its application in evaluating the effects of road safety policy.

The paper presents an exploratory study of a road safety policy index developed for Norway. The index consists of ten road safety measures for which data on their use from 1980 to 2021 are available. The ten measures were combined into an index which had an initial value of 50 in 1980 and increased to a value of 185 in 2021. To assess the application of the index in evaluating the effects of road safety policy, negative binomial regression models and multivariate time series models were developed for traffic fatalities, fatalities and serious injuries, and all injuries. The coefficient for the policy index was negative, indicating the road safety policy has contributed to reducing the number of fatalities and injuries. The size of this contribution can be estimated by means of at least three estimators that do not always produce identical values. There is little doubt about the sign of the relationship: a stronger road safety policy (as indicated by index values) is associated with a larger decline in fatalities and injuries. A precise quantification is, however, not possible. Different estimators of effect, all of which can be regarded as plausible, yield different results.

Frailty and poor physical functioning as risk factors for driving cessation.

Introduction: Frailty and low physical performance are modifiable factors and, therefore, targets for interventions aimed at delaying driving cessation (DC). The objective was to determine the impact of frailty and physical performance on DC. Methods: Multisite prospective cohort of older drivers. The key inclusion criteria are as follows: active driver age 65-79 years, possessing a valid driver's license, without significant cognitive impairment, and driving a 1996 car or a newer model car. Of the 2,990 enrolled participants, 2,986 (99.9%) had at least one frailty or Short Physical Performance Battery (SPPB) measure and were included in this study. In total, 42% of participants were aged 65-69 years, 86% were non-Hispanic white, 53% were female, 63% were married, and 41% had a high degree of education. The Fried Frailty Phenotype and the Expanded Short Physical Performance Battery (SPPB) from the National Health and Aging Trends Study were utilized. At each annual visit, DC was assessed by the participant notifying the study team or self-reporting after no driving activity for at least 30 days, verified via GPS. Cox proportional hazard models, including time-varying covariates, were used to examine the impact of the SPPB and frailty scores on time to DC. This assessment included examining interactions by sex. Results: Seventy-three participants (2.4%) stopped driving by the end of year 5. Among women with a fair SPPB score, the adjusted hazard ratio (HR) of DC was 0.26 (95% confidence interval (CI) 0.10-0.65) compared to those with a poor SPPB score. For those with a good SPPB score, the adjusted HR of DC had a p-value of <0.001. Among men with a fair SPPB score, the adjusted hazard ratio (HR) of DC was 0.45 (95% CI 0.25-0.81) compared to those with a poor SPPB score. For men with a good SPPB score, the adjusted HR of DC was 0.19 (95% CI 0.10-0.36). Sex was not an effect modifier between frailty and DC. For those who were categorized into pre-frail or frail, the adjusted ratio of HR to DC was 6.1 (95% CI 2.7-13.8) compared to those who were not frail. Conclusion and relevance: Frailty and poor physical functioning are major risk factors for driving cessation. Staying physically active may help older adults to extend their driving life expectancy and mobility.

Analyzing the Prevalence of and Factors Associated with Road Traffic Crashes (RTCs) among Motorcyclists in Bangladesh.

Methods: A cross-sectional survey was conducted using a structured questionnaire involving 402 motorcyclists from four major southeastern towns, comprising 350 (86.07%) males and 52 (12.93%) females. The chi-square test was applied in bivariate analysis, and binary multivariable logistic regression was performed to determine the risk factors of road traffic crashes. Results: This study's findings revealed that the overall reported prevalence of road traffic crashes involving motorcycle drivers over one year was 68.66%. Multivariable logistic regression analysis revealed several factors that significantly impacted road traffic crashes. These factors included driving without a valid driving license, the young age (<20) of motorcyclists, driving in rainy weather, exceeding the speed limit, per-week working hours, smoking status, motorcycle ownership, the brand of motorcycle, and not wearing a helmet while driving. Conclusion: The study findings highlight the need for improving motorcycle safety by implementing measures such as imposing per-week work hour limits for riders, enforcing traffic regulations, and promoting helmet use among motorcycle drivers. The results of this study draw attention to the Bangladesh Road Transport Authority (BRTA) and motorcycle drivers in the country to decrease motorcycle crashes and the severity of injuries by implementing efficient guidelines and strategies for driving motorcycles. The findings of this study can assist policymakers and concerned authorities in taking the essential steps to lessen road traffic crashes among motorcyclists in Bangladesh.

Assessing the predictability of surrogate safety measures as crash precursors based on vehicle trajectory data prior to crashes.

This study aims to investigate the predictability of surrogate safety measures (SSMs) for real-time crash risk prediction. We conducted a year-long drone video collection on a busy freeway in Nanjing, China, and collected 20 rear-end crashes. The predictability of SSMs was defined as the probability of crash occurrence when using SSMs as precursors to crashes. Ridge regression models were established to explore contributing factors to the predictability of SSMs. Four commonly used SSMs were tested in this study. It was found that modified time-to-collision (MTTC) outperformed other SSMs when the early warning capability was set at a minimum of 1 s. We further investigated the cost and benefit of SSMs in safety interventions by evaluating the number of necessary predictions for successful crash prediction and the proportion of crashes that can be predicted accurately. The result demonstrated these SSMs were most efficient in proactive safety management systems with an early warning capability of 1 s. In this case, 308, 131, 281, and 327,661 predictions needed to be made before a crash could be successfully predicted by TTC, MTTC, DRAC, and PICUD, respectively, achieving 75 %, 85 %, 35 %, and 100 % successful crash identifications. The ridge regression results indicated that the predefined threshold had the greatest impact on the predictability of all tested SSMs.

Investigating built environment and traffic flow impact on crash frequency in urban road networks.

While numerous studies have examined the factors that influence crash occurrence, there remains a gap in understanding the intricate relationship between built environment, traffic flow, and crash occurrences across different spatial units. This study explores how built environment attributes, and dynamic traffic flow characteristics affect crash frequency by focusing on proposed traffic density-based zones (TDZs). Utilizing a comprehensive dataset from Greater Melbourne, Australia, this research emphasizes on the dynamic traffic flow variables and insights from the Macroscopic Fundamental Diagram model, considering parameters such as shockwave velocity and congestion index. The association between the potential influencing factors and crash frequency is examined using a random parameter negative binomial regression model. Results indicate that the data segmentation based on TDZs is instrumental in establishing a more refined crash model compared to traditional planning-based zones, as demonstrated by improved goodness-of-fit measures. Factors including density (e.g., employment density), network design (e.g., road density and highway density), land use diversity (e.g., job-housing balance and land use mixture), and public transit accessibility (e.g., bus route density) are significantly associated with crash occurrence. Furthermore, the unobserved heterogeneity effects of the shockwave velocity and congestion index on crashes are revealed. The study highlights the significance of incorporating dynamic traffic flow variables in understanding crash frequency variations across different spatial units. These findings can inform optimal real-time traffic monitoring, environmental design, and road safety management strategies to mitigate crash risks.

How would autonomous vehicles behave in real-world crash scenarios?

Autonomous Vehicles (AVs) have the potential to revolutionize transportation systems by enhancing traffic safety. Safety testing is undoubtedly a critical step for enabling large-scale deployment of AVs. High-risk scenarios are particularly important as they pose significant challenges and provide valuable insights into the driving capabilities of AVs. This study presents a novel approach to assess the safety of AVs using in-depth crash data, with a particular focus on real-world crash scenarios. First, based on the high-definition video recording of the whole process prior to the crash occurrences, 453 real-world crashes involving 596 passenger cars from China In-depth Mobility Safety Study-Traffic Accident (CIMSS-TA) database were reconstructed. Pertinent static and dynamic elements needed for the construction of the testing scenarios were extracted. Subsequently, 596 testing scenarios were created via each passenger car's perspective within the simulation platform. Following this, each of the crash-involved passenger cars was replaced with Baidu Apollo, a famous automated driving system (ADS), for counterfactual simulation. Lastly, the safety performance of the AV was assessed using the simulation results. A logit model was utilized to identify the fifteen crucial scenario elements that have significant impacts on the test results. The findings demonstrated that the AV could avoid 363 real-world crashes, accounting for approximately 60.91% of the total, and effectively mitigated injuries in the remaining 233 unavoidable scenarios compared to a human driver. Moreover, the AV maintain a smoother speed in most of the scenarios. The common feature of these unavoidable scenarios is that the AV is in a passive state, and the crashes are not caused by the AV violating traffic rules, but rather caused by abnormal behavior exhibited by the human drivers. Additionally, seven specific scenarios have been identified wherein AVs are unable to avoid a crash. These findings demonstrate that, compared to human drivers, AVs can avoid crashes that are difficult for humans to avoid, thereby enhancing traffic safety.

State Department of Motor Vehicles Reporting Mandates of Dementia Diagnoses and Dementia Underdiagnosis.

Importance: With older drivers representing the fastest growing segment of the driver population and dementia prevalence increasing with age, policymakers face the challenge of balancing road safety and mobility of older adults. In states that require reporting a dementia diagnosis to the Department of Motor Vehicles (DMV), individuals with dementia may be reluctant to disclose symptoms of cognitive decline, and clinicians may be reluctant to probe for those symptoms, which may be associated with missed or delayed diagnoses. Objective: To assess whether DMV reporting policies for drivers with dementia are associated with primary care clinicians' underdiagnosing dementia. Design, Setting, and Participants: This cross-sectional study used data from the 100% Medicare fee-for-service program and the Medicare Advantage plans from 2017 to 2019 on 223 036 primary care clinicians with at least 25 Medicare patients. Statistical analysis was performed from July to October 2023. Exposures: State DMV reporting policies for drivers with dementia. Main Outcomes and Measures: The main outcome was a binary variable indicating whether the clinician underdiagnosed dementia or not. Each clinician's expected number of dementia cases was estimated using a predictive model based on patient characteristics. Comparing the estimation with observed dementia diagnoses identified clinicians who underdiagnosed dementia vs those who did not, after accounting for sampling errors. Results: Four states have clinician reporting mandates, 14 have mandates requiring drivers to self-report dementia diagnoses, and 32 states and the District of Columbia do not have explicit requirements. Among primary care clinicians in states with clinician reporting mandates (n = 35 620), 51.4% were female, 91.9% worked in a metropolitan area, and 19.9% of the patient panel were beneficiaries dually eligible for Medicare and Medicaid. Among primary care clinicians in states with patient self-reporting mandates (n = 57 548), 55.7% were female, 83.1% worked in a metropolitan area, and 15.4% of the patient panel were dually eligible for Medicare and Medicaid. Among clinicians in states without mandates, 55.7% were female, 83.0% worked in a metropolitan area, and 14.6% of the patient panel were dually eligible for Medicare and Medicaid. Clinicians in states with clinician reporting mandates had an adjusted 12.4% (95% CI, 10.5%-14.2%) probability of underdiagnosing dementia compared with 7.8% (95% CI, 6.9%-8.7%) in states with self-reporting and 7.7% (95% CI, 6.9%-8.4%) in states with no mandates, an approximately 4-percentage point difference (P < .001). Conclusions and Relevance: Results of this cross-sectional study of primary care clinicians suggest that mandatory DMV policies for clinicians to report patients with dementia may be associated with a higher risk of missed or delayed dementia diagnoses. Future research is needed to better understand the unintended consequences and the risk-benefit tradeoffs of these policies.

Modeling temporal correlation and heterogeneity in real-time conflict rates using Bayesian Tobit models for signalized intersections.

The use of real-time traffic conflicts for safety studies provide more insight into how important dynamic signal cycle-related characteristics can affect intersection safety. However, such short-time window for data collection raises a critical issue that the observed conflicts are temporally correlated. As well, there is likely unobserved heterogeneity across different sites that exist in conflict data. The objective of this study is to develop real-time traffic conflict rates models simultaneously accommodating temporal correlation and unobserved heterogeneity across observations. Signal cycle level traffic data, including traffic conflicts, traffic and shock wave characteristics, collected from six signalized intersections were used. Three types of Tobit models: conventional Tobit model, temporal Tobit (T-Tobit) model, and temporal grouped random parameters (TGRP-Tobit) model were developed under full Bayesian framework. The results show that significant temporal correlations are found in T-Tobit models and TGRP-Tobit models, and the inclusion of temporal correlation considerably improves the goodness-of-fit of these Tobit models. The TGRP-Tobit models perform best with the lowest Deviance Information Criteria (DIC), indicating that accounting for the unobserved heterogeneity can further improve the model fit. The parameter estimates show that real-time traffic conflict rates are significantly associated with traffic volume, shock wave area, shock wave speed, queue length, and platoon ratio.

Getting Rides From Others As a Coping Mechanism in the Transition to Non-Driving.

OBJECTIVES: To characterize the effect of the actual and potential ability to get rides from others on older adults' driving reduction at 3-year follow-up in the United States. METHODS: We analyzed National Health and Aging Trends Study data from community-dwelling drivers in 2015 (unweighted n = 5,102). We used weighted logistic regression models to estimate whether getting rides from others in 2015 was associated with older adults increasing the number of driving behaviors they avoided, decreasing the frequency with which they drove, or not driving at 3-year follow-up after adjusting for biopsychosocial variables. We also measured presence of social network members living nearby including household and non-household members and estimated associated odds of driving reduction at 3-year follow-up. RESULTS: Older adults who got rides from others in 2015 had greater odds of reporting no longer driving at 3-year follow-up compared to those who did not get rides (adjusted odds ratio [aOR] = 1.53, 95% confidence interval [CI]: 1.11-2.11). We found no statistically significant association between older adults living with others or having more nearby confidantes outside their household and their odds of reducing driving at 3-year follow-up. DISCUSSION: These findings suggest that getting rides from others plays an important role in the transition to non-driving for older adults. Future research should examine whether other aspects of social networks (e.g., type, quality, and closer proximity) might also be key modifiable coping factors for older adults transitioning to non-driving.

Prevalence of vision zero action plans or strategies: USA, 2021.

BACKGROUND: Vision Zero is a strategy to eliminate traffic fatalities and to promote equitable mobility options for all road users. Using a nationally representative survey, we aimed to estimate the prevalence of Vision Zero action plans or strategies in the USA. METHODS: Municipal officials were surveyed in 2021. In this cross-sectional study, we calculated the prevalence of Vision Zero plans or strategies and compared municipalities with adjusted prevalence ratios (PR) to account for region and sociodemographic characteristics. RESULTS: Among 1955 municipalities participating in the survey (question-specific response rate: 44.3%), the prevalence of a Vision Zero action plan or strategy was 7.7%; 70.5% responded no and 21.8% don't know. Prevalence was 4.8% in small municipalities (1000-2499 residents), 20.3% in medium-large municipalities (50 000-124 999 residents; PR=4.1), and 37.8% in large municipalities (≥125 000 residents; PR=7.6). CONCLUSION: The prevalence of Vision Zero plans and strategies across the USA is low. Additional adoption of Vision Zero plans and strategies could help address traffic fatalities.

Prevalence of lower urinary tract symptoms in taxi drivers: a cross-sectional web-based survey.

PURPOSE: Aim of the study was to evaluate the prevalence of LUTS in taxi drivers. METHODS: Between February 24th 2021 and March 26th 2021 a web based survey was administered to Taxi drivers in the city of Florence. Taxi drivers were evaluated with baseline characteristics such as: age, BMI, smoking, career length, comorbidities, and treatment. LUTS were evaluated using the international prostate symptom score (IPSS) and the overactive bladder (OAB) score. As well sexual function was evaluated using the international index erectile function (IIEF) and female sexual function index (FSFI) questionnaires. Risk factors for LUTS were evaluated using regression analysis. RESULTS: The overall response rate was 64.6% (537/830 taxi drivers filled the questionnaires). Among them, 449 (83.6%) were men and 88 (16.4%) females. Overall, median IPSS was 5 (2/9) and median OAB score was 10 (7/14). On multivariate binary regression analysis age > 50 (OR:1.60; p < 0,05), Smoking (OR:1.57; p < 0,05), chronic treatment (OR:1.57; p < 0,05), recurrent cystitis (OR: 2.66; p < 0,05) and chronic pelvic pain (OR:4.94; p < 0,05) were independent risk factors for moderate/severe LUTS. On multivariate binary logistic regression analysis, risk factors for erectile dysfunction were age older than 50 years (OR = 3.64; p < 0.05) and urinary incontinence (OR = 5.53; p = 0.005). CONCLUSIONS: According to our web-based survey, Taxi drivers in the metropolitan city of Florence had non-negligible symptomatic LUTS and even sexual dysfunction. Our data suggest as LUTS are particular influenced by several life-style and behavioural factors as type and duration of work.

Overview of road traffic injuries among migrant workers in Guangzhou, China, from 2017 to 2021.

INTRODUCTION: There are many migrant workers in China's first-tier cities, but little is known about road safety. This paper systematically analysed road traffic injuries and risk factors among migrant workers in Guangzhou, China. METHODS: Road traffic crash data from 2017 to 2021 were obtained from the Guangzhou Public Security Traffic Management Integrated System. We plotted the crash network of road users in road traffic crashes and used logistic regression to analyse the risk factors for migrant workers of motorcycle and four-wheeled vehicle crashes. Moreover, the roles of migrant workers and control individuals as perpetrators in road traffic crashes were also analysed. RESULTS: Between 2017 and 2021, 76% of road traffic injuries were migrant workers in Guangzhou. Migrant workers who were motorcyclist drivers most commonly experienced road traffic injuries. Crashes between motorcyclists and car occupants were the most common. The illegal behaviours of migrant worker motorcyclists were closely related to casualties, with driving without a licence only and driving without a licence and drunk driving accounting for the greatest number. Migrant workers were responsible for many injuries of other road users. Motorcycle drivers have a higher proportion of drunk driving. DISCUSSION: Migrant workers play an important role in road traffic safety. They were both the leading source of road traffic injuries and the main perpetrators of road traffic crashes. Measures such as strict requirements for migrant workers to drive motorcycles with licences, prohibit drunk driving, greater publicity of road safety regulations, and combining compulsory education with punishment for illegal behaviours.

Driving status and attitudes of patients with epilepsy holding a driving license in eastern China.

PURPOSE: Patients with epilepsy (PWE) remain completely and permanently banned from driving under the latest changes to China's laws. The twoaims of this study were, firstly, to evaluate the driving status of PWE with a driving license and the determinants of them continuing to drive; secondly, to investigate awareness and perceptions of epilepsy driving restrictions among PWE and the general population. METHODS: Patients with epilepsy with a driver's license who attended the Fourth Affiliated Hospital and the Second Affiliated Hospital of Zhejiang University for treatment of their condition were invited to participate in a questionnaire survey between June 2021 and June 2022. During the same period, age-matched people with driver's licenses without epilepsy living in the cities of Hangzhou and Yiwu, Zhejiang province were invited to participate in the questionnaire study. RESULTS: A total of 291 PWE with a driver's license and 289 age-matcheddrivers among the general public participated in the survey. Of the sample, 41.6% of PWE and 26.0% of general drivers stated that they were aware of legal driving restrictions for PWE in China. In the past year, 54% of PWE had driven and 42.5% drove a vehicle daily. Logistic regression revealed that male sex (95% confidence interval [CI]: 1.36-3.61, P = 0.001), age (95% CI: 1.12-3.27, P ≤ 0.036), and the number of antiseizure medications taken (95% CI: 0.24-0.25, P ≤ 0.001) were independently associated with illegally driving with epilepsy. In terms of legalissues, 71.1% of PWE did not support a lifetime ban on driving and 50.2% disagreedwith physician reporting of PWE to the traffic authorities. CONCLUSION: Illegal driving is highly prevalent among PWE who hold a driving license, and male gender, age, and number of ASMs had an independent association with illegal driving in patients with epilepsy. There are highly varying opinions on the current driving laws with respect to PWE. Detailed national standards for medical fitness for driving that are easy to implement and enforce are urgently required for China.

A Systematic Review of the Risks of Motor Vehicle Crashes Associated with Psychiatric Disorders.

OBJECTIVE: Psychiatric disorders and their treatments have the potential to adversely impact driving skills. However, it is unclear to what extent this poses a public health risk by increasing the risk of motor vehicle crashes (MVCs). The aim of this systematic review was to synthesize and critically appraise evidence on the risk of MVC for drivers with psychiatric disorders. METHOD: We conducted a systematic review of the MVC risk associated with psychiatric disorders using seven databases in November 2019. Two reviewers examined each study and extracted data. The National Heart, Lung, and Blood Institute Quality Assessment tools were used to assess each study's quality of evidence. RESULTS: We identified 24 studies that met the inclusion criteria, including eight cohort, 10 case-control, and six cross-sectional designs. Quality assessment ratings were "Good" for four studies, "Fair" for 10, and "Poor" for 10. Self-report or questionnaires were used in place of objective measures of either MVC, psychiatric disorder, or both in 12 studies, and only seven adjusted for driving exposure. Fifteen studies reported an increased risk of MVC associated with psychiatric disorders, and nine did not. There was no category of disorder that was consistently associated with increased MVC risk. CONCLUSION: The available evidence is mixed, not of high quality, and does not support a blanket restriction on drivers with psychiatric disorder. An individualized approach, as recommended by international guidelines, should continue. Further research should include objective assessments of psychiatric disorders and MVC risk and adjust for driving exposure.

Effects of levels of automation and non-driving related tasks on driver performance and workload: A review of literature and meta-analysis.

This study assessed the effects of different levels of automation and non-driving related tasks (NDRT) on driver performance and workload. A systematic literature review was conducted in March 2021 using Compendex, Google Scholar, Web of Science, and Scopus databases. Forty-five studies met the inclusion criteria. A meta-analysis was conducted and Cochrane risk of bias tool and Cochran's Q test were used to assess risk of bias and homogeneity of the effect sizes respectively. Results suggested that drivers exhibited safer performance when dealing with critical incidents in manual driving than partially automated driving (PAD) and highly automated driving (HAD) conditions. However, drivers reported higher workload in the manual driving mode as compared to the HAD and PAD conditions. Haptic, auditory, and visual-auditory takeover request modalities are preferred over the visual-only modality to improve takeover time. Use of handheld NDRTs significantly degraded driver performance as compared to NDRTs performed on mounted devices.

Pandemic effects to autonomous vehicles test operations in California.

Companies developing automated driving system (ADS) technologies have spent heavily in recent years to conduct live testing of autonomous vehicles operating in real world environments to ensure their reliable and safe operations. However, the unexpected onset and ongoing resurgent effects of the Covid-19 pandemic starting in March 2020 has serve to halt, change, or delay the achievement of these new product development test objectives. This study draws on data obtained from the California automated vehicle test program to determine the extent that testing trends, test resumptions, and test environments have been affected by the pandemic. The importance of government policies to support and enable autonomous vehicles development during pandemic conditions is highlighted.

Helmet wearing behavior where people often ride motorcycle in Ethiopia: A cross-sectional study.

BACKGROUND: Road traffic accidents are a major global concern that affects all people regardless of their age, sex, wealth, and ethnicity. Injuries and deaths due to motorcycles are increasing, especially in developing countries. Wearing helmet is effective in reducing deaths and injuries caused by motorcycle accidents. OBJECTIVES: To assess the magnitude of helmet wearing behavior and its determinants among motorcycle riders in Sawula and Bulky towns, Gofa zone, Southern Ethiopia. METHODS: A community-based cross-sectional study was conducted from April, 15 to May 25, 2020, among 422 motorcycle drivers in Sawula and Bulky towns, where people often drive motorcycles. A stratified sampling technique was used to recruit sampled drivers in a face-to-face interview. Data were entered into EPI-data version 3.1 software and exported to SPSS version 23 software to manage analysis. Descriptive analyses such as frequency, percentage, mean and standard deviation were performed as necessary. Logistic regression models were fitted to identify the predictors of helmet wearing behavior. Adjusted odds ratios (AOR) with 95% confidence interval (CI) were used to determine the magnitude and strength of the association. RESULTS: A total of 403 motorcycle drivers participated in the study which gave a 95.5% response rate. Among 403 motorcycle riders, only 12.4% (95% CI, 9.2 to 15.6%) wore helmets while driving motorcycles. Having license [AOR 3.51(95% C.I 1.56-7.89)], driving distance >10Km [AOR 2.53(95% C.I 1.08-5.91)], History of exposure to accident [AOR 2.71(95% C.I 1.32-5.55)], driving experience of ≥10 years [AOR 2.98 (95% C.I 1.25-7.09)] and high perceived susceptibility to accident [AOR 3.10(95% C.I 1.29-7.46)] had statistically significant association with helmet wearing compared to their counterparts. CONCLUSIONS: This study found that helmet-wearing behavior was very low. Having a license, driving distance, exposure to accidents, driving experience, and accident risk perception were determinants of helmet wearing behavior. These determinants imply the need for interventions that focus on behavioral change communications such as awareness creation campaigns and mandatory helmet wearing laws.

Exploring the effect of glaucomatous visual field defects of current drivers on a neuropsychological test battery.

PURPOSE: This study explores the effect of glaucomatous visual field defects on several neuropsychological tests that are often used in research and in clinical settings. METHODS: Nineteen glaucoma patients and nineteen healthy participants, which are current drivers and older than 65 years old were included. All participants completed the Montreal Cognitive Assessment (MoCA), the Trail Making Test (TMT), the Benton Visual Retention Test (BVRT), the Snellgrove Maze Task (SMT) and the Digit Span Test (DST). All participants were also tested on contrast sensitivity and near and far visual acuity. For the glaucoma patients, visual field tests were downloaded from hospital servers. RESULTS: On the MoCA test, glaucoma patients scored lower than the healthy group, but not significantly. On the MoCA-Blind, the difference was statistically significant. Glaucoma patients also had lower percentile scores on the TMT, with a significant difference in the TMT-A, but this difference largely disappeared in the calculated TMT B-A index, which isolates the cognitive component. The BVRT and SMT showed no significant differences between both groups. In the only non-visual test, the DST, glaucoma patients outperformed the healthy group. Glaucoma severity did not influence results, except for the BVRT on which the moderate/severe group has better scores. CONCLUSION: Using visual items might lead to conclusions about cognition when it should be one about vision. Therefore, careful selection of tests is needed when examining cognition in glaucoma patients.

Freeway ramp metering based on PSO-PID control.

Ramp metering on freeway is one of the effective methods to alleviate traffic congestion. This paper advances the field of freeway ramp metering by introducing an application to the on-ramp, capitalizing on the macro traffic follow theory and improved the freeway traffic flow. The Particle Swarm Optimization (PSO) based on Proportional Integral Derivative (PID) controller is further developed to single ramp metering as well as to optimize the PID parameters. The approach is applied to a case study of the Changyi Freeway(G5513) in Hunan, China. The simulation is conducted by applying the actual profile traffic data to PID controller to adjust the entering traffic flow on the freeway on-ramp. The results show that the PSO-PID controller tends to converge in about 80 minutes, and the density tends to be stable after 240 iterations. The system has smaller oscillation, more accurate adjustment of ramp regulation rate, and more ideal expected traffic flow density. The traffic congestion on mainline is effectively slowed down, traffic efficiency is improved, and travel time and cost are reduced. The nonlinear processing ability of PSO-PID controller overcomes the defects of the traditional manual closing ramp, and can be successfully applied in the field of intelligent ramp metering.