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.

Associação entre horas de trabalho e de descanso e o uso de substâncias psicoativas entre motoristas profissionais de caminhão / Association between hours of work and rest and the use of psychoactive substances among professional truck drivers

OBJETIVO: Investigar a associação de horas diárias de trabalho e de descanso com o uso de substâncias psicoativas entre motoristas profissionais de caminhão. MÉTODOS: Estudo transversal conduzido em 2016 com 354 motoristas profissionais de caminhão que aguardavam a inspeção da mercadoria transportada em um Posto de Controle Fiscal localizado na cidade de Itatiaia, RJ, Brasil. A associação entre horas diárias de trabalho (exposição), horas diárias de descanso (exposição) e uso de substâncias psicoativas (desfecho) foi investigada por meio de modelos de regressão linear que estimaram coeficientes de regressão (ß) e respectivos erros-padrão, considerando p < 0,05. RESULTADOS: Mostraram-se positivas as associações entre horas diárias de trabalho e uso de anfetamina (ß = 0,91; erro-padrão = 0,19; p < 0,01) e de cocaína/crack (ß = 1,32; erro-padrão = 0,35; p < 0,01) e negativa a associação entre horas diárias de descanso e uso de anfetamina (ß = -0,43; erro-padrão = 0,09; p < 0,01). CONCLUSÃO: Horas diárias de trabalho e de descanso parecem ser determinantes do uso de anfetamina e de cocaína/ crack entre motoristas profissionais de caminhão.

OBJECTIVE: To investigate the association of hours of work and rest with use of psychoactive substances among professional truck drivers. METHODS: Cross-sectional study conducted in 2016 with 354 professional truck drivers waiting for the inspection of the goods transported at a Fiscal Control Post located in the city of Itatiaia, RJ, Brazil. The association between daily working hours (exposure), daily rest hours (exposure) and use of psychoactive substances (outcome) was investigated using linear regression models that estimated regression coefficients (ß) and respective standard error, considering p < 0.05. RESULTS: They were positive the associations between daily working hours and use of amphetamine (ß = 0.91; standard error = 0.19; p < 0.01) and cocaine/crack (ß = 1.32; standard error = 0.35; p < 0.01) and the association between daily rest hours and use of amphetamine (ß = - 0.43; standard error = 0.09; p < 0.01) was negative. CONCLUSION: Daily hours of work and rest seem to be determinants of the use of amphetamine and cocaine/crack among professional truck drivers.

Protocol for the conceptualization and evaluation of a screening-tool for fitness-to-drive assessment in older people with cognitive impairment.

INTRODUCTION: Due to aging and health status people may be subjected to a decrease of cognitive ability and subsequently also a decline of driving safety. On the other hand there is a lack of valid and economically applicable instruments to assess driving performance. OBJECTIVE: The study is designed to develop a valid screening-tool for fitness-to-drive assessment in older people with cognitive impairment externally validated on the basis of on-road driving performance. METHODS: In a single-centre, non-randomized cross-sectional trial cognitive functioning and on-road-driving-behavior of older drivers will be assessed. Forty participants with cognitive impairment of different etiology and 40 healthy controls will undergo an extensive neuropsychological assessment. Additionally, an on-road driving assessment for external validation of fitness to drive will be carried out. Primary outcome measures will be performance in attention, executive functions and visuospatial tasks that will be validated with respect to performance on the on-road-driving-test. Secondary outcome measures will be sociodemographic, clinical- and driving characteristics to systematically examine their influence on the prediction of driving behavior. DISCUSSION: In clinical practice counselling patients with respect to driving safety is of great relevance. Thus, having valid, reliable, time economical and easily interpretable screening-tools on hand to counsel patients is of great relevance for practitioners. ETHICS AND DISSEMINATION: Ethics approval was obtained from the Ethics Committee at the Ludwig-Maximilians-University Munich. The trial results will be disseminated through peer-reviewed publications and various conferences. TRIAL REGISTRATION: 18-640. Trial registration: German Clinical Trials Register. Registration number: DRKS00023549.

Effects of dietary patterns on driving behaviours among professional truck drivers: the mediating effect of fatigue.

OBJECTIVE: To explore the impact of the dietary patterns of truck drivers on their driving behaviours and the mediation effect of fatigue between these factors. METHODS: A sample of 389 male truck drivers from a transport company in Suzhou, China completed the Food Frequency Questionnaire (FFQ), the Multidimensional Fatigue Inventory (MFI), the Positive Driver Behaviours Scale (PDBS) and the Driver Behaviour Questionnaire (DBQ). The associations among dietary patterns, fatigue and driving behaviour were examined using pathway analysis. RESULTS: Four dietary patterns were identified based on principal component analysis: animal-derived foods, staple foods, snacks and vegetables. The pathway analysis showed that the vegetable-rich pattern had a direct positive impact on positive driving behaviour (ß=0.211, p<0.001); the animal-derived pattern had a direct positive impact on errors (ß=0.094, p<0.05) and ordinary violations (ß=0.071, p<0.05); the snacks pattern had a direct negative impact on positive driving behaviour (ß=-0.191, p<0.001); fatigue mediated the effect of dietary patterns on driving behaviours (p<0.001); and the staple foods had an indirect effect on driving behaviours. CONCLUSIONS: Overall, the driving behaviours of truck drivers are correlated with their dietary patterns. Drivers who preferred vegetables and staple foods had more positive driving behaviour, while the animal-derived food and snack patterns were related to dangerous driving behaviour. The experience of fatigue could explained the underlying mechanism between these factors.

COVID-19 suppression of human mobility releases mountain lions from a landscape of fear.

Humans have outsized effects on ecosystems, in part by initiating trophic cascades that impact all levels of the food chain.1,2 Theory suggests that disease outbreaks can reverse these impacts by modifying human behavior,3,4 but this has not yet been tested. The COVID-19 pandemic provided a natural experiment to test whether a virus could subordinate humans to an intermediate link in the trophic chain, releasing a top carnivore from a landscape of fear. Shelter-in-place orders in the Bay Area of California led to a 50% decline in human mobility, which resulted in a relaxation of mountain lion aversion to urban areas. Rapid changes in human mobility thus appear to act quickly on food web functions, suggesting an important pathway by which emerging infectious diseases will impact not only human health but ecosystems as well.

Driving specialist's ratings of on-road performance and naturalistic driving crashes and near-crashes.

BACKGROUND: This study aimed to evaluate the association between a Certified Driving Rehabilitation Specialist's (CDRS) ratings of on-road driving performance by older drivers and at-fault crash and near-crash involvement using naturalistic driving techniques where crashes and near-crashes are recorded in everyday driving through in-vehicle instrumentation. METHODS: This is a cohort study of 144 drivers aged 70 years and over who were recruited due to a recent ophthalmology clinic visit at the University of Alabama at Birmingham. Baseline measurements consisted of demographics, visual status, and other health variables. At-fault crashes and near-crashes over 6 months were identified through instrumentation placed in their personal vehicle that recorded vehicle kinematics and video. After 6 months, a CDRS completed an on-road assessment and provided a composite rating on specific driving behaviors and a global score. RESULTS: Rate ratios examining the association between older drivers with worse CDRS composite scores and rates of at-fault crashes, at-fault near-crashes, and combined at-fault crashes and near-crashes were significantly higher compared to drivers with better scores. Results were similar for the CDRS global score. CONCLUSIONS: Motor vehicle administrations use CDRS ratings to make decisions about licensure, and in clinical programs such as those based at rehabilitation clinics use them to make recommendations about fitness to drive and rehabilitation. This study suggests that these decisions and recommendations are valid from a safety standpoint.

Vehicle trajectory prediction and generation using LSTM models and GANs.

Vehicles' trajectory prediction is a topic with growing interest in recent years, as there are applications in several domains ranging from autonomous driving to traffic congestion prediction and urban planning. Predicting trajectories starting from Floating Car Data (FCD) is a complex task that comes with different challenges, namely Vehicle to Infrastructure (V2I) interaction, Vehicle to Vehicle (V2V) interaction, multimodality, and generalizability. These challenges, especially, have not been completely explored by state-of-the-art works. In particular, multimodality and generalizability have been neglected the most, and this work attempts to fill this gap by proposing and defining new datasets, metrics, and methods to help understand and predict vehicle trajectories. We propose and compare Deep Learning models based on Long Short-Term Memory and Generative Adversarial Network architectures; in particular, our GAN-3 model can be used to generate multiple predictions in multimodal scenarios. These approaches are evaluated with our newly proposed error metrics N-ADE and N-FDE, which normalize some biases in the standard Average Displacement Error (ADE) and Final Displacement Error (FDE) metrics. Experiments have been conducted using newly collected datasets in four large Italian cities (Rome, Milan, Naples, and Turin), considering different trajectory lengths to analyze error growth over a larger number of time-steps. The results prove that, although LSTM-based models are superior in unimodal scenarios, generative models perform best in those where the effects of multimodality are higher. Space-time and geographical analysis are performed, to prove the suitability of the proposed methodology for real cases and management services.

Investigating the uniqueness of crash injury severity in freeway tunnels: A comparative study in Guizhou, China.

INTRODUCTION: With the rapid development of transportation infrastructures in precipitous areas, the mileage of freeway tunnels in China has been mounting during the past decade. Provided the semi-constrained space and the monotonous driving environment of freeway tunnels, safety concerns still remain. This study aims to investigate the uniqueness of the relationships between crash severity in freeway tunnels and various contributory factors. METHOD: The information of 10,081 crashes in the entire freeway network of Guizhou Province, China in 2018 is adopted, from which a subset of 591 crashes in tunnels is extracted. To address spatial variations across various road segments, a two-level binary logistic approach is applied to model crash severity in freeway tunnels. A similar model is also established for crash severity on general freeways as a benchmark. RESULTS: The uniqueness of crash severity in tunnels mainly includes three aspects: (a) the road-segment-level effects are quantifiable with the environmental factors for crash severity in tunnels, but only exist in the random effects for general freeways; (b) tunnel has a significantly higher propensity to cause severe injury in a crash than other locations of a freeway; and (c) different influential factors and levels of contributions are found to crash severity in tunnels compared with on general freeways. Factors including speed limit, tunnel length, truck involvement, rear-end crash, rainy and foggy weather and sequential crash have positive contributions to crash severity in freeway tunnels. Practical applications: Policy implications for traffic control and management are advised to improve traffic safety level in freeway tunnels.

Investigation of injury severities in single-vehicle crashes in North Carolina using mixed logit models.

INTRODUCTION: Roadway departure (RwD) crashes, comprising run-off-road (ROR) and cross-median/centerline head-on collisions, are one of the most lethal crash types. According to the FHWA, between 2015 and 2017, an average of 52 percent of motor vehicle traffic fatalities occurred each year due to roadway departure crashes. An avoidance maneuver, inattention or fatigue, or traveling too fast with respect to weather or geometric road conditions are among the most common reasons a driver leaves the travel lane. Roadway and roadside geometric design features such as clear zones play a significant role in whether human error results in a crash. METHOD: In this paper, we used mixed-logit models to investigate the contributing factors on injury severity of single-vehicle ROR crashes. To that end, we obtained five years' (2010-2014) of crash data related to roadway departures (i.e., overturn and fixed-object crashes) from the Federal Highway Administration's Highway Safety Information System Database. RESULTS: The results indicate that factors such as driver conditions (e.g., age), environmental conditions (e.g., weather conditions), roadway geometric design features (e.g., shoulder width), and vehicle conditions significantly contributed to the severity of ROR crashes. CONCLUSIONS: Our results provide valuable information for traffic design and management agencies to improve roadside design policies and implementing appropriately forgiving roadsides for errant vehicles. Practical applications: Our results show that increasing shoulder width and keeping fences at the road can reduce ROR crash severity significantly. Also, increasing road friction by innovative materials and raising awareness campaigns for careful driving at daylight can decrease the ROR crash severity.

Continued trends in older driver crash involvement rates in the United States: Data through 2017-2018.

INTRODUCTION: With the growing older adult population due to the aging baby-boom cohort, there was concern that increases in fatal motor-vehicle crashes would follow. Yet, previous analyses showed this to be untrue. The purpose of this study was to examine current trends to determine if previous declines have persisted or risen with the recent increase in fatalities nationwide. METHODS: Trends among drivers ages 70 and older were compared with drivers 35-54 for U.S. passenger vehicle fatal crash involvements per 100,000 licensed drivers from 1997 to 2018, fatal and all police-reported crash involvements per vehicle miles traveled using the 1995, 2001, 2009, and 2017 National Household Travel Surveys, and driver deaths per 1,000 crashes. RESULTS: Since the mid-1990s, fatal crashes per licensed driver trended downward, with greater declines for drivers ages 70 and older than for middle-aged drivers (43% vs. 21%). Fatal crash rates per 100,000 licensed drivers and police-reported crash rates per mile traveled for drivers ages 70-79 are now less than those for drivers ages 35-54, but their fatal crash rates per mile traveled and risk of dying in a crash remain higher as they drive fewer miles. As the economy improved over the past decade, fatal crash rates increased substantially for middle-aged drivers but decreased or remained stable among older driver age groups. CONCLUSIONS: Fatal crash involvements for adults ages 70 and older has recently increased, but they remain down from their 1997 peak, even as the number of licensed older drivers and the miles they drive have increased. Health improvements likely contributed to long-term reductions in fatal crash rates. As older drivers adopt vehicles with improved crashworthiness and safety features, crash survivability will improve. Practical Application: Older adults should feel confident that their independent mobility needs pose less risk than previously expected.

Mobile phone use while driving: Development and validation of knowledge, attitude, and practice survey instruments.

INTRODUCTION: Instruments that assess the knowledge, attitude, and practice (KAP) of mobile phone use serve as a primary assessment tool on which mobile phone distracted driving interventions can be designed. The objective of this study is to develop and validate KAP-modeled survey instruments that measure the knowledge of mobile phone hazards while driving (KMPHD), the attitude of drivers towards mobile phone use while driving (AMPUD), and the practice of mobile phone use while driving (PMPUD). METHOD: This study was a cross-sectional analytical survey conducted in Ibadan, Nigeria. Three instruments were designed to measure KMPHD, AMPUD, and PMPUD. Content validity, item analysis, exploratory factor analysis were conducted, and items were excluded based on the collective results of the analysis. The domains of the constructs and the reliability of the instruments are reported. A confirmatory factor analysis was used to assess the regression weights of each item and the model fit. RESULTS: From an original list of 13, 12, and 10 items in the KMPHD, AMPUD, and PMPUD instruments, a final list of 7, 5, and 7 items were generated in each survey instrument, respectively. Two domains of the knowledge of hazards and practice of mobile phone use were obtained, and attitude to phone use while driving was a single domain. The reliabilities (Cronbach alpha) of the KMPHD (0.881), AMPUD (0.954), and PMPUD (0.920) were sufficiently high. Also, all items in the three instruments had moderate-to-high regression coefficients, and the model fits of the instruments were good. CONCLUSIONS: This study provides KAP-modeled survey instruments that can be used to assess a population-based knowledge, attitude, and practice of mobile phone use while driving. Practical Applications: This survey instrument can be used in assessing baseline knowledge, attitude, and practice of phone use while driving and determine the focus and effectiveness of mobile phone-induced distracted driving interventions.

Evaluating barriers to access for cataract surgery in Waikato: analysis of calculated driving distance and visual acuity.

AIM: This cross-sectional study aimed to investigate whether presenting visual acuity or patient demographic variables were associated with geographic proximity to primary and secondary ophthalmic services. METHODS: Demographics for all patients referred within the Waikato District between October 2017 and March 2019 that met the threshold for publicly funded cataract surgery were analysed. GPS coordinates for all patient and optometrist addresses were obtained. The driving distance and driving time for each patient to travel to their referring optometrist were calculated. Quality-of-life data were obtained. Analysis of visual acuity, driving distance, age, ethnicity and gender was completed using. Furthermore, a comparative analysis of Maori and New Zealand European defined as having remote access was completed. RESULTS: A total of 1,260 patients were included. Multivariate analysis showed no significant association between driving distance and visual acuity. Comparative analysis of Maori and New Zealand European defined as having remote access showed Maori had significantly worse visual acuity than New Zealand Europeans at the time of referral. No significant difference was found in quality of life. Maori were on average younger than New Zealand European. Driving time and distance were on average 27% longer for Maori compared with New Zealand Europeans defined as having remote access. CONCLUSIONS: Maori presenting with cataract typically are younger and have lower visual acuity than New Zealand European. Longer driving distances represent a potential geographic barrier for Maori to access ophthalmic care and referral to tertiary services. No significant association was found between driving distance and visual acuity.

Modelling of integrated scheduling problem of capacitated equipment systems with a multi-lane road network.

The coordination of different container-handling equipment is an important method for improving the overall efficiency of automated container terminals. In the real terminal, we should consider many real-life issues, such as the equipment capacity, the equipment collision, changing lanes in the multi-lane road, and choosing one of container-handling lanes for each container. This paper proposes the integrated scheduling problem of three container-handling equipment with the capacity constraint and the dual-cycle strategy, for simultaneously solving the equipment scheduling problem, the assignment problem of the container-handling lane and the conflict-free route planning problem of automated guided vehicles (AGVs). With the objective of minimizing the ship's berth time, we propose a mixed-integer programming model based on the space-time network representation method and two bilevel optimization algorithms based on conflict resolution rules. Finally, numerical experiments are conducted to verify the effectiveness of the proposed model and two bilevel optimization algorithms.

Toward the development of a hybrid approach to speed estimation in urban and rural areas.

OBJECTIVE: Given the strong relationship between road accident and traffic speed, the evaluation and prediction of this latter have always been considered as a critical issue for road safety analysis and for the evaluation of road network safety improvements. Prediction models developed to date mainly focused on spot speed in a rural environment or on running speed in an urban one. Very few analyze the speed estimation in "transition" areas. The objective of this paper is to develop a generalized speed estimation model able to predict mean speed in urban, rural, and "transition" environment as a function of road layout characteristics. It is believed that the proposed estimation tool can be effectively employed by road engineers in the road safety design and retrofitting stage. METHODS: The basic idea of the paper is to shed some light on this issue by making use of a hybrid estimation approach able to combine the information gathered from both previously mentioned models within a generalized speed adaptation framework that reflects road user behavior. The calibration and validation of the generalized estimation model have been carried out following a collection of Floating Car Data (FCD) on several candidate sites. RESULTS: Preliminary results seem to indicate that the methodology proposed may be effective in estimating the spot speed in two-lane rural and urban arterials. CONCLUSIONS: FCD data can be useful to develop more efficient estimation models to better manage the safety of urban and rural roads.