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1.
Accid Anal Prev ; 134: 105324, 2020 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-31648116

RESUMO

OBJECTIVE: Side crashes between vehicles which usually lead to high casualties and property loss, rank first among total crashes in China. This paper aims to identify the factors associated with injury severity of side crashes at intersections and to provide suggestions for developing countermeasures to mitigate the levels of injuries. METHOD: In order to investigate the role of striking and struck vehicles in side crashes simultaneously, bivariate probit model was proposed and Bayesian approach was employed to evaluate the model, compared to the corresponding univariate probit model. DATA: Crash data from Beijing, China for the period 2009-2012 were used to carry out the statistical analysis. Based on the investigation with vehicles and data analysis on events, 130 intersection side crash cases were selected to form a specific dataset. Then, the influence of human, vehicles, roadway and environmental variables on crash severity was examined by means of bivariate probit regression within Bayesian framework. RESULTS: The effects of the factors on striking vehicle drivers and struck vehicle drivers were considered separately and simultaneously to find more targeted conclusions. The statistical analysis revealed vehicle type, lane number, no non-motorized lane and speeding have the corresponding influence on the injury severity of striking vehicles, while time of day and vehicle type of struck vehicles increased the likelihood of being injured. CONCLUSIONS: From the results it can be concluded that there indeed exists correlation between striking and struck vehicles in side crashes, although the correlation is not so strong. Importantly, Bayesian bivariate probit model can address the role of striking and struck vehicles in side crashes simultaneously and can accommodate the correlation clearly, which extends the range of univariate probit analysis. The general and empirical countermeasures are presented to improve the safety at intersections.


Assuntos
Acidentes de Trânsito/estatística & dados numéricos , Ferimentos e Lesões/mortalidade , Teorema de Bayes , Pequim/epidemiologia , Ambiente Construído/estatística & dados numéricos , Humanos , Modelos Logísticos , Veículos Automotores/classificação , Veículos Automotores/estatística & dados numéricos , Probabilidade
2.
Accid Anal Prev ; 132: 105278, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31518763

RESUMO

Traffic accidents can take place in very different ways and involve a substantially distinct number and types of vehicles. Thus, it is of interest to know which parts of a road structure present an overrepresentation of a specific type of traffic accident, specially for some typologies of collisions and vehicles that tend to trigger more severe consequences for the users being involved. In this study, a spatial approach is followed to estimate the risk that different types of collisions and vehicles present in the central area of Valencia (Spain), considering the accidents observed in this city during the period 2014-2017. A directed spatial linear network representing the non-pedestrian road structure of the area of interest was employed to guarantee an accurate analysis of the point pattern. A kernel density estimation technique was used to approximate the probability of risk along the network for each collision and vehicle type. A procedure based on these estimates and the sample size locally available within the network was designed and tested to determine a set of differential risk hotspots for each typology of accident considered. A Monte Carlo based simulation process was then defined to assess the statistical significance of each of the differential risk hotspots found, allowing the elaboration of rankings of importance and the possible rejection of the least significant ones.


Assuntos
Acidentes de Trânsito/prevenção & controle , Veículos Automotores/estatística & dados numéricos , Acidentes de Trânsito/classificação , Acidentes de Trânsito/estatística & dados numéricos , Ambiente Construído , Humanos , Método de Monte Carlo , Veículos Automotores/classificação , Medição de Risco , Espanha , Análise Espacial
3.
Accid Anal Prev ; 132: 105285, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31476585

RESUMO

Over the years the characteristics of traffic on Dutch motorways has changed, but its design guidelines did not develop as rapidly and large parts remain unchanged since the first guidelines from the 1970s. During the latest revision of the Dutch motorway design guidelines it became clear that a solid and comprehensive theoretical, or evidence based, background was lacking for the validity of the prescribed ramp spacing and required length for weaving segments. This article presents the underpinning of revising the Dutch design manual for motorways for turbulence in traffic. For this study loop detector data at eight on-ramps and five off-ramps were collected as well as empirical trajectory data at fourteen different on-ramps (three), off-ramps (three) and weaving segments (eight) in The Netherlands. The results show that the areas around ramps that are influenced by turbulence are smaller than described in the design manuals and that, in their present form, the microscopic simulation software packages VISSIM and MOTUS fail to simulate the number and location of lane-changes around ramps realistically.


Assuntos
Condução de Veículo/estatística & dados numéricos , Ambiente Construído/normas , Ambiente Construído/estatística & dados numéricos , Guias como Assunto , Humanos , Veículos Automotores/estatística & dados numéricos , Países Baixos
4.
Accid Anal Prev ; 132: 105226, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31465934

RESUMO

While the cost of crashes exceeds $1 Trillion a year in the U.S. alone, the availability of high-resolution naturalistic driving data provides an opportunity for researchers to conduct an in-depth analysis of crash contributing factors, and design appropriate interventions. Although police-reported crash data provides information on crashes, this study takes advantage of the SHRP2 Naturalistic Driving Study (NDS) which is a unique dataset that allows new insights due to detailed information on driver behavior in normal, pre-crash, and near-crash situations, in addition to trip and vehicle performance characteristics. This paper investigates the role of pre-crash driving instability, or driving volatility, in crash intensity (measured on a 4-point scale from a tire-strike to an injury crash) by analyzing microscopic vehicle kinematic data. NDS data are used to investigate not only the vehicle movements in space but also the instability of vehicles prior to the crash and their contribution to crash intensity using path analysis. A subset of the data containing 617 crash events with around 0.18 million temporal trajectories are analyzed. To quantify driving instability, microscopic variations or volatility in vehicular movements before a crash are analyzed. Specifically, nine measures of pre-crash driving volatility are calculated and used to explain crash intensity. While most of the measures are significantly correlated with crash intensity, substantial positive correlations are observed for two measures representing speed and deceleration volatilities. Modeling results of the fixed and random parameter probit models revealed that volatility is one of the leading factors increasing the probability of a severe crash. Additionally, the speed prior to a crash is highly correlated with intensity outcomes, as expected. Interestingly, distracted and aggressive driving are highly correlated with driving volatility and have substantial indirect effects on crash intensity. With volatile driving serving as a leading indicator of crash intensity, given the crashes analyzed in this study, early warnings and alerts for the subject vehicle driver and proximate vehicles can be helpful when volatile behavior is observed.


Assuntos
Acidentes de Trânsito/estatística & dados numéricos , Condução de Veículo/psicologia , Coleta de Dados/métodos , Acidentes de Trânsito/prevenção & controle , Condução de Veículo/estatística & dados numéricos , Fenômenos Biomecânicos , Humanos , Veículos Automotores/estatística & dados numéricos , Medição de Risco/métodos
5.
Accid Anal Prev ; 132: 105256, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31442922

RESUMO

This study analyzed the potentially dangerous driving behaviors of commercial truck drivers from both macro and micro perspectives. The analysis was based on digital tachograph data collected over an 11-month period and comprising 4373 trips made by 70 truck drivers. First, different types of truck drivers were identified using principal component analysis (PCA) and a density-based spatial clustering of applications with noise (DBSCAN) at the macro level. Then, a multilevel model was built to extract the variation properties of speeding behavior at the micro level. Results showed that 40% of the truck drivers tended to drive in a substantially dangerous way and the explained variance proportion of potentially extremely dangerous truck drivers (79.76%) was distinctly higher than that of other types of truck drivers (14.70%˜34.17%). This paper presents a systematic approach to extracting and examining information from a big data source of digital tachograph data. The derived findings make valuable contributions to the development of safety education programs, regulations, and proactive road safety countermeasures and management.


Assuntos
Condução de Veículo/psicologia , Comportamento Perigoso , Adulto , Condução de Veículo/estatística & dados numéricos , Big Data , Humanos , Masculino , Pessoa de Meia-Idade , Veículos Automotores/estatística & dados numéricos , Análise Multinível , Ocupações/estatística & dados numéricos , Análise Espaço-Temporal
6.
Accid Anal Prev ; 132: 105270, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31445463

RESUMO

Mode shift from private vehicle to public transport is often considered as a potential means of improving road safety, given public transport's lower fatality rates. However, little research has examined how public transport travel contributes to road safety at a macroscopic level. Further, there is a limited understanding of the individual effects of different public transport modes. This paper explores the effects of commuting by public transport on road safety at a macroscopic level, using Melbourne as a case study. A random effect negative binomial (RENB) and a conditional autoregressive (CAR) model are adopted to explore links between total and severe crash data to commuting mode shares and a range of other zonal explanatory factors. Overall, results show the great potential of public transport as a road safety solution. It is evident that mode shift from private vehicle to public transport (i.e. train, tram, and bus), for commuting would reduce not only total crashes, but also severe crashes. Modelling also demonstrated that CAR models outperform RENB models. In addition, results highlight safety issues related to commuting by motorbike and active transport. Effects of sociodemographic, transport network, and land use factors on crashes at the macroscopic level are also discussed.


Assuntos
Acidentes de Trânsito/estatística & dados numéricos , Transportes/métodos , Transportes/estatística & dados numéricos , Acidentes de Trânsito/prevenção & controle , Austrália , Humanos , Modelos Estatísticos , Veículos Automotores/classificação , Veículos Automotores/estatística & dados numéricos , Segurança
7.
Accid Anal Prev ; 131: 327-335, 2019 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-31377496

RESUMO

Freight truck-involved crashes result in a high mortality rate and significantly impact logistic costs; therefore, many researchers have analyzed the causes of truck-involved traffic crashes. In the existing literature, it was found that truck-involved crashes are affected by factors such as road geometry, weather, driver and vehicle characteristics, and traffic volume based on a variety of statistical methodologies; however, the endogenous impact resulting from driver traffic violation has not been considered. The goal of the study is to discover the factors influencing freight vehicle crashes and develop more accurate crash probability estimation by explaining the endogenous driver traffic violations. To achieve the purpose of this study, we applied the two-stage residual inclusion (2SRI) approach, a methodology used in the nonlinear regression analysis model for capturing the endogeneity issue. This method improves the accuracy of the model by capturing the unobserved effects of driver traffic violations. From the results, traffic violations were identified to be influenced by the driver's physical condition, as well as driver and vehicle characteristics. Furthermore, variables of driver traffic violations such as improper passing, speeding, and safe distance violation were found to be endogenous in the probability model of freight truck crashes on expressway mainlines.


Assuntos
Acidentes de Trânsito/estatística & dados numéricos , Condução de Veículo/estatística & dados numéricos , Veículos Automotores/estatística & dados numéricos , Condução de Veículo/legislação & jurisprudência , Humanos , Análise de Regressão , Fatores de Risco
8.
Traffic Inj Prev ; 20(sup1): S7-S12, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31381450

RESUMO

Objective: The objective of this article is to describe the characteristics of fatal crashes with bicyclists on Swedish roads in rural and urban areas and to investigate the potential of bicycle helmets and different vehicle and road infrastructure interventions to prevent them. The study has a comprehensive approach to provide road authorities and vehicle manufacturers with recommendations for future priorities. Methods: The Swedish Transport Administration's (STA) in-depth database of fatal crashes was used for case-by-case analysis of fatal cycling accidents (2006-2016) on rural (n = 82) and urban (n = 102) roads. The database consists of information from the police, medical journals, autopsy reports, accident analyses performed by STA, and witness statements. The potential of helmet use and various vehicle and road infrastructure safety interventions was determined retrospectively for each case by analyzing the chain of events leading to the fatality. The potential of vehicle safety countermeasures was analyzed based on prognoses on their implementation rates in the Swedish vehicle fleet. Results: The most common accident scenario on rural roads was that the bicyclist was struck while cycling along the side of the road. On urban roads, the majority of accidents occurred in intersections. Most accidents involved a passenger car, but heavy trucks were also common, especially in urban areas. Most accidents occurred in daylight conditions (73%). Almost half (46%) of nonhelmeted bicyclists would have survived with a helmet. It was assessed that nearly 60% of the fatal accidents could be addressed by advanced vehicle safety technologies, especially autonomous emergency braking with the ability to detect bicyclists. With regard to interventions in the road infrastructure, separated paths for bicyclists and bicycle crossings with speed calming measures were found to have the greatest safety potential. Results indicated that 91% of fatally injured bicyclists could potentially be saved with known techniques. However, it will take a long time for such technologies to be widespread. Conclusions: The majority of fatally injured bicyclists studied could potentially be saved with known techniques. A speedy implementation of important vehicle safety systems is recommended. A fast introduction of effective interventions in the road infrastructure is also necessary, preferably with a plan for prioritization.


Assuntos
Acidentes de Trânsito/mortalidade , Acidentes de Trânsito/prevenção & controle , Ciclismo/lesões , Planejamento Ambiental/estatística & dados numéricos , Veículos Automotores/estatística & dados numéricos , Acidentes de Trânsito/estatística & dados numéricos , Bases de Dados Factuais , Dispositivos de Proteção da Cabeça , Humanos , Estudos Retrospectivos , População Rural/estatística & dados numéricos , Segurança , Suécia/epidemiologia , População Urbana/estatística & dados numéricos
9.
Int J Inj Contr Saf Promot ; 26(3): 205-215, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-31169057

RESUMO

Drivers' instantaneous decisions regarding speed and acceleration/deceleration, as well as the time rate of acceleration change (jerk) can result in a volatility driving behaviour with significant impact on cyclist safety. The contribution of this article is the assessment of driving volatility in motor vehicle (MV)-bicycle interactions at two-lane roundabouts. Traffic flow and bicycle GPS data were collected from two two-lane roundabouts. Then, traffic, emissions and safety models were used to evaluate volatility impacts on safety, pollutant emissions and traffic performance. The findings showed jerk have an impact on driving volatility between MVs and bicycles, regardless of roundabout design with higher amplitude of variation for MVs. However, MVs had higher acceleration-deceleration variation than bicycles.


Assuntos
Condução de Veículo/estatística & dados numéricos , Ciclismo , Veículos Automotores , Aceleração , Ciclismo/estatística & dados numéricos , Planejamento Ambiental , Feminino , Humanos , Masculino , Modelos Estatísticos , Veículos Automotores/estatística & dados numéricos , Segurança/estatística & dados numéricos , Emissões de Veículos
10.
Accid Anal Prev ; 129: 126-135, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31150919

RESUMO

Motor vehicle crashes (MVCs) are a significant cause of lost-workday injuries, and consistently the leading cause of work-related fatalities in the United States for all industries combined. Prevention research has focused mainly on collisions fatal to the drivers of large trucks. This analytical observational study addresses gaps in the literature by: conducting a descriptive analysis of motor vehicle claim events involving light-vehicle drivers in a large health care industry fleet; identifying risk factors for work-related MVCs and injuries based on vehicle miles traveled; and providing details on circumstances of these events. The study examined 8068 motor vehicle events resulting in vehicle damage, property damage, or injury reported by 6680 U.S.-based drivers in a light-vehicle sales and service fleet operated by a health care company over a 4 ½-year period (January 2010 through June 2014). Thirty-three percent (n = 2660) of the events were collisions. Collisions were segmented as recoverable or non-recoverable according to whether the company could recover costs from another party, and mileage-based collision and injury rates were calculated by gender, age, tenure, and vehicle type. Differences in collision and injury rates between groups of interest (for example, tenure and age categories) were assessed with Poisson regression techniques adjusted using generalized estimating equations (GEE) for repeated observations on the same employee over time. Age, gender, and job tenure were significant collision risk factors, and risk patterns for recoverable and non-recoverable collisions were similar to those for total collisions. Collisions per million miles (CPMM) were significantly higher for drivers 21-24.9 years of age compared to drivers age 25-54.9 years (9.58 CPMM vs 4.96 CPMM, p = .025), drivers employed for less than 2 years compared to those employed 2 or more years (6.22 CPMM vs 4.82 CPMM, p < .001), for female drivers compared to male drivers (6.37 CPMM vs 4.16 CPMM, p < .001), and for drivers of passenger cars compared to all other vehicles (5.27 CPMM vs 4.48 CPMM, p < .001). Among collisions between the employee's vehicle and another vehicle in transport, those where the front of one vehicle hit another vehicle at an angle were the most likely to result in injury to the employee driver or another party (26%), followed by rear-end collisions (25%). Special attention should be given to preventing collisions among newly-hired employees, and to preventing angle and rear-end collisions, which were the most common types of collisions and also were most likely to result in injury than all other collisions combined.


Assuntos
Acidentes de Trabalho/estatística & dados numéricos , Acidentes de Trânsito/estatística & dados numéricos , Condução de Veículo/estatística & dados numéricos , Veículos Automotores/estatística & dados numéricos , Acidentes de Trabalho/prevenção & controle , Acidentes de Trânsito/prevenção & controle , Adulto , Distribuição por Idade , Feminino , Setor de Assistência à Saúde , Humanos , Masculino , Pessoa de Meia-Idade , Análise de Regressão , Fatores de Risco , Distribuição por Sexo , Estados Unidos , Ferimentos e Lesões/epidemiologia , Adulto Jovem
11.
Environ Monit Assess ; 191(7): 461, 2019 Jun 24.
Artigo em Inglês | MEDLINE | ID: mdl-31236686

RESUMO

This study assessed the effect of road development on vegetation fragmentation in and around a protected area network in western Isfahan Province, Central Iran. As the first study in Iran, an attempt was also made using the weighted linear combination-informed ecological value index of roadless area (EVIRA), to evaluate the environmental value of roadless areas based on a set of ecological and anthropogenic factors. Toward these aims, a Landsat 8-OLI image was processed to delineate land use/cover of the region. Road-induced fragmentation was then estimated by comparing the results of a small set of landscape metrics (DIVISION, SPLIT, MESH, LPI, and NP) measured from the original and road-included LULC map. The results showed road-induced increasing DIVISION (by 4.8-85.9%) and SPLIT (by 0.01-23.1%) and decreasing MESH (by 2.7-14%), LPI (by 1.3-32.4%), and NP (by 6-97.8%) values within all protected areas and across the entire study area, indicating a significant rise in landscape fragmentation and habitat loss. Roadless patch area and Thiessen connectivity stood out as the most salient criteria in determining environmentally valuable roadless areas. The results of EVIRA showed that the study region comprises some valuable but unprotected roadless areas which should be protected against road development or any kind of destructive human activities by laying out conservation plans or their inclusion to the current protected area network.


Assuntos
Conservação dos Recursos Naturais/métodos , Monitoramento Ambiental/métodos , Veículos Automotores/estatística & dados numéricos , Imagens de Satélites/métodos , Ecologia , Ecossistema , Atividades Humanas/estatística & dados numéricos , Humanos , Irã (Geográfico)
12.
Environ Int ; 129: 35-41, 2019 08.
Artigo em Inglês | MEDLINE | ID: mdl-31108391

RESUMO

The first national-scale assessment of lead (Pb) contamination in agricultural soils across China was conducted based on >1900 articles published between 1979 and 2016. Pb concentrations, temporal and spatial variations, and influencing factors were analyzed. Children's blood lead levels (BLLs) were also estimated using the integrated exposure uptake biokinetic (IEUBK) model. Pb concentrations in different areas of China varied greatly, which was closely associated with the distribution of Pb-related industries, especially Pb-zinc mine smelting, non-ferrous polymetallic mine smelting, e-waste recycling, and leaded gasoline consumption. The year 2000 was a significant transition year for Pb concentrations, with a rapid increase pre-2000 and a subsequent slow upward trend. Pb concentrations were found to be strongly associated with indicators of economic and social development including gross domestic product (GDP), population size, and vehicle ownership. Leaded gasoline, coal combustion, and non-ferrous smelting were the main sources of atmospheric Pb during the different periods. Predicted BLLs were higher in South China than those in the north. This study details the overall Pb contamination status of agricultural soils in China, and thus provides insights for policymakers with respect to pollution prevention measures.


Assuntos
Desenvolvimento Econômico , Monitoramento Ambiental , Chumbo/análise , Mudança Social , Poluentes do Solo/análise , China , Produto Interno Bruto/estatística & dados numéricos , Veículos Automotores/estatística & dados numéricos , Propriedade/estatística & dados numéricos , Densidade Demográfica
13.
PLoS One ; 14(5): e0217241, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31120962

RESUMO

Accurate Origin-Destination (OD) prediction is significant for effective traffic monitor, which can support operation decision in traffic planning and management field. The enclosed expressway network system like toll gates system in China can collect mounts of trip records which can be gathered for OD prediction. The paper develops a novel neural network, which is named Expressway OD Prediction Neural Network (EODPNN) for toll data-based prediction. The network consists of the following three modules: The Feature Extension Module, the Memory Module, and the Prediction Module. In the process, the attributes data which can reflect the city attribute such as GDP, population, and the number of vehicles are considered to embeded into the notwork to increase the accuracy of the model. For the applicability improvment of the model, we categorize the cities in multiple classes based on their economy and population scales in this paper, which can provide a higher accurate prediction of OD by EODPNN. The results shows that, comparing to the traditional model like ARIMA and SVM, or typical neural networks like Bidirectional Long Short-term Memory, the EODPNN delivers a better prediction performance. The method proposed in this paper has been fully verified and has a potential to transplant to the other OD data-based management systems for a more accurate and flexible prediction.


Assuntos
Condução de Veículo/estatística & dados numéricos , Veículos Automotores/estatística & dados numéricos , China , Interpretação Estatística de Dados , Humanos , Modelos Teóricos , Veículos Automotores/economia
14.
PLoS One ; 14(4): e0215656, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31034481

RESUMO

Data about human trajectories has been widely used to study urban regions that are attractive to researchers and are considered to be hotspots. It is difficult, however, to quantify the function of urban regions based on the varieties of human behavior. In this research, we developed a clustering method to help discover the specific functions that exist within urban regions. This method applies the Gaussian Mixture Model (GMM) to classify regions' inflow and trip count characteristics. It regroups these urban regions using the Pearson Correlation Coefficient (PCC) clustering method based on those typical characteristics. Using a large amount of vehicle trajectory data (approximately 1,500,000 data points) in the Chinese city of Chengdu, we demonstrate that the method can discriminate between urban functional regions, by comparing the proportion of surface objects within each region. This research shows that vehicle trajectory data in different functional urban regions possesses different time-series curves, while similar types of functional regions can be identified by these curves. Compared with remote sensing images and other statistical methods which can provide only static results, our research can provide a timely and effective approach to determine an urban region's functions.


Assuntos
Veículos Automotores/estatística & dados numéricos , População Urbana/estatística & dados numéricos , China , Cidades , Análise por Conglomerados , Humanos , Modelos Estatísticos , Distribuição Normal , Tecnologia de Sensoriamento Remoto , Viagem/estatística & dados numéricos
15.
Artigo em Inglês | MEDLINE | ID: mdl-31027255

RESUMO

INTRODUCTION: Every year more than 1.2 million people worldwide die due to trauma sustained in road crashes, with an additional number of people injured exceeding 50 million. To a large extent, this applies to so called "unprotected road users", including pedestrians. The risk involved in a traffic crash for pedestrians can result from many factors, one of which is participation in road traffic when under the influence of alcohol. The aim of this study was to analyze the impact of alcohol use among pedestrians as unprotected road traffic participants, and the consequences of them being struck by motor vehicles. MATERIAL AND METHODS: The source of data was the medical documentation of the Department of Forensic Medicine at the Medical University of Warsaw. The sample for this research consisted of 313 pedestrians who were victims of fatal road crashes resulting from a collision with a mechanical vehicle. The obtained results were subjected to statistical analysis using the STATISTICA version 12.5 program (StatSoft Polska, Cracow, Poland). RESULTS: Male fatalities constituted the majority of the study sample. Nearly half of the fatal pedestrian victims were found to be under the influence of alcohol. The statistical analysis demonstrated a significant relationship between the gender and age of the victims, as well as between the place of the event, the place of death, the mechanism of the event, and the presence of alcohol in pedestrians. CONCLUSIONS: Among pedestrians, victims of road crashes who were under the influence of alcohol were predominantly drunk young males. Victims under the influence of alcohol were more likely to become fatalities in crashes where the mechanism of the incident was being struck by a passenger car, and when the place of the incident was a rural area, in these cases the rates of death directly at the scene were much more frequent. The eradication of alcohol consumption by all road users should be the overriding objective of all measures aimed at reducing the number of road crashes.


Assuntos
Acidentes de Trânsito/mortalidade , Acidentes de Trânsito/estatística & dados numéricos , Intoxicação Alcoólica/epidemiologia , Etanol/efeitos adversos , Veículos Automotores/estatística & dados numéricos , Pedestres/estatística & dados numéricos , Ferimentos e Lesões/epidemiologia , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Criança , Pré-Escolar , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Polônia/epidemiologia , Adulto Jovem
16.
Chin J Traumatol ; 22(2): 63-68, 2019 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-30962130

RESUMO

PURPOSE: Vehicle-pedestrian conflicts are common at road intersections when traffic lights change. However, the impact of traffic light on transportation safety and efficiency remains poorly understood. METHODS: A two-stage study was used to survey the proportion of intersections with conflicting traffic lights and the related transportation efficiency and safety were evaluated as well. First, a cross-sectional study estimated the proportion of signalized intersections with conflicting left-turning vehicle-pedestrian traffic lights in Changsha city, China. Second, a natural experiment compared transportation efficiency and safety between intersections with and without conflicting left-turning vehicle-pedestrian traffic lights. Risky conflicts, where motor vehicles violated laws and failed to yield to pedestrians in crosswalk were used as a surrogate for transportation safety. The number of motor vehicles and pedestrians passing through the intersections per second and per meter were used to estimate transportation efficiency. Data were collected and analyzed in 2015 (from March to December). A search of online news from domestic media sources was also conducted to collect pedestrian injury data occurring at the intersections. RESULTS: About one-fourth (57/216) intersections had conflicting left-turning traffic lights (95% CI: 20.5%, 32.3%). Risky vehicle-pedestrian conflicts were more frequently observed at intersections with conflicting lights compared to those without (incidence rate ratio (IRR) = 3.13; pedestrians: IRR = 4.02), after adjusting for type of day (weekday vs. weekend), the time period of observation, and motor vehicles traffic flow. Intersections without conflicting vehicle-pedestrian traffic lights had similar transportation efficiency to those with conflicting lights after controlling for covariates (p > 0.05). The systematic review of news media reports yielded 10 left-turning vehicle-pedestrian crash events between 2011 and 2017, involving 11 moderate or severe pedestrian injuries and 3 fatal pedestrian injuries. CONCLUSION: Over one-fourth of road intersections in Changsha city, China have conflicting left-turning traffic lights. Conflicting traffic lights cannot improve transportation efficiency, but increase risky conflicts between vehicles and pedestrians.


Assuntos
Acidentes de Trânsito/prevenção & controle , Acidentes de Trânsito/estatística & dados numéricos , Veículos Automotores/estatística & dados numéricos , Pedestres/estatística & dados numéricos , Ferimentos e Lesões/epidemiologia , China/epidemiologia , Estudos Transversais , Humanos , Segurança , Fatores de Tempo
17.
Accid Anal Prev ; 128: 253-260, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-30981377

RESUMO

BACKGROUND: Understanding factors that influence the distance that drivers provide when passing cyclists is critical to reducing subjective risk and improving cycling participation. This study aimed to quantify passing distance and assess the impact of motor vehicle and road infrastructure characteristics on passing distance. METHODS: An on-road observational study was conducted in Victoria, Australia. Participants had a custom device installed on their bicycle and rode as per their usual cycling for one to two weeks. A hierarchical linear model was used to investigate the relationship between motor vehicle and infrastructure characteristics (location, presence of on-road marked bicycle lane and the presence of parked cars on the kerbside) and passing distance (defined as the lateral distance between the end of the bicycle handlebars and the passing motor vehicle). RESULTS: Sixty cyclists recorded 18,527 passing events over 422 trips. The median passing distance was 173 cm (Q1: 137 cm, Q3: 224 cm) and 1085 (5.9%) passing events were less than 100 cm. Relative to sedans, 4WDs had a reduced mean passing distance of 15 cm (Q1: 12 cm, Q3: 17 cm) and buses had a reduced mean passing distance of 28 cm (Q1: 16 cm, Q3: 40 cm). Relative to passing events that occurred on roads without a marked bicycle lane and without parked cars, passing events on roads with a bike lane with no parked cars had a reduced mean passing distance of 27 cm (Q1: 25 cm, Q3: 29 cm), and passing events on roads with a bike lane and parked cars had a mean lower passing distance of 40 cm (Q1: 37 cm, Q3: 43 cm). CONCLUSIONS: One in every 17 passing events was a close (<100 cm) passing event. We identified that on-road bicycle lanes and parked cars reduced passing distance. These data can be used to inform the selection and design of cycling-related infrastructure and road use with the aim of improving safety for cyclists.


Assuntos
Acidentes de Trânsito/prevenção & controle , Condução de Veículo/estatística & dados numéricos , Ciclismo/estatística & dados numéricos , Veículos Automotores/estatística & dados numéricos , Acidentes de Trânsito/estatística & dados numéricos , Adulto , Planejamento Ambiental , Feminino , Humanos , Masculino , Comportamento de Redução do Risco , Vitória
18.
Accid Anal Prev ; 128: 32-39, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-30954784

RESUMO

Most agencies and decision-makers rely on crash and crash severity (property damage only, injury or fatality) data to assess transportation safety; however, in the context of public health where perceptions of safety may influence the willingness to adopt active transportation modes (e.g. bicycling and walking), pedestrian-motor vehicle and other similar conflicts types may define a better performance measure for safety assessment. In the field of transportation safety, an absolute conflict occurs when two parties' paths cross and one of the parties must undertake an evasive maneuver (e.g. change direction or stop) to avoid a crash. Other less severe conflicts where paths cross but no evasive maneuver is required may also impact public perceptions of safety especially for vulnerable modes. Most of the existing literature focuses on vehicle conflicts. While in the past several years, more research has investigated bicycle and pedestrian conflicts, most of this has focused on the intersection environment. A comprehensive analysis of conflicts appears critical. The major objective of this study is two fold: 1) Development of an innovative and cost effective conflict data collection technique to better understand the conflicts (and their severity) involving vulnerable road users (e.g. bicycle/pedestrian, bicycle/motor vehicle, and pedestrian/motor vehicle) and their severity. 2) Test the effectiveness and practicality of the approach taken and its associated crowd sourced data collection. In an endeavor to undertake these objectives, the researchers developed an android-based crowd-sourced data collection app. The crowd-source data collected using the app is compared with traditional fatality data for hot spot analysis. At the end, the app users provide feedback about the overall competency of the app interface and the performance of its features to the app developers. If widely adopted, the app will enable communities to create their own data collection efforts to identify dangerous sites within their neighborhoods. Agencies will have a valuable data source at low-cost to help inform their decision making related to bicycle and pedestrian education, encouragement, enforcement, programs, policies, and infrastructure design and planning.


Assuntos
Acidentes de Trânsito/prevenção & controle , Crowdsourcing , Planejamento Ambiental/estatística & dados numéricos , Aplicativos Móveis , Veículos Automotores/estatística & dados numéricos , Acidentes de Trânsito/mortalidade , Ciclismo/estatística & dados numéricos , Humanos , Pedestres/estatística & dados numéricos , Fatores de Risco , Caminhada/estatística & dados numéricos
19.
Rev Bras Epidemiol ; 22: e190011, 2019 Mar 14.
Artigo em Português, Inglês | MEDLINE | ID: mdl-30892474

RESUMO

OBJECTIVE: To verify the effects of PM2.5 and temperature on mortality due to cardiovascular diseases according to socioeconomic status and traffic proximity. METHOD: Time series were used, using the generalized additive models with the Poisson regression option, at 5% significance level. Interactionbetween proximity of traffic and socioeconomic status was analyzed through stratification. The proximity to the traffic was divided into distances up to 150m or over 150m. Socioeconomic status in the residential environment was categorized as high and low based on the median (3.9%). The relative risk percentage (%RR) of cardiovascular disease deaths was calculated for each linear increase of 10 µg/m3 at PM2.5 and 1ºC at the maximum temperature. RESULTS: Mortality due to cardiovascular diseases presented %RR 1.64 (95%CI -0.03; 3.33), related to the maximum temperature and %RR 4.60 (95%CI 0.78; 8.56) related to PM2.5, in areas with high traffic exposure. In areas with poor living conditions, %RR 1.34 (95%CI -0.31; 3.01) was observed, related to maximum temperature and RR% 3.95 (95%CI -0.27; 8.34) associated with PM2.5. CONCLUSION: Areas with poor living conditions and high-exposure to vehicular traffic had an increased risk of cardiovascular disease mortality related to high temperature and PM2.5.


Assuntos
Poluentes Atmosféricos/efeitos adversos , Poluição do Ar/efeitos adversos , Doenças Cardiovasculares/etiologia , Doenças Cardiovasculares/mortalidade , Exposição Ambiental/efeitos adversos , Veículos Automotores/estatística & dados numéricos , Temperatura Ambiente , Brasil/epidemiologia , Humanos , Pessoa de Meia-Idade , Fatores de Risco , Fatores Socioeconômicos , População Urbana
20.
Accid Anal Prev ; 125: 174-187, 2019 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-30771587

RESUMO

Despite the recognized benefits of electronic toll collection (ETC) system as an important part of toll plaza area, the mixed traffic of electronic toll collection (ETC) vehicles and manual toll collection (MTC) vehicles in the toll plaza diverging area are considered risky to vehicles, in which complex diverging and crossing behavior of vehicles would increase the collision risks. Therefore, it is vitally important to investigate the vehicle collision risk in the up stream toll plaza area. Video data are collected from a typical toll plaza in Nanjing, China, and vehicle trajectory data are extracted using an automated analysis system based on OpenCV. An extended Time-To-Collision (TTC) is proposed to evaluate the vehicle collision risk. Subsequently, the different effects on vehicle collision risk of vehicles with different toll collection types, target lanes and locations are compared. Furthermore, the random parameters logistic model is developed to investigate the effects of explanatory factors on the collision risk of vehicles diverging or adjusting their lane position. The results suggested that the MTC vehicles have the highest collision risk in the toll plaza diverging area and there are significant different effects on collision risk among vehicles with different target toll collection lanes. Further, more dangerous situations could be found for a vehicle if it is closer to the toll collection lanes and surrounded by heavy traffic. It is also confirmed that mixed traffic with MTC and ETC vehicles could increase the crash risk in the toll plaza diverging area. It is expected that the findings could help engineers and operators select the appropriate engineering and traffic control solutions to enhance the safety at the toll plaza diverging area.


Assuntos
Acidentes de Trânsito/estatística & dados numéricos , Ambiente Construído/normas , Veículos Automotores/estatística & dados numéricos , Condução de Veículo/psicologia , Condução de Veículo/estatística & dados numéricos , China , Coleta de Dados/métodos , Humanos , Modelos Logísticos , Fatores de Risco , Gravação em Vídeo
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