970 resultados para Road safety algorithms
Resumo:
Over the last fifty years mobility practices have changed dramatically, improving the way travel takes place, the time it takes but also on matters like road safety and prevention. High mortality caused by high accident levels has reached untenable levels. But the research into road mortality stayed limited to comparative statistical exercises which go no further than defining accident types. In terms of sharing information and mapping accidents, little progress has been mad, aside from the normal publication of figures, either through simplistic tables or web pages. With considerable technological advances on geographical information technologies, research and development stayed rather static with only a few good examples on dynamic mapping. The use of Global Positioning System (GPS) devices as normal equipments on automobile industry resulted in a more dynamic mobility patterns but also with higher degrees of uncertainty on road traffic. This paper describes a road accident georeferencing project for the Lisbon District involving fatalities and serious injuries during 2007. In the initial phase, individual information summaries were compiled giving information on accidents and its majour characteristics, collected by the security forces: the Public Safety Police Force (Polícia de Segurança Pública - PSP) and the National Guard (Guarda Nacional Republicana - GNR). The Google Earth platform was used to georeference the information in order to inform the public and the authorities of the accident locations, the nature of the location, and the causes and consequences of the accidents. This paper also gives future insights about augmented reality technologies, considered crucial to advances to road safety and prevention studies. At the end, this exercise could be considered a success because of numerous consequences, as for stakeholders who decide what to do but also for the public awareness to the problem of road mortality.
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Nowadays, road accidents are a major public health problem, which increase is forecasted if road safety is not treated properly, dying about 1.2 million people every year around the globe. In 2012, Portugal recorded 573 fatalities in road accidents, on site, revealing the largest decreasing of the European Union for 2011, along with Denmark. Beyond the impact caused by fatalities, it was calculated that the economic and social costs of road accidents weighted about 1.17% of the Portuguese gross domestic product in 2010. Visual Analytics allows the combination of data analysis techniques with interactive visualizations, which facilitates the process of knowledge discovery in sets of large and complex data, while the Geovisual Analytics facilitates the exploration of space-time data through maps with different variables and parameters that are under analysis. In Portugal, the identification of road accident accumulation zones, in this work named black spots, has been restricted to annual fixed windows. In this work, it is presented a dynamic approach based on Visual Analytics techniques that is able to identify the displacement of black spots on sliding windows of 12 months. Moreover, with the use of different parameterizations in the formula usually used to detect black spots, it is possible to identify zones that are almost becoming black spots. Through the proposed visualizations, the study and identification of countermeasures to this social and economic problem can gain new grounds and thus the decision- making process is supported and improved.
Resumo:
The historically-reactive approach to identifying safety problems and mitigating them involves selecting black spots or hot spots by ranking locations based on crash frequency and severity. The approach focuses mainly on the corridor level without taking the exposure rate (vehicle miles traveled) and socio-demographics information of the study area, which are very important in the transportation planning process, into consideration. A larger study analysis unit at the Transportation Analysis Zone (TAZ) level or the network planning level should be used to address the needs of development of the community in the future and incorporate safety into the long-range transportation planning process. In this study, existing planning tools (such as the PLANSAFE models presented in NCHRP Report 546) were evaluated for forecasting safety in small and medium-sized communities, particularly as related to changes in socio-demographics characteristics, traffic demand, road network, and countermeasures. The research also evaluated the applicability of the Empirical Bayes (EB) method to network-level analysis. In addition, application of the United States Road Assessment Program (usRAP) protocols at the local urban road network level was investigated. This research evaluated the applicability of these three methods for the City of Ames, Iowa. The outcome of this research is a systematic process and framework for considering road safety issues explicitly in the small and medium-sized community transportation planning process and for quantifying the safety impacts of new developments and policy programs. More specifically, quantitative safety may be incorporated into the planning process, through effective visualization and increased awareness of safety issues (usRAP), the identification of high-risk locations with potential for improvement, (usRAP maps and EB), countermeasures for high-risk locations (EB before and after study and PLANSAFE), and socio-economic and demographic induced changes at the planning-level (PLANSAFE).
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This report synthesizes the safety corridor programs of 13 states that currently have some type of program: Alaska, California, Florida, Kentucky, Minnesota, New Jersey, New Mexico, New York, Ohio, Oregon, Pennsylvania, Virginia, and Washington. This synthesis can help Midwestern states implement their own safety corridor programs and select pilot corridors or enhance existing corridors. Survey and interview information about the states’ programs was gathered from members of each state department of transportation (DOT) and Federal Highway Administration (FHWA) division office. Topics discussed included definitions of a safety corridor; length and number of corridors in the program; criteria for selection of a corridor; measures of effectiveness of an implemented safety corridor; organizational structure of the program; funding and legislation issues; and engineering, education, enforcement, and emergency medical service strategies. Safety corridor programs with successful results were then examined in more detail, and field visits were made to Kansas, Oregon, Pennsylvania, and Washington for first-hand observations. With the survey and field visit information, several characteristics of successful safety corridor programs were identified, including multidisciplinary (3E and 4E) efforts; selection, evaluation, and decommissioning strategies; organization structure, champions, and funding; task forces and Corridor Safety Action Plans; road safety audits; and legislation and other safety issues. Based on the synthesis, the report makes recommendations for establishing and maintaining a successful safety corridor program.
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Adverse weather conditions dramatically affect the nation’s surface transportation system. The development of a prototype winter Maintenance Decision Support System (MDSS) is part of the Federal Highway Administration’s effort to produce a prototype tool for decision support to winter road maintenance managers to help make the highways safer for the traveling public. The MDSS is based on leading diagnostic and prognostic weather research capabilities and road condition algorithms, which are being developed at national research centers. In 2003, the Iowa Department of Transportation was chosen as a field test bed for the continuing development of this important research program. The Center for Transportation Research and Education assisted the Iowa Department of Transportation by collecting and analyzing surface condition data. The Federal Highway Administration also selected five national research centers to participate in the development of the prototype MDSS. It is anticipated that components of the prototype MDSS system developed by this project will ultimately be deployed by road operating agencies, including state departments of transportation, and generally supplied by private vendors.
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There were 338 road fatalities on Irish roads in 2007. Research in 2007 by the Road Safety Authority in Ireland states that young male drivers (17 – 25 years) are seven times more likely to be killed on Irish roads than other road users. The car driver fatality rate was found to be approximately 10 times higher for young male drivers than for female drivers in 2000. Young male drivers in particular demonstrate a high proclivity for risky driving behaviours. These risky behaviours include drink driving, speeding, rug-driving and engaging in aggressive driving. Speed is the single largest contributing factor to road deaths in Ireland. Approximately 40% of fatal accidents are caused by excessive or inappropriate speed. This study focuses on how dangerous driving behaviours may be addressed through social marketing. This study analyses the appropriate level of fear that needs to be induced in order to change young male driving behaviour.
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Friction plays a key role in causing slipperiness as a low coefficient of friction on the road may result in slippery and hazardous conditions. Analyzing the strong relation between friction and accident risk on winter roads is a difficult task. Many weather forecasting organizations use a variety of standard and bespoke methods to predict the coefficient of friction on roads. This article proposes an approach to predict the extent of slipperiness by building and testing an expert system. It estimates the coefficient of friction on winter roads in the province of Dalarna, Sweden using the prevailing weather conditions as a basis. Weather data from the road weather information system, Sweden (RWIS) was used. The focus of the project was to use the expert system as a part of a major project in VITSA, within the domain of intelligent transport systems
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This edition of the FAL Bulletin approaches road safety and the need for urgent, coordinated measures to be established between the public and private sectors and civil society in order to prevent the rapid increase in deaths and casualties in road accidents in Latin America and the Caribbean, an issue which is threatening the sustainability of regional development.
Resumo:
This paper presents a modeling effort for developing safety performance models (SPM) for urban intersections for three major Brazilian cities. The proposed methodology for calibrating SPM has been divided into the following steps: defining the safety study objective, choosing predictive variables and sample size, data acquisition, defining model expression and model parameters and model evaluation. Among the predictive variables explored in the calibration phase were exposure variables (AADT), number of lanes, number of approaches and central median status. SPMs were obtained for three cities: Fortaleza, Belo Horizonte and Brasilia. The SPM developed for signalized intersections in Fortaleza and Belo Horizonte had the same structure and the most significant independent variables, which were AADT entering the intersection and number of lanes, and in addition, the coefficient of the best models were in the same range of values. For Brasilia, because of the sample size, the signalized and unsignalized intersections were grouped, and the AADT was split in minor and major approaches, which were the most significant variables. This paper also evaluated SPM transferability to other jurisdiction. The SPM for signalized intersections from Fortaleza and Belo Horizonte have been recalibrated (in terms of the COx) to the city of Porto Alegre. The models were adjusted following the Highway Safety Manual (HSM) calibration procedure and yielded C-x of 0.65 and 2.06 for Fortaleza and Belo Horizonte SPM respectively. This paper showed the experience and future challenges toward the initiatives on development of SPMs in Brazil, that can serve as a guide for other countries that are in the same stage in this subject. (C) 2014 Elsevier Ltd. All rights reserved.
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The objective of this paper is compare the common traffic lights (CTL) to three different types of traffic lights with countdown displays (SCD) and assess their effects on road safety and capacity. This comparison is required because the results found in the literature are divergent among countries and cities, and one of the SCD analyzed in our study is different from the SCD used worldwide. An observational before-after study was conducted to evaluate the safety and capacity in a period of one year before and one year after the implementation of the SCD in three Brazilian cities. The results indicate that the SCD models 1 and 3 had around 35%±14% reduction in the total number of accidents; the model 2, does not have significant reduction. In order to perform the capacity analysis a framework for data collection and an adaptation for estimation of initial lost time in each phase were developed. Considering the capacity analysis there was a reduction around 11% in the lost time in SCD model 1, 7% in SCD model 2 and 3% in SCD model 3. However the implications of this on capacity are trifle due to a small increase in the average headways for all SCD models compare to CTL.
Resumo:
Public Private Partnerships (PPPs) are mostly implemented to circumvent budgetary constraints, and to encourage efficiency and quality in the provision of public infrastructure in order to reach social welfare. One of the ways of reaching the latter objective is by the introduction of performance based standards tied to bonuses and penalties to reward or punish the performance of the contractor. This paper focuses on the implementation of safety based incentives in PPPs in such a way that the better the safety outcome the greater larger will be the economic reward to the contractor. The main aim of this paper is to identify whether the incentives to improve road safety in PPPs are ultimately effective in improving safety ratios in Spain. To that end, Poisson and negative binomial regression models have been applied using information of motorways of the Spanish network of 2006. The findings indicate that even though road safety is highly influenced by variables that are not much controllable by the contractor such as the Average Annual Daily Traffic and the percentage of heavy vehicles, the implementation of safety incentives in PPPs has a positive influence in the reduction of fatalities, injuries and accidents.
Resumo:
Many countries around the world are implementing Public?Private?Partnership (PPP) contacts to manage road infrastructure. In some of these contracts the public sector introduces economic incentives to the private operator to foster the accomplishment of social goals. One of the incentives that have been introduced in some PPP contracts is related to safety in such a way that the better the safety outcome the greater will be the economic reward to the contractor. The aim of this paper is at identify whether the incentives to improve road safety in highway PPPs are ultimately effective in improving safety ratios. To this end Poisson and negative binomial regression models have been applied using information from highway sections in Spain. The findings indicate that even though road safety is highly influenced by variables that are not much controllable by the contractor such as the Average Annual Daily Traffic and the percentage of heavy vehicles, the implementation of safety incentives in PPPs has a positive influence in the reduction of fatalities, injuries and accidents.
Resumo:
Sight distance is of major importance for road safety either when designing new roads or analysing the alignment of existing roads. It is essential that available sight distance in roads is long enough for emergency stops or overtaking manoeuvres. Also, it is vital for engineers/researchers that the tools used for that analysis are both powerful and intuitive. Based on ArcGIS, the application to be presented not only performs an exhaustive sight distance calculation, but allows an accurate analysis of 3D alignment, using all new tools, from a Digital Elevation Model and vehicle trajectory. The software has been successfully utilised to analyse several two-lane rural roads in Spain. In addition, the software produces thematic maps representing sight distance in which supplementary information about crashes, traffic flow, speed or design consistency could be included, allowing traffic safety studies.
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Using the Bayesian approach as the model selection criteria, the main purpose in this study is to establish a practical road accident model that can provide a better interpretation and prediction performance. For this purpose we are using a structural explanatory model with autoregressive error term. The model estimation is carried out through Bayesian inference and the best model is selected based on the goodness of fit measures. To cross validate the model estimation further prediction analysis were done. As the road safety measures the number of fatal accidents in Spain, during 2000-2011 were employed. The results of the variable selection process show that the factors explaining fatal road accidents are mainly exposure, economic factors, and surveillance and legislative measures. The model selection shows that the impact of economic factors on fatal accidents during the period under study has been higher compared to surveillance and legislative measures.
Resumo:
Because of the high number of crashes occurring on highways, it is necessary to intensify the search for new tools that help in understanding their causes. This research explores the use of a geographic information system (GIS) for an integrated analysis, taking into account two accident-related factors: design consistency (DC) (based on vehicle speed) and available sight distance (ASD) (based on visibility). Both factors require specific GIS software add-ins, which are explained. Digital terrain models (DTMs), vehicle paths, road centerlines, a speed prediction model, and crash data are integrated in the GIS. The usefulness of this approach has been assessed through a study of more than 500 crashes. From a regularly spaced grid, the terrain (bare ground) has been modeled through a triangulated irregular network (TIN). The length of the roads analyzed is greater than 100 km. Results have shown that DC and ASD could be related to crashes in approximately 4% of cases. In order to illustrate the potential of GIS, two crashes are fully analyzed: a car rollover after running off road on the right side and a rear-end collision of two moving vehicles. Although this procedure uses two software add-ins that are available only for ArcGIS, the study gives a practical demonstration of the suitability of GIS for conducting integrated studies of road safety.