953 resultados para road safety application


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Blowing snow can cause significant problems for mobility and safety during winter weather in three distinct ways. It may drift onto the road, thus requiring almost continuous plowing while the wind is blowing (which may occur when a given winter storm is over). Snow may drift onto wet pavement (perhaps caused by ice control chemicals) and dilute out the chemicals on the road, creating ice on the road. And sufficient blowing snow can cause a major deterioration in visibility on the road, a factor which has been shown to be significant in winter crashes. The problem of blowing snow can be very effectively addressed by creating a snow storage device upwind of the road that requires protection from snow drifting. Typically, these storage devices are fences. Extensive design guidance exists for the required height and placement of such fences for a given annual snowfall and given local topography. However, the design information on the placement of living snow fences is less complete. The purpose of this report is to present the results of three seasons of study on using standing corn as snow fences. In addition, the experience of using switch grass as a snow storage medium is also presented. On the basis of these experimental data, a design guide has been developed that makes use of the somewhat unique snow storage characteristics of standing corn snow fences. The results of the field tests on using standing corn showed that multiple rows of standing corn store snow rather differently than a traditional wooden snow fence. Specifically, while a traditional fence stores most of the snow downwind from the fence (and thus must be placed a significant distance upwind of the road to be protected, specifically at least 35 times the snow fence height) rows of standing corn store the majority of the snow within the rows. Results from the three winters of testing show that the standing corn snow fences can store as much snow within the rows of standing corn as a traditional fence of typical height for operation in Iowa (4 to 6 feet) can store. This finding is significant because it means that the snow fences can be placed at the edge of the farmer’s field closest to the road, and still be effective. This is typically much more convenient for the farmer and thus may mean that more farmers would be willing to participate in a program that uses standing corn than in traditional programs. ii On the basis of the experimental data, design guidance for the use of standing corn as a snow storage device in Iowa is given in the report. Specifically, it is recommended that if the fetch in a location to be protected is less than 5,000 feet, then 16 rows of standing corn should be used, at the edge of the field adjacent to the right of way. If the fetch is greater than 5,000 feet, then 24 rows of standing corn should be used. This is based on a row spacing of 22 inches. Further, it should be noted that these design recommendations are ONLY for the State of Iowa. Other states of course have different winter weather and without extensive further study, it cannot be said that these guidelines would be effective in other locations with other winter conditions.

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This paper explores the effects of a standard influencing care choice. Firm(s) may increase the probability of offering safe products by incurring a cost. Under duopoly, they compete either in prices or in quantities. Under perfect information about safety for consumers, the selected standard that corrects a safety underinvestment is always compatible with competition. Safety over investment only emerges under competition in quantities and relatively low values of the cost. Under imperfect information about safety for consumers, the standard leads to a monopoly situation. However, for relatively large values of the cost, a standard cannot impede the market failure coming from the lack of information.

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We analyze crash data collected by the Iowa Department of Transportation using Bayesian methods. The data set includes monthly crash numbers, estimated monthly traffic volumes, site length and other information collected at 30 paired sites in Iowa over more than 20 years during which an intervention experiment was set up. The intervention consisted in transforming 15 undivided road segments from four-lane to three lanes, while an additional 15 segments, thought to be comparable in terms of traffic safety-related characteristics were not converted. The main objective of this work is to find out whether the intervention reduces the number of crashes and the crash rates at the treated sites. We fitted a hierarchical Poisson regression model with a change-point to the number of monthly crashes per mile at each of the sites. Explanatory variables in the model included estimated monthly traffic volume, time, an indicator for intervention reflecting whether the site was a “treatment” or a “control” site, and various interactions. We accounted for seasonal effects in the number of crashes at a site by including smooth trigonometric functions with three different periods to reflect the four seasons of the year. A change-point at the month and year in which the intervention was completed for treated sites was also included. The number of crashes at a site can be thought to follow a Poisson distribution. To estimate the association between crashes and the explanatory variables, we used a log link function and added a random effect to account for overdispersion and for autocorrelation among observations obtained at the same site. We used proper but non-informative priors for all parameters in the model, and carried out all calculations using Markov chain Monte Carlo methods implemented in WinBUGS. We evaluated the effect of the four to three-lane conversion by comparing the expected number of crashes per year per mile during the years preceding the conversion and following the conversion for treatment and control sites. We estimated this difference using the observed traffic volumes at each site and also on a per 100,000,000 vehicles. We also conducted a prospective analysis to forecast the expected number of crashes per mile at each site in the study one year, three years and five years following the four to three-lane conversion. Posterior predictive distributions of the number of crashes, the crash rate and the percent reduction in crashes per mile were obtained for each site for the months of January and June one, three and five years after completion of the intervention. The model appears to fit the data well. We found that in most sites, the intervention was effective and reduced the number of crashes. Overall, and for the observed traffic volumes, the reduction in the expected number of crashes per year and mile at converted sites was 32.3% (31.4% to 33.5% with 95% probability) while at the control sites, the reduction was estimated to be 7.1% (5.7% to 8.2% with 95% probability). When the reduction in the expected number of crashes per year, mile and 100,000,000 AADT was computed, the estimates were 44.3% (43.9% to 44.6%) and 25.5% (24.6% to 26.0%) for converted and control sites, respectively. In both cases, the difference in the percent reduction in the expected number of crashes during the years following the conversion was significantly larger at converted sites than at control sites, even though the number of crashes appears to decline over time at all sites. Results indicate that the reduction in the expected number of sites per mile has a steeper negative slope at converted than at control sites. Consistent with this, the forecasted reduction in the number of crashes per year and mile during the years after completion of the conversion at converted sites is more pronounced than at control sites. Seasonal effects on the number of crashes have been well-documented. In this dataset, we found that, as expected, the expected number of monthly crashes per mile tends to be higher during winter months than during the rest of the year. Perhaps more interestingly, we found that there is an interaction between the four to three-lane conversion and season; the reduction in the number of crashes appears to be more pronounced during months, when the weather is nice than during other times of the year, even though a reduction was estimated for the entire year. Thus, it appears that the four to three-lane conversion, while effective year-round, is particularly effective in reducing the expected number of crashes in nice weather.

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Audit report on applying agreed-upon procedures for the City of Linden’s compliance with road use tax requirements for the period July 1, 1999 through June 30, 2004

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Audit report on Highway Safety Projects administered by The Integer Group Midwest for the year ended September 30, 2006

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Audit report on the Iowa Department of Public Safety for the year ended June 30, 2006

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A vehicle may leave its travel lane for a number of reasons, such as driver error, poor surface conditions, or avoidance of a collision with another vehicle in the travel lane. When a vehicle leaves the travel lane, pavement edge drop-off poses a potential safety hazard because significant vertical differences between surfaces can affect vehicle stability and reduce a driver’s ability to handle the vehicle. Numerous controlled studies have tested driver response to encountering drop-offs under various conditions, including different speeds, vehicle types, drop-off height and shape, and tire scrubbing versus non-scrubbing conditions. The studies evaluated the drivers’ ability to return to and recover within their own travel lane after leaving the roadway and encountering a drop-off. Many of these studies, however, have used professional drivers as test subjects, so results may not always apply to the population of average drivers. Furthermore, test subjects are always briefed on what generally is to be expected and how to respond; thus, the sense of surprise that a truly naïve driver may experience upon realizing that one or two of his or her tires have just dropped off the edge of the pavement, is very likely diminished. Additionally, the studies were carried out under controlled conditions. The actual impact of pavement edge drop-off on drivers’ ability to recover safely once they leave the roadway, however, is not well understood under actual driving conditions. Additionally, little information is available that quantifies the number or severity of crashes that occur where pavement edge drop-off may have been a contributing factor. Without sufficient information about the frequency of edge drop-off-related crashes, agencies are not fully able to measure the economic benefits of investment decisions, evaluate the effectiveness of different treatments to mitigate edge drop-off, or focus maintenance resources. To address these issues, this report details research to quantify the contribution of pavement edge drop-off to crash frequency and severity. Additionally, the study evaluated federal and state guidance in sampling and addressing pavement edge drop-off and quantified the extent of pavement edge drop-off in two states. This study focused on rural two-lane paved roadways with unpaved shoulders, since they are often high speed facilities (55+ mph), have varying levels of maintenance, and are likely to be characterized by adverse roadway conditions such as narrow lanes or no shoulders.

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Quarterly publication of the Governor's Traffic Safety Bureau, Iowa Department of Public Safety containing traffic safety and related information and news articles

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Quarterly publication of the Governor's Traffic Safety Bureau, Iowa Department of Public Safety containing traffic safety and related information and news articles

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Achieving a high degree of dependability in complex macro-systems is challenging. Because of the large number of components and numerous independent teams involved, an overview of the global system performance is usually lacking to support both design and operation adequately. A functional failure mode, effects and criticality analysis (FMECA) approach is proposed to address the dependability optimisation of large and complex systems. The basic inductive model FMECA has been enriched to include considerations such as operational procedures, alarm systems. environmental and human factors, as well as operation in degraded mode. Its implementation on a commercial software tool allows an active linking between the functional layers of the system and facilitates data processing and retrieval, which enables to contribute actively to the system optimisation. The proposed methodology has been applied to optimise dependability in a railway signalling system. Signalling systems are typical example of large complex systems made of multiple hierarchical layers. The proposed approach appears appropriate to assess the global risk- and availability-level of the system as well as to identify its vulnerabilities. This enriched-FMECA approach enables to overcome some of the limitations and pitfalls previously reported with classical FMECA approaches.

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One of the challenges that faces the winter maintainer is how much chemical to apply to the road under given conditions. Insufficient chemical can lead to the road surface becoming slick, and the road thus becoming unsafe. In all likelihood, additional applications will have to be made, requiring additional effort and use of resources. However, too much chemical can also be bad. While an excess of chemical will ensure (in most circumstances) that a safe road condition is achieved, it may also result in a substantial waste of chemical (with associated costs for this waste) and in ancillary damage to the road itself and to the surrounding environment. Ideally, one should apply what might be termed the “goldilocks” amount of chemical to the road: Not too much, and not too little, but just right. Of course the reality of winter maintenance makes achieving the “goldilocks” application rate somewhat of a fairy tale. In the midst of a severe storm, when conditions are poor and getting worse, the last thing on a plow operator’s mind is a minute adjustment in the amount of chemical being applied to the road. However, there may be considerable benefit and substantial savings to be achieved if chemical applications can be optimized to some degree, so that wastage is minimized without compromising safety. The goal of this study was to begin to develop such information through a series of laboratory studies in which the force needed to scrape ice from concrete blocks was measured, under a variety of chemical application conditions.

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Previous research on pavement markings from a safety perspective tackled various issues such as pavement marking retroreflectivity variability, relationship between pavement marking retroreflectivity and driver visibility, or pavement marking improvements and safety. A recent research interest in this area has been to find a correlation between retroreflectivity and crashes, but a significant statistical relationship has not yet been found. This study investigates such a possible statistical relationship by analyzing five years of pavement marking retroreflectivity data collected by the Iowa Department of Transportation (DOT) on all state primary roads and corresponding crash and traffic data. This study developed a spatial-temporal database using measured retroreflectivity data to account for the deterioration of pavement markings over time along with statewide crash data to attempt to quantify a relationship between crash occurrence probability and pavement marking retroreflectivity. First, logistic regression analyses were done for the whole data set to find a statistical relationship between crash occurrence probability and identified variables, which are road type, line type, retroreflectivity, and traffic (vehicle miles traveled). The analysis looked into subsets of the data set such as road type, retroreflectivity measurement source, high crash routes, retroreflectivity range, and line types. Retroreflectivity was found to have a significant effect in crash occurrence probability for four data subsets—interstate, white edge line, yellow edge line, and yellow center line data. For white edge line and yellow center line data, crash occurrence probability was found to increase by decreasing values of retroreflectivity.

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Public travel by motor vehicles is often necessary in road and street sections that have been officially closed for construction, repair, and/or other reasons. This authorization is permitted in order to provide access to homes and businesses located beyond the point of closure. The MUTCD does address appropriate use of specific regulatory signs at the entrance to closed sections; however, direct guidance for temporary traffic control measures within these areas is not included but may be needed. Interpretation and enforcement of common practices may vary among transportation agencies. For example, some law enforcement officers in Iowa have indicated a concern regarding enforcement and jurisdiction of traffic laws in these areas because the Code of Iowa only appears to address violations on roadways open to “public travel.” Enforcement of traffic laws in closed road sections is desirable to maintain safety for workers and for specifically authorized road users. In addition, occasional unauthorized entry by motor vehicles is experienced in closed road areas causing property damage. Citations beyond simple trespass may be advisable to provide better security for construction sites, reduce economic losses from damage to completed work, and create safer work zones.

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Integrated approaches using different in vitro methods in combination with bioinformatics can (i) increase the success rate and speed of drug development; (ii) improve the accuracy of toxicological risk assessment; and (iii) increase our understanding of disease. Three-dimensional (3D) cell culture models are important building blocks of this strategy which has emerged during the last years. The majority of these models are organotypic, i.e., they aim to reproduce major functions of an organ or organ system. This implies in many cases that more than one cell type forms the 3D structure, and often matrix elements play an important role. This review summarizes the state of the art concerning commonalities of the different models. For instance, the theory of mass transport/metabolite exchange in 3D systems and the special analytical requirements for test endpoints in organotypic cultures are discussed in detail. In the next part, 3D model systems for selected organs--liver, lung, skin, brain--are presented and characterized in dedicated chapters. Also, 3D approaches to the modeling of tumors are presented and discussed. All chapters give a historical background, illustrate the large variety of approaches, and highlight up- and downsides as well as specific requirements. Moreover, they refer to the application in disease modeling, drug discovery and safety assessment. Finally, consensus recommendations indicate a roadmap for the successful implementation of 3D models in routine screening. It is expected that the use of such models will accelerate progress by reducing error rates and wrong predictions from compound testing.

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Traffic safety engineers are among the early adopters of Bayesian statistical tools for analyzing crash data. As in many other areas of application, empirical Bayes methods were their first choice, perhaps because they represent an intuitively appealing, yet relatively easy to implement alternative to purely classical approaches. With the enormous progress in numerical methods made in recent years and with the availability of free, easy to use software that permits implementing a fully Bayesian approach, however, there is now ample justification to progress towards fully Bayesian analyses of crash data. The fully Bayesian approach, in particular as implemented via multi-level hierarchical models, has many advantages over the empirical Bayes approach. In a full Bayesian analysis, prior information and all available data are seamlessly integrated into posterior distributions on which practitioners can base their inferences. All uncertainties are thus accounted for in the analyses and there is no need to pre-process data to obtain Safety Performance Functions and other such prior estimates of the effect of covariates on the outcome of interest. In this slight, fully Bayesian methods may well be less costly to implement and may result in safety estimates with more realistic standard errors. In this manuscript, we present the full Bayesian approach to analyzing traffic safety data and focus on highlighting the differences between the empirical Bayes and the full Bayes approaches. We use an illustrative example to discuss a step-by-step Bayesian analysis of the data and to show some of the types of inferences that are possible within the full Bayesian framework.