293 resultados para Roadside


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Most of the air quality modelling work has been so far oriented towards deterministic simulations of ambient pollutant concentrations. This traditional approach, which is based on the use of one selected model and one data set of discrete input values, does not reflect the uncertainties due to errors in model formulation and input data. Given the complexities of urban environments and the inherent limitations of mathematical modelling, it is unlikely that a single model based on routinely available meteorological and emission data will give satisfactory short-term predictions. In this study, different methods involving the use of more than one dispersion model, in association with different emission simulation methodologies and meteorological data sets, were explored for predicting best CO and benzene estimates, and related confidence bounds. The different approaches were tested using experimental data obtained during intensive monitoring campaigns in busy street canyons in Paris, France. Three relative simple dispersion models (STREET, OSPM and AEOLIUS) that are likely to be used for regulatory purposes were selected for this application. A sensitivity analysis was conducted in order to identify internal model parameters that might significantly affect results. Finally, a probabilistic methodology for assessing urban air quality was proposed.

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In this paper, a novel method for modelling a scaled vehicle–barrier crash test similar to the 20◦ angled barrier test specified in EN 1317 is reported. The intended application is for proof-of-concept evaluation of novel roadside barrier designs, and as a cost-effective precursor to full-scale testing or detailed computational modelling. The method is based on the combination of the conservation of energy law and the equation of motion of a spring mass system representing the impact, and shows, for the first time, the feasibility of applying classical scaling theories to evaluation of roadside barrier design. The scaling method is used to set the initial velocity of the vehicle in the scaled test and to provide scaling factors to convert the measured vehicle accelerations in the scaled test to predicted full-scale accelerations. These values can then be used to calculate the Acceleration Severity Index score of the barrier for a full-scale test. The theoretical validity of the method is demonstrated by comparison to numerical simulations of scaled and full-scale angled barrier impacts using multibody analysis implemented in the crash simulation software MADYMO. Results show a maximum error of 0.3% ascribable to the scaling method.

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This paper evaluates the potential of gabions as roadside safety barriers. Gabions have the capacity to blend into natural landscape, suggesting that they could be used as a safety barrier for low-volume road in scenic environments. In fact, gabions have already been used for this purpose in Nepal, but the impact response was not evaluated. This paper reports on numerical and experimental investigations performed on a new gabion barrier prototype. To assess the potential use as a roadside barrier, the optimal gabion unit size and mass were investigated using multibody analysis and four sets of 1:4 scaled crash tests were carried out to study the local vehicle-barrier interaction. The barrier prototype was then finalised and subjected to a TB31 crash test according to the European EN1317 standard for N1 safety barriers. The test resulted in a failure due to the rollover of the vehicle and tearing of the gabion mesh yielding a large working width. It was found that although the system potentially has the necessary mass to contain a vehicle, the barrier front face does not have the necessary stiffness and strength to contain the gabion stone filling and hence redirect the vehicle. In the EN1317 test, the gabion barrier acted as a ramp for the impacting vehicle, causing rollover. 

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In this paper the tracking system used to perform a scaled vehicle-barrier crash test is reported. The scaled crash test was performed as part of a wider project aimed at designing a new safety barrier making use of natural building materials. The scaled crash test was designed and performed as a proof of concept of the new mass-based safety barriers and the study was composed of two parts: the scaling technique and of a series of performed scaled crash tests. The scaling method was used for 1) setting the scaled test impact velocity so that energy dissipation and momentum transferring, from the car to the barrier, can be reproduced and 2) predicting the acceleration, velocity and displacement values occurring in the full-scale impact from the results obtained in a scaled test. To achieve this goal the vehicle and barrier displacements were to be recorded together with the vehicle accelerations and angular velocities. These quantities were measured during the tests using acceleration sensors and a tracking system. The tracking system was composed of a high speed camera and a set of targets to measure the vehicle linear and angular velocities. A code was developed to extract the target velocities from the videos and the velocities obtained were then compared with those obtained integrating the accelerations provided by the sensors to check the reliability of the method.

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Run Off Road (ROR) crashes are road accidents that often result in severe injuries or fatalities. To reduce the severity of ROR crashes, “forgiving roadsides” need to be designed and this includes identifying situations where there is a need for a Vehicle Restraint System (VRS) and what appropriate VRS should be selected for a specific location and traffic condition. Whilst there are standards covering testing, evaluation and classification of VRS within Europe (EN1317 parts 1 to 8), their selection, location and installation requirements are typically based upon national guidelines and standards, often produced by National Road Authorities (NRA) and/or overseeing organisations. Due to local conditions, these national guidelines vary across Europe.
The European SAVeRS project funded by CEDR has developed a practical and readily understandable VRS guidance document and a user-friendly software tool which allow designers and road administrations to select the most appropriate solution in different road and traffic conditions.
This paper describes the main outcomes of the project, the process to select the most appropriate roadside barrier, and the user friendly SAVeRS tool.

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Roadside surveys such as the Breeding Bird Survey (BBS) are widely used to assess the relative abundance of bird populations. The accuracy of roadside surveys depends on the extent to which surveys from roads represent the entire region under study. We quantified roadside land cover sampling bias in Tennessee, USA, by comparing land cover proportions near roads to proportions of the surrounding region. Roadside surveys gave a biased estimate of patterns across the region because some land cover types were over- or underrepresented near roads. These biases changed over time, introducing varying levels of distortion into the data. We constructed simulated population trends for five bird species of management interest based on these measured roadside sampling biases and on field data on bird abundance. These simulations indicated that roadside surveys may give overly negative assessments of the population trends of early successional birds and of synanthropic birds, but not of late-successional birds. Because roadside surveys are the primary source of avian population trend information in North America, we conclude that these surveys should be corrected for roadside land cover sampling bias. In addition, current recommendations about the need to create more early successional habitat for birds may need reassessment in the light of the undersampling of this habitat by roads.

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Grassland bird species continue to decline steeply across North America. Road-based surveys such as the North American Breeding Bird Survey (BBS) are often used to estimate trends and population sizes and to build species distribution models for grassland birds, although roadside survey counts may introduce bias in estimates because of differences in habitats along roadsides and in off-road surveys. We tested for differences in land cover composition and in the avian community on 21 roadside-based survey routes and in an equal number of adjacent off-road walking routes in the grasslands of southern Alberta, Canada. Off-road routes (n = 225 point counts) had more native grassland and short shrubs and less fallow land and road area than the roadside routes (n = 225 point counts). Consequently, 17 of the 39 bird species differed between the two route types in frequency of occurrence and relative abundance, measured using an indicator species analysis. Six species, including five obligate grassland species, were more prevalent at off-road sites; they included four species listed under the Canadian federal Species At Risk Act or listed by the Committee on the Status of Endangered Wildlife in Canada: Sprague’s Pipit (Anthus spragueii), Baird’s Sparrow (Ammodramus bairdii), the Chestnut-collared Longspur (Calcarius ornatus), and McCown’s Longspur (Rhynchophanes mccownii). The six species were as much as four times more abundant on off-road sites. Species more prevalent along roadside routes included common species and those typical of farmland and other human-modified habitats, e.g., the European Starling (Sturnus vulgaris), the Black-billed Magpie (Pica hudsonia), and the House Sparrow (Passer domesticus). Differences in avian community composition between roadside and off-road surveys suggest that the use of BBS data when generating population estimates or distribution models may overestimate certain common species and underestimate others of conservation concern. Our results highlight the need to develop appropriate corrections for bias in estimates derived from roadside sampling, and the need to design surveys that sample bird communities across a more representative cross-section of the landscape, both near and far from roads. 

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The North American Breeding Bird Survey (BBS) is the principal source of data to inform researchers about the status of and trend for boreal forest birds. Unfortunately, little BBS coverage is available in the boreal forest, where increasing concern over the status of species breeding there has increased interest in northward expansion of the BBS. However, high disturbance rates in the boreal forest may complicate roadside monitoring. If the roadside sampling frame does not capture variation in disturbance rates because of either road placement or the use of roads for resource extraction, biased trend estimates might result. In this study, we examined roadside bias in the proportional representation of habitat disturbance via spatial data on forest “loss,” forest fires, and anthropogenic disturbance. In each of 455 BBS routes, the area disturbed within multiple buffers away from the road was calculated and compared against the area disturbed in degree blocks and BBS strata. We found a nonlinear relationship between bias and distance from the road, suggesting forest loss and forest fires were underrepresented below 75 and 100 m, respectively. In contrast, anthropogenic disturbance was overrepresented at distances below 500 m and underrepresented thereafter. After accounting for distance from road, BBS routes were reasonably representative of the degree blocks they were within, with only a few strata showing biased representation. In general, anthropogenic disturbance is overrepresented in southern strata, and forest fires are underrepresented in almost all strata. Similar biases exist when comparing the entire road network and the subset sampled by BBS routes against the amount of disturbance within BBS strata; however, the magnitude of biases differed. Based on our results, we recommend that spatial stratification and rotating panel designs be used to spread limited BBS and off-road sampling effort in an unbiased fashion and that new BBS routes be established where sufficient road coverage exists.