815 resultados para Trucks


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In 2004, with the increasing overloading restriction requirements of society in Anhui, a provincial comprehensive overloading transportation survey has been developed to take evaluations on overloading actuality and enforcement efficiency with the support of the World Bank. A total of six site surveys were conducted at Hefei, Fuyang, Luan, Wuhu, Huainan and Huangshan Areas with four main contents respectively: traffic volume, axle load, freight information and registration information. Via statistical analysis on the survey data, conclusions were gained that: vehicle overloading are very universal and serious problems at arterial highways in Anhui now. The traffic loads have far exceeded the designed endure capacity of highways and have caused prevalent premature pavement damage, especially for rigid pavement. The overloading trucks are unimpeded engaged in highway freight transportation actually due to the disordered overloading enforcement strategies and the deficient inspecting technologies.

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Purpose: The purpose of this paper is to present an artificial neural network (ANN) model that predicts earthmoving trucks condition level using simple predictors; the model’s performance is compared to the respective predictive accuracy of the statistical method of discriminant analysis (DA).

Design/methodology/approach: An ANN-based predictive model is developed. The condition level predictors selected are the capacity, age, kilometers travelled and maintenance level. The relevant data set was provided by two Greek construction companies and includes the characteristics of 126 earthmoving trucks.

Findings: Data processing identifies a particularly strong connection of kilometers travelled and maintenance level with the earthmoving trucks condition level. Moreover, the validation process reveals that the predictive efficiency of the proposed ANN model is very high. Similar findings emerge from the application of DA to the same data set using the same predictors.

Originality/value: Earthmoving trucks’ sound condition level prediction reduces downtime and its adverse impact on earthmoving duration and cost, while also enhancing the maintenance and replacement policies effectiveness. This research proves that a sound condition level prediction for earthmoving trucks is achievable through the utilization of easy to collect data and provides a comparative evaluation of the results of two widely applied predictive methods.

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In her December 2014 interview with Michelle Dubert-Bellrichard, Louise “Lou” Trucks detailed her thoughts and memories of her time at Winthrop. Trucks spoke of the time period from 1960-1964 as a music and music education double major. Trucks shared the benefits of being a music major, her involvement in campus traditions and organizations, and the rigor of her studies. Trucks concludes her interview detailing her life after Winthrop in Bloomington, IN and Rochester, NY. This interview was conducted for inclusion into the Louise Pettus Archives and Special Collections Oral History Program.

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In the last few years, the European Union (EU) has become greatly concerned about the environmental costs of road transport in Europe as a result of the constant growth in the market share of trucks and the steady decline in the market share of railroads. In order to reverse this trend, the EU is promoting the implementation of additional charges for heavy goods vehicles (HGV) on the trunk roads of the EU countries. However, the EU policy is being criticised because it does not address the implementation of charges to internalise the external costs produced by automobiles and other transport modes such as railroad. In this paper, we first describe the evolution of the HGV charging policy in the EU, and then assess its practical implementation across different European countries. Second, and of greater significance, by using the case study of Spain, we evaluate to what extent the current fees on trucks and trains reflect their social marginal costs, and consequently lead to an allocative-efficient outcome. We found that for the average case in Spain the truck industry meets more of the marginal social cost produced by it than does the freight railroad industry. The reason for this lies in the large sums of money paid by truck companies in fuel taxes, and the subsidies that continue to be granted by the government to the railroads.

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Outside of relatively limited crash testing with large trucks, very little is known regarding the performance of traffic barriers subjected to real-world large truck impacts. The purpose of this study was to investigate real-world large truck impacts into traffic barriers to determine barrier crash involvement rates, the impact performance of barriers not specifically designed to redirect large trucks, and the real-world performance of large-truck-specific barriers. Data sources included the Fatality Analysis Reporting System (2000-2009), the General Estimates System (2000-2009) and 155 in-depth large truck-to-barrier crashes from the Large Truck Crash Causation Study. Large truck impacts with a longitudinal barrier were found to comprise 3 percent of all police-reported longitudinal barrier impacts and roughly the same proportion of barrier fatalities. Based on a logistic regression model predicting barrier penetration, large truck barrier penetration risk was found to increase by a factor of 6 for impacts with barriers designed primarily for passenger vehicles. Although large-truck-specific barriers were found to perform better than non-heavy vehicle specific barriers, the penetration rate of these barriers were found to be 17 percent. This penetration rate is especially a concern because the higher test level barriers are designed to protect other road users, not the occupants of the large truck. Surprisingly, barriers not specifically designed for large truck impacts were found to prevent large truck penetration approximately half of the time. This suggests that adding costlier higher test level barriers may not always be warranted, especially on roadways with lower truck volumes.

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The study aim was to determine whether using automated side loader (ASL) trucks in higher proportions compared to other types of trucks for residential waste collection results in lower injury rates (from all causes). The primary hypothesis was that the risk of injury to workers was lower for those who work with ASL trucks than for workers who work with other types of trucks used in residential waste collection. To test this hypothesis, data were collected from one of the nation’s largest companies in the solid waste management industry. Different local operating units (i.e. facilities) in the company used different types of trucks to varying degrees, which created a special opportunity to examine refuse collection injuries and illnesses and the risk reduction potential of ASL trucks.^ The study design was ecological and analyzed end-of-year data provided by the company for calendar year 2007. During 2007, there were a total of 345 facilities which provided residential services. Each facility represented one observation.^ The dependent variable – injury and illness rate, was defined as a facility’s total case incidence rate (TCIR) recorded in accordance with federal OSHA requirements for the year 2007. The TCIR is the rate of total recordable injury and illness cases per 100 full-time workers. The independent variable, percent of ASL trucks, was calculated by dividing the number of ASL trucks by the total number of residential trucks at each facility.^ Multiple linear regression models were estimated for the impact of the percent of ASL trucks on TCIR per facility. Adjusted analyses included three covariates: median number of hours worked per week for residential workers; median number of months of work experience for residential workers; and median age of residential workers. All analyses were performed with the statistical software, Stata IC (version 11.0).^ The analyses included three approaches to classifying exposure, percent of ASL trucks. The first approach included two levels of exposure: (1) 0% and (2) >0 - <100%. The second approach included three levels of exposure: (1) 0%, (2) ≥ 1 - < 100%, and (3) 100%. The third approach included six levels of exposure to improve detection of a dose-response relationship: (1) 0%, (2) 1 to <25%, (3) 25 to <50%, (4) 50 to <75%, (5) 75 to <100%, and (6) 100%. None of the relationships between injury and illness rate and percent ASL trucks exposure levels was statistically significant (i.e., p<0.05), even after adjustment for all three covariates.^ In summary, the present study shows that there is some risk reduction impact of ASL trucks but not statistically significant. The covariates demonstrated a varied yet more modest impact on the injury and illness rate but again, none of the relationships between injury and illness rate and the covariates were statistically significant (i.e., p<0.05). However, as an ecological study, the present study also has the limitations inherent in such designs and warrants replication in an individual level cohort design. Any stronger conclusions are not suggested.^

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In the last few years, the European Union (EU) has become greatly concerned about the environmental costs of road transport in Europe as a result of the constant growth in the market share of trucks and the steady decline in the market share of railroads. In order to reverse this trend, the EU is promoting the implementation of additional charges for heavy goods vehicles (HGV) on the trunk roads of the EU countries. However, the EU policy is being criticised because it does not address the implementation of charges to internalise the external costs produced by automobiles and other transport modes such as railroad. In this paper, we first describe the evolution of the HGV charging policy in the EU, and then assess its practical implementation across different European countries. Second, and of greater significance, by using the case study of Spain, we evaluate to what extent the current fees on trucks and trains reflect their social marginal costs, and consequently lead to an allocative-efficient outcome. We found that for the average case in Spain the truck industry meets more of the marginal social cost produced by it than does the freight railroad industry. The reason for this lies in the large sums of money paid by truck companies in fuel taxes, and the subsidies that continue to be granted by the government to the railroads.

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Mode of access: Internet.

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Texas State Department of Highways and Public Transportation, Transportation Planning Division, Austin

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Energy Department, Office of Operational Safety Programs, Washington, D.C.

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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

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National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.