• International Journal of Highway Engineering
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• v.16 no.5
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• pp.173-182
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• 2014

PURPOSES : The purpose of the study is to a) explore the operating speed of trucks on rural highways affected by road geometry, and thereby b) develop a predictive model for the operating speed of trucks on rural highways. METHODS : Considering that most of the existing studies have focused on cars, the current study aimed to predict the operating speed of trucks by conducting linear regression analysis on the speed data of trucks operating on the linear-curved-linear portions of the road as a single set. RESULTS : The operating speed in the plane curve portion increased with the length of the curve, and decreased with a lower vertical grade and a smaller curve radius. In the straight plane portion, the operating speed increased with a larger curve radius(upstream), and decreased with an increase in the change of the vertical grade, depending on the length of the vertical curve. CONCLUSIONS : This study developed estimation models of truck for operational speed and evaluated the degree of safety for horizontal and vertical alignments simultaneous. In order to represent whole area of the rural highway, the models should be ew-analyzed with vast data related with road alignment factor in the near future.

• Journal of Korean Society of Transportation
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• v.29 no.6
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• pp.117-128
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• 2011

In this study, a model is developed to predict emission factors, which aims to objectively evaluate the impact of transport projects on air quality. Two emission prediction models for the years of 2015 and 2030 are developed using the historical trends in vehicle aging and vehicle deterioration factors. The analysis results show that the emission factors under the operating speed of 30km/h for the year 2030 are 5~37% and 2~83% less than those used in the current studies for passenger cars and bus/trucks, respectively. The statistically validated experiment results demonstrate the applicability of the proposed model to evaluation of the impact of transport policies on air quality.