Gradient effect of road transportation on economic development in different geomorphic regions

The economic benefits of transport infrastructure investment have been widely accepted.However,the varying influence of road transport development across vertical space has rarely been discussed.Taking Sichuan province in China as case study area where the landform is diverse and complex,administrative counties were categorized into 4 main types:plain counties,hill counties,mountain counties,and plateau counties.Using statistical data during 2006-2014,theperformanceofeconomic development and transport construction level in the four types of counties are discussed.Subsequently,the heterogeneous effect of each grade road on economy was calculated by local regression model(GWR).The results indicate that plain counties largely surpassed the other geomorphic counties in economic development level,while the gradient gap among them was on the decline.Similarly,distribution of transport infrastructure presented a decreasing trend from the low plain counties to high plateau counties.Regional imbalances were mainly reflected in the County road and Village road.Regarding the changes of regional gaps,National&Provincial roads and County roads were constantly expanding,whereas the disparity of Village road was slowly narrowing over time.Particularly noteworthy was the non-stationary economic influence of traffic factors across vertical gradients.On average,National&Provincial roads generated higher benefits in the high elevation regions than the lowlands.In contrast,County road and Village road were found to be more effective in promoting economic development in plains.With regard to local estimates of traffic factors,coefficients in mountain counties exhibited larger fluctuation ranges than other geomorphic units.The conclusions provide a basis for government decisionmaking in a more reasonable construction arrangement of road facilities and sustainable economic development.

Estimating traffic volume on Wyoming low volume roads using linear and logistic regression methods

Traffic volume is an important parameter in most transportation planning applications. Low volume roads make up about 69% of road miles in the United States. Estimating traffic on the low volume roads is a cost-effective alternative to taking traffic counts. This is because traditional traffic counts are expensive and impractical for low priority roads. The purpose of this paper is to present the development of two alternative means of cost- effectively estimating traffic volumes for low volume roads in Wyoming and to make recommendations for their implementation. The study methodology involves reviewing existing studies, identifying data sources, and carrying out the model development. The utility of the models developed were then verified by comparing actual traffic volumes to those predicted by the model. The study resulted in two regression models that are inexpensive and easy to implement. The first regression model was a linear regression model that utilized pavement type, access to highways, predominant land use types, and population to estimate traffic volume. In verifying the model, an R^2 value of 0.64 and a root mean square error of 73.4% were obtained. The second model was a logistic regression model that identified the level of traffic on roads using five thresholds or levels. The logistic regression model was verified by estimating traffic volume thresholds and determining the percentage of roads that were accurately classified as belonging to the given thresholds. For the five thresholds, the percentage of roads classified correctly ranged from 79% to 88%. In conclusion, the verification of the models indicated both model types to be useful for accurate and cost-effective estimation of traffic volumes for low volume Wyoming roads. The models developed were recommended for use in traffic volume estimations for low volume roads in pavement management and environmental impact assessment studies.

An optimization model for improving highway safety

This paper developed a traffic safety management system （TSMS） for improving safety on county paved roads in Wyoming. TSMS is a strategic and systematic process to improve safety of roadway network. When funding is limited, it is important to identify the best combination of safety improvement projects to provide the most benefits to society in terms of crash reduction. The factors included in the proposed optimization model are annual safety budget, roadway inventory, roadway functional classification, historical crashes, safety improvement countermeasures, cost and crash reduction factors （CRFs） associated with safety improvement countermeasures, and average daily traffics （ADTs）. This paper demonstrated how the proposed model can identify the best combination of safety improvement projects to maximize the safety benefits in terms of reducing overall crash frequency. Although the proposed methodology was implemented on the county paved road network of Wyoming, it could be easily modified for potential implementation on the Wyoming state highway system. Other states can also benefit by implementing a similar program within their jurisdictions.