Do rural highways narrow Chinese farmers'income gap among provinces?

To achieve complete poverty alleviation,the improvement of infrastructure and living conditions is fundamental.Promoting the flow of factors through infrastructure investment,thereby reducing the income gap among residents,has become an important focus of poverty alleviation.Because of the high amount of investment in transportation infrastructure,greater attention has been paid to the income distribution effect it brings,but few studies have analysed the effect of rural highways on the income gap of farmers.Based on the panel data pertaining to 30 provinces in China from 1993 to 2013,this paper uses a fixed-effect model to test the impact of rural highways supply on the income gap of farmers.The empirical results show that:(1)The effect of Chinese rural highways on the farmers'income gap among provinces is"U-shaped".(2)Chinese national and provincial trunk highways are helpful in narrowing the farmers'income gap among provinces.(3)The level of education,household productive fixed assets investment,level of urbanization,and level of regional economic development have multiple effects on the farmers'income gap among provinces.Then,based on the empirical analysis,the paper analyzes the mechanism of rural highways affecting the income gap of farmers from a theoretical perspective and focuses on the causes of the"U-shaped"relationship between rural highways supply and farmers'income gap.

GIS-Based Methodology for Crash Prediction on Single-Lane Rural Highways

Due to the need to update the current guidelines for highway design to focus on safety, this study sought to build an accident prediction model using a Geographic Information System (GIS) for single-lane rural highways, with a minimum of statistically significant variables, adequate to the Brazilian reality, and improve accident prediction for places with similar characteristics. A database was created to associate the accident records with the geometric parameters of the highway and to fill in the gaps left by the absence of geometric highway plans through geometric reconstitution or semi-automatic extraction of highways using satellite images. The Generalized Estimating Equation (GEE) method was applied to estimate the coefficients of the model, assuming negative distribution of the binomial error for the count of observed accidents. The accident frequency and annual average daily traffic (AADT) were analyzed, along with the spatial and geometric characteristics of 215 km of federal single-lane rural highways between 2007 and 2016. The GEE procedure was applied to two models having three variations of distinct homogeneous segmentation, two based on segments and one based on the kernel density estimator. To assess the effect of constant traffic, two more variations of the models using AADT as an offset variable were considered. The predominant correlation structure in the models was the exchangeable. The principal contributing factors for the occurrence of collisions were the radius of the horizontal curve, the grade, segment length, and the AADT. The study produced clear indicators for the design parameters of roadways that influence the safety performance of rural highways.

Factors associated with crash severities in built-up areas along rural highways of Nevada:A case study of 11 towns

In 2014, 32,675 deaths were recorded in vehicle crashes within the United States. Out of these, 51% of the fatalities occurred in rural highways compared to 49% in urban highways. No specific crash data are available for the built-up areas along rural highways. Due to high fatalities in rural highways, it is important to identify the factors that cause the vehicle crashes. The main objective of this study is to determine the factors associated with se- verities of crashes that occurred in built-up areas along the rural highways of Nevada. Those factors could aid in making informed decisions while setting up speed zones in these built-up areas. Using descriptive statistics and binary logistic regression model, 337 crashes that occurred in 11 towns along the rural highways from 2002 to 2010 were analyzed. The results showed that more crashes occurred during favorable driving conditions, e.g., 87% crashes on dry roads and 70% crashes in clear weather. The binary logistic regression model showed that crashes occurred from midnight until 4 a.m. were 58.3% likely to be injury crashes rather than property damage only crashes, when other factors were kept at their mean values. Crashes on weekdays were three times more likely to be injury crashes than that occurred on weekends. When other factors were kept at their mean value, crashes involving motorcycles had an 80.2% probability of being injury crashes. Speeding was found to be 17 times more responsible for injury crashes than mechanical defects of the vehicle. As a result of this study, the Nevada Department of Transportation now can take various steps to improve public safety, including steps to reduce speeding and encourage the use of helmets for motorcycle riders.

A Novel Network Screening Methodology for Rural Low-Volume Roads

Low-volume roads (LVRs) are an integral part of the rural transportation network providing access to remote rural areas and facilitating the movement of goods from farms to markets. These roads pose unique challenges for highway agencies including those related to safety management on the highway network. Specifically, traditional network screening methods using crash history can be effective in screening rural highways with higher traffic volumes and more frequent crashes. However, these traditional methods are often ineffective in screening LVR networks due to low traffic volumes and the sporadic nature of crash occurrence. Further, many of the LVRs are owned and operated by local agencies that may lack access to detailed crash, traffic and roadway data and the technical expertise within their staff. Therefore, there is a need for more efficient and practical network screening approaches to facilitate safety management programs on these roads. This study proposes one such approach which utilizes a heuristic scoring scheme in assessing the level of risk/safety for the purpose of network screening. The proposed scheme is developed based on the principles of US Highway Safety Manual (HSM) analysis procedures for rural highways and the fundamentals in safety science. The primary application of the proposed scheme is for ranking sites in network screening applications or for comparing multiple improvement alternatives at a specific site. The proposed approach does not require access to detailed databases, technical expertise, or exact information, making it an invaluable tool for small agencies and local governments (e.g. counties, townships, tribal governments, etc.).

Research on Extension Evaluation of Rural Road Maintenance Quality Based on Game Theory

The importance of rural highway maintenance is self-evident, and it is also a basic work of the highway operation department. Selecting an appropriate evaluation method can timely and accurately find the pavement diseases, and improve the timeliness of pavement repair. To improve the accuracy of pavement quality comprehensive evaluation, based on the game theory, the improved extension evaluation method was combined with subjective and objective weight determination methods in this paper, to propose a comprehensive weight determination method with a good operability. The results show that the improved extension evaluation method provides a feasible scheme for rural highway maintenance quality evaluation