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Gravel roads deterioration having absence of maintenance is one of the serious issue and common problem in the world. In order to achieve the objectives of the study, the researchers were used questioner survey. To achieve this, first identified the road sections those having lack of maintenance on time existed in the study area. Then the representative road (Sarbo-Busa, Saka-Ushane and Buxure-Sanxama) and questioner surveys samples have been selected by non-probabilistic purposive and systematic sampling respectively. The questioner’s survey was focused on identifying the causes of absence of maintenance and pre-conditions considered. Questioner survey was analyzed by RII. The absence of maintenance was occurred due to lack of budget fund, poor management, lack of skilled manpower, lack of good material quality, lack of regular inspections, poor working environments. The pre-conditions considered while maintaining the gravel roads are: Cost of maintenance, class as the road, maintenance schedule, skilled manpower, topography, number of road users, traffic volume, and economic standards of the society and location of the road from the center. In Jimma zone the deteriorations of gravel roads has been increasing with the absence of maintenance time.

The focus of this research is to develop a systematic method for ascertaining the level of service (LOS) of gravel roads in the US. To date, such a method does not exist in the highway capacity manual (HCM). In this research, a methodology comprising eight criteria that affect gravel road traffic operations is developed. For each criterion, a rating is assigned. It is either “Good”, “Fair” or “Poor”. The results of each individual criterion rating are combined to develop an overall LOS rating. Furthermore, a non-parametric machine learning technique, namely the classification and regression tree (CART) modeling structure, is employed to quantify the contribution of each criterion to the overall gravel roads’ LOS. As a case study, the developed methodology is implemented to assess traffic operations of gravel roads in Laramie County, Wyoming. The studied gravel road network is compiled and managed in a Geographic information system (GIS) shapefile prepared for the purpose of this research. That is to provide decision-makers in local agencies a computerized tool to efficiently track the performance of their gravel road network. Roughly 63.5% of the gravel road segments are operating at an LOS “Fair”, while 19% are operating at an LOS “Poor” and unexpectedly 17.5% are operating at an LOS “Good”. All gravel roads assessed are low-volume roads with 400 vpd or less. The developed methodology is intended to benefit traffic engineers, decision-makers, and any other stakeholders. The gravel road LOS methodology was developed and applied to Wyoming’s conditions. Minor adjustments might be needed for implementation in other jurisdictions.

In extreme bad weather conditions, vehicles can timely adjust the speed and distance according to the road information, which will effectively reduce the occurrence of traffic accidents. Road type and road adhesion coefficient are the main factors affecting road condition. The traditional identification method of road adhesion coefficient has the characteristics of high cost and low reliability. At the same time, the road surface information recognition technology based on machine vision has become a hot spot in the current research, but the low accuracy and poor robustness are always the difficulties in the research. Based on the semantic segmentation model which is popular in machine vision, a new pavement type recognition technology is proposed by improving the model output network. According to the existing literature, vehicle road surface can be divided into the following 9 categories, including wet asphalt road, dry asphalt road, wet concrete road, dry concrete road, wet soil road, dry soil road, gravel road, compacting snow road and icy road. The standard data set is made by collecting road pictures through taking photos, downloading and other ways, and the pre-processed data set is used to train the improved semantic segmentation network model. Through many tests, training parameters that achieve the desired effect are selected for model parameter solidification, and the semantic segmentation model after solidification is used to predict the road image acquired by the camera. According to the prediction results of the model, the categories of the current driving road surface are obtained. The test results of a large number of road images show that the average classification accuracy of the nine road types is about 94%, which effectively improves the identification accuracy and robustness of the current road types. At the same time, the predicted time of a single frame image on a specific test platform is about 0.028 6 s, which meets the real-time requirements.

The interaction between off-road tires and granular terrain has a great influence on the tractive performance of off-road vehicles. However, the finite element method or the discrete element method cannot effectively study the interaction between off-road tires and granular terrain. The three-dimensional combined finite element and discrete element method is applied to handle this problem. In this study, a calibrated finite element method–discrete element method model is established, in which the finite element model of off-road tire is validated by stiffness tests, while the discrete element model of gravel particles is validated by triaxial compression tests. The calibrated finite element method–discrete element method model can describe the structural mechanics of the off-road tire and the macroscopic mechanical properties of the gravel road. Tractive performance simulations of the off-road tire on gravel road under different slip conditions are performed with the commercial software LS-DYNA. The simulation results are basically corresponded with the soil-bin test results in terms of granular terrain deformation and tractive performance parameters versus the slip rates. Finally, the effects of tread pattern, wheel load, and tire inflation pressure on tractive performance of off-road tire on granular terrain are investigated. It indicates that the calibrated finite element method–discrete element method can be an effective tool for studying the tire–granular terrain interaction and predicting the tractive performance of off-road tire on granular terrain.

Gravel road safety is a crucial area of road safety since gravel roads represent a substantial proportion of the entirety of the nation’s roadway network. Also, gravel roads pose inherent hazards t...

Gravel roads require extensive maintenance and rehabilitation. That is because of the dynamic behavior of gravel road conditions. This study is aimed at investigating road condition factors affecting the traffic-generated dust on gravel roads. The study concerns Laramie County, Wyoming. The parametric binary probit regression structure and the non-parametric Bayesian regularization artificial neural network (BRANN) methods were implemented to model traffic-generated dust levels as a function of the factors that contribute to dust generation. The BRANNs method simplifies the model building process by precluding irrelevant and redundant weights of artificial neural networks (ANNs). In this study, the BRANN method is utilized with one single hidden layer using the MATLAB® function for neural networks. In the hidden layer, multiple neuron counts ranging from three to thirty were attempted. The parametric and non-parametric techniques mentioned were adopted to provide comprehensive insights into important factors that contribute to dust generation. Therefore, both techniques complement each other. A total of 206 gravel road segments were used for model building for both analyses. As per the results of the BRANN model, it was found that twenty neurons produced the most accurate results. Furthermore, it was found that the BRANN model had more variables than the binary probit regression model, whereas the probit model provided general insights into the factors affecting the dust on gravel roads such as average travel speed and soil type. Also, it would be an easy-to-use method to assist local agencies and DOT practitioners in addressing the dust problems on gravel roads.

Our old grey Subaru crept slowly up the dusty gravel road. It was a muggy evening, but you couldn’t turn the air con on or open any windows unless you wanted a car full of dust. I got to sit in the front for this last stretch to Nanny’s, so I oversaw switching out Dad's Prince Tui Teka CDs. Dad went extra slow so as not to scratch the discs, but that was hard on a gravelly road full of potholes.

Road condition evaluation is a critical part of gravel road maintenance. One of the assessed parameters is the amount of loose gravel, as this determines the driving quality and safety. Loose gravel can cause tires to slip and the driver to lose control. An expert assesses the road conditions subjectively by looking at images and notes. This method is labor-intensive and subject to error in judgment, therefore, its reliability is questionable. Road management agencies look for automated and objective measurement systems. In this study, acoustic data on gravel hitting the bottom of a car was used. The connection between the acoustics and the condition of loose gravel on gravel roads was assessed. Traditional supervised learning algorithms and convolution neural network (CNN) were applied, and their performances are compared for the classification of loose gravel acoustics. The advantage of using a pre-trained CNN is that it selects relevant features for training. In addition, pre-trained networks offer the advantage of not requiring days of training or colossal training data. In supervised learning, the accuracy of the ensemble bagged tree algorithm for gravel and non-gravel sound classification was found to be 97.5%, whereas, in the case of deep learning, pre-trained network GoogLeNet accuracy was 97.91% for classifying spectrogram images of the gravel sounds.

Daily traffic on arid gravel roads can easily generate dust. Dust emitted from gravel roads creates several problems such as aggravated asthma, breathing difficulties, reducing crop yields, and even death. Therefore, local agencies tend to track the dust amounts on the gravel roads in order to maintain them in good conditions. An accurate detection of dust amounts is very crucial in Gravel Roads Management System (GRMS). Data collection is considered as one of the main challenges facing local agencies due to budget constraints. This paper establishes a novel method for an automatic recognition of dust amounts on gravel roads. This algorithm, “Simple Dust Classification Algorithm”, uses images taken from smartphone application, “Road roid”, to classify dust amounts by using proprietary Digital Image Processing algorithms. A Dustometer device was used to validate the proposed algorithm. Dustometer measurements, supported by statistical analysis, demonstrate that the proposed algorithm achieves an outstanding dust amount classification accuracy. Hence, the proposed algorithm is a promising alternative to assist local agencies in data collection and maintenance planning.

Maintenance of low volume roads especially gravel roads is costly, and millions of funding annually are spent for aggregate replacement alone. Otta seal, compared to other bituminous surface treatments (BSTs) for low volume roads that require high-quality materials and specialized expertise, can be constructed using cheaper local aggregates and accessible equipment. However, only three states have reported Otta seal constructions and performance in the US. In this study, an economic analysis was conducted to compare the cost of maintaining a gravel road to the cost of upgrading an existing gravel road to a double Otta seal surface. This analysis was conducted at three levels: deterministic life-cycle cost analysis (LCCA), a stochastic Monte Carlo simulation-based LCCA, and a traffic based economic analysis. A generic one-mile rural road in Midwest was considered as a case study location. Although, according to the analysis conducted in this paper, an upgrade to Otta seal investment might be justif...

Due to importance of developing the North and Arctic territories, it is essential to ensure working capacity of machinery in cryolithozone. To solve these problems, it is necessary to study accumulation of structural damage and changes in material properties. The purpose of this article is to study influence of operation in the northern roads conditions on fatigue damage, brittle fracture resistance and the working capacity of a leaf spring of a KAMAZ truck widely used in Yakutia. Methods of mathematical statistics, metallography, microindentation, standard mechanical tests, etc. were applied. Results of analysis of distribution of the KAMAZ vehicle springs failures on the months of the year are given, taking into account the seasonal changes in a profile of the typical for Yakutia gravel road. To assess the fatigue damage of metal, the structural and statistical study of microhardness (microdamage) and porosity (mesodamage) was carried out. Impact toughness values were determined and it was found that the accumulated damage did not lead to metal embrittlement at low temperatures. The more significant impact of the cryolithozone road microprofile on the working capacity of the KAMAZ truck springs as compared to the factor of the low temperatures has been substantiated.

Heavy vehicle traffic on unpaved roads in western North Dakota, due to increasing oil extraction activities, is generating coarse particulate matter (PM10) and fine PM (PM2.5), and total suspended particles (TSP), potentially raising concerns for animal and human health and impacts on crop and plant growth. However, limited quantification and characterization are available for PM from unpaved roads next to oil activities. Therefore, a study was conducted to characterize and quantify the PM concentrations from heavy traffic on unpaved roads due to increasing oil activities in western North Dakota. Three unpaved road sites were selected and paired with application of two dust suppressants (brine and magnesium chloride). MiniVol air samplers were used to quantify PM, scanning electron microscopy (SEM) was used to characterize the minerals in PM samples, and inductively coupled plasma mass spectrometry (ICP-MS) was used to analyze the chemical composition of soil samples. The average PM10 and PM2.5 concentrations were higher at site 2 (untreated loose gravel road) than at site 1 (periodically treated with dust suppressants) during the study period (2015-2016). In addition, the PM concentrations were lower in 2016 because of decreased oil activities at site 2. Statistical analyses revealed that the PM concentrations were mostly correlated with vehicle count in addition to temperature, wind direction, and rainfall. Magnesium chloride was the most effective treatment for reducing PM. The SEM analyses of PM samples revealed that most particulates were quartz, other silicates, or biogenic particles. Soil sample analyses revealed that the concentrations of most elements were lower than the threshold values set by the USGS National Geochemical Survey. Keywords: Air pollution, Air quality, Dust, North Dakota, Oil development, Particulate matter.

An analysis of vibration signals has been proposed for a personal gasoline-engine car while driving on three types of roads including paved road, concrete road, and gravel road. The wired sensors are placed upon three positions inside the passenger room: right-front seat surface, left-front seat surface, and rear seat surface. The objectives of this analysis are to differentiate the corresponding vibration reflecting from driving upon three types of roads and to differentiate the vibration at three different positions of sensors inside the passenger room. The signal analysis technique of Fast Fourier Transform is utilized in this analysis, the obtained spectrum is investigated to extract the dominant peaks. Thereafter, the averages of the peak values are calculated for six different engine speeds ranging from 0-30 km/h. These averaging calculations are based on 50 five-second-length samples of vibration signals. To achieve the first objective, the experimental results insist that the highest peak values are mostly of the gravel road, meanwhile, the lowest peak values are of the paved road. To accomplish the second objective, the experimental results strongly confirm the following comparisons. In the case of paved road, the highest peak values are at the rear seat surface, meanwhile, in the case of concrete road, the highest peak values are at the left-front seat surface. Finally, in the case of gravel road, the highest peak values are at the rear seat surface. In conclusion, this study confirmed that the proposed approach can be used to differentiate the signal features of all scenarios.

In developing countries, improvement of trafficability of rural roads, which are generally earth or graveled, are crucial for rural development. Under the circumstances with financial constraints of those countries, locally available material-based approach towards improvement of trafficability are regarded as one of the practical measures. Do-nou, which is Japanese term for soilbag, have been utilized for reinforcing base course. Do-nou method is requiring only labor even for compaction of base material and used polyester fiber woven bags for crops, fertilizer, etc. as one of geotextile. In 29 countries of Asia, Africa and the Pacific, about 180 km rural road has been improved using the Do-nou method, by the NGO which one of the authors is belong to. Because of the easiness and effectiveness of Do-nou method, it enables minor and small enterprises, generally operated by the youth, to be involved in road construction implemented by public works. In order to improve trafficability of rural roads while solving social problem, high unemployment rate among the youth in developing countries, the method needs to be adopted by road authorities for further extension. In this study, therefore, the performance of gravel road with base course consist of Do-nou have been evaluated through the series of full-size driving tests. The settlement of road surfaces with conventionally designed base course and with that consist of Do-nou with the same thickness subjected to the traffic load were measured and compared. Dynamic cone penetration index of these base course structure was also compared. Load distribution effects were also examined using earth pressure gages located on subgrade and road surface during driving tests. The mechanism of reducing settlement of road surface with Do-nou base course were verified. The performance of base course with Do-nou are defined in comparison to conventional base course structure, which enable road authorities adopt Do-nou method.

Road condition evaluation is a critical part of gravel road maintenance. One of the parameters that are assessed is loose Gravel. An expert does this evaluation by subjectively looking at images taken and written text for deciding on the road condition. This method is labor-intensive and subjected to an error of judgment; therefore, it is not reliable. Road management agencies are looking for more efficient and automated objective measurement methods. In this study, acoustic data of gravel hitting the bottom of the car is used, and the relation between these acoustics and the condition of loose gravel on gravel roads is seen. A novel acoustic classification method based on Ensemble bagged tree (EBT) algorithm is proposed in this study for the classification of loose gravel sounds. The accuracy of the EBT algorithm for Gravel and Nongravel sound classification is found to be 97.5. The detection of the negative classes, i.e., non- gravel detection, is preeminent, which is considerably higher than Boosted Trees, RUSBoosted Tree, Support vector machines (SVM), and decision trees.

Conventional road condition evaluation is an expensive and time-consuming task. Therefore data collection from indirect economical methods is desired by road monitoring agencies. Recently intelligent road condition monitoring has become popular. More studies have focused on automated paved road condition monitoring, and minimal research is available to date on automating gravel road condition assessment. Road roughness information gives an overall picture of the road but does not help in identifying the type of defect; therefore, it cannot be helpful in the more specific road maintenance plan. Road monitoring can be automated using data from conventional sensors, vehicles' onboard devices, and audio and video streams from cost-effective devices. This paper reviews classical and intelligent methods for road condition evaluation in general and, more specifically, reviews studies proposing automated solutions targeting gravel or unpaved roads.

Under the road development programme of Ethiopian Roads Authority (ERA) in Ethiopia, many roads spreading all over the country were upgraded from the existing gravel road to the widened asphalt road. Due to the rugged and mountainous terrain condition, natural and man-made slope failures such as landslides usually occur in almost all the hilly and mountainous terrain in Ethiopia. The main cause for the occurrences of failures at different locations along project roads which were widened either by cutting the hill slope and/or filling the valley slope was high rainfall in the area during the month of June to September. In this paper, the case study on the investigations of landslide failures along hill slope, valley slope, slope of bridge approaches, slope of hillside on upstream and valley side on downstream of culverts along project roads is described. The analysis of landslides and its different methods of mitigation measures, namely flattening of slope with or without provision of intermediate berms, provision of lateral support by gravity retaining wall at toe of hill slope or at road edge on valley slope side including proper slope protection and drainage measures adopted in the rehabilitation works along different project roads in Ethiopia, are presented here.

In gravel roads management systems (GRMS), the need for a holistic approach for detecting the dust amounts on gravel roads has enabled the development of a solution that works based on one ...

This study developed a model to select the optimum sections of unpaved roads for chemical treatments as dust suppressants within a limited budget. In the state of Wyoming, more than 19,312 ...

Small-scale race events are a popular form of recreation in natural areas with the potential for social and environmental impacts. Leave No Trace-based communication and education strategies are the most prevalent form of mitigating recreation impacts on public lands. To understand competitive race participants’ perceptions of Leave No Trace, this exploratory study compared race event participants’ attitudes, evaluative beliefs, and global perceptions of Leave No Trace by event type: gravel road running, trail running, mountain biking, and motorcycle trail racing. Data were collected using online post-event surveys. Participants were sampled from five competitive race events on public land held during fall 2015 to summer 2016. Significant differences between event types were found for all constructs examined. Motorcycle racers were the least likely to agree that Leave No Trace is an effective method for protecting the environment, least likely to believe that humans have the potential to cause social or environmental impacts, and were the least willing to change their behavior if they found out it was damaging the environment. Runners’ attitudes toward specific Leave No Trace behaviors were the least in line with Leave No Trace recommendations, while mountain bikers were the most in-line. Management implications When issuing permits and managing events on public natural areas, managers should approach each affair differently, realizing that the type of event may influence the level of social and ecological impact. Managers should contact event organizers as early as possible to raise awareness of possible impacts, provide tailor-made messaging to participants, and develop management plans specific to the event and location that monitor and adaptively manage impacts to preserve social experiences and ecological resources. This will help managers remain flexible in their event management.

In 2009, pulp mill fly ash was used for stabilizing the road base of a low-volume gravel road. Six years after stabilization, a two-year monitoring program and a complementary study were conducted ...

The government proliferantion in Indonesia become a consequence of the existence of a policy of fiscal desentalisasi. The existence of the government proliferantion is expected to shorten the span of control so that the goal of improving the well-being of society and the public service can be achieved. This study goals to analyze the impact of the government proliferantion on the regional educational and economic outcomes against on 491 Kabupaten/Kota in Indonesia. This research uses the Difference in Difference as a tool of analysis. Data obtained from the Indodapoer-World Bank year 2001 until 2014. The impact of the presence of the government proliferantion against outcomes education is lowering the level of literacy through a decrease in the number of buildings on the SD output though it is insignificant and its impact on economic outcomes effect increasing income per capita community that in proxy through household spending per capita and GDP per capita, increasing the number of workers, and lower levels of poverty through increased output in the electricity, road access to the village dirt road, and the village gravel road. The impact in General of the expansion area is a local Government has succeeded in transferring funds to the poor but not with a business climate that is shown by the results of the constant price GDP as a whole which indicates significant results negative. Keywords: Government Proliferantion, Difference in Difference, Educational, Economic.JEL : R1, H00, I21, I25

In many developing countries, roads start their lives as footpaths. These paths later develop into vehicle tracks, engineered natural surfaces, gravel roads and, eventually, bituminous roads. This paper is concerned with the stage of transition of roads from gravel to bituminous standard. This transition is common in many countries that have gravel roads as a significant proportion of the road network. On many gravel roads, it is not uncommon to find particles larger than 40 mm in the gravel matrix. During upgrading of a gravel road to a bituminous standard, it is common to incorporate some of the existing gravel layer in the new pavement. A dynamic cone penetrometer (DCP) is frequently used to assess the strength of the existing gravel layer. However, if the pavement being tested contains a high proportion of large and coarse gravels, a DCP will produce highly variable results. The issue therefore is how to assess adequately the strength of the existing layer in order to produce a more cost-effective pavement design. This paper proposes a method of combining deflection and DCP tests for an effective pavement design.

Sweden has a wide network of gravel roads. When the water table levels rise during the freeze-thaw and wet seasons, the bearing capacity of the roads will decrease and rut depths increase. The road will suffer a small deterioration every time a vehicle travel over it. Therefore, it has been decided to investigate the long-term performance of a Swedish designed gravel road using an accelerated pavement testing facility. A trial gravel road was constructed and exposed to various levels of ground water table which simulate the weather changes in Sweden. The structure of the trial gravel road consisted of 15 cm (base and surface layer), 20 cm sub-base layer and 260 cm subgrade soil. The trial road was tested using the Heavy Vehicle Simulator (HVS) and the vertical surface deformations and the vertical dynamic deformations were measured by means of laser profile measurement and eMU coils respectively. At the end of 85 000 HVS passes, the tested road suffered from serious deformations as discussed in details in this paper. Furthermore, a transverse trench section was excavated at the end of HVS trafficking in order to investigate the possible mechanism contributing to the tested road failure.

This study presents the performance of a trial gravel road subjected to HVS (Heavy Vehicle Simulator) trafficking in a compressed time period. The road structure was constructed with 150 mm-thick aggregate base course, and 125 mm-thick sub-base course. The test road responses, such as surface deformation and rutting were recorded using laser profile measurement instrument while the unbound layers’ dynamic deflections and strains data were periodically recorded at different depths during the execution of the test by means of an array of micro strain gauges. The test road was also instrumented with Water Content Reflectometers to record the changes in moisture contents in the road layers caused by the raising of the water table level under HVS trafficking. A total number of 85,000 HVS passes were applied to the trial gravel road structure under near-optimum as well as partially submerged subgrade moisture conditions. The test results emphasize the fact that the partial soaking of the subgrade soil by raising the groundwater table level caused a serious damage to the tested gravel road, as further detailed in this paper.

This paper presents a mobile robot prototype used for mallard navigation in a paddy field. One shortcoming of rice-duck farming is that a flock of mallards tends to gather in a specific area that produces a spring pond. This study was designed to develop a prototype of an autonomous mobile robot that guides a mallard flock to achieve highly efficient rice-duck farming. We developed a robot and waterproof boxes used for the protection of electric devices, including motors. The robot body is 270 mm long, 210 mm wide, and 250 mm high. Its body width is less than the length between rice stalks. After checking the waterproof capability for the body waterproof box, we conducted an indoor driving test for manual operation. Moreover, we conducted an outdoor evaluation tests to assess running on a gravel road and on a snowy road. We evaluated the robot performance not only for uneven surface roads including steps, but also for the range of wireless communication for controlling the robot.

In the northern Great Plains, a potential road dust abatement is the application of oil-well produced water, also known as “brine.” However, little is known about the effectiveness of brine or its potential impacts on dispersion of road materials and the creation of dusts. This study aimed to investigate how sodium adsorption ratios (SAR), electrical conductivity (EC), and Ca/Mg ratios of simulated and non-simulated brine influenced dispersive reactions of three mineralogically different gravel road fine fractions. Ca/Mg ratios had little to no significant influence on the outcome of dispersion. Irrespective of the SAR or clay mineralogy, a threshold EC of 4 dS m−1 was sufficient to control road fine fraction dispersion. Actual oil-well produced water effect on dispersion followed the same order as that treated by simulated solution and the dispersion value can be well-predicted from EC. This information is useful to managers, regulators, scientists, and industry professionals considering the use of brine as a road dust control abatement.

Rural accessibility is the only metric used in the Sustainable Development Goals to track progress toward better transport services in low- and middle-income countries. This paper estimates the rural accessibility index, defined as the proportion of the rural population who live within 2 kilometers of an all-season road, in 166 countries using open data. It then explores the cost of increasing the rural accessibility index in 19 countries, using an algorithm that prioritizes rural roads investments based on their impact on rural access and connectivity. Investment costs quickly balloon as the rural accessibility index increases, questioning the affordability of universal access to paved roads for many countries by 2030. If countries spent 1 percent of their gross domestic product annually on the upgrade of rural roads, even under optimistic assumptions on growth of gross domestic product, rural accessibility would only increase from 39 to 52 percent by 2030 across all developing countries. Alternative solutions to rural integration must thus be implemented in the short run until countries can afford to increase significantly access to all weather roads. For example, drones that supply regular food and medicine supply to remote communities are much more affordable than roads in the short term.

The road sector in Ethiopia continues to develop its road network throughout the country at a tremendous rate with the aim of connecting all kebeles (administrative districts) to nearby higher class roads using all-weather gravel road solutions. These should provide access to the rural areas where most of the country's population is found, by means of the universal rural road access program (URRAP). Currently, Ethiopia is constructing many URRAP road projects which are susceptible to defects and there is not enough study that addresses the frequent causes. This study investigated the nature and causes of defects based on extensively reviewed literature, questionnaire responses, site visits and design reviews on two selected road projects, as well as in an interview with professionals. The major defects identified are poor vertical alignment and excessive road gradient, stoniness of the surface, inconsistency of road character without warning signs, poor drainage elements and aggregate loss. It was concluded that the lack of a prompt payment system, an ineffective project management system, inadequate and experienced human resources on the owner side, together with design error and omissions and insufficient data for design and construction in predicting underground conditions were some of the critical factors causing defects. The major causes of defects were shared 40 % by the consultant and 60% by the client.

The rural population of India lack adequate transport infrastructure to access the nearby towns/headquarters. The Ministry of Rural Development (MoRD), Government of India (GoI) decided to develop various rural roads under Pradhan Mantri Gram Sadak Yojna (PMGSY). The main objective of PMGSY is to achieve all weather connectivity to all habitations. Hence, a pilot study was initiated over a 7 km gravel road stretch from “Ghanapur-Palakurthy Public Works Department (PWD) Road to Komatigudem via Ippagudem, and Rangaraigudem” in the Warangal district of Telangana State, India. There are various disadvantages associated with construction using gravel like dust generation and gravel loss over a period of time due to passage of vehicles. The best solution to minimize these problems is to seal the gravel roads. The pilot road considered in this study was constructed using locally available gravel up to the surface course and then sealed using surface dressing. The performance of the road sections were evaluated in terms of roughness, skid resistance, and texture depth. The initial set of data was collected immediately after construction and one month after construction. Later, four sets of pavement performance data was collected after seven months of construction of the surface dressing layer in November 2013, January 2014, April 2014, and June 2014. Altogether, six sets of data were collected. The data was analyzed and important observations are reported in this paper. There is a considerable change in surface texture and skid resistance values after the first one month of construction whereas no significant changes were observed in the roughness values. Further, there is no significant difference in the results of surface texture, skid resistance and roughness values when the pavement sub-sections were evaluated for four times even after seven months of construction of the sealing layer.

The Arba Rekete-Gelemso gravel Road section is affected by the presence of expansive soil, this soil has shrinking and swelling behavior due moisture fluctuation. The main objective of this research work is to investigate the Characterization of Borrow materials for embankment fill and capping layer based on their index and strength properties for Road Construction of the proposed route. In order to achieve the objectives, field investigation and nine (9) samples were also collected from the identified borrow area and laboratory test analysis were performed such as, Atterberg limits, compaction, CBR and percentage of swell tests. ERA‘s and AASHTO’s standard technical specifications have been used to interpret the data by integrating the field with laboratory test results. The subgrade soil of route, having liquid limit value greater than 60% and plastic index value greater than 30% and CBR value less than 5%, at Chainage km 0+000-4+000, 5+900-8+000, 9+400-12+900, 13+500-14+000, 15+000-16+000, 17+100-17+600, 18+500-20+500, 21+500-34+900, and 35+200-47+000 unsuitable. The index and strength properties of the borrow materials fulfill the requirement for embankment fill and subgrade improvements. Finally, all unsuitable subgrade soil along the study route corridor are recommended to remove and replace with suitable and non-expansive subgrade materials, since enormous amount of selected fill materials that fulfill the requirements for subgrade soils improvement are available nearby the study area.

The following paper presents results of research carried out on oiled gravel aggregate. In Russia, the oil-treated aggregate mixture is called “loose-bound organic-mineral mixture” (hereinafter abbreviated as LOM). The aim of the research was to explore the possibility of using oil waste products and their heavy residues generated during oil transportation as a binder in oil-treated gravel aggregate or LOM. Currently, this waste is not used anywhere, it is widely burned, polluting the environment. Studies were carried out using Infra-red spectroscopy of samples of the original oil waste, heavy residues of oil waste and road oil bitumen of BND 90/130 quality type. The fractional composition of oil wastes and their heavy residues was studied during their distillation by heating to a temperature of +335 °C. It was found that for preparing LOM it is more effective to use oil residues. The number of LOM compositions samples were prepared and their main physical and mechanical indicators were determined. Based on the tests, it was concluded that the residues of oil waste can be used as a binder in the composition of LOM such as oil-treated gravel.

We focus on rally drivers’ eye movements and behaviors when they are driving around a corner on a gravel road in this research. Recent studies of visual strategy regarding visual control in driving have been conducted in a driving simulator and on a racing course or paved roads. However, this study was conducted in the real environment of gravel roads and with real vehicles. In this study, the difference between the accomplished and intermediate rally driver’s eye movements and fixation points were defined. The study’s purpose was to understand how expert drivers move their eyes while driving around a corner on a gravel road. Twelve subjects, who were rally drivers in Japan, participated in the experiment; the accomplished driver had won the World Rally Championship (WRC) and was the fast rally driver in Japan. Each subject’s eye movement was measured with mobile eye tracker (Tobii Pro Glasses 2, Tobii, Sweden) and operated at 50 Hz. The eye tracker recordings were analyzed using Frame-By-Frame analysis. This study suggests that the eye movements of accomplished drivers allow them to control the car safely and be conscious of oncoming corners. Furthermore, by looking and thinking ahead like accomplished drivers, the cognitive load associated with driving is likely to decrease; furthermore, it may serve to activate their memories of previous rallies.

Rural access is among the most important infrastructure constraints in rural Africa. Using the results from comprehensive household surveys and other data from Ethiopia, the paper recasts light on the heterogeneous impacts of road accessibility on agriculture and nonagricultural growth. It is found that crop production is increased by major and feeder road improvements. Significant synergy is also found. When investigating further into this effect, there are two impacts: farmers' access to the input market, especially fertilizer, was improved mainly by major corridor improvement. And output market access was improved by feeder road improvement. In addition, the household's nonagricultural income is somehow increased by improved road connectivity. There must be secondary effects. The transport demand function estimated with additional data indicates that as the road network improves, people's mobility increases. Furthermore, local business employment is found to increase with road improvements. To meet the increasing demand for mobility, efficiency and frequency of transport services are important.

This paper presents a methodology to identify key priority areas for transport investments. The methodology uses a geospatial data-driven approach and then proposes an innovative economic analysis for project appraisal. The two main steps involve (i) prioritization of road interventions based on a set of economic, social, and risk reduction criteria; and (ii) assessment of monetized and nonmonetized costs and benefits of road interventions under many scenarios covering the uncertainty on future risks and other factors. This methodology is used at different stages of project preparation for a rural roads lending operation to the Government of Mozambique. In the two regions of Mozambique considered, the analysis prioritizes regions along the coast when combining agriculture, fisheries, poverty, network criticality, and hazard risk criteria. With a limited budget of US$15 million per district, the results show that investing in repairing and rehabilitating culverts and bridges is the intervention that performs better under most of the scenarios.

One of the main objectives for vehicle designers is to achieve flat, safe ride in any environmental conditions. When a vehicle is moving along the road it is exposed to vibrations in multiple axes and directions. Vehicle behavior is extensively investigated in reference to road imperfections that could be expressed as single step disruptions, like remote bumps on the road. A simulation model, previously designed, was already used to investigate vehicle behavior, when riding over the step inputs. This model is further upgraded and now can perform simulations of the scenarios when vehicle is subjected to continuous imperfections on the road, like long runs of the gravel road in the country areas. Vehicle behavior is analyzed for few, common, speed levels in such scenarios. We can achieve lover amplitudes of pitch vibrations driving with the certain speed, but far the best outcome is obtained when active suspension is applied.

The occurrence of 36 arable weed species across 13 counties in the eastern Arkansas–Mississippi Delta area on 489 randomly selected road sites was surveyed in 2012. Palmer amaranth, johnsongrass, large crabgrass, barnyardgrass, prickly sida, and broadleaf signalgrass were the top six weed species, with occurrence noted at 313, 294, 261, 238, 176, and 136 sites, respectively. Factors found to affect weed occurrence along Mississippi Delta roadsides included topographical characteristics, weed species, ditch slope, road type, and nearby land use. Among roadside topographical characteristics, road shoulder was found to strongly affect weed occurrence. In addition, paved and gravel road types with moderate roadside slope explained most of the variability of weed occurrence at each sampling site. Additionally, nearby arable land use affected weed occurrence more so than natural, residential, and pastoral land. Barnyardgrass, johnsongrass, and Palmer amaranth were 3.6 to 4.3 times more likely to occur than all other species identified. An effective weed management plan along eastern Arkansas–Mississippi Delta roadsides should focus on road shoulder, adjacent arable land use, road type, and specific weed species (e.g., Palmer amaranth, johnsongrass, and barnyardgrass). The inclusion of these parameters in future weed control programs can prove invaluable for preventing the spread of the herbicide-resistant Palmer amaranth, barnyardgrass, and johnsongrass.

Running or developing the local MMS or PMS, be it for unsealed or sealed pavements, needs a team of well-trained and experienced road organization staff and appropriate equipment. The data employed to run a gravel roads MMS should reflect the capacity of the road organization personnel to collect them. In this regard, the team should be of adequate size, education and experience. It is, therefore, essential for the benefit of road users, road organization, the environment, and the sustainability of gravel roads to establish the capacity of road organization personnel responsible for running gravel road maintenance management with the intention of meeting social, economic, and political demands.The need to establish the adequacy of Tanzania road organizations in running gravel road MMS and PMS was the reason for conducting the qualitative research aspect of this study. The survey also intended to find out which parameters are readily collected by the surveyed road organizations, so as to include them as variables in formulating a gravel loss prediction model.This paper presents analysis and discussion of the questionnaire responses. The study notes the challenges being faced by road organizations responsible for the maintenance management of gravel road network in Tanzania and attempts to map a way forward.

Gravel road dust has significant health effect. The study was conducted to assess road dust suppression effect of molasses stillage in gravel at a Sugarcane Estate in Zimbabwe. Three, 2 km long gravel road sections (steep, sloping and gentle) had the following dust suppression treatments applied to 500m long segments: (i) molasses stillage, (ii) water and (iii) control. Data on dust deposition rates were subjected to Analysis of Variance (ANOVA) to compare treatment means. Mean road dust deposition rates ranged from 998.46±50.04 to 6184.02±257 mg/m

Unacceptable levels of dust, poor riding quality, impassability in wet weather, and unsustainable maintenance and gravel replacement practices are experienced on most unpaved road networks, and although it is acknowledged that unpaved roads are fundamental to local, regional, and national economies, many current management practices used on these roads leave much to be desired. Over the past 100 years a range of chemical treatments has been developed to fill the need for reducing the environmental and social impacts of road dust, improving the performance and safety of unpaved roads, and/or improving the properties of marginal materials to the extent that a road can be given all-weather status or upgraded to a paved standard. Most of these chemical treatments are proprietary and there is often little documented information regarding the chemistry of the treatment, the results of experimental trials to determine under what conditions the chemical treatment will work best, or guidelines on where and how to use the treatment. Most unpaved road chemical treatments carry no formal specification nor do they adhere to formal environmental testing requirements. Consequently, there has been no large-scale effort to establish and/or implement formal unpaved road chemical treatment programs anywhere in the world, other than those used in site-specific industrial applications such as mining operations. This guide introduces a new process for selecting an appropriate chemical treatment category for a specific set of unpaved road conditions using ranked potential performance. The process is based on the practitioner setting an objective for initiating a chemical treatment program and understanding the road in terms of materials, traffic, climate, and geometry. Using the information collected, the most appropriate chemical treatment subcategories for a given situation can be selected from a series of charts and ranked using a simple equation. This process can be completed manually using a paper form, or by using a web-based (www.ucprc.ucdavis.edu) or spreadsheet tool. Matrices for each of the objectives were developed based on documented field experiments and the experience of a panel of practitioners. Guidance on specification language for procuring and applying unpaved road chemical treatments is also provided, along with comprehensive guidance on understanding unpaved road wearing course material performance.

Recently, electrical welfare vehicles with free casters are widely used by patients and elders indoors. However, welfare vehicles may not be able to move well on gravel or dirty roads as seen in suburbs. In order to expand driving area, the skid steer mechanism is focused on. The skid steer vehicle (SSV) has been used for its high traveling ability on rough road. However, the SSV has disadvantage that the driving assistance is required because its steering is highly affected by road conditions. In this paper, a driving assistance control of SSV using the model error compensator and state estimator, i.e. EKF and cornering power estimator is proposed. The maneuverability is evaluated by correlation coefficient of joystick operation comparing asphalt road and gravel road.

Rural access is among the most important infrastructure elements to stimulate economic growth in rural and remote areas. The sustainability of feeder road maintenance is a challenge in many developing countries. Many feeder roads are unpaved and need to be maintained frequently, but they are often neglected under budget pressure. Output- and performance-based road contracts are an instrument to ensure the sustainability of road maintenance. Contractors are required not only to improve roads, but also to maintain them. Using micro data from household surveys in Zambia, the paper examines the impacts of output- and performance-based road contracts on agricultural production. It shows that the contracts have a significant impact on crop production, especially maize and groundnuts, two major crops grown in the study area. The paper also finds that the measured impacts are associated with actual road maintenance works, regardless of contractual methods. Any road work can improve people's connectivity, even if it is not an output- and performance-based road contracts. The impact of the contracts is catalytic: more road works were implemented on contract roads than non-contract roads, holding everything else constant. This is an important contribution to the sustainability of road maintenance. Finally, road improvement works are found to facilitate farmers' market participation, but the impact seems weak. There may be other constraints. Transport service costs are found to have a negative impact on farmers' market sales. Thus, although roads are improved, transport services may be not available or too expensive, which still hamper farmers' market participation.

Road transport is one of the biggest soil polluter. There are a lot of investigations of soil pollution near highways, but soil pollution near gravel roadsides needs more experimental research. In this experimental study we selected gravel road Juseviciai – Būdvietis – Derviniai and analyzed soil pollution near this road. Soil samples were collected on both sides of the road by making the transversal profile, the sampling points move away of the road at a distance 1; 2; 5; 10 meters, the samples were collected in 600 meters long strip. All samples were collected by using the envelope principle, samples were taken from the top of the soil layer 0 - 10 cm depth. It was established that Mn concentration in the soil sample, which was taken from the middle of gravel road carriageway, reached 238,5 mg/kg – it means 1,79 times less than background value. This value is more than 6 times less than maximum allowed concentration and quit close to the values, which were established on both sides in the soil close to gravel road. The modelling of Mn concentration where made in appropriate scale of mathematical model – 15 meter to both sides of gravel road, the width of the road – 4 meters. The simulated soil volume is 34 x 14 meters, the soil type - medium-coarse sandy loam. It was modeled that after one year Mn concentration in the soil, close to gravel road remains 1,8 times less than background value (at a constant Mn emission in the environment). Moving away from driveway till 10-15 meters the concentration of Mn decrease to 2,48 less in the soil depth of 0,5 m. After 10 years this concentration will reach 1 meter depth. Bet there would be no changes of Mn concentration in the groundwater level. DOI: https://doi.org/10.3846/enviro.2017.036

As South Africa moves further away from the political transition of 1994, the economic history of the post-apartheid era is coming up for debate. The optimism generated by the ANC’s early successes must now, after more than two decades of democracy, be tempered by its conspicuous failures. Not all is lost, though. African growth, technological innovation and private-sector participation in public sector services offer credible opportunities for accelerated development, but will only be effective if policy-makers are cognizant of the political realities. The long walk to economic freedom for many will, unfortunately, continue along a rocky gravel road.

Terrestrial reconnaissance in the border provinces in Thailand is very risky and dangerous mission for troops and government officers. Many of troops were killed and injured by the incendiary bombs buried in the roads. In order to preventing the loss of life and property damages, many inventions of bomb detector have been commercially used such as GPR (Ground Penetration Radar) and REST (Remote Explosive Scent Tracing). Unfortunately, these technologies are expensive and inappropriate in some situations. This paper presents the forthcoming technology of the real-time image recognition for terrestrial reconnaissance. By using the road texture analysis in image analytic, the data set of normal surfaces of the road (e.g. asphalt road and gravel road) will be trained as the prior-knowledge. The system can compare the buried surface with the normal surface of the road and warning the troops beforehand.