________________________________________________________________________________________________________ Abstract— the purpose of this study is to conduct a physical survey for distresses analysis of 50 lanes of urban flexible roads and to conduct a comparative study on pavementconditionrating methods (PCRM) using IRC method, and Highway preservation system. 50 lanes of urban flexible pavements from all over Pune city are selected as a case study. The lanes are visually surveyed to detect the types, severity and extent of the distresses based on IRC and WDOT guidelines (Distress identification manuals). Firstly the lane wise data base is created. Secondly the severity and extent is determined based on IRC and WDOT (DIM). And thirdly the lane wise Pavementcondition index (PCI) values are calculated by the methods of IRC, and HPS. To differentiate between both the methods the correlation analysis has been carried out.
Pavement surface distress data collection is one of the main elements of a cost-effective PMS, so several methods have been proposed worldwide to support the pavement management process. The main contribution to the state-of-the-art has been developed by the U.S. Army Corps of Engineers (USACE) in the 1980s, defining the PavementCondition Index (PCI) rating procedure. The PCI measures the integrity and the surface operational condition of the pavement, based on a numerical scale, ranging from 100 (perfect condition) to 0 (failed pavement) . The American Society for Testing and Materials (ASTM) adopted this procedure, as documented in ASTM D6433: Standard Test Method for Roads and Parking Lots PavementCondition Index Surveys . This methodology has been widely used by roadway agencies throughout the USA by readapting the definition of the pavement overall index to suit their local conditions (such as data collection techniques). Researchers and highway agencies around the USA summarized the use of pavement scores by US states, including: the rating methods used, the score scales, and distress definitions [5–7]. In particular, they did a complete literature review comparing the level of agreement among six condition indexes from five US Department of Transportation (DOT) agencies, testing pavement data obtained from the Pavement Management Information System of the Texas DOT. Some pavement state agencies are using the pavement score indexes combined with other pavement functional measurements, such as the International Roughness Index (IRI). Pavement indexes have been developed based on the aggregation of several distress types in order to measure the overall condition of the pavement, agency-specific pavementcondition data collection procedures and distress rating protocols . For example, the Federal Highway Administration (FHWA) road inventory program for the National Park Service (NPS) uses the PavementConditionRating (PCR), a combination of pavement surface distresses and pavement roughness, as a weighted combination of the contribution of both components . Nevertheless, the pavement structural condition affects the pavement performance and the knowledge of the structural condition is vital for pavement management at both the network level and the project level . The pavement structural capacity is typically obtained by using non-destructive techniques based on surface deflection measurements, such as the Falling Weight Deflectometer (FWD), Rolling Weight Deflectometer (RWD) and Traffic Speed Deflectometer (TSD); or based on destructive techniques that rely on the extraction of material in situ (coring) and the testing of extracted materials [11–14].
Pavementcondition survey is taking a big role in the Pavement Management System at network level. Also, gives the information for pavement serviceability analysis, predict maintenance & rehabilitation needs and priorities, and distribute funding (Youssef and Elbasher, 2014). Pavement distress (surface condition) is one of the characteristics of pavementcondition for evaluating pavement rehabilitation needs (Garber and Hoel, 2010). Pavementcondition can be measured by the PavementConditionRating (PCR). It considers current and future pavementcondition and priorities, this helps maintain pavement structural capacity (Abdulhameed and Sarsam, 2014). There is agreement between the laboratory and PCI methods in the determination of pavement conditions and their causes (Alwan,2015).
A laboratory soil investigation for failed and serious pavementconditionrating show that the liquid limit varies from 33.02% -44.48% and Plasticity index from 11.3% - 25.56%, according to ERA manual, soils with LL< 50% and PI > 25% are suitable subgrade materials so all station are good. The soils were classified by ASSHTO under the A-6 and A-7-6 category which showed that the soils were fair to poor as a sub-grade material. The soaked CBR values of subgrade soil materials are between 7.9% - 10.4%. According to ERA manual CBR values greater than 5% are good subgrade materials. Therefore, from the laboratory test results the subgrade soil was not the cause of pavement failure for failed and serious pavementconditionrating.
Fuzzy logic is a form of multi-valued logic derived from fuzzy set theory used to deal with reasoning that is approximate rather than precise. In pavement maintenance, fuzzy-logic can be used to provide a pavementconditionrating score for each distress, and to provide a basis for maintenance needs assessment in terms of various user-defined severity terms. The user- defined severity levels are a key input to programming and scheduling maintenance activities using this approach. The fuzzy logic approach was created to accommodate the uncertainties involved in subjective pavement assessments, and variations among the subjective assessment of experts. Fuzzy logic can receive different opinions (expressed in term of maintenance needs) from different sources, and arrive at an aggregated decision. This eliminates subjectivity by using a consistent analytical procedure to address the differences in maintenance needs assessments. The opinion on maintenance needs from difference sources, together with the aggregated membership functions of a distress can be converted into a numerical score useful to categorize pavement needs (Fwa et al., 2003).
In the current PMP projects rating system at KYTC, the experts of KYTC have concerns that the IRI (or adjusted IRI in the case of non-interstate/parkways) receives too much weight in the overall score when recent studies suggest that the impact of roughness index on pavement life may not be significant. To this end, we propose to develop a new and rather objective method of reconciling various indices using AHP. Similar to the car buying example presented previously, our goal for this new method is to decide the weights for WPC_EXT, WPC_SEV, RF_EXT, RF_SEV, OC_EXT, OC_SEV, OS_EXT, OS_SEV, APPEAR, JS and (adjusted)IRI in prioritizing PMP projects. Thus, in the AHP there are 11 criteria and 55 pairwise comparisons.
provides guidance to determine the functional condition ratings and upgrade strategies of existing guardrail systems. The term “guardrail systems” refers to typical guardrail sections such as W and cable barriers, transition areas, and guardrail end treatments. The functional condition ratings are designed to measure the functionality of guardrail systems compared with the current FHWA/VDOT standards. The ratings are to be used to determine the level of upgrade an recommended improvement timelines to guide investment decisions. This memo is to be used in conjunction with TE Memo-367, which provides condition ratings and repair strategies for damaged guardrail systems and end treatments as part of the “Hits Repair”
It is a common practice to decide the pavement maintenance based on mere observations and personal judgment and experience. As the observations are subjective, to overcome this limitation, a scientific approach for defining condition state of pavement with respect to age of pavement and its maintenance cost is developed by the authors. Typical construction procedure used by Public Works Department of Maharashtra state is considered. Average pavement life of bituminous rural road is observed as 14 years and hence the entire life span is divided into 7 equal periods i.e. regularly at 2 years. Maintenance cost for such several pavement stretches in single lane rural road network is calculated for each of 2 year span of observation. Average cost of each condition state is then identified from this data. Based on this observations condition state pavements are defined in to 7 categories – from 7 (new condition state) to 1 (poor condition needing immediate total rehabilitation). For rate analysis, District Schedule Rates of Public Work Department, Pune 2012-13 is referred. Table 1 shows the different condition state descriptions of the pavements and corresponding repair cost required for rehabilitation / renovation up to new condition state.
A recent study found that composite indices purporting to measure the same attributes of condition rated test sections of pavement substantially differently (Gharaibeh et al., 2010). This conclusion is troubling given the proliferation of different composite condition indices in use today. Difficulties arise even when a single condition index is used. When sections of pavement with similar condition ratings are subject to similar stresses, future condition ratings can “vary considerably” (Carnahan et al., 1987). Models that seek to capture stochasticity have been and are being developed. However, it has proved difficult to select appropriate forms and to accurately parameterize such models. This has led to a distinction between stochasticity and uncertainty, with the latter continuing to haunt pavement management systems (Kuhn and Madanat, 2005). One of the major causes of stochasticity and uncertainty in modelling composite condition index evolution is unobserved heterogeneity (Prozzi and Madanat, 2003). Sections of pavement that are identical in terms of data analyzed currently are, in fact, behaving quite differently.
In this paper, an overview of ANN has been presented along with design and functionaries of BPA.PCI was calculated for base year and future year based on visual surface condition survey.PCI estimated from the adopted model is almost same to the observed PCI in future year. Forecasted PCI over fifteen years indicates the trend of deterioration of the pavement surface condition that may be used for planning of maintenance and repair works in long run. However, the results indicate that the proposed model has good capability to be used to predict the surface condition in future of pavement sections.
Pavement distress is a feasible imperfection in shape, performance, and felt-bad serviceability of pavement surface in time-scale of the life cycle of the pavement. Pavement structure is an inventory that needs tracing. Evaluation of surface conditions helps keep an eye, focus on pavement conditions and level of maintenance. It is introduced as pavement maintenance management systems (PMMS) and conducted a periodic survey to follow the distress conditions of pavement surface. Distress survey, includes detailed identification of distress types, severity, extent, and location. To combine these details, an index is assigned to each pavement in a general rating. Every highway agency either develops its evaluation procedure or selects a developed one for pavement survey. It is neither based on highway system size nor on complications of PMMS, PMMS show support at two levels: network level is related to management with board-based data of the entire system, information for planning purposes and financial and fiscal planning. Project level provides information for engineering design, construction, and cost . Highway pavement management systems (PMS) are used throughout the United States (U.S.) to identify the roads and pavement sections which require repair, maintenance or reconstruction. They are also used by the Federal Highway Administration  to allocate federal money to state transportation agencies for the maintenance of roadways.
Infrared thermography (IRT), an effective nondestructive testing method, is used to obtain an initial evaluation of the concrete pavement surface and near surface in a time effective manner. In this paper, the effect of the depth of delamination inside concrete pavement on infrared thermography technique is studied for bridge decks inspection. To be able to mimic the delamination in subsurface, two Styrofoam cubes have been inserted in different depth near the surface of the concrete cylinder. After heating up the specimen, thermal images were taken from the surface using an infrared thermal camera to evaluate the effect of subsurface defects on detection sensitivity and accuracy. We also investigated the precision to which the shape and the size of the subsurface anomalies can be perceived using an uncooled thermal camera. To achieve this goal, we used image processing technique to accurately compute the size of delamination in order to compare it with the actual size. In addition, distance/thermal graph is used to detect the presence of the defect underneath the concrete surface. Furthermore, thermal transfer modeling was adopted in this paper to assist the setup of this experiment and the results are compared with laboratory findings.
Abstract : The permanence and serviceability of asphalt is defined mainly by its degradation overtime which is influenced by the climatic change that can vary the surrounding ambience, lead to that increase the rate of damaging steps that will act on the durability and safety of pavement in many locations .Alteration of Climate in largely range acts on the environment. Variation in precipitation schema is may lead to drastic water deficiency and/or inundation. Weather conditions have often offered jeopardy to the pavement status, and it is considered as major reasons of of degradation. The amount of vulnerability of asphalt pavement to meteorological status is related to agents like as pavement category and condition, geology, vicinity to water direction and flow of traffic. This instruction recognize how weather condition, degree of temperature and water influence in the various kinds of road pavement such as: rigid, asphalt bituminous and modular pavements. The efficacy of weather alteration on the pavement damage cannot be neglected, and it can be considered during pavement design. Presenting pavement structures, that considered the effect climatic alteration during design has more resistance for disintegrate and damaging than the types not considered.
To identify effective management and maintenance, Pavement management system (PMS) involves systematic activities to this, based on Pavementcondition index (PCI). To calculate PCI value for “Al Shahid Mohammed Ali Al Hassani” road branch in Al-Muthanna governorate, Al- Rumaitha city, used PAVER 5.2.3 program. The length of the selected road is 2 km and two lanes in each direction. After sampling process, visual survey is managed for studying type, level of severity and quantity of distress in the sample units at the selected road. Further, collection road for selected road are inventoried and estimated using PAVER 5.2.3 to compute the PCI. As the PCI of the inspected pavement was “85” that means the pavement needs preventive maintenance. Each type of distresses has been studied to identify failure causes. The treatments of each type of distresses have been suggested as a countermeasure. These treatments include pothole patching, crack filling and isolated overlay.
A consensus among the engineering team was sought as a substitute for mathematical curve fitting. This decision was based on the intuition that (1) Manual data collection was not able to rate all the pavement sections in a uniform manner since several data collection teams were used, (2) members of data collection teams tended to rate pavement differently later in the project compared to their early ratings, (3) data collection teams tended to impose their opinions on the numbers they assigned to certain type of conditions that would be different from team to team 4). Tehran’s street network has developed so rapidly in the past 12 years that has caused considerable traffic generation and considerable shift in traffic stream movements. Therefore, the utilization of streets by traffic streams has been changing and has not followed a steady pattern 5). The four above mentioned reasons cause variation in the data points that a mathematical curve-fitting scheme may not be able to account for without considerable use of theories and statistical techniques, many of which require considerable historical data that was missing here. Whenever a consensus among the project team, to agree on a curve that would resemble
Since the beginning of attitude measurement, social scientists have defined attitudes as evaluations expressing the degree of favorableness toward an attitude object. Therefore, attitude measurement relies on responses expressing this degree of favorableness on a continuum extending from favor to disfavor, agree to dis- agree, etc. The use of rating scales in social science surveys has a decades-long tradition. Information retrieved from scale handbooks (Bruner, 2013; Fowler, 1995; Robinson, Shaver and Wrightsman, 1999) shows that over 90 per cent of attitude measurement used the rating scale technique developed by Likert (1932). This technique originally applied a five-point, fully labeled scale offering response cat- egories on an approve/disapprove continuum with a neutral midpoint (i.e., strongly approve, approve, undecided, disapprove, strongly disapprove). Since these early days, a vast amount of methodological research has investigated the effects of dif- ferent response-scale attributes on response behavior.
This paper proposes a novel approach to estimate the Pavement Indicator (PI) for the entire city (or any area of interest) with cost effective. The proposed approach exploits the newly available miniature cameras, GPS, wireless networking and Digital Signal Processing to automatically and continually collect visual information about different segments of the road and combine these images to establish a live map of the city roads where different colors correspond to an approximate estimate of the PI. This technique is not a replacement of the tradional method but rather it is a tool to continually identify sections that need to be repaired. The technique involves taking pictures of various sections of the road network using cameras mounted on public vehicles and transmitting these pictures to a processing centre. The cumulative effect of these estimates produces regional estimates that become more statistically accurate as time goes by and the overall PI map is continually updated to maintain a global visual map of the PI and can be linked to optimization software package to determine the most cost effective rehabilitation schedule.
Immense costs of traffic accidents have caused the safety conditions of ways to become one of the most crucial objectives of most of the countries in field of transportation engineering (Ziari, and Khabiri, 2006, Castro-Nuño et. al. 2018). Several researches have revealed that pavement characteristics and its deterioration state is one of significant parameters in accidents' possibility. On the other hand various research activities are performed to improve and rehabilitate the engineering infrastructures, all over the world. Data mining tool is widely being used in civil engineering these years (Chen, et. al., 2018). Transportation engineering also uses this tool to optimally manage the transportation networks (Tafti, et. al.2016). Data mining and its methods in design, performance and management of pavement in recent studies (Khabiri, 2010). Road maintenance operations are highly important for early deterioration of roads and utilizing the highest road capacity during its expected service-life (Khadka, Paz, and Singh, 2018; Ziari, Ameri, and Khabiri 2010) additives and wastes are also used in pavement life (Nabiun and Khabiri 2010). Prioritization and implementation of optimizing decision methods that could predict the pavement state without implementing expensive and complicated equipment, is determined as a requirement, for developing countries by the scientists (Wang, et. al., 2018). Development of traffic data clusters is critical for use of the Mechanistic–Empirical Pavement Design Guide (MEPDG) while site-specific traffic data are not existing and statewide data are too general. However, an ideal method to traffic data clustering is not specified in the MEPDG. A study in the United Statesoffered a new clustering combination method, correlation-based clustering, that considered the effects of traffic inputs on pavement design depths, so that purpose of the amount of clusters is made accurately (Mai, et.al. 2013).
material and was shown to be a good indicator representing the change of metal oxides in the spectral region 450nm- 550nm. The angle of slope of the spectral line in this region, is shown to be better than the VIS2 metric. The angle of the slope utilizes more information from the spectral response than the previous VIS2 indicator. Exploiting more spectral information is good to improve the clues used to find material changes and hence associate this with cracks and potholes and even normal wear of the road surface. This finding may allow fast extraction of defective road pavement areas.