Pavement management for airports, roads, and parking lots: Second edition
Abstract
Emphasizing sound, cost-effective management rather than emergency repairs, this comprehensive volume offers practical guidelines on evaluating and managing pavements for airports, municipalities, and commercial real estate firms. © 2005 Springer Science+Business Media, LLC. All rights reserved.
... Ada beberapa metode pendekatan yang dapat digunakan dalam penilaian kondisi jalan seperti metode Bina Marga, metode PCI (Pavement Condition Index), dan metode PDI (Pavement Distress Index). Metode PCI lazim digunakan dalam penilaian kondisi jalan, karena dalam penggunaannya di lapangan tidak memerlukan peralatan khusus, hanya berbasis pengamatan visual dan pengukuran kerusakan di lapangan yang akan mendapatkan tipe kerusakan dan tingkat keparahan kerusakan (Shahin, 2005). Dalam studi evaluasi kondisi dan kerusakan jalan ini menggunakan metode PCI (Pavement Condition Index). ...
... Proses pemadatan lapisan diatas tanah yang kurang baik. Shahin (2005) mengemukakan bahwa hal terpenting dalam sistem manajemen perkerasan adalah kemampuannya baik dalam menetapkan kondisi eksisting dari suatu ruas jalan maupun dalam memprediksi kondisi di masa yang akan datang. Metode PCI (Pavement Condition Index) yang dikembangkan oleh U.S. Army Corps of Engineers (Shahin, 2005) dapat digunakan untuk memprediksi kondisi jalan dengan sistem perangkingan dengan menyatakan kondisi perkerasan yang sesungguhnya dengan data yang dapat dipercaya dan obyektif. ...
... Shahin (2005) mengemukakan bahwa hal terpenting dalam sistem manajemen perkerasan adalah kemampuannya baik dalam menetapkan kondisi eksisting dari suatu ruas jalan maupun dalam memprediksi kondisi di masa yang akan datang. Metode PCI (Pavement Condition Index) yang dikembangkan oleh U.S. Army Corps of Engineers (Shahin, 2005) dapat digunakan untuk memprediksi kondisi jalan dengan sistem perangkingan dengan menyatakan kondisi perkerasan yang sesungguhnya dengan data yang dapat dipercaya dan obyektif. Penggunaan Metode PCI telah meluas di Amerika Serikat, dipergunakan dalam beberapa penilain kondisi perkerasan seperti perkerasan bandara, jalan dan tempat parkir. ...
The Gunung Selatan Road is a road of secondary collector with the class of road is IIIB, has a width of 6.0 meters and a length of 4.109 km, has an important role in driving the economy and connecting sub-districts in the north and west with sub-districts in the central and eastern parts of the city of Tarakan. The use of this road is directed to serve the transportation of construction materials which generally have a load to overloading which has the potential to cause damage to the road. This study aims to assess the condition of road pavement, using the method of the Pavement Conditition Index (PCI). Observation areas along the road segment are divided into road segments or sample units of observation with a width of 6.0 meters and a length of 50 m, so that the size of each segment of 300 m 2 is obtained, with a total of 40 road sample units. The types of damage found at the time of observation include: alligator crack, bleeding, block cracking, corrugation, depression, edge cracking, longitudinal/transverse cracking, patching and utility cut patching, pothole, and weathering/raveling. The average assessment results show the road is in criteria is very good condition with a value of PCI = 71, but there is one observation that gives a criteria is poor, namely the sample unit at Sta. 1 + 350 to 1 + 400 with a PCI value of 29.5. This happened, at the time of observation the field condition was damaged and was being repaired.
... The repair operations in warmer weather 30 conditions are usually applied by conventional Hot Mix Asphalt (HMA) that has a low initial 31 cost but desired performance [10,11]. However, the availability and application of HMA in 32 wintertime are strongly affected by low temperatures, which induce its thermal dissipation 33 4 follows ( The severity of the potholes is ranked slightly differently by Shahin [36]. According to Table 104 2, for potholes with an average diameter of up to 762 mm, both the depth and the diameter are 105 considered to classify the pothole severity. ...
... If the diameter is higher than 762 mm, the pothole 106 area is determined and divided by 0.47 square meters. If the result is higher than 25.4, the 107 severity is considered high, otherwise medium [36]. If the distance between the potholes is less 108 than 200 mm, they should be measured together and considered one big pothole [3]. ...
... 109 Table 1. Classification of potholes based on depth and diameter according to Shahin [36] o Edge seal method: The repair method is similar to throw-and-roll, but after 154 compaction, the perimeter of the repaired section is covered with a tack coat 155 and sand. Then, it is left for about one day to dry. ...
Cold Mix Patching Materials (CMPMs) are usually used instead of Hot Mix Asphalt (HMA) to repair potholes and localized distresses. Although these materials provide immediate serviceability, they have a relatively short life. However, worldwide interest in these solutions, which started as fragmented industrial initiatives, is growing. This article provides a critical comparison between several aspects regarding using CMPMs and HMA in repairing potholes. Specifically, repair techniques, productivity and costs were investigated in detail. Plus, the impact of the main crucial factors, i.e., workability, bonding, water susceptibility, stability, and storageability, on the performance of CMPMs was investigated through an overview.
... For this reason, the aerodrome operator needs to periodically assess their conditions and schedule rehabilitation to optimize the use of available budget. An extensive technical and scientific bibliography is available on these topics, including articles presenting case studies [1][2][3] and books, the validity of which, for some of these, is now internationally recognized [4]. ...
... The Airport Pavement-Management System (APMS) is a dynamic process to monitor representative indexes under known operational conditions to forecast the short-medium term evolution of the airport pavement and to define the best maintenance strategy. To accomplish this important task, the APMS needs systematic procedures for the storage and the analysis of an updated set of data and information that fully describe the pavement condition [4]. ...
... As recommended in various national and international references [4,11,12], the pavement-management system has been organized according to the following structure of the airport infrastructure network: ...
The conditions of airport movement-area pavements play a primary role on safety and regularity of airport operations; for this reason, the aerodrome operator needs to periodically survey their condition and provide their maintenance and rehabilitation in order to ensure the required operational characteristics. To meet these needs efficiently and effectively, the Airport Pavement-Management System (APMS) has proved to be a strategic tool to support decisions, aimed at defining a technically and economically sustainable management plan. This paper aims to investigate the theoretical elements and structure of the APMS; the appropriate methodologies to guarantee a constant updating of the system in all its aspects are presented, focusing on the specific case study of a medium-dimension Italian airport. The article describes the methods and the equipment used for the high-performance surveys and the condition indexes used for collecting and analyzing the data implemented to populate the APMS of Cagliari airport. Two major survey campaigns were carried out: the first in 2016 and the second in 2019. Both surveys were carried out using the same subdivision into sample units, following the ASTM D5340-12 criteria, to correctly compare data collected in different years. In order to sufficiently populate the APMS database, the measured and back-calculated data were stored and integrated using daily acquired pavement reports since 2009 and stored with the specific intention to develop customized decay curves for Cagliari Airport pavements. Preliminary results on the sustainable use of the APMS were reported even with data collected in a limited period and successfully applied to runway flexible pavement.
... erefore, there are various indices to determine the quality of asphalt pavement, the most important of which are pavement condition index (PCI), present serviceability index (PSI), and present serviceability rating (PSR). PCI is the custom index for evaluating pavement quality and is a numerical index regarding structural and functional surface distress based on a specified guideline, ranging from 0 for a failed pavement to 100 for pavement in perfect condition [2]. ...
... It can also be used for summarizing roughness qualities that affect vehicle response. Road surface roughness is an important parameter that indicates the comfort level of the ride over a road surface and is also related to safety, vehicle vibration, operating speed, vehicle operating cost, etc. [2]. at is why IRI has become a prominent index in Pavement Management System (PMS), especially to calculate vehicle operating cost in many countries [7]. ...
... In addition, placing IRI � 7 in equation (5), PCI was approximately 25. erefore, roads with IRI > 7 had a PCI < 25 which is a weak condition, and the relationship between IRI and PCI was not reasonable because pavement profiles require major rehabilitation activities or reconstruction. Figure 6 illustrates the overall range of the model IRI values and the predicted PCI based on Shahin's PCI classification [2]. ...
The main objective of this paper was to investigate the relationship between PCI and IRI values of the rural road network. To this end, 6000 pavement sections of the rural road network in Iran were selected. Road surface images and roughness linear profiles were collected using an automated car to calculate PCI and IRI, respectively. Three exponential regression models were developed and validated in three different IRI intervals. Analysis of the results indicated that exponential regression was the best model to relate IRI and PCI. In these models, R2 values were found to be acceptable, equal to 0.75, 0.76, and 0.59 for roads with good, fair, and very poor qualities, respectively, indicating a good relationship between IRI and PCI. Moreover, validation results showed that the model had a high accuracy. Also, the relation between IRI and PCI became weaker as a result of increasing the level of road surface roughness, which can be caused by the increase in the number and severity of failures. Furthermore, two failures of rail R.C. and rutting were rarely observed in the studied roads. Therefore, the proposed model is more applicable for roads without the mentioned failures and asphalt-pavement rural road network.
... Since the 1970s, pavement management systems (PMS) have been applied to roads and airports, and currently, they are considered a good and useful aid for the infrastructure manager [1][2][3][4]. A PMS provides a systematic and consistent method for assessing the current state of a pavement, predicting its future condition, determining priorities and the optimal time for repair, and selecting maintenance or repair and rehabilitation (M or R&R, respectively) needs [5]. This process has overturned how to approach the maintenance of transport infrastructure pavements. ...
... For these reasons, unlike APMS, HPMS of pavements designed for rotary-wing vehicles does not consider smoothness and adherence, it only considers the pavement condition index (PCI), a common distress survey method that rates the general condition of a pavement considering the extent and severity of the surface defects. The proposed method includes the creation of the heliport network inventory, the visual surveys of the pavement, and the evaluation of its condition by PCI [5], and it allows analysis and modeling for heliport managers to compare alternative maintenance strategies and define the priority needs on their managed network. Moreover, the proposed method can be easily adapted to all the infrastructures in the heliport and it does not require a large amount of time and money for its implementation. ...
... Forecasting of the pavement condition derives from treatment of data collected during survey campaigns, using several regression curves, such as straight-line extrapolation, mechanistic empirical, polynomial constrained least square, S-shaped curve, probability distribution, and Markovian. The simplest regression model is based on a straight-line extrapolation of the last two condition points [5,24]. This method can be used when the monitoring of the pavement is in the starting phase and consolidated data are not available. ...
Maintenance and rehabilitation (M&R) scheduling for airport pavement is supported by the scientific literature, while a specific tool for heliport pavements lacks. A heliport pavement management system (HPMS) allows the infrastructure manager to obtain benefits in technical and economic terms, as well as safety and efficiency, during the analyzed period. Structure and rationale of the APSM could be replicated and simplified to implement a HPMS because movements of rotary-wing aircrafts have less complexity than fixed-wing ones and have lower mechanical effects on the pavement. In this study, an innovative pavement condition index-based HPMS has been proposed and implemented to rigid and flexible surfaces of the airport of Vergiate (province of Varese, Italy), and two twenty-year M&R plans have been developed, where the results from reactive and proactive approaches have been compared to identify the best strategy in terms of costs and pavement level of service. The result obtained shows that although the loads and traffic of rotary-wing aircrafts are limited, the adoption of PMS is also necessary in the heliport environment.
... The distress information obtained as part of the PCI condition survey provides insight into the causes of distress and whether it is related to load, climate and other. (Shahin, 2005). Table 1. ...
... Table 1. Distress classification for roads and parking areas (Shahin, 2005). ...
... Pavement Condition Index (PCI) Rating Scale(Shahin, 2005) ...
Benghazi city like any city throughout Libya, is facing a big challenge in dealing with aging its pavement networks. The current situation reveals that, poor management for its existing roads network and difficulties in carrying out planning of the maintenance requirements. This paper aims to present a review of Pavement Management Maintenance System (PMMS) using Micro PAVER program. The program can provide a systematic procedure for pavement condition evaluation and can make best possible use of resources available and maximize benefits for the community. In this paper, an attempt was made to evaluate the pavement condition of one-kilometer of Jamal Abd El-Naser Street in Benghazi city as a case study, using Micro PAVER software. The results found that, Patching, Alligator Cracking and Longitudinal and Transverse Cracking are the most common distresses on the road section. The PCI results appeared that, the left lane direction of the road is better than the right direction, the overall PCI of the left lane direction is 72%, while the PCI of right lane direction is 36%. The causes of deterioration on the road were primarily by load-related distresses, while the climate causes comprise the smallest percentage of distress causes.
... Firstly, the pavement section divided into sample units, according to shahin [14] the area of sample unit for asphalt surface is 2500±1000 ft 2 (225±90 m 2 ). For all highway sections an area of sample is considering equal to 270 m 2 . ...
... [14], and sampling interval calculated by i= N/n. the total number of sample units in pavement section. e: allowable error in the estimate PCI (usually, used e= 5[14]). ...
... [14], and sampling interval calculated by i= N/n. the total number of sample units in pavement section. e: allowable error in the estimate PCI (usually, used e= 5[14]). s: standard deviation of sample units in the section (usually, taking value of s= 10[14]. ...
Pavements are the main assets of highway infrastructure. Pavement Condition Index (PCI) is a numerical index used to describe the general condition of a pavement. This paper is another trial in monitoring and find pavement condition index (PCI) by applying PAVER software version 5.2. This work aims to evaluate (PCI) of a flexible pavement of some miner collector highways in the north sector in Najaf city divaricate from both sides of Najaf- Karbala suburban main collector highway in its part away from Al- Askariin intersection towards Karbala. These highway sections are Al-Rahma, Al Hizam Al Akhdar, and Al Muearid, Al Shamalii garage highways which cover a total length approximately 11.54 km in both direction of traffic movement (diverging from Najaf- Karbala highway and return to it). Field survey data such as highway section geometric design and distresses type, dimension, and severity, were collected depending on sample size and number of samples extracted, and then entered into the PAVER program to calculate PCI. The result of PAVER shows Results approved that Al-Rahma and Al Shamalii garage highways sections are in satisfactory level, while Al Muearid highway section in (fair) and Al Hizam Al Akhdar in worst case (poor). In addition to that, reasons of these defects had been figuring out according to results obtained.
... Condition prediction models are utilized to conduct analysis and forecasting the condition that is vital for maintenance and rehabilitation (M&R), budget planning, inspection scheduling, and work planning [6]. Condition prediction models are essential in a pavement management system. ...
... Condition prediction models are essential in a pavement management system. Condition prediction models mimic the function similar to that of a car engine [6]. ...
The friction of runway pavement is critical for the safety of aircraft landing and movement on the runway. Tire hydroplaning may lead the aircraft to move off the runway and hinder the safe landing during wet weather conditions. Grooving on the runway is one way to develop frictional braking resistance and diminish hydroplaning's potential risk by improving runway surface drainage capacity during damp weather. According to the Federal Aviation Administration (FAA), groove construction must follow specific dimensions to maintain skid-resistant airport pavement surfaces. However, the groove area can be reduced for several reasons, and regrooving is essential if 40% of the runway groove of a substantial length decreased to 50% of its original dimension. Grooves initiate different potential distress mechanisms that are not found in an ungrooved pavement surface. Groove closure in different airports with hot weather is a frequent and prominent form of distress that substantially declines the grooves’ effectiveness. Moreover, the degree of the declination of groove dimensions has not been quantified in a theoretical method. This paper discussed the current technique and importance of runway grooving. In addition to this, this paper reviews different potential distress mechanisms and issues related to groove deterioration. Finally, a brief of a predictive modeling requirement is illustrated, which is significant for the authority concern for maintenance and reinstate the grooving in the runway for friction development.
... Other types of damage include potholes, polished aggregate, as well as railroad crossings, shoving and rutting as well as slippage cracks, corrugation, weathering/raveling, swell, depression, joint reflection cracking, edge cracking, lane/shoulder drop off, transversal & longitudinal crack, patching and utility cut patching. [10] ...
... The PCI of the tested road sections was calculated and compared to the field-measured operating speeds. The effective association between the value of the PCI and the operating speed is one of the investigation's primary 10 conclusions. The lower the condition index, the slower the operating speed on the road due to the existence of damage to the road pavement surface. ...
In general, roads are a very important infrastructure to facilitate people’s access to their social and economic activities, so knowing the things that affect the efficiency of these roads is very important and how to maintain them. One of the aims of this research is to shed light on previous studies that showed the relationship between traffic characteristics and noise intensity on the condition of the breakable Pavement. The results of previous studies show that flexible Pavement has 19 potential failures and how to address them. There is a relationship between the characteristics of traffic flow and failures that occur in flexible paving. It is also possible to calculate the road condition by knowing the types of faults on the road using several roads or by using specific formulas to calculate the road condition index. There are relationships between the road condition index, the vehicles’ speed, and the models that link Noise to speed. And that most of the relationships that were used to calculate the elastic pavement condition index and its relationship to the movement characteristics are statistical relationships using ANOVA, recreation, and R2
... Standard failures of pavement are called distresses, which are divided into several types that affect the performance of the road. These distresses can be categorized as follows: cracking which is the major distress type in main roads, while in secondary roads, potholes, patches, and rutting are often found (Oliveira 2013;Obaidat et al. 1997;Al-Suleiman et al. 2000;and Shahin 2005). Mainly, nineteen distresses do exist in flexible pavement. ...
... Pavement rutting severity levels(Shahin 2005) ...
This research work was anticipated to quantify pavement rut depths for one of the main roads in Jordan. New techniques using mobile and terrestrial laser scanning systems were used in order to detect, assess, and evaluate the surface measured rutting values. A study area located to the south of Amman, the capital city of Jordan, was used for data collection purpose. Accuracy assessment was carried out with reference to ground measurements using differential global position system (GPS). GPS static measurements were used to have accurate and precise rutting locations and depths. Captured images were rectified, enhanced, and processed using threshold values and noise removal filters. Pavement rut depths were measured for different severity levels for the three mentioned different methods using digital surface models (DSM) extracted from the mobile and terrestrial laser scanning systems point clouds. Statistical analysis of the extracted surfaces showed that the mean difference of measured rut depths between mobile laser scanning and GPS was 24 mm, while it was 45 mm for the terrestrial laser scanning system. Results showed consistent accuracy and preference for terrestrial laser scanner measurements associated with least commission errors; however, mobile laser scanning system had lowest omission errors, whereas the potential accuracy measured in terms of root mean square error (RMSE) was 74 mm for the mobile laser scanning system and 93 mm of the static terrestrial laser scanner system, respectively. On the other hand, the consistency of accuracy of measurements was slightly better for the static terrestrial laser system with a mean average error (MAE) of 66 mm, while it was 97 mm for the mobile system. High correlation does exist between mobile laser scanner and GPS measurements with R2 of 0.92, while it was 0.89 between static terrestrial laser system and GPS systems. These results and potential accuracies of rut depth measurements of the new used techniques would open the door to adapt them in different micro and macro measurements in numerous transportation engineering applications.
... The effective pavement structural number and the original structural number have been calculated by the following Eqn. (3,4) respectively and shown in table (12,13) [17] [19]. ...
... Comparing the plotted values with the tolerance limits of SN field measurements, presented in Table ( 12,13), it was found that about 1 records from a total of 6 sections are outside the tolerance limits, as shown in Fig. 10 This result means that the variation in 91% of the verification sections result, the verification sections results may be due to the variability in field measurements. The prediction model that was used in this research depends on two main factors to predict the pavement performance :the pavement age (years after construction or last overlay) and the pavement structural number, with age being the most important factor and the structural number being of minor importance in this study. ...
... The same method was proposed for measuring crack severity of both longitudinal and transverse cracks, and subsequently suggests repairs for both together. Shahin (1994) concluded that both longitudinal and transverse cracks equally decreased the quality of asphalt pavements. Zhou et al. (2010) used a new method for evaluating transverse cracking in asphalt pavement. ...
... Third, according to the PCI method and the MicroPaver guideline, longitudinal and transverse cracks are categorized as one distress group, for which the repair methods are as follows (Shahin 1994): (1) no action is required if the widths of cracks are less than 3 mm, (2) crack sealing is required if the widths of cracks are 3-76 mm, and (3) partial depth patching is required if the widths of cracks are larger than 76 mm. There are some differences in the repair methods if the LTE criterion is used, instead of crack width, for repairing the cracks. ...
The purpose of this study is to evaluate longitudinal and transverse cracks in asphalt pavements. Using the concept of load transfer efficiency (LTE), the effects of the crack on reducing the load-bearing capacity (LBC) of the pavement were measured in the field using a portable falling weight deflectometer device. The collected data were analyzed using statistical methods (t-test and box plot), regression method, time history graphs, and artificial neural network approach. Unlike the conventional method of placing longitudinal and transverse cracks in one group, the results showed that these two crack types should be treated separately as they have different behavior. The results also show that for crack width less than 5 mm, the longitudinal cracks have a greater effect on reducing LBC, while for crack width larger than 5 mm, the transverse cracks have a greater effect on reducing LBC. Based on these results, LTE is proposed as a criterion (instead of crack width) for selecting a proper crack-repair method.
... Yang et al., 2005 [88] General Dynamic Markov chain approach, incorporating a logistic model for explicit transition probabilities. By capturing crack state transitions and randomness, it provides a more suitable and efficient method for pavement deterioration modeling. ...
This paper provides a review of predictive analytics for roads, identifying gaps and limitations in current methodologies. It explores the implications of these limitations on accuracy and application, while also discussing how advanced predictive analytics can address these challenges. The article acknowledges the transformative shift brought about by technological advancements and increased computational capabilities. The degradation of pavement surfaces due to increased road users has resulted in safety and comfort issues. Researchers have conducted studies to assess pavement condition and predict future changes in pavement structure. Pavement Management Systems are crucial in developing prediction performance models that estimate pavement condition and degradation severity over time. Machine learning algorithms, artificial neural networks, and regression models have been used, with strengths and weaknesses. Researchers generally agree on their accuracy in estimating pavement condition considering factors like traffic, pavement age, and weather conditions. However, it is important to carefully select an appropriate prediction model to achieve a high-quality prediction performance system. Understanding the strengths and weaknesses of each model enables informed decisions for implementing prediction models that suit specific needs. The advancement of prediction models, coupled with innovative technologies, will contribute to improved pavement management and the overall safety and comfort of road users.
... Each section is split into sample units. Visual evaluation of pavement sample units determines the kind and severity of pavement deterioration [18]. The quantity of the distress is measured accordingly and the PCI is determined for each sample unit. ...
Road maintenance is essential to the growth of the transportation infrastructure and, thereby, has a big impact on a nation's overall economic stability and prosperity. It is impossible to simultaneously monitor and maintain the entire network. As a result, transportation authorities are eager to develop scientific foundations for assessing the importance of maintenance tasks within the network of roads. Hence, pavement assessment methods are needed to establish the priorities and achieving the most convenient level of service. In this study, a road stretch was assessed using the sixteen criteria in the Distress Identification Manual for pavement defects, using pavement condition index (PCI) and multi-criteria decision-making models (MCDM). The two methods were compared to determine the possibility of using MCDM. The study came to the conclusion that MCDM is reliable in assessing pavement performance because both methods indicated that the road pavement is deteriorating.
... Menurut (MKJI, 1997) jenis kendaraan dibagi menjadi 4 yaitu : kendaraan ringan (LV), kendaraan berat (HV), sepeda motor (MC) dan kendaraan tak bermotor (UM). (Shahin, 2005) Ada beberapa jenis pengerukan jalan yaitu retak kulit buaya, keriting, tenggelam, cacat tepi perkerasan, shoulder drop, retak memanjang dan melintang, patch, lubang, alur, runtuh, aspal dari permukaan jalan, retak blok dan retak geser. Untuk pemeliharaan jalan akan bergantung pada nilai urutan prioritas yang ada. ...
Saat ini pertumbuhan penduduk semakin pesat dan tentunya akan berbanding lurus dengan pertumbuhan kebutuhan transportasi. Pada saat yang sama, perlu dipastikan bahwa infrastruktur pendukung penggunaan transportasi dalam keadaan baik, jika tidak maka aktivitas pengguna transportasi akan hancur. Penelitian ini bertujuan untuk mendapatkan volume lalulintas, skor kerusakan jalan dan beban standar (CESA5) terhadap kerusakan pada ruas Jalan Gubernur Sarkawi. Metode Bina Marga merupakan metode yang akan digunakan, yang mana dengan menggunakan analisis regresi dan korelasi, sehingga untuk mendapatkan hubungan tersebut dengan nilai rdan yang menunjukkan besarnya pengaruh antara tingkat kerusakan jalan dengan volume lalu lintas dan beban lalu lintas. Dari analisa yang dilakukan mendapatkan hubungan antara volume lalu lintas per jenis kendaraan dan beban standar terhadap kerusakan jalan, sehingga dari analisa yang dilakukan mendapatkan hubungan terkuat adalah untuk jenis kendaraan mobil penumpang dan kendaraan ringan terhadap jenis kerusakan jalan dengan nilai r sebesar 0,2179, untuk jenis kendaraan 5B (bus besar) terhadap jenis kerusakan mendapatkan nilai r sebesar 0,2184, untuk jenis kendaraan 6A (truk 4 roda 2 sumbu), untuk jenis kendaraan 6B (truk 2 sumbu 6 roda) terhadap jenis kerusakan mendapatkan nilai r sebesar 0,6436, untuk jenis kendaraan 7A1 (truk 3 sumbu) terhadap jenis kerusakan mendapatkan nilai r sebesar 0,2074, untuk jenis kendaraan 7C1 (truk 4 sumbu) terhadap jenis kerusakan mendapatkan nilai r sebesar 0,4498, untuk jenis kendaraan 7C2A (truk 5 sumbu tandem) terhadap jenis kerusakan mendapatkan nilai r sebesar 0,7432 dan untuk LHR (smp/jam) terhadap kerusakan mendapatkan nilai r sebesar 0,8787. Sedangkan untuk hubungan beban standar (CESA5) terhadap skor kerusakan jalan mendapatkan nilai r sebesar 0,7263. Dari analisa yang dilakukan untuk jenis kendaraan yang berpengaruh adalah kendaraan 7C2A (truk 5 sumbu tandem) dengan intepretasi kuat dan untuk beban standar mendapatkan nilai kuat hal ini dikarenakan beban kendaraan yang melewati jalan tersebut secara berulang.
... Researchers have employed a variety of pavement surface distress classification standards. [ Miscellaneous distresses based on [45], and [46]. [1] used the United States Department of Transportation guideline [47] that includes Cracking, Patching and potholes, Surface deformation, Surface defects, and Miscellaneous distresses. ...
Pavement management systems play a significant role in country's economy since road authorities are concerned about preserving their priceless road assets for a longer time to save maintenance costs. An essential part of such systems is how to collect and analyze pavement condition data. This paper reviews the state-of-the-art techniques in pavement condition data evaluation using machine learning techniques, more specifically, the application of machine learning methods: image classification, object detection, and segmentation in pavement distress assessment is investigated. Furthermore, the pavement automated data collection tools and pavement condition indices have been reviewed from the lens of machine learning applications. The review concludes that the overall trends in pavement condition evaluation is to apply machine learning techniques although there are some limitations not only in detection of few pavement distresses with complicated patterns but also in indication of the severity and density of distresses leading to avenues for future research.
... For the purpose of the inspection and evaluation, airfield pavements within the airport are divided in a hierarchical structure of network, branches and sections which is considered to be the first step in establishing a APMS [12,19]. The inventory data was obtained from the airport authority. ...
Airports are vital national resources. Airfield Pavements within an airport represents a large capital investment in infrastructural development made by a country. Timely and appropriate maintenance and rehabilitation of such in-service facilities are essential to provide an all-weather surface for safe and regular operations of the aircraft. Pavement maintenance is done based on functional and structural pavement condition evaluation. This paper presents a case study dealing with functional evaluation of airfield pavements of a small sized airport in India. The considered airport consists of two runway, seven link taxiways, three apron areas and an isolation bay with different surface types. Present paper reports the methodology adopted for the functional condition evaluation of the airfield pavements with help of Automated Road Survey System. Further, the evaluated pavement condition was quantified in terms of Pavement Condition Index (PCI) as per the ASTM D5340 with help of PAVER and GIS based software. GIS was used for preparing inventory database and base maps for the concerned pavements which were then used in PAVER software for determining the PCI. The airfield pavement network within the airport was divided into a four-level hierarchy consisting of the network, branch, section and sample. The obtained PCI rating shows that the overall condition of the airfield pavements within the considered airport is satisfactory to good, however some of the areas have distresses that needs to be repaired by localized maintenance.
... In the Roman Empire, roads were constructed on a larger scale, and they were spread in many directions, assisting them in military maneuverings. Thus, the Romans are deemed to be forerunners in road construction [2,3]. ...
Pavement degradation results due to both ecological and structural reasons. It is never easy to sustain the road to the exact specifications that were kept at the time of opening. With the passage of time, the pavement structure deteriorates. Hence, pavement distresses like different kinds of cracks, holes, and undulations start appearing. Maintenance is an essential practice in providing for the prolonged performance and the aesthetic manifestation of an asphalt pavement. Pavement maintenance aims to rectify deficiencies triggered by distresses and protect the pavement from further damage. The present research seeks to evaluate the distresses produced in flexible pavement. The northern bypass road located in Peshawar, Pakistan, was under consideration as a case study. A methodology was proposed to investigate the pavement condition, consisting of a manual survey performed as per the ASTM D 6433 standard. The pavement was split into different sections. Each section was further divided into sample groups. The kind and severeness of sample distresses were evaluated by visual scrutiny of the pavement sample groups, and the amount of each distress was quantified. This process required a crew of two engineers. It was inferred that identifying defects and knowing their roots could help improve rating pavement conditions and select cost-effective repairing methods. The periodic inspection was found to be necessary for providing current and valuable evaluation data. It was recommended that ratings should be updated every year.
... This condition will eventually burden the economy as a whole [8]. Pavement Condition Index (PCI) is one of the road pavement condition evaluation systems based on the type, level of damage that occur, and can be used as a reference in maintenance efforts on road pavement [9]. Pavement condition assessment is needed to determine the level or level of road conditions [10]. ...
... Naturally, river bed aggregates, which are polished and smooth, also pose a slip hazard if they are used on pavement without crushing. Such aggregates, whose surfaces have become polished, become completely slippery when moisture (Shahin, M.Y.;, Asi, 2005Fwa T. et al. 2003). ...
... Naturally, river bed aggregates, which are polished and smooth, also pose a slip hazard if they are used on pavement without crushing. Such aggregates, whose surfaces have become polished, become completely slippery when moisture (Shahin, M.Y.;, Asi, 2005Fwa T. et al. 2003). ...
Due to rapidly depleting fossil fuels, the demand for higher performance
vehicles, global warming, and stringent emission standards, automotive
and aviation manufacturers are continuously looking for new strategies
to further increase the fuel efficiency (Giampieri et al., 2020). Although these
are important problems for manufacturers, weight reduction method is one of
the strategies in solving these problems. If the weight of a vehicle is reduced
by 10%, the specific fuel consumption will be reduced by 3 to 7% (Manladan
et al., 2017). Therefore, the need for lightweight materials is increasing in the
automotive and aerospace industries.
Aluminum is of great importance among light materials, with its low
density (2.7 gr/cm3
), low melting temperature (660.3 °C), low cost, high
108 ENGINEERING SCIENCES New Trends, Concepts and Research
corrosion resistance and good recycling properties. Moreover, while the
mechanical properties of aluminum can be enhanced by alloying, there is no
big difference between the thermal conductivity, thermal expansion and melting
points of these aluminum alloys (Cao et al., 2020; Dursun & Soutis, 2014; Kurt
et al., 2020; Manladan et al., 2017; Omar Cooke, 2020; Pratap et al., 2021).
As shown in Figure 1, there are eight series of aluminum and many aluminum
alloys derived from them. With the development of precipitation hardening,
the mechanical properties of aluminum have improved enormously and it has
gained a great importance in the metal industry (Starke & Staley, 1996). Thanks
to these properties, aluminum ranks second in the metal market of the world
(Onat, 2018). On the other hand, aircraft and automotive manufacturers are
trying to reduce the number of parts in vehicles and avoid screw or rivet joints.
One method of achieving these is by using the welding process.
... In this regard, firstly, the panel evaluation technique, which envisages the relative evaluation of at least three evaluation experts, was used (Haas et al. 1994). However, although the evaluators are experts in their field, mechanical measurement and evaluation techniques have been developed in the next process since objective results cannot always be obtained during human evaluation (Shahin 2005). In developing the criteria for evaluating the current performance of pavements, many indices have emerged concerning pavement roughness (Haas et al. 1994). ...
The study is aimed to mathematically model the relationship between the amount of whole-body vibration exposed in a passenger car type vehicle and the ride speed of the vehicle in the same section and the International Roughness Index (IRI), which is used as a pavement performance indicator. Vibration measurements were analysed according to the evaluation method determined in the ISO 2631 standard, and frequency-weighted root-mean-square acceleration (aw) values were obtained in the vertical direction. Mathematical relationships between real measurement data performed in 1114 road sections were investigated using regression analysis, artificial neural networks (ANN) and Adaptive Neural Fuzzy Inference System (ANFIS) modelling techniques. The models' performance levels were determined using comparison metrics, and it was determined that ANFIS was the model with the best goodness of fit, with the regression coefficient 0.955, mean absolute error (MAE) 0.013, and root mean squared error (RMSE) 0.020. The threshold values affecting the ride comfort of IRI and the ride comfort values corresponding to the IRI limit values recommended by the Federal Highway Administration (FHWA) were determined through the ANFIS mathematical model. Then, a sensitivity analysis was conducted to determine the effects of a certain increase in the IRI value on discomfort.
... Sebelum dilakukan analisis PCI, ditentukan tipe kerusakan yang terjadi pada jalan berdasarkan tingkat kerusakan yaitu, low (L), medium (M), dan High (H) (Arhin, Williams, Ribbiso, & Anderson, 2015;Setyawan, Nainggolan, & Budiarto, 2015;ASTM, 2008). Untuk lebih jelas, ditampilkan pada Tabel 1 (Shahin, 2000). Vol. 4, No. 4, November 2021: hlm ...
Large vehicles that repeatedly pass a road cause damage to the pavement of the Jatisari National Road, Karawang. Various pavement damage that occurs such as holes, patches, crocodile skin cracks, groove cracks, sungkur, roadside cracks, and subsidence. Pavement Condition Index (PCI) is a method commonly used to indicate the condition of road pavement, so that it can be known good handling to maintain the pavement. The Surface Distress Index (SDI) method can also be used to indicate the condition of the road surface. With the PCI method, the results of the calculation in the Pamanukan direction are classified as perfect at 78%, very good 14%, good 4% and moderate 4%. while the Cikampek direction is classified as perfect at 74%, very good 12%, good 8%, moderate 4%, and bad 2%. Using the SDI method, good results were obtained for both directions. Based on the results of the analysis, research using the PCI and SDI methods showed different results, because the PCI method observed all the damage that occurred on the pavement, while the SDI method only observed 4 elements of damage, so the results displayed were different. ABSTRAKKendaraan besar yang berulang kali melewati sebuah jalan menyebabkan kerusakan pada perkerasan Jalan Nasional Jatisari, Karawang. Berbagai Kerusakan perkerasan yang terjadi seperti, lubang, tambal, retak kulit buaya, retak alur, sungkur, retak tepi jalan, dan amblas. Pavement Condition Index (PCI) merupakan metode yang biasa digunakan untuk menunjukkan kondisi perkerasan jalan, sehingga bisa diketahui penanganan yang baik untuk memelihara perkerasan jalan tersebut. Selain itu, digunakan metode Surface Distress Index (SDI) untuk menunjukkan kondisi permukaan jalan. Dengan Metode PCI, hasil perhitungan pada arah Pamanukan digolongkan sempurna sebesar 78%, sangat baik 14%, baik 4% dan sedang 4%. sedangkan pada arah Cikampek digolongkan sempurna sebesar 74%, sangat baik 12%, baik 8%, sedang 4%, dan buruk 2%. Dengan metode SDI, diperoleh hasil Baik untuk kedua arah jalan. Berdasarkan hasil analisis, penelitian menggunakan metode PCI dan SDI menunjukkan hasil yang berbeda, dikarenakan dalam metode PCI mengamati semua kerusakan yang terjadi pada perkerasan jalan, sedangkan untuk metode SDI hanya mengamati 4 unsur kerusakan, sehingga hasil yang ditampilkan berbeda.
... However, current pavement performance prediction models do not account for the influence of M&R activities during the service life of the pavement, which can affect the accuracy of the predictions [3]. Pavement roughness models are necessary to identify rehabilitation needs, analyze rehabilitation effects, and estimate future pavement conditions to implement different M&R activities to extend the pavement life cycle and provide good surface quality for road users [4,5]. The International Roughness Index (IRI) is accepted as an important indicator of pavement performance and used as the standard for pavement roughness [6]. ...
A large number of paved highway surfaces comprises composite pavements as a result of concrete pavement rehabilitation that uses an asphalt overlay on top of the concrete surface. Annually, billions of dollars are spent on the maintenance and rehabilitation of road networks. Roughness is one of the several indicators of road conditions used to make objective decisions related to road network management. The irregularities in the pavement surface affecting the ride quality of road users can be described by a standard roughness index defined as the International Roughness Index (IRI). Roughness prediction models can identify rehabilitation needs, analyze rehabilitation effects, and estimate future pavement conditions to implement different Maintenance and Rehabilitation (M&R) activities to extend the pavement life cycle and provide a smooth surface for road users. This study intended to develop pavement performance models to predict roughness for asphalt overlay on concrete pavement sections using the Long-Term Performance Pavement (LTPP) program database. Artificial Neural Networks (ANNs) approach was used to develop roughness prediction models. A total of 52 pavement sections with 592 data points were analyzed. Five models were developed, and the best performing model, Model 5 was found with an average square error (ASE) of 0.0023, mean absolute relative error (MARE) of 12.936, and coefficient of determination (R ² ) of 0.88. Model 5 utilized one output variable (IRIMean) and 14 input variables (i.e., Initial IRIMean, Age, Wet-Freeze, Wet Non-Freeze, Dry-Freeze, Dry Non-Freeze, Asphalt Thickness, Concrete Thickness, CN Code, ESAL, Annual Air Temperature, Freeze Index, Freeze-Thaw, and Precipitation). The ANN model structure utilized for Model 5 was 14-9-1 (14 inputs, 9 hidden nodes, and 1 output). Environmental impacts and traffic repetitions can cause severe damage to the pavement if timely maintenance and rehabilitation are not performed. By considering the effects of the M&R history of the pavement, it is possible to obtain realistic prediction models for future planning. Therefore, the developed ANN roughness performance models in this paper can be used as a prediction tool for IRI values and guide decision-makers to develop a better M&R plan. Local and state agencies can use available historical traffic and climatological data in the developed models to estimate the change in IRI values. Utilizing these prediction models eliminates time-consuming data collection and post-processing, and consequently, a cost reduction. This low-cost tool will improve the condition assessment and effective M&R scheduling.
... Entende-se, portanto que, com as devidas manutenções, o pavimento deva manter as funções técnicas no decorrer de sua vida útil. (Shahin, 1994). Contudo, logo começaram a ser utilizados na quantificação da condição de pavimentos rodoviários e aplicados no âmbito dos Sistemas de Gerência de Pavimentos. ...
... Therefore, it is imperative to monitor pavement condition, the present state, measuring various parameters such as the visual distresses, surface roughness, skid resistance, and structural capacity (AASHTO 1993(AASHTO , 2012. In this regard, various methods and indices have been established for measurement of these parameters including Pavement Condition Index (PCI), International Roughness Index (IRI), and Structural Condition Index (SCI) (Sayers 1986b, Zhang et al. 2003, Shahin 2005, AASHTO 2012, ASTM 2018, Fakhri et al. 2021a. ...
Pavement roughness, commonly estimated by the International Roughness Index (IRI), plays an essential role in pavement assessment. However, accessibility to IRI data requires the operation of profiling equipment, which may be costly for the agencies. In this regard, the use of IRI prediction models from pavement distresses could be an alternative solution. In this research, 507 kilometres of asphalt pavements in Kermanshah, Iran, were investigated using IRI and Pavement Surface and Evaluation Rating (PASER) as a rapid and cost-effective index. The IRI prediction models from PASER were developed using regression (R² = 0.66) and Artificial Neural Network (ANN) (R² = 0.69). Regarding the restrictions of the results, the data clustering using k-means and fuzzy c-means (FCM) was taken into consideration to acquire the IRI ranges based on the pavement condition. Using the FCM as the superior approach, the IRI prediction model from PASER and the corresponding membership degrees was developed based on ANN. The results of model development (R² = 0.97) and validation (R² = 0.85) indicated the desirable performance of the ANN model. This case study can be counted as a practical approach for the agencies to economically investigate the pavement condition, predict the roughness, and also make decisions for maintenance targets at the network level.
... The capacity of a specific segment of the pavement to handle high-speed, high-volume, mixed (truck and vehicle) (Hall & Correa Muñoz, 1998). (Shahin, 1994) Şekil 4: Kaplama Durumu İndeksini Belirleme Prosedürü Figure 5a) and dividing by the profile length to yield a summary roughness index with units of slope. (Sayers, 1995) • IRI is computed from a single longitudinal profile. ...
Gerek karayolu idareleri gerekse araştırmacılar tarafından yol kaplamalarının karakteristiklerini belirlemek veya hizmet düzeyleri değerlendirmek üzere çeşitli durum indeksleri kullanmaktadır. Bu çalışmada, beton yollar özelinde kaplama durumunun değerlendirilmesi için literatürde sıkça kullanılan farklı (PSI, PCI, IRI) indeksler ve değerlendirme yöntemlerine ele alınarak, tanımları, hesaplama prosedürleri ve birbirleri ile
olan ilişkileri incenmiş ve en önemlisi beton kaplamaların bu yöntemler vasıtasıyla nasıl değerlendirildiği araştırılmıştır. /
Researchers and highway agencies all over the world have created a wide range of pavement indices to measure or assess the condition of the pavement. This study reviews the common indicators that have been applied to evaluate the condition of concrete pavements. Definition and calculation procedure for all indicators and evaluation methods including PSI, PCI, FWD, and IRI are given, respectively. The main focus of this study is on how concrete pavement are evaluated by these methods.
... Therefore, highway agencies seek to develop an appropriate road M&R plan to achieve acceptable pavement performance, which increases a pavement's service life and saves a limited M&R budget (Han et al. 2020b). By implementing M&R during the beginning phases of deterioration, over half of the maintenance costs can be saved, while travel time, fuel consumption, the number of crashes and user dissatisfaction decrease (Shahin 2005). In this regard, highway agencies use a Pavement Management System (PMS) to manage M&R pavement networks. ...
Maintenance and Rehabilitation (M&R) scheduling is one of the vital aspects of a pavement management system (PMS). This study aims to establish accurate M&R plans for a large-scale pavement network. To this intent, parameters affecting pavement deterioration were identified from the literature, then Random Forest Regression was employed to determine the effective features for pavement deterioration modelling. An accurate pavement deterioration function was generated by applying significant features. The most robust metaheuristic and evolutionary algorithms were selected and adjusted to solve the M&R scheduling optimisation problem, including the Water Cycle Algorithm (WCA), Arithmetic Optimisation Algorithm (AOA), Differential Evolutionary (DE), Ant Colony Optimisation (ACO), Particle Swarm Optimisation (PSO), and Genetic Algorithm (GA). The performance of the mentioned algorithms was compared to help researchers and decision-makers to select the appropriate algorithm for M&R scheduling optimisation. WCA and AOA showed to have the best performance among the adapted algorithms. Compared to AOA, DE, ACO, PSO, and GA, WCA's objective function was calculated to be 45%, 74%, 74%, 77% and 83% less, while its M&R cost was cheaper by 13%, 16%, 27%, 19%, and 18%, respectively.
... Road maintenance activities are classified by the road assets on which they are performed (Alberta Department of Transportation, 2000;Illinois, 2008;Texas Department of Transportation, 2018;Shahin, 2005) into the following categories: pavement, roadside, bridge, traffic control, right of way, drainage, signs, safety items, and illumination activities. ...
Road transport is a major source of environmental pollution. Cars and trucks, which are the most common types of vehicles, exhaust a variety of pollutants (e.g., nitrogen oxides and particulate matter) that are detrimental to human health. Research on the ecological impacts of road vehicles has highlighted the importance of reducing pollutant emissions. This chapter aims to investigate the impacts of road maintenance sites on pollution in the surrounding environment, which is a slightly different and interdisciplinary aspect of the problem.
Road pavement and infrastructure (bridges, viaducts, and tunnels) must be maintained for the road network to function properly. Maintenance sites interrupt the normal flow of traffic, which leads to traffic jams, higher travel times, and pollutant emissions.
This chapter explores a variety of approaches to traffic emissions modeling to identify a numerical model capable of determining the ecological impacts of maintenance sites on the surrounding environment. A simple simulation will be conducted to demonstrate the importance of the subject. Research gaps are presented at the end of the chapter to guide future studies.
... Besides regulators, various researchers have sought to optimise the application of resources in APMSs by proposing improvements and implementing procedures while considering the particularities inherent to the aviation sector. Using data on construction, conservation and restoration recorded by public authorities, Shahin (2005) proposed the use of survival curves for planning maintenance and repair (M&R) alternatives for paved areas in general. Ismail et al. (2009) showed it is possible to develop pavement management systems through specialised systems based on artificial intelligence. ...
An efficient Airport Pavement Management System is essential to judge the current and predict the future runway conditions and support decisions. However, one of the limitations is the insufficient scope for analysis of the infrastructure environment, particularly regarding the loss of revenue due to the need for total or partial closure of the runway in Life Cycle Cost Analysis (LCCA) approaches. This article proposes a method for calculating indirect/user costs, based on the net present value related to the closed runway time in the cash flow variable. This method integrates passenger demand forecasts based on machine learning and net operating revenue of the airport. Relying on a case study of Brasília International Airport, the consideration of a variable called "equivalent operational susceptibility area" improved understanding of the financial impacts on the indirect/user costs and the direct/owner costs. This variable enabled visualisation of the conditions for the financial feasibility of pavement intervention scenarios. The proposed method uses the required time of runway closure and the area to be maintained as balance weights between the direct and indirect costs of an LCCA. Therefore, it is not reasonable to relegate indirect/user costs to estimated values or some few aircraft and passenger movement fees.
... The system consists of data and analysis provided by pavement performance evaluation conducted under various climate conditions, with different pavement materials, pavement implementations, and traffic loadings (3,4). Pavement performance is evaluated based on surface distresses such as different types of cracks, deformations, bleeding, weathering, and potholes, as well as roughness and ride quality, skid resistance, and the structural capacity of pavement sublayers (5,6). This evaluation is performed periodically and pavement maintenance and rehabilitation are taken into account based on the results with reasonable timing. ...
Roughness is one of the most significant parameters in the evaluation of pavement performance. Surface distresses are among the main factors leading to roughness. The collection and evaluation of roughness data require the application of modern equipment such as road surface profilers. In the absence of such equipment, roughness prediction models that are based on surface distresses might provide a desirable assessment of pavement conditions. This research employs the laser crack measurement system (LCMS) to detect and measure surface distresses and roughness along 268 km of primary roads in Iran. Compared with manual survey, LCMS provides maximum detection and measurement accuracy. Based on the LCMS output, distresses with a higher correlation with the International Roughness Index (IRI) were selected as predictors in linear regression models and artificial neural networks (ANN). The models were developed for 10 m and 100 m length sections of the roads under different climate and traffic conditions. The results indicate that the performance of ANN for the 100 m sections with coefficient of determination ( R ² ) of 0.82 is superior to other models. The best case was that of using ANN in 100 m sections for regions with moderate climate and medium traffic levels, with a 0.94 correlation. Satisfactory results in field validation of the models demonstrated that agencies can use other methods of data collection (e.g., manual, right of way [ROW]) to assess the surface distresses and roughness condition of their roads from the developed models with minimum spending and without expensive equipment. Such estimates can be employed to make informed decisions in pavement maintenance programs at the network level.
... The authors of [29][30][31][32] researched the performances of modern electronic tachymeters and their incorporation into the monitoring of the deformations. Therefore, the maintenance of the runways must be managed with precautions, so they are kept in the best condition and, with the use of APMS, with minimal costs [11,33]. Thus, the risks, caused by inadequate maintenance, and consequently, the closure or limited function of the runway are diminished [6]. ...
The demand for safety and to provide safety are increasing, parallel with the growth of the need for mobility, transport and logistics. A big part of the demands and recommendations to provide safety in air traffic is related to the safety at and in the surroundings of the runways. The research focused on exploring the airport infrastructure; mainly with the aim of detecting and monitoring the deformations (cracks, displacements, etc.) of the runways which are causally connected with unusual landings or taking offs, with trips from the runways and with loss of control over the aircraft during the landings, taking offs and while moving the runways or taxiways, etc., and researching their effect on providing safety and the efficiency of the airports’ function. The research was executed at the Maribor Edvard Rusjan Airport in three phases; the first two were meant for geodetic measurements to determine vertical deformations and the third for supplementary measurements to determine static load capacity. The result of the research is an innovative model for the continuous monitoring of the deformations on the runways. The suggested model enables determination and display of the areas of the vertical deviations which are impossible to detect with a visual check-up, joining the supplementary methods and assessing the condition of the runway based on executed measurements.
... Other researchers have developed methods that minimize the sum of residuals (errors), defined as the difference between the observed distress ratings and their corresponding predicted values obtained from the Markov model [44,55,56]. ...
Road transportation has always been inherent in developing societies, impacting between 10–20% of Gross Domestic Product (GDP). It is responsible for personal mobility (access to services, goods, and leisure), and that is why world economies rely upon the efficient and safe functioning of transportation facilities. Road maintenance is vital since the need for maintenance increases as road infrastructure ages and is based on sustainability, meaning that spending money now saves much more in the future. Furthermore, road maintenance plays a significant role in road safety. However, pavement management is a challenging task because available budgets are limited. Road agencies need to set programming plans for the short term and the long term to select and schedule maintenance and rehabilitation operations. Pavement performance prediction models (PPPMs) are a crucial element in pavement management systems (PMSs), providing the prediction of distresses and, therefore, allowing active and efficient management. This work aims to review the modeling techniques that are commonly used in the development of these models. The pavement deterioration process is stochastic by nature. It requires complex deterministic or probabilistic modeling techniques, which will be presented here, as well as the advantages and disadvantages of each of them. Finally, conclusions will be drawn, and some guidelines to support the development of PPPMs will be proposed.
... An unbiased and repeatable survey procedure is usually selected, preferably also one that is easily understood and relatively simple to perform in the field. A commonly used technique is the PCI procedure developed back in the 1970s by the United States Army Corps of Engineers [42]. The PCI evaluation procedure for flexible pavements follows the MicroPAVER distress guide methodology [25]. ...
Public agencies use pavement management systems to make objective decisions and maintain pavements above the minimum acceptable performance conditions at minimal costs. To achieve this goal, pavement condition is monitored, so its deterioration could be accurately predicted, in order to decide on any required maintenance and rehabilitation. The Pavement Condition Index (PCI) is a composite index used to assess the condition of flexible pavements. The International Roughness Index (IRI) is a smoothness or quality of ride indicator, which is the cumulative vertical movements or vibrations divided by the profile length. Collecting IRI is straightforward and much more affordable than collecting pavement distress data. Predicting the PCI for pavement management assessments without evaluating the extent and severity of the distresses saves costs and person-hours. In this paper, gene expression programming (GEP) was adopted for the first time to predict the PCI from the IRI, using data that was half compiled from the existing literature and the other half was measured and collected in the field by the authors. The PCI values predicted by the GEP model were compared to the estimated PCI values from applying models published in previous studies. The GEP model outperformed all the other available models in the literature, with a maximum R2 of 82% for the complete dataset.
... Various factors that affect prioritization includes pavement condition, traffic volume, age of pavement, previous maintenance undertaken and financial constraints. In today's economic environment, as the pavements are aging and getting overburdened, a more systematic approach for determining M&R needs and priorities is necessary [3]. To prioritize pavement maintenance activities, a number of decision making methods have been introduced and implemented under PMS. ...
Prioritisation of pavement sections in a road network is an important aspect of decision making in an efficient Pavement Management System (PMS). Prioritisation is done either empirically based on single condition parameter or subjectively based on decision maker’s experience which results in discrepancies as there always exists a difference of opinion among the different members of committee making decisions. A methodology for prioritisation has been suggested in this paper using one of the MCDM techniques i.e. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). TOPSIS approaches a problem based on condition data and provides relative priority ranks of the sections considered in a dataset. TOPSIS results in the ranking list of candidate sections based on their Relative Closeness (C*) to ideal solutions. Further the results of priority rankings are compared with the corresponding rankings obtained from a subjective method i.e. Road Condition Index (RCI). Strong positive association was observed between the two methods, but TOPSIS being an objective method and having ease of applicability was found to be more suitable for prioritisation purpose of roads in a network for Maintenance and Rehabilitation (M&R).
This study presents two methods for airport asphalt pavements distresses data collection tested on the main runway of Amílcar Cabral International Airport, located at Sal Island in Cape Verde. The two methods tested were traditional visual inspection (by foot) and an indirect method using a vehicle equipped with image capture and recording, lasers and geopositioning devices (in-vehicle inspection).
The aim of this research is to contribute to the validation of the proposed low-cost in-vehicle pavement distress inspection system in order to be considered in the implementation of the pavement condition assessment component of an Airport Pavement Management System (APMS). This is a particularly important component as from the collected distress data it is possible to assess the condition of the pavements and define intervention strategies.
Validation of the indirect data collection method is evaluated by statistical comparison of the collected distress data and Pavement Condition Index (PCI) obtained whit the two methods. Statistically non-significant differences between the result sets validate the proposed indirect method, resulting in significant advantages in respect to the amount of pavement area inspected (larger), inspection time (shorter), data collection cost, processing and results visualization (on a GIS), revaluation of the dataset (possible on indirect method) and quality control (simpler and faster).
Pavement distress is a major contributor to overall road quality degradation. Maintaining roadways with the use of a Pavement Management System requires an extensive and up-to-date inventory of the many types of roadway distress. Such inventory for a road network can be labor-intensive and time-consuming to create. This study introduces a novel method, called Hybrid Method, to detect asphalt pavement surface cracks based on 2D images. Hybrid Method consists of two separate techniques, proposed by this study, which are combined to detect cracks. The first is a supervised learning-based technique which requires annotated images. This approach utilizes the Local Binary Pattern (LBP) as a texture descriptor algorithm to encode image data. Random Forest is the classifier, employed to learn from the extracted LBP features and predict new observations. The second, density-based technique, relies primarily on thresholding. This technique searches for crack objects iteratively while considering their spatial and geometric properties. These techniques were merged to create a hybrid crack detection method that was found to be effective for detecting pavement surface cracks. Four datasets were analyzed using the proposed Hybrid Method, which resulted in an average precision, recall, and F1 scores of 90%, 78%, and 84%, respectively. The results suggest that the Hybrid Method performed well in challenging situations, such as images with shadows, road markings, and oil stains. Its performance on images of different resolutions, pavement textures, and lighting conditions was remarkable as well.
This study explored the outcomes of utilizing genetic algorithms and artificial neural networks to assess the pavement quality index on the principal road by analyzing 500 flexible pavement sections in Amman, Jordan. Pavement sections are selected in areas that are exposed to many variables, such as traffic, pavement materials, and different climatic zones. Pavement deterioration is determined by a number of factors, including cumulative equivalent single axle load, pavement structure, and material properties. The study aims to develop a performance model of PQI based on using surface rating (SR), present serviceability rating (PSR), and pavement age. Several techniques were used to propose the PQI model, such as multiple linear regression, genetic algorithm, and artificial neural network. Multiple linear regression showed that PSR and SR had a statistically significant influence only on PQI (P= 0.0001). However, age is less significant on PQI (p = 0.506). The genetic algorithm and the artificial neural network techniques were applied to propose two PQI models with an R2 value for the training model of 0.98 and 0.94, respectively. The study results show means that the genetic algorithm model performs better than the neural network.
Pavement maintenance management system motivates to provide a scientific tool for maintenance and rehabilitation of roads pavement at desired serviceability levels. In view of the fund’s constraints and the need for judicious spending of available resources, the maintenance planning and budgeting are required to be done based on scientific methods. Unfortunately, the current maintenance practices are ad-hoc and subjective in nature. Pavement condition responsive maintenance is very useful for judicious disbursement of maintenance funds. The objective of this paper is to select a feasible treatment for routine maintenance based on pavement condition parameters of flexible pavement using Fuzzy Logic Expert System (FLES). Six different national highways have been selected to provide the maintenance based on the PCI, traffic volume, pavement age, precipitation, temperature and budget. FLES offers a convenient tool to better represent the uncertainty involved in pavement condition rating and assessment. The pavement maintenance treatment needs are generally determined based on the results of visual inspection, which in most of the cases does not give an adequate representation of pavement condition. Treatment selection FLES model has considered anticipated distresses-based condition index, anticipated traffic, and prevailing climate, age of the pavement and budget for treatments. Model predicts treatment types based upon their expected life. The triangular membership function for all the parameter is considered and analyzed with sufficient number of fuzzy rules as suggested by the maintenance engineers. The predicted result was compared with the twenty-five maintenance engineer’s responses, which shows homological results. Hence, this approach may provide an appropriate and economically viable maintenance treatment.
Quantification of present pavement condition in terms of an index term i.e., Pavement Condition Index (PCI) is one of the most important and primary steps while taking decision related to Maintenance and Rehabilitation of Pavements. PCI as proposed by ASTM D6433 rates pavement in seven conditions viz. Good, Satisfactory, Fair, Poor, Very Poor, Serious and Failed. Determination of rating condition of pavement using distress severity and extent turns out to be tedious process. Hence, present study investigates application machine learning techniques for assessment of present pavement condition. Three different algorithms i.e., Logistic Regression, Naïve Bayes and K-Nearest Neighbor have been tested in the present study using Long Term Pavement Performance database consisting of over 10,000 datapoints. The dataset was divided into 7:3 ratio for training and testing phase. Employed algorithms were tested based on accuracy, precision, recall and f-measure. Logistic Regression Classifier was found to have highest accuracy of 0.92 among three classifiers used in the study.
Volume 18, Nomor 02, Desember 2021
Terdapat beberapa program pengelolaan anggaran biaya pemeliharaan jalan, salah satu yang banyak digunakan belakangan ini adalah LCCA ( Life Cycle Cost Analysis ). Disamping program tersebut, Kementerian PU memperkenalkan program KRMS ( Kabupaten Road Management System ) yaitu program baru yang bukan hanya menghitung anggaran biaya yang terdapat di perkerasan saja, melainkan menghitung pula anggaran komponen-komponen jalan daerah. Akan tetapi penggunaan program tersebut masih dalam masa percobaan, sehingga diperlukan sebuah penelitian untuk melihat sejauh mana program tersebut dapat digunakan dengan cara membandingkannya dengan program LCCA. Lokasi penelitian adalah sembilan ruas jalan Kabupaten Takalar, yang menghubungkan antara daerah di Kabupaten. Selain hal tersebut, penelitian ini juga menghitung analisis sensitivitas terhadap Program KRMS dan LCCA akibat perubahan parameter-parameter biaya pemeliharaan . Hasil yang diperoleh nilai t-hitung -0,631 setelah dikonsultasikan dengan t-tabel yaitu -2,306 sampai 2,306 thit berada dalam t-tabel, sehingga terdapat persamaan perhitungan antara KRMS dan LCCA. Selain itu dalam analisis sensitivitas, biaya pemeliharaan jalan dengan menggunakan KRMS maupun LCCA sensitif terhadap perubahan LHR dan tidak sensitif terhadap perubahan peningkatan harga bahan bangunan. Program KRMS lebih sensitif dari pada program LCCA terhadap perubahan yang terjadi pada LHR.
Punctually and appropriate maintenance of pavement black top surface using suitable material and method is significant for the preservation of road assets and to serve the intended purpose. An adequate maintenance management system that would be useful to highway agencies in regularly planning pavement maintenance strategies to ensure the minimal maintenance fund is used rationally. The target of this paper is to develop a hypothetic overall pavement condition index (OPCI) for the maintenance strategy selection for Indian Highways, exclusively for flexible pavements. This index incorporates salient indicators as distress, structural capacity, roughness and skid resistance. The distress index has been computed considering the maximum allowable extent principle. Multiplicative Index Approach was applied to develop OPCI. An expert opinion survey was conducted to evaluate the weightage for each indicator using the relative impact on pavement condition. The results reveal that the weight factor is 0.6 for structure capacity, 0.5 for roughness and 0.15 for skid resistance which is lower than the distress weight factor. The relative importance that should be given to each indicator are calculated to be 80% for distresses, 10% for structural capacity, 8% for roughness and 2% for skid resistance. The combined distress pavement condition index infests in almost one higher rating scale than PCI whereas OPCI is 21% lower than the PCI. This indicates the requirement of a conservative maintenance alternative. However, a condition indicator that consists of multiple indices is much more important in identifying suitable maintenance alternative approaches to fully restore the structural integrity and riding quality of the pavement.
Runway surface conditions are fundamental to ensure safety during landing and takeoff
operations of aircrafts. In this manner, airport operators are required to monitor the
coefficient of friction and macrotexture of runways to maintain its safety and plan
maintenance and rehabilitation strategies when appropriate, since both these parameters
get deteriorated with time. Thus, to assist aerodrome operators and regulatory
agencies in the decision-making process for conservation and monitoring of airfield
pavements, this study aimed to develop a prediction model for runway friction using
Artificial Neural Network. Our results were satisfactory and may contribute to the
decision-making process in the context of the Airport Pavement Management System.
The back-calculation of layer moduli using falling weight deflectometer (FWD) data is an essential part of the pavement maintenance measures in pavement asset management systems (PAMS). It is necessary to provide the back-calculation predicted layer moduli and other pavement distresses as a part of PAMS to estimate the optimal maintenance strategy. The predicted layer moduli can be introduced as a part of PAMS if the back-calculation model can be easily integrated. In this study, the cuckoo search algorithm (CSA) was used as an optimization tool to develop a back-calculation model, BACKCSA, for predicting the pavement layer moduli using FWD data. The developed model was validated by comparing it with the laboratory-measured resilient moduli (MR) values of the field core samples obtained from five different highway sections. The variation between the laboratory MR values and the BACKCSA model predicted layer moduli was marginal. The pavement layer moduli values obtained from the BACKCSA model were also compared with the back-calculated layer moduli obtained using the BAKFAA model. The statistical hypothesis testing revealed that the predicted layer moduli from BACKCSA and BAKFAA models were similar to the laboratory-measured MR values. The mean absolute percentage error (MAPE) between the BACKCSA model predicted layer moduli and the laboratory-measured MR values was 2.49% on an average, indicating a marginal error between the predicted and the measured values. One of the most significant benefits of using the BACKCSA model over the other back-calculation models is its ability to handle deflection data from any FWD equipment, in general.
Penurunan kualitas jalan mengakibatkan terjadinya kerusakan jalan. Hal tersebutlah yang membuat peneliti ingin mengetahui kondisi jalan sugio-kedungpring untuk menganalisis kerusakannya menggunakan metode PCI. Dilakukannya penelitian ini yaitu untuk mengetahui kondisi jalan yang mengalami kerusakan sebagai dasar acuan untuk perbaikan jalan agar jalan tersebut dapat berfungsi dengan layak. Penelitian akan dilakukan dengan pengumpulan data primer berupa jenis kerusakan jalan, luasan kerusakan jalan tingkat kerusakan dan lain-lain yang didapat dengan cara survei di lapangan, serta data sekunder berupa tinjauan literatur dan curah hujan harian dengan cara studi dokumen, setelah itu data akan dianalisis menggunakan metode PCI dan didapat kesimpulan jenis kerusakan jalan didominasi dengan kerusakan retak kulit buaya dengan nilai kondisi perkerasan sebesar 53,952. Dilakukannya penelitian ini bertujuan untuk mengetahui dominasi kerusakan jalan, dan besaran nilai kondisi perkerasan jalan di jalan sugio-kedungpring.
Since environmental factors at pavement construction sites are usually changed, the behavior of plastic shrinkage cracking, which is a common type of distress in concrete pavement, needs to be assessed to avoid deterioration and apply a more appropriate preventive method. This study evaluates the effects of different ambient temperature (30, 35, and 40 °C), relative humidity of the air (20, 45, and 70%), and wind speed (18, 24, and 30 km/h) on the characteristics of plastic shrinkage cracking distress in concrete pavement that are more practical in terms of inspection. These practical characteristics include temporal characteristics (time of balance of bleeding and evaporation, and time of the start of crackling) and geometric characteristics (mean cracking width, length of cracking, and area of cracking). They were examined in different environmental conditions according to ASTM C1579 standard test method, using an environmental simulator chamber and a digital monitoring approach consisted of digital image analysis. The results showed that practical characteristics are useful in denoting the behavior of plastic shrinkage cracking distress in concrete pavements in different environmental conditions. Each environmental factor has a different significant effect on the behavior of plastic shrinkage cracking distress. The time of balance was the most affected temporal characteristics, which shows higher sensitivity of the bleeding state of concrete pavement to environmental factors. Among geometric characteristics, the area of cracking was changed the most. Different environmental factors also had a more significant effect on the transverse changing of cracking than its longitudinal. The relative humidity had the most effects on the temporal and geometric characteristics, and the effects of temperature and wind speed were close to each other. A significant relationship was observed between the time of balance and the area of cracking, which indicates that the time of balance can be used effectively to predict cracking severity in different environmental conditions.
The culmination of a research effort to improve the prediction, optimization, and budget allocation abilities of the Micro PAVER pavement management system is a prioritization scheme capable of taking in available budget estimates for any number of years and outputting the sections recommended for repair and the type and cost of repair to be applied. The scheme uses as its base the effectiveness/cost ratios obtained from a dynamic programming module. These ratios are then modified by weights that are related to section characteristics by each individual pavement manager. This enables a customized output to be obtained for each database. The available budget for repair is determined as the actual budget less the cost of routine and stopgap repairs on every section. This budget is then allocated to the highest-scoring (in terms of weighted effectiveness/cost ratio) sections until the budget is exhausted. Deterministic Pavement Condition Index (PCI) versus age curves are used to predict each section's condition in the following year, and the process is then repeated. A completed example is included to illustrate the working of the program logic.
This report contains the results of an intensive study of response-type road roughness measuring systems (primarily Mays- and PCA-type road meters) for the purpose of developing calibration and correlation procedures. An artificial road bump approach is described as a simplified method for a calibration check of road meter systems. The method offers potential for calibrating systems over the moderate-to-rough range of the roughness scale.