Development of Pavement Condition Rating Model and Pavement Roughness Model for Saudi Highways

2013 ◽  
Vol 723 ◽  
pp. 820-828 ◽  
Author(s):  
Muhammad Mubaraki
Keyword(s):  
Iri Model ◽  
International Roughness Index ◽  
Pavement Condition ◽  
Safety Issues ◽  
Condition Rating ◽  
Pavement Roughness ◽  
Roughness Model ◽  
Pavement Deterioration ◽  
Total Observation ◽  
Rating Model

The Pavement Condition Rating (PCR) has been used by the Ministry of Transport (MOT) in Saudi Arabia to report pavement condition. The World Bank developed the PCR in 1986. PCR is based on International Roughness Index (IRI), Rutting (RUT), Cracking (CRA), and Raveling (RAV). The MOT collects pavement condition data using a digital inspection vehicle called Road Surface Tester (RST) vehicle. On some expressways, the MOT measures the Skid Number (SN) using a Skid Test Unit as complimentary measurement for safety issues. The objective of this paper is to develop PCR model and pavement roughness model using survey data for overlaid sections on some expressways in the network with total observation number is 3469. The PCR model is a function of pavement age (T), Traffic Volume (TV), and IRI. The IRI model is a function of RUT, RAV, and CRA. Overlaid sections across the entire network have been selected to study the mechanisms of pavement deterioration, to develop the model and to draw conclusions.

scholarly journals Optimization of International Roughness Index Model Parameters for Sustainable Runway

2021 ◽  
Vol 13 (4) ◽  
pp. 2184
Author(s):  
Yu Tian ◽  
Shifu Liu ◽  
Le Liu ◽  
Peng Xiang
Keyword(s):  
Frequency Response ◽  
Dynamic Responses ◽  
Model Parameters ◽  
Response Distribution ◽  
Iri Model ◽  
International Roughness Index ◽  
Pavement Roughness ◽  
Study Results ◽  
Roughness Index ◽  
Roughness Evaluation

Pavement roughness is a critical airport pavement characteristic that has been linked to impacts such as safety and service life. A properly defined roughness evaluation method would reduce airport operational risk, prolong the life of aircraft landing gear, and optimize the decision-making process for pavement preservation, which together positively contribute to overall airport sustainability. In this study, we optimized the parameters of the International Roughness Index (IRI) model to resolve the current poor correlation between the IRI and aircraft vibration responses in order to adapt and extend the IRI’s use for airport runway roughness evaluation. We developed and validated a virtual prototype model based on ADAMS/Aircraft software for the Boeing 737–800 and then employed the model to predict the aircraft’s dynamic responses to runway pavement roughness. By developing a frequency response function for the standard 1/4 vehicle model, we obtained frequency response distribution curves for the IRI. Based on runway roughness data, we used fast Fourier transform to implement the frequency response distribution of the aircraft. We then utilized Particle Swarm Optimization to determine more appropriate IRI model parameters rather than modifying the model itself. Our case study results indicate that the correlation coefficient for the optimized IRI model and aircraft vibration response shows a qualitative leap from that of the original IRI model.

Investigating the Effects of Pavement Roughness on Freeway Safety using Data from Five States

2020 ◽  
Vol 2674 (2) ◽  
pp. 127-134
Author(s):  
Jaeyoung Lee ◽  
Mohamed Abdel-Aty ◽  
Eric Nyame-Baafi
Keyword(s):  
Traffic Volume ◽  
Speed Limit ◽  
International Roughness Index ◽  
Related Factors ◽  
Vehicle Performance ◽  
Pavement Condition ◽  
Pavement Roughness ◽  
Large Numbers ◽  
Using Data ◽  
Median Width

Traffic crashes occur usually because of a combination of human, roadway/environment, and vehicle factors. Pavement condition is closely related to these three factors as it is one of the most important roadway/environment factors and it affects driving behavior and vehicle performance at the same time. Previous studies have shown that pavement condition plays an important role in safety. This study develops four different safety performance functions to evaluate the effect of pavement roughness, measured by the International Roughness Index (IRI), on the number of crashes using the interstate highway data from five U.S. states representing different geographical and weather regions: Arizona, Colorado, Florida, Maryland, and Michigan. The modeling results identify many significant variables including traffic volume and proportion of trucks, through lane count, shoulder type, median width, high-occupancy vehicle (HOV) lane operation and HOV lane count, speed limit, area type along with IRI-related factors. The results indicate that increased IRI (deterioration of pavement quality) contributes to large numbers of total crashes. On interstate highways with speed limits of 70 mph and higher, the effects of IRI are relatively smaller. On the other hand, the effects of IRI increase with a larger traffic volume. Based on the modeling results, seven crash modification functions of IRI values by crash type and speed limit were estimated. The findings from this study are expected to be useful for both pavement and safety engineers to understand the relationship between IRI and safety on freeways.

Adequate data collection frequency and gauging length for surface condition rating in Alberta

2001 ◽  
Vol 28 (5) ◽  
pp. 871-874
Author(s):  
Ashraf El-Assaly ◽  
Simaan AbouRizk ◽  
Jane Stoeck
Keyword(s):  
Data Collection ◽  
Surface Condition ◽  
Pavement Condition ◽  
Condition Rating ◽  
Deterioration Rate ◽  
Pavement Evaluation ◽  
Pavement Deterioration ◽  
Transportation Departments ◽  
Data Collection Procedure ◽  
Adequate Data

In order to ensure safe and comfortable riding, increase network serviceability, and slow pavement deterioration rate, two different strategies are being used simultaneously by transportation departments: routine maintenance and major rehabilitation. Within Alberta Infrastructure, the decision between these alternatives is made based on the pavement condition. Data are collected frequently for the purpose of pavement evaluation. Experienced engineers and technicians normally decide the most appropriate data collection procedure and gauging length associated with it.Key words: pavement, data collection, evaluation, gauging length, condition rating.

Optimized maintenance model for wastewater treatment plants

2020 ◽  
Vol 47 (8) ◽  
pp. 929-938
Author(s):  
Khalid Kaddoura ◽  
Tarek Zayed ◽  
Zhi Chen ◽  
Altayeb Qasem ◽  
Serter Atabay
Keyword(s):  
Wastewater Treatment ◽  
Wastewater Treatment Plants ◽  
Absolute Error ◽  
Assessment Model ◽  
Binary Integer Programming ◽  
Significant Deterioration ◽  
Condition Rating ◽  
Statistics Canada ◽  
Rating Model ◽  
Maintenance Model

Wastewater treatment plants (WWTPs) are facing significant deterioration due to aging and improper maintenance. Statistics Canada reported that 22% and 14% of the wastewater treatment plants in Alberta and Ontario, respectively, are in poor and very poor conditions. Because of the non-capital and capital improvement requirements for any WWTP, intervention decision-making tools are paramount. The objectives of this research were to develop an integrated condition rating model for the WWTP and an optimized maintenance, rehabilitation, and replacement (MR&R) intervention model. The condition assessment model was applied on case studies and the indices supplied by the operators were used to compare the results of model through the mean absolute error (MAE) calculation, which was minimal. To optimize the intervention decisions for various units of the WWTP, the binary integer programming was used. These models are expected to enhance the evaluation of WWTPs and facilitate intervention plans based on an optimized methodology.

scholarly journals Studying the Applicability of X-Band SAR Data to the Network-Scale Mapping of Pavement Roughness on US Roads

2020 ◽  
Vol 12 (9) ◽  
pp. 1507 ◽  
Author(s):  
Franz J. Meyer ◽  
Olaniyi A. Ajadi ◽  
Edward J. Hoppe
Keyword(s):  
High Resolution ◽  
Remote Sensing Data ◽  
Ride Quality ◽  
International Roughness Index ◽  
Pavement Roughness ◽  
X Band ◽  
The Us ◽  
Network Scale ◽  
Sar Data ◽  
Satellite Radar

The traveling public judges the quality of a road mostly by its roughness and/or ride quality. Hence, mapping, monitoring, and maintaining adequate pavement smoothness is of high importance to State Departments of Transportation in the US. Current methods rely mostly on in situ measurements and are, therefore, time consuming and costly when applied at the network scale. This paper studies the applicability of satellite radar remote sensing data, specifically, high-resolution Synthetic Aperture Radar (SAR) data acquired at X-band, to the network-wide mapping of pavement roughness of roads in the US. Based on a comparison of high-resolution X-band Cosmo-SkyMed images with road roughness data in the form of International Roughness Index (IRI) measurements, we found that X-band radar brightness generally increases when pavement roughness worsens. Based on these findings, we developed and inverted a model to distinguish well maintained road segments from segments in need of repair. Over test sites in Augusta County, VA, we found that our classification scheme reaches an overall accuracy of 92.6%. This study illustrates the capacity of X-band SAR for pavement roughness mapping and suggests that incorporating SAR into DOT operations could be beneficial.

scholarly journals Pavement Deterioration Rate and Maintenance Cost for Low-Volume Roads

2020 ◽  
Vol 312 ◽  
pp. 06002
Author(s):  
Turki I Al-Suleiman ◽  
Subhi M Bazlamit ◽  
Mahmoud Azzama ◽  
Hesham S Ahmad
Keyword(s):  
Surface Defects ◽  
Condition Index ◽  
Maintenance Cost ◽  
Pavement Condition ◽  
Pavement Maintenance ◽  
Deterioration Rate ◽  
Pavement Deterioration ◽  
Pavement Condition Index ◽  
Traffic Volumes ◽  
Over Time

Allocated budgets for maintenance of road networks are normally limited. Therefore, not all roads receive the required attention they deserve in a timely manner. These roads are left to deteriorate until the next maintenance round. The cost associated with delayed maintenance is significantly excessive. A Pavement Maintenance Management System (PMMS) can be a useful tool for evaluation, prioritization of Maintenance and Rehabilitation (M&R) projects, and determination of funding requirements and allocations. The pavement condition is normally indexed using a parameter called Pavement Condition Index (PCI) which represents an overall assessment of surface defects by type, severity and extent. Periodic collections of PCI over time for different sections within the roadway network provide an approach to monitor changes in pavement serviceability over time and can produce useful data to predict and evaluate required maintenance solutions and their associated cost. The researchers intend to use available data collected over the span of a year and a half on sections within the roadway network at the campus of Al-Zaytoonah University of Jordan (ZUJ) to study the relation between the maintenance cost and the pavement deterioration rate. This study may incorporate variables such as pavement age, traffic volumes, maintenance history and pavement condition assessment results. The available records of PCI will be analyzed and the findings will be clearly presented. The practical inclusion of the findings within the current PMMS used at the university will also be detailed.

scholarly journals Study of Pavement Condition Index (PCI) relationship with International Roughness Index (IRI) on Flexible Pavement.

2019 ◽  
Vol 258 ◽  
pp. 03019 ◽  
Author(s):  
Rijal Psalmen Hasibuan ◽  
Medis Sejahtera Surbakti
Keyword(s):  
Condition Index ◽  
International Roughness Index ◽  
Pavement Condition ◽  
The Road ◽  
Roughness Index ◽  
Pavement Condition Index ◽  
Local Roads ◽  
Actual Field ◽  
Two Parameters

Road is an infrastructure that built to support the movement of the vehicle from one place to another for different purposes. Today, it is often found damage to road infrastructure, both local roads, and arterial roads. Therefore, to keep the pavement condition to remain reliable, in Indonesia has a periodic program by conducting an objective functional inspection of roads regulated by Bina Marga using the International Roughness Index (IRI). However, the IRI examination is not sufficient to represent the actual field condition; it is necessary to perform subjective functional examination by appraising the road one of them is Pavement Condition Index (PCI, ASTM D 6433). This method has been widely applied in some countries because it has many advantages. However, to do this inspection requires considerable cost, then there needs to be a model to get the relationship between these two parameters of the road. The selected case study was arterial road segment in Medan City, that is in Medan inner ring road. Based on the results of the analysis, there is a difference between the functional conditions of PCI and IRI. The equation derived from these two parameters is by exponential regression equation, with equation IRI = 16.07exp-0.26PCI. with R2 of 59% with correlation coefficient value (r) of -0.768. The value of R2 indicates that PCI gives a strong influence on IRI value.

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