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Charalambos Kyriakou and Symeon E. Christodoulou

Detecting Pavement Patches Utilizing Smartphones Technology and Vehicles

Abstract: Presented herein is a study on the utilization of low-cost technology for detection of roadway pavement anomalies (patches and potholes), by use of sensors on smartphones and of automobilesÕ on-board diagnostic (OBD-II) devices for the collection and analysis of vibration-related data while vehicles are in movement. The mobile data collection kit consists of a triaxial accelerometer, a gyroscope and a global positioning sensor. The smartphone-based data collection is complimented with robust regression analysis and a bagged-trees classification model for the classification of pavement anomalies. The proposed system is readily available, low-cost and adequately accurate, and can be utilized in crowd-sourced applications for pavement monitoring. Further, the proposed methodology has been field-tested, exhibiting detection accuracy levels higher than 90% for pavement patches, and it is currently expanded to include larger datasets and a bigger number of pavement defect types.

Keywords: Pavement Anomalies, Detection and Classification, Smartphones Technology, Robust Regression, Bagged Trees

DOI: https://doi.org/10.24928/JC3-2017/0109

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Series: jc3:2017 (browse)
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Ching-Tsung Hung, Jia-Ruey Chang, Hsin-Lung Liu, and Gwo-Hshiung Tzeng

Optimal Resource Allocation Model For Pavement Maintenance Established By De Novo Programming Method

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Full text: content.pdf (498,617 bytes) (available to registered users only)

Series: w78:2006 (browse)
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Georgios Hadjidemetriou and Symeon E. Christodoulou

Pavement Anomalies Detection and Classification Using Entropic Texture Segmentation and Support Vector Machines

Abstract: Presented herein is a vision-based method for the detection of anomalies on roadway pavements, utilizing low-cost video acquisition and image processing of road surface frames collected by a smartphone (or camera) located on a vehicle moving in a real-life urban network, along with entropy-based texture segmentation filters, and support vector machine (SVM) classification. The proposed system, which has been developed in MATLAB, pre-processes video streams for the identification of video frames of changes in image-entropy values, isolates these frames and performs texture segmentation to identify pixel areas of significant changes in entropy values, and then classifies and quantifies these areas using SVMs. The developed SVM is trained and tested by feature vectors generated from the histogram and two texture descriptors of non-overlapped square blocks, which constitute images that includes ÔÔpatchÕÕ and ÔÔno-patchÕÕ areas. The outcome is composed of block-based and image-based classification, as well as measurement of the patch area.

Keywords: Pavement Condition Evaluation, Road Anomaly Detection, Vision-Based, Entropy, Texture Segmentation

DOI: https://doi.org/10.24928/JC3-2017/0191

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Jia-Ruey Chang, Ching-Tsung Hung, Gwo-Hshiung Tzeng, and Wen-Hsiung Hsiao

Pavement Maintenance And Rehabilitation Decisions Derived By Rough Set Theory

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Full text: content.pdf (578,376 bytes) (available to registered users only)

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Jiwen Zhang, Tim Taylor, Roy Sturgill, Gabe Dadi and Nikiforos Stamatiadis

Predictive Risk Modeling of Differential Bridge Settlement

Abstract: Differential settlement between the roadway pavement resting on embankment fill and the bridge abutment built on more rigid foundation often creates a bump when driving from roadway to bridge, and vice versa. This paper studies the problem at a macroscopic level by determining a method to predict the levels of approach settlement to assist designers in developing remediation plans during project development to minimize the lifecycle costs of bridge bump repairs. A macro method considering a combination of maintenance times, maintenance measures, and observed settlement was used to classify the differential settlement scale as minimal, moderate, and severe. A set of project characteristics including approach, abutment type, embankment, foundation, and traffic volume that may influence the formation of differential settlement were identified and used as parameters to develop a model to predict the settlement severity for a given approach. Logistic regression analyses were implemented to identify the relationships between the levels of differential settlement and the input variables for a sample of 600 randomly selected bridges in Kentucky. Geographic region, approach age, average daily traffic, and the use of approach slabs are identified as the four most predominant factors that can significantly affect the formation of differential settlement. Based on the performance of bridge approaches in Kentucky, how those parameters interacted in the prediction model is illustrated in the logistic regressions.

Keywords: Differential Settlement, Logistic Regression, Prediction Model

DOI: https://doi.org/10.24928/JC3-2017/0060

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Mohsen J P, Sabnis G, James M B

Computer based AASHTO pavement design methodology

Abstract: A computer expert system has been developed for design of flexible pavements(FLEXPAVE). The design procedure follows the latest AASHTO Guide for Design ofPavement Structures. The system evaluates required thickness for initial pavement designand the subsequent overlays. The system is an educational and training tool as well as adesign tool. The user is assisted in selecting design inputs by a rule-base expert system. Therules used to determine the recommended values are shown on the screen along with a briefexplanation during the design process. Help screens and various worksheets help the user inselecting design inputs. A sensitivity analysis option allows the user to investigate therequired precision for design inputs. The rules in the expert system are derived from the1993 AASHTO manual and related literature.

Keywords: Pavement Design, Flexible Pavements, Pavement Sensitivity Analysis

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Series: ecce:2001 (browse)
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Omar Smadi, Zachary Hans, and Neal Hawkins

GIS Use In Pavement Marking And Sign Management - An Integrated Approach

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Radovic N, Uzelac D, Lukic A

Analyses of pavement surface distresses with “road vision” software

Abstract: Determining real pavement surface condition has important role in Pavement Management Systems. There are many different techniques and possibilities for interpretation of pavement surface distresses. In this paper are described using of “Road vision” software in analysing of pavement surface distresses and its practical implementation. Pavement surface distress data are collected with special vehicle with videocamera. “Road Vision” software presents integral part of integrated road data base intended for graphical presentation of pavement surface distresses and calculating of pavement condition index and quantity of maintenance works.

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Series: ecce:1997 (browse)
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Uzelac D, Radovic N

Integrated information system as the basis for road management system

Abstract: When the Road Directorate of Serbia decided in 1991 to start with pavement and bridge management system development, it had no experience with contemporary informatics. But, starting from zero had a certain advantage -there were no problems with the heritage from former systems: old habits, old hardware and software, old methods, old organisation. From the very beginning, a new system was planned as Integrated Road Information System, and has been developed using the latest ideas and technology novelties.

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