جستجوی مقالات مرتبط با کلیدواژه « pavement management system » در نشریات گروه « عمران »

Pavement inspection is an important part of pavement management systems because this part provides input and raw material information to the system. If the pavement situation has not been assessed or incorrectly assessed, it will not be possible to carry out optimum maintenance and repair operations. It can also cause higher maintenance costs and the risk of accidents. Pavement distress information is crucial data that should be collected and evaluated in the pavement inspection process. Accordingly, wide research has been conducted to develop more efficient systems for the evaluation of pavement distresses using new technologies. Bleeding is one of the asphalt pavement distresses, which directly affects the skid resistance and vehicle maneuverability. Based on the literature, pavement bleeding received the attention from the research community less than other pavement distress such as cracks, rutting, raveling, and potholes. This research attempts to develop an efficient system for the automatic evaluation of asphalt pavement bleeding. For this aim, the transfer learning method was applied to train a pre-trained convolutional neural network for bleeding detection. Also, various image processing techniques (wavelet transform analysis as the main technique) were used to segment bleeding regions in pavement images. Results indicated that the proposed system has good performance in bleeding detection and segmentation with 98% and 87%, respectively. Accordingly, this system can be applied as an efficient system for pavement bleeding evaluation.

Choosing an appropriate strategy to maintain pavements has become a significant concern. Recently, pavement agencies tackle large-scale networks, which makes the problem complicated. To prevail in this complexity, utilizing metaheuristic algorithms can be an ideal approach. By increasing the dimension of the problem, the competency of metaheuristic algorithms is by far enhanced. To this end, the water cycle algorithm is applied to solve the problem. In this investigation, two models, including single objective optimization and multi-objective optimization, are taken into consideration. In the single-objective model, the minimization of the network International Roughness Index (IRI) is considered as the objective function. In multi-objective optimization modeling, minimization of the network International Roughness Index and embodied CO2 emission are taken into account simultaneously. Furthermore, a new constraint is considered in the model, which leads to restricting the budget fluctuation in different years of the analysis period. A network, including 79 segments, is the case study of this investigation. The results reveal that the water cycle algorithm is highly qualified to solve the pavement maintenance and rehabilitation problem. According to the results, multi-objective optimization reduces the CO2 emission by 47.2% compared with single-objective modeling. Furthermore, the variation of minimum and maximum costs is less than 20% in the planning horizon.

The road pavement surface has an important role in relation to address the primary demands of vehicle movement, such as safety and eco-compatibility. In order to reduce road maintenance and rehabilitation costs and optimize the service condition of road networks, pavement management systems (PMS) need detailed and reliable data of the highway network characteristics. Laser imaging devices can be employed to collect information on an in-service pavement surface layer through a single measurement with data homogeneity and representativeness in an innovative method. With the recent developments in 3D laser sensors and information technology, high-speed 3D line laser imaging systems with high-resolution has been introduced for measuring key features of pavement surface condition. This research presents some of the key developments in recent years for laser-based distress measurement systems and explains the technology used in laser-based crack measurement system. Laser-based systems key features are introduced and compared with former data collection methods. These new systems are evaluated and described in terms of their applicability and potential for future developments.

Road maintenance is considered as one of the major and important factors in the pavement management system (PMS). Regarding the type of data collection in this study, the observation method based on index PCI (Pavement Condition Index) according to ASTM D6433 standard was used. Research aims to assess the priority of road maintenance using the Pavement Condition Index (PCI). Locations for this research were the roads at the EMU campus to length 10 km in Northern Cyprus and 16 road segments were taken from each district. There were 9 distress types that had been recorded. We intend to add to this project a new dimension by analyzing the EMU campus road. The results of the research as obtained from the method of PCI and prioritization can be identified as follows: five road segments are in good condition, four are satisfactory, six are in fair condition, one is in a failed condition, and one road segment is in serious condition. In total, 15 of 16 road segments are in stable condition. The result generally indicates that the road was 80.63% in satisfactory condition. In general, it can be concluded that road pavements are constantly exposed to various types of stresses such as heavy traffic load, temperature, humidity and bed soil displacement, which over time lead to damage such as cracks in the Alligator cracking, Patching and Utility cut, Block cracking, Long and Trans cracking, Rutting, and Asphalt Bleeding are in the pavement. Patching and Utility cut, Alligator cracking and Long and Trans cracking were assessed as the most severe.

The implementation of an efficient pavement management system is dependent on the acquiring desired information from the pavement condition. The automatic data collection were welcomed by mechanized systems due to adequate precision and speed. But the various systems were developed that had high construction and operation costs. Therefore, the development of cost-effective devices that is independent from the vehicle vibrations and equipped with instrumentation is necessary. In this study, the Health Monitoring System (HMS) is developed as a system of longitudinal profile measurement and road roughness evaluation based on response-type vehicle with applying the mode combined of accelerometers, distance meter, GSM. Upon harvesting the vibration response of the HMS and the vehicle, data preparation and signal filtration are performed through the Digital Signal Processing (DSP) techniques. So the dynamic equations governing the behavior of the HMS are derived based on one degree of freedom. The dynamic parameters of system are extracted based on optimization approach using GA and PSO algorithms. Afterwards, the extracted longitudinal profile based on the vibration responses is become to the longitudinal profile with the specific speed by the algorithm of the relationship between speed and frequency of harvested data. Then, the International Roughness Index (IRI) is calculated from the longitudinal profile of the studied pathway by ProVal software. Finally, the accuracy of the HMS results is validated by manual method with measuring the AEP and the NRMSD between the outputs of the system and the Road Surface Profiler (RSP) with values of 19.72% and 9.68% respectively.

Evaluation of pavement structure is an important part of the pavement management system at the network and project levels, which is usually performed by using falling weight deflectometer (FWD) device. In using the FWD device, strength of the pavement layers is determined by back-calculations method. Using this method is not financially and temporally affordable for management at network level because of complexity and need for accurate initial information, and therefore it is usually used at the project level. Dynamic cone penetrometer (DCP) is another equipment, which is fast and cheap, and is used in evaluation of pavement structure at network level. In this research, 50 km of arterial road of Kermanshah province was tested by using the FWD and DCP devices. Results showed acceptable correlation between penetration index, as DCP output, and the obtained data of FWD device for pavement layers. The PI variation range for different pavement structure situations at network level was presented by analyzing the FWD and DCP outputs. Output results of network analysis using both methods showed acceptable PI criterion validity as simple and cheap criterion for pavement structure evaluation in pavement management at network level.

Road networks and in particular their Pavements are the fundamental components of a transportation infrastructure. Pavements need continuous maintenance. Allocation of sufficient funds for maintenance of pavements is an important process of pavement management systems. Importance of a modern and efficient pavement management system is evident, specially, for countries, where most transfers are done through road transportation networks.
Capability of estimating future pavement performance based on existing condition and presenting preventive operations are most important criterion of an efficient pavement management system. There is always an optimal time for M&R operations. Distresses progression rate and M&R costs will be increased, in case of no action at this optimal time. Pavement performance prediction models are the best tool for determination of this time.
In this paper, pavement performance prediction models will be introduced and compared with each other. Their exact comparison is discussed, by investigation models prediction accuracy, efficiency, calibration criteria and database and features needed.

The rapid development of roadways and the limited budget require establishing an effective pavement management system. The paper aimed to utilize the Life Cycle Cost Analysis (LCCA) and implement HDM-4 Software to determine the most appropriate maintenance and rehabilitation technique in part of a network in South Khorsan Region in Iran. In doing so, initial homogenous segments were assigned based on Pavement Condition Index (PCI), International Roughness Index (IRI) and maximum deflection under the center of the load plate in Falling Weight Deflectmeter (FWD) device. The final homogenous segments were determined based on the selected maintenance and rehabilitation work items. The effects of each rehabilitation alternative on roughness and the attributed costs were analyzed at the network level. Finally, the effects of change in the budget heads and the discount rates were investigated performing sensitivity analysis. Results indicated that all the maintenance and rehabilitation alternatives, except for the base method, decreased the IRI values. Furthermore, the higher amount of road user costs, compared with road agency costs, indicated the importance of considering the user cost in LCCA. With increasing the discount rates, the proposed work program would change. Taking into consideration various maintenance alternatives, the importance of inserting the correct discount rate in LCCA was confirmed. Regarding allocated budget for the analysis period, it was revealed that the allocated 100 billion Rials in the first year of the analysis period, followed by 10 percent annual increase, was enough for implementing the proposed program. With further analysis, it was found that the 700 billion Rials (54 percent of the total allocated budget) was considered a minimum budget required for application of the proposed work program, saving large amounts of national financial sources.

Pavement maintenance and rehabilitation is of great importance in increasing the lifetime of the roads which requires a huge finance. Through a pavement management system (PMS), these actions can be proioritized with optimized financial costs. In order to establish such situation, a database is required to investigate gathered information in different periods. As the establishment of PMS in Iran is in the beginning stages and there is no access to a long-term database, planning and proioritization of road maintenance can be effective and operational, considering the current condition of pavements’ defects. In this paper, the surface condition of about 800 km of arterial road network in Kermanshah province is evaluated based on International Roughness Index (IRI) and Pavement Surface Evaluation and Rating (PASER). In fact, this paper proposes the maintenance options required for each section based on the pavement condition through the aforesaid indices and their combination. Reviewing the data and their results show that the high intensity of surface roughness (high IRI) does not necessarily mean the existance of surface defects with high intensity (low PASER), and vice versa. Therefore, the combination of these two indices can have more appropriate performance than each of them to show the pavement condition. A regression model is introduced to create a relationship between IRI and PASER which expresses the capability of proper estimation of each index according to the other one.

The pavement management system (PMS) is a synchronous and regular procedure to conduct all of the works related to the pavement maintenance and repair. Through a proper PMS، sustainable and correct decisions in maintenance، repair and rehabilitation of pavements are possible. Pavement management is proceeded at two levels: Project level and Network level. Pavement management at project level copes with detailed design decisions for each project separately and at network level it copes with building a priority and schedule program for construction، maintenance and rehabilitation of a new pavement along with budget limitations. PMS software input includes 3 types of data: road inventory، pavement situation and maintenance and repair strategies and their costs. The aim of gathering pavement deterioration data and their reasons is identification of the situation for each road section based on the scale of pavement deterioration. The next step is classification of pavements based on the scale of pavement deterioration. The PMS software identifies the potential repair options for each section and estimates the repair costs and then prioritizes and determines the most economic methods of maintenance and repair. Finally، it represents the result of data analysis as a detailed report including prioritized maintenance options for each section along with their costs.