Application of Mining Co-Location Patterns in Pavement Management and Rehabilitation

2021 ◽  
pp. 117-148
Author(s):  
Guoqing Zhou
Keyword(s):  
Pavement Management ◽  
Location Patterns

Economic Value of Pavement for the Elderly: Case Study of Bangkok, Thailand

2018 ◽  
Vol 9 (11) ◽  
pp. 927-937
Author(s):  
Somskaow Bejranonda ◽  
◽  
Aekkapat Laksanacom ◽  
Waranan Tantiwat ◽  
◽  
...  
Keyword(s):  
Contingent Valuation Method ◽  
Economic Value ◽  
The Elderly ◽  
Pavement Management ◽  
Sustainable Urban Development ◽  
Public Facility ◽  
Average Value ◽  
Valuation Method ◽  
The People ◽  
The City

Based on the concept of a livable and global age-friendly city, pavements are a public facility that the city should provide to the people. Appropriate pavements will be beneficial for the people, particularly for good quality of life for the elderly to move around in the city. This study explored the behaviour of the elderly in the use of pavements and the problems confronted. The study also evaluated the value of the pavement walking area as it reflected the benefits of pavements to the elderly by applying the Contingent Valuation Method (CVM). During March-May 2017, data were collected using interviews with 601 elderly living in Bangkok. The study indicated that the main problem for senior citizens regarding their use of pavements was from being disturbed by motorbikes riding on the pavements. The average value of pavement for the elderly was about THB 160 (USD 5.30) per person per year. Thus, the benefits of pavements to the elderly in Bangkok was approximately THB 158 million (USD 5.2 million) per year. Thus, policy makers should make proper budget allocations for elderly-friendly pavement management and seriously address the problems confronting the elderly in using pavements, to maximize the usefulness of pavements not only for the elderly but also for the public and to support a sustainable urban development.

Inter-Metropolitan Location Patterns of Craft Breweries in the United States

2016 ◽  
Vol 46 (1) ◽  
pp. 115-129 ◽  
Author(s):  
Ralph B. McLAUGHLIN ◽  
Neil REID ◽  
Michael S. MOORE
Keyword(s):  
United States ◽  
The United States ◽  
Location Patterns

Local Calibration of Pavement Mechanistic-Empirical Faulting Reliability using Pavement Management Data

2021 ◽  
pp. 036119812110013
Author(s):  
Lucio Salles de Salles ◽  
Lev Khazanovich
Keyword(s):  
Model Calibration ◽  
Prediction Models ◽  
Plain Concrete ◽  
Performance Model ◽  
Pavement Management ◽  
Pavement Design ◽  
Reliability Model ◽  
Transverse Joint ◽  
Design Characteristics ◽  
And Performance

The Pavement ME transverse joint faulting model incorporates mechanistic theories that predict development of joint faulting in jointed plain concrete pavements (JPCP). The model is calibrated using the Long-Term Pavement Performance database. However, the Mechanistic-Empirical Pavement Design Guide (MEPDG) encourages transportation agencies, such as state departments of transportation, to perform local calibrations of the faulting model included in Pavement ME. Model calibration is a complicated and effort-intensive process that requires high-quality pavement design and performance data. Pavement management data—which is collected regularly and in large amounts—may present higher variability than is desired for faulting performance model calibration. The MEPDG performance prediction models predict pavement distresses with 50% reliability. JPCP are usually designed for high levels of faulting reliability to reduce likelihood of excessive faulting. For design, improving the faulting reliability model is as important as improving the faulting prediction model. This paper proposes a calibration of the Pavement ME reliability model using pavement management system (PMS) data. It illustrates the proposed approach using PMS data from Pennsylvania Department of Transportation. Results show an increase in accuracy for faulting predictions using the new reliability model with various design characteristics. Moreover, the new reliability model allows design of JPCP considering higher levels of traffic because of the less conservative predictions.

scholarly journals Exploiting Data Analytics and Deep Learning Systems to Support Pavement Maintenance Decisions

2021 ◽  
Vol 11 (6) ◽  
pp. 2458
Author(s):  
Ronald Roberts ◽  
Laura Inzerillo ◽  
Gaetano Di Mino
Keyword(s):  
Deep Learning ◽  
Management Practices ◽  
Prediction Models ◽  
Road Networks ◽  
Pavement Management ◽  
Efficient Operation ◽  
Pavement Maintenance ◽  
Goods And Services ◽  
Maintenance Decisions ◽  
Computational Systems

Road networks are critical infrastructures within any region and it is imperative to maintain their conditions for safe and effective movement of goods and services. Road Management, therefore, plays a key role to ensure consistent efficient operation. However, significant resources are required to perform necessary maintenance activities to achieve and maintain high levels of service. Pavement maintenance can typically be very expensive and decisions are needed concerning planning and prioritizing interventions. Data are key towards enabling adequate maintenance planning but in many instances, there is limited available information especially in small or under-resourced urban road authorities. This study develops a roadmap to help these authorities by using flexible data analysis and deep learning computational systems to highlight important factors within road networks, which are used to construct models that can help predict future intervention timelines. A case study in Palermo, Italy was successfully developed to demonstrate how the techniques could be applied to perform appropriate feature selection and prediction models based on limited data sources. The workflow provides a pathway towards more effective pavement maintenance management practices using techniques that can be readily adapted based on different environments. This takes another step towards automating these practices within the pavement management system.

scholarly journals A Framework for Modelling Economic Regional Location Processes Under Uncertainty

2021 ◽  
Author(s):  
Roy Cerqueti ◽  
Eleonora Cutrini
Keyword(s):  
Theoretical Model ◽  
Theoretical Analysis ◽  
Site Selection ◽  
Decision Problem ◽  
Stochastic Theory ◽  
Spatial Location ◽  
Probabilistic Framework ◽  
Location Patterns ◽  
Regional Location ◽  
Quantitative Tool

AbstractThis paper deals with the theoretical analysis of the spatial concentration and localization of firms and employees over a set of regions. In particular, it provides a simple site-selection theoretical model to describe the probabilistic framework of the location patterns. The adopted quantitative tool is the stochastic theory of urns. The model moves from the empirical evidence of the deviation of the spatial location of companies from the uniform distribution and of employees from the distribution of firms. Factors leading to such deviations are taken into consideration. Specifically, we formalize a decision problem grounded on the economic attributes of the regions and also on the distribution of the existing firms and employees in the territory. To our purpose, the site-selection model is presented as a stepwise process.

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