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The construction industry relies on construction cost indexes to prepare cost estimate benchmarks and develop cost estimates. Subsequently, government agencies, non-profit organizations, and private companies routinely publish construction cost indexes for cities. Currently, all construction cost indexes are released in a tabular format for 649 cities across the conterminous United States, which is not effective in illustrating construction cost variations at the national level. This study explored the utility of various established interpolation methods and mapping techniques to visualize construction cost indexes at the national level. Geovisualization techniques such as thematic mapping provide a visual representation of construction cost data in addition to traditional tabular formats. This study explored the utility of Thiessen polygon and inverse distance weighted (IDW) methods to create thematic maps which can be used to interactively visualize construction costs at the national level. A qualitative comparison revealed that the IDW method can produce the most intuitive, interactive, and continuous surface maps to identify dynamic and previously unrecognized patterns. These continuous surface maps allow construction practitioners and academics, real estate developers, and the public to locate the geographic proximity of high or low construction costs while cost change maps allow investors and businesses to identify patterns in changing construction costs over a certain period. This work contributes to the body of knowledge by introducing interpolated maps for visualizing any construction cost-related indexes at a large scale such as the national level.

Highway project delivery is a disruption-prone process in which resilience is essential to project success, because different project stages experience disruptions and struggle to reach des...

Ensuring the resiliency of a nation’s transportation infrastructure network requires a skilled and dependable workforce; this relies heavily on a transportation agency’s ability to recruit ...

Commercial and residential buildings consume about 27% of total energy used in the US, out of which nearly half is consumed by commercial building sector and it expected to grow in the next 30-year period. Literature suggests that occupancy data may improve the energy consumption of the buildings, especially in HVAC operation. In the past few years studies came up with various frameworks based on existing infrastructure to estimate occupancy, out of which commodity WiFi gained popularity in detecting, estimating, and tracking occupants within buildings. However, there are concerns with those frameworks such as added infrastructure and computational efforts, upgrades to existing infrastructure, and privacy of occupants. This paper presents a simplistic framework based on commodity WiFi to estimate real time occupancy data without any added infrastructure or upgrades, while protecting the occupant privacy and can produce significant energy reduction in HVAC operation. The framework is tested on a large lecture hall in an institutional building that has multiple classes scheduled. The initial tests showed that the WiFi based occupancy had a 0.96 correlation with the established ground truth. Additionally, the WiFi based occupancy schedule resulted in at least 50% savings in HVAC energy consumption over static schedule.

Project delivery is often subject to uncertainties and disruptions throughout the entire process. The ability of project delivery to resist and recover from disruptions is a measure of the ...

All transportation management agencies face the yearly challenge of inspecting the condition of myriad miles of road surface. With routinely acquired and publicly available geospatial data and geospatial modelling techniques, there is potential to substantially reduce the number of survey sites required to characterize overall pavement surface distress condition. Using roadway pavement assets in the State of New Mexico as an example, this study investigated if overall pavement surface conditions could be estimated based on geospatial modelling. A total of 17 explanatory variables, which were extracted from three types of geospatial data, including traffic volumes, environmental conditions and topography, were used to estimate overall pavement surface distress conditions. Results show that overall pavement surface conditions can be effectively (R2 > 0.9) estimated based on the extent of geospatial data and inferential modelling techniques with fewer survey sites, substantially reducing the cost and...

Building energy retrofits aim to reduce the energy consumption of existing facilities. The most significant impact of any energy retrofit project is during the operation phase of a building...

Sinkholes cause subsidence and collapse problems for many transportation infrastructure assets. Subsequently, transportation infrastructure management agencies dedicate a considerable amount of time and money to detect and map sinkholes as part of their asset management programs. Traditionally, sinkholes are detected through area reconnaissance, which includes visual inspection of a site to locate existing sinkholes or device inspection of a site to locate potential sinkholes or previously filled sinkholes. Another method for sinkhole detection is through a review of maps such as geological maps. These methods are expensive, time-consuming, and labor-intensive. Recent advances in remote sensing, especially airborne light detection and ranging (LiDAR), allows for the examination of the change in the Earth's surface elevation accurately and rapidly. The focus of this study is to develop a conceptual framework for sinkhole detection and mapping with airborne LiDAR. This conceptual framework lays the foundation for the future application of airborne LiDAR for sinkhole detection and mapping.

The objective of this study was to evaluate the construction, material characterization, initial structural assessment, and cost of a novel jointless Engineered Cementitious Composite Ultra-Thin Whitetopping (ECC-UTW) overlay. After construction, early-age cracks (from less than 0.25 mm to up to 2.54 mm width) were observed in the 101.6-mm (4 in.) jointless ECC-UTW section; yet, the majority of the cracks coincided with areas where fiber clumps were observed during construction and places of heavy instrumentation. On the other hand, no cracks were observed in the 63.5-mm (2.5 in.) jointless ECC-UTW at early ages; yet, when winter arrived, micro-cracks (

In recent years, unmanned airborne systems (UAS) have emerged as an important platform for collecting hyper-spatial resolution airborne remote sensing data. Using this hyper-spatial resolution imagery as input, modern aerial triangulation (AT) techniques, also known as structure-from-motion or SfM, can rapidly produce orthophotos and digital surface models (DSMs) at fine scales. Such data hold great promise for a number of applications, including routine and post-disaster assessment of transportation infrastructure, which provided the impetus for this research. Using hyper-spatial resolution (0.002 m) natural colour digital aerial photography acquired from a low-altitude UAS as input images, this research systematically investigated the horizontal and vertical accuracy of the AT generated orthophotos and DSMs, respectively. Hyper-spatial resolution aerial data were collected for a total of 28 study sites and, for each study site, coordinate information of 16 ground control points (GCPs) was collec...

State transportation agencies regularly collect data on pavement surface distresses. These data are used to assess overall pavement conditions and to make maintenance and repair decisions. Routinely-acquired and publically-available high spatial resolution (hsr) multispectral digital aerial photography provides a potential method for collecting distress information that can supplement or replace currently-used technologies. Principal component analysis and linear least squares regression models were used to evaluate the potential of using HSR multispectral digital aerial photographs to estimate pavement surface overall distress conditions. Various models were developed using HSR multispectral digital aerial photographs of different spatial resolution (6-inch, 12-inch, and 24-inch) and reference pavement surface distress data collected manually at multiple sample sites using standard protocols. The results show that the spectral response of HSR multispectral digital aerial photographs correlate strongly with reference distress rates at all tested spatial resolutions, but the 6-inch aerial photos exhibit the strongest correlation (R 2 > 0.95), even when using only half of the sample sites (R 2 > 0.92). These results indicate that straightforward analysis of HSR multispectral digital aerial photographs, routinely acquired by most municipalities and states, can permit assessment of pavement surface distress conditions as well as current manual evaluation protocols.

Increasing the use of social sustainability in the decision-making process for building and infrastructure projects requires that it be defined such that it can be evaluated objectively. One potential indicator of social sustainability in infrastructure projects is public opinion, which can provide a means to evaluate the level of social sustainability on a project based on personal values. Public opinion includes both support and opposition for a project. In this study, the causes or triggers for public opposition to a construction project are identified and then compared to principles of social sustainability to determine if they are related. Eight case study projects were used to identify common triggers of public opposition. The results suggest that common triggers of public opposition are related to land acquisition, escalating construction costs and the presence of endangered species on the project site. Eight of the twelve principles of social sustainability that were identified were determined to be related to public opposition. The results of this study suggest that public opposition could be used as a measure for some elements of social sustainability but that further research into other measures for social sustainability is necessary.

A fundamental process in construction cost estimation is the appropriate adjustment of costs to reflect project location. Unfortunately, location adjustment factors are not available for all locations. To overcome this lack of data, cost estimators in the United States often use adjustment factors from adjacent locations, referred to as the nearest neighbor (NN) method. However, these adjacent locations may not have similar economic conditions, which limit the accuracy of the NN method. This research proposes a new method of using nighttime light satellite imagery (NLSI) to estimate location adjustment factors where they do not exist. The NLSI method for estimating location adjustment factors was evaluated against an established cost index database, and results show that NLSI can be used to effectively estimate location adjustment factors. When compared with NN and other alternative proximity-based location adjustment methods, the proposed NLSI method leads to a 25–40% reduction of the median abso...

Roadway networks, as part of transportation infrastructure, play an indispensable role in regional economies and community development. The high-quality pavement serviceability of these networks is essential to ensure safe, cost-effective daily traffic operations. In-depth analyses of network-wide pavement surface condition data are necessary inputs for optimal pavement design and maintenance, traffic safety enhancement, and sustainable traffic infrastructure system development. This study aims to investigate various pavement distress condition performance measurements and their correlations to better understand temporal–spatial characteristics of roadway distress based on pavement distress condition data collected in New Mexico from 2006 to 2009. Eight major corridors across various urban and rural areas were selected for analyzing pavement surface-distress conditions and discovering their intrinsic characteristics and patterns across both temporal and spatial domains. The results show that there are not strong correlations among different distress measurements, implying the rationality of the current pavement performance measurement protocol used by the state transportation agencies. Regression models were established and GIS-based spatial analyses were performed to extract temporal and spatial patterns of Distress Rate (DR) data. The model results illustrate significant correlations of the DR data on the same route between two consecutive years, which can be partially characterized by a Markov process. GIS-based spatial investigations also show unique features of pavement condition deterioration attributed to diverse geometric characteristics and traffic conditions, such as vehicle compositions and volumes and urban and rural areas. The research findings are helpful to understand the characteristics of pavement distress conditions more clearly and to optimize traffic infrastructure design and maintenance.

The monitoring of construction workforce physical strain can be a valuable management strategy in improving workforce productivity, safety, health, and quality of work. Nevertheless, clear relationships between workforce performance and physical strain have yet to be established. An exploratory investigation of the relationship between task level productivity and physical strain was conducted. Nine participants individually performed a four-hour simulated construction task while a wearable physiological status monitor continuously assessed their physiological condition. Heart rate, relative heart rate, and breathing rate were utilized as predictors of physical strain, and task level–single factor productivity was used as an index of productivity. Numerous regression models were generated using the collected data. This investigation initially unsuccessfully attempted to establish a relationship between physiological condition and productivity at the individual worker level. However, an analysis of the regr...

Previous studies on building, industrial, and transportation projects found that projects delivered using design-build tend to perform better than projects delivered with the traditional de...

Sustainability is often described in terms of the triple bottom line, which refers to its environmental, economic, and social dimensions. However, the economic and environmental impacts of decisions have been easier to determine than have been the social impacts. One area of social sustainability that is particularly applicable to construction projects is that of construction workforce safety and well-being. This is a critical part of sustainability, and a socially sustainable construction industry needs to consider the safety and well-being of construction workers. However, construction activities are generally physically demanding and performed in harsh environments. Monitoring workers’ physical strain may be an important step toward enhancing the social sustainability of construction. Recently introduced physiological status monitors (PSMs) have overcome the past limitations, allowing physical strain to be monitored without hindering workers’ activities. Three commercially available PSMs have b...

Owners of water/wastewater facilities can choose from several project delivery methods, including the traditional design-bid-build method or an alternative design-build method. When choosing a project delivery method, the owner should consider both the project goals as well as the performance of different project delivery methods. Detailed data on project delivery performance allow owners to match project goals, such as time savings, with project delivery methods. Detailed data on project delivery performance do not currently exist for the water/wastewater sector. Through a survey of water/wastewater facility owners, data were collected on 31 design-build projects and sixty-nine design-bid-build projects. A statistical analysis of the data determined that schedule growth for design-build projects was half that of design-bid-build projects; more design-build projects finished at or below budget; and both project delivery methods produced projects of comparable quality. Although this is the first st...

Roadway pavement surface distress information is critical for effective pavement asset management, and subsequently, transportation management agencies at all levels (i.e., federal, state, and local) dedicate a large amount of time and money to routinely evaluate pavement surface distress conditions as the core of their asset management programs. However, currently adopted ground-based evaluation methods for pavement surface conditions have many disadvantages, like being time-consuming and expensive. Aircraft-based evaluation methods, although getting more attention, have not been used for any operational evaluation programs yet because the acquired images lack the spatial resolution to resolve finer scale pavement surface distresses. Hyper-spatial resolution natural color aerial photography (HSR-AP) provides a potential method for collecting pavement surface distress information that can supplement or substitute for currently adopted evaluation methods. Using roadway pavement sections located in the State of New Mexico as an example, this research explored the utility of aerial triangulation (AT) technique and HSR-AP acquired from a low-altitude and low-cost small-unmanned aircraft system (S-UAS), in this case a tethered helium weather balloon, to permit characterization of detailed pavement surface distress conditions. The Wilcoxon Signed Rank test, Mann-Whitney U test, and visual comparison were used to compare detailed pavement surface distress rates measured from HSR-AP derived products (orthophotos and digital surface models generated from AT) with reference distress rates manually collected on the ground using standard protocols. The results reveal that S-UAS based hyper-spatial resolution imaging and AT techniques can provide detailed and reliable primary observations suitable for characterizing detailed pavement surface distress conditions comparable to the ground-based manual measurement, which lays the foundation for the future application of HSR-AP for automated detection and assessment of detailed pavement surface distress conditions.