Assessment of Risk and Uncertainty Factors Inherent in Nigerian Highway Project Using Analytical Hierarchical Process

The study presents a framework through which risk and uncertainties in Nigeria highway projects can be appraised using the analytical hierarchical process model. Pairwise comparison matrix was performed on eleven (11) risk and uncertainty factors that affect highway project performance through a questionnaire survey conducted among two hundred and four (204) respondents, which involved various stakeholders in the highway construction industry using Saaty’s AHP rating scale. The relative weights (significance/impact level) of each of the highway risk factors were estimated during the AHP model development. The results in descending order of risk factors priorities are Standard & Regulations (S&R), Construction (C), Project Staff (PS), Project Sponsor (PSp), Design (D), Project Finance (PF), Economic (E), Equipment (EQ), Environmental & Geotechnical (En&G), Site Location (SL) and Subcontractor (S) with impact levels of 16.6%, 14.2%, 13.9%, 13%, 12.7%, 12.2%, 10.8%, 9.8%, 6.2%, 4.2%, and 3.8% respectively. The model was validated using the statistical consistency test, with the model showing a consistency ratio equal to 0.1. The model was then applied to five (5) highway construction projects which had been constructed to predict the ones with the most and least risks. The result was in tandem with that which was given by the project managers from experiences on the project. This study showed that the Analytical Hierarchical Process (AHP) decision support model can effectively be used for risk assessment and prioritization of highway construction projects for efficient resource utilization in Nigeria.

Mapping Unmanned Aerial System Data onto Building Information Modeling Parameters for Highway Construction Progress Monitoring

The transportation infrastructure management sector lacks automated procedures that can help it find and resolve the performance deviations. The objective of this research is to illustrate the mapping of Unmanned Aerial System (UAS) collected photogrammetric data to building information modeling (BIM) parameters, and their application for automated construction progress monitoring and the generation of as-built models. The goal is to support project managers to estimate project progress during highway construction. As a part of ongoing work, this paper takes into account 4D (3D + time) data that is acquired from 3D surface digital elevation models, point clouds, LiDAR data, and orthographic photos. It maps these 4D data onto BIM parameters to create as-built models of the project at different intervals. A comparison between as-planned and as-built models using the earned value management method is employed to develop metrics that can be used for indicating cost and schedule deviations during construction. The mapping methodology introduced in this paper is illustrated using an ongoing highway construction project case study. The main contribution of this paper is the organization, processing, and integration of UAS data with BIM data structures and project management workflows. The research outcomes will assist project managers in an easy and quick identification of potential performance problems and support the project management decision-making process.

Fuel Consumption of Wheeled Vehicle and Transportation Costs during Highway Construction/Reconstruction

A method is proposed for determining the fuel consumption of a wheeled vehicle depending on its speed, road surface flatness and road slope in the longitudinal direction. The purpose of the research is to derive mathematical relationships for calculating the fuel consumption of vehicles, which is one of the transport cost factors during the construction/reconstruction or overhaul of a highway. The proposed polynomial dependencies for calculating fuel in addition to vehicle speed, road surface flatness and its longitudinal slope take into account the mass-dimensional parameters of vehicles involved in road traffic. New mathematical relationships between the speed of wheeled vehicles, road surface flatness and longitudinal road slope allow to simulate the change in the value of fuel consumption of a wheeled vehicle when the speed of traffic flow or the slope of the road surface changes in the forward or reverse direction of the vehicle. In a graphic way, the influence of the pavement slope on the value of fuel consumption, both loaded and unloaded wheeled vehicle is presented. When determining transport costs associated with the highway construction, reconstruction or overhaul it is proposed to use empirical mathematical relationships, which make it possible to obtain fuel consumption with an accuracy of 5 % and save up to 15 % of budget (private) investments. The analysis of scientific publications of the existing approach determine the transport costs associated with highway construction, reconstruction or overhaul. The presented method for determining the fuel consumption of wheeled vehicles with small and large loading capacity increases the accuracy of determining transportation costs and reduces the level of financial costs for highway construction, reconstruction or overhaul.

Assessing The Impact Of Sediments On Best Management Practices (Bmps) For Highway Runoff Control At Wolaita Sodo Town

The goals of this work are to estimate the amount of erosion and to evaluate the impacts of sediments on Best Management Practices (BMPs) for highway runoff and also used to estimate the annual erosion and sediment yield from the construction sites considering various erosion control management methods that might be used in the sites. Once the sediment yield is found, a model was designed to estimate the sediment capture efficiency of different Best Management Practices (BMPs) and to evaluate the service year of each BMP before it is filled with sediment. The two major objectives of this project are: to predict sediment yield from highway construction sites under different erosion management conditions and secondly to estimate the service year of sediment control BMPs treating runoff from highway construction sites. The BMPs selected for evaluation were: detention ponds, infiltration trenches, grass lined swales, grass lined swales with rock check dams, and bio retention areas. Each respective BMP requires different measures of efficiency to accurately assess its effectiveness and service year.

The Effect of “Federal -Aid Swap” Programs and Davis-Bacon Prevailing Wages on Highway Construction Costs and Contractor Composition: Evidence From Iowa

“Federal-aid swap” programs allow states and local governments to bypass federal Davis-Bacon prevailing wages and Disadvantaged Business Enterprise (DBE) goals by exchanging federal funds that have been allocated to highway projects with state funds. The Iowa Department of Transportation approved a federal-aid swap program in February 2018. Using data on more than 1,200 highway construction projects in Iowa from 2016 to 2020, I find that the cost of projects in the federal-aid swap program are not statistically different from those that were not swapped, after accounting for project size and complexity, project type, and project location. Regression results indicate that Davis-Bacon prevailing wages and DBE goals have no effect on total construction costs. However, the federal-aid swap program is statistically associated with a decrease in the likelihoods that a project is covered by the Davis-Bacon Act by 10 percentage points and DBE goals by 4 percentage points. Because the payment of Davis-Bacon prevailing wages is statistically associated with an 8 percentage-point decrease in the chances that a highway project is awarded to an out-of-state contractor, the federal-aid swap program may have increased the market share of out-of-state contractors at the expense of Iowa-based contractors.

Can Highway Networks Promote Productivity? Evidence from China

The total mileage of highways in China ranks first in the world and constitutes an important symbol of China’s modernization. Economists, however, continue to debate whether highways always promote economic growth in every region and how to assess the impact. In this paper, we first use the OD-MATRIX method to calculate the shortest highway traveling time among 332 prefecture-level cities in China from 2000 to 2013. It is shown that the reduction of traveling time brought by highway construction significantly improves enterprise productivity. Second, to further explore the mechanism at work, we apply market potential approach to examine its effect on productivity. It is found that on average, the enhanced market potential induced by highway construction in China positively affect enterprise productivity. Finally, we calculate urban centrality via the space gravity model and conduct a sample regression according to the rank of urban centrality. Interestingly, we find that the impact of highways on productivity varies depending on cities’ degree of urban centrality. Highways have a positive impact in high-centrality cities but a negative impact in low-centrality cities. This correlation can be explained, in turn, by factors that include labor and capital flow from low-centrality cities to high-centrality cities.