Muhammad Sherif is an assistant professor in the Department of Civil, Construction and Environmental Engineering at the University of Alabama at Birmingham (UAB). His research program is dedicated for the development of novel multifunctional materials and smart infrastructural systems.
The main interests of Sherif’s research program include: 1) Development and Characterization of Resilient, Sustainable and Smart Materials; 2) Additive Manufacturing; 3) Structural Health Monitoring and Decision-Making Systems; and 4) Development and Analysis of Smart Infrastructural and Structural Systems. You can find more about Sherif’s research interests at www.amsis.us.
Sherif’s research activities are intended to enhance the overall civil infrastructure including the transportation network. Currently, Sherif and his colleague, Dr. Virginia P. Sisiopiku of UAB, are involved in a STRIDE year 6 project titled Analysis of Impacts of Pavement Quality Deterioration on Recurring Traffic Congestion. The goal of this project is to provide insight on the correlation between pavement quality and traffic operations by showcasing the feasibility and value of an integrated traffic data and pavement quality management approach for monitoring traffic and infrastructure performance.
This study is important because of the extensive road network in the U.S. encompassing 4.2 million miles, with 220,000 miles of high-volume corridors. The literature confirms that surface deficiencies of transportation infrastructure cause non-recurrent congestion as they represent a contributing factor to 1/3 of all severe traffic crashes in the U.S. There’s a good argument to be made that recurrent congestion and accidents are correlated to poor pavement conditions when drivers have to continuously adjust their driving behaviors, sometimes abruptly, to avoid pavement cracks and other infrastructure deficiencies. However, those correlations are not documented in detail in the literature.
“Using machine learning algorithms for assessing pavement quality and congestion data, this project will quantify the extent to which pavement quality deterioration affects traffic congestion in urban settings,” Sherif said.
The project will provide a clear understanding on how pavement deterioration impacts recurring traffic congestion. The results will assist in the identification of locations where pavement deficiencies have the greatest burden on traffic operations and allow for prioritization and scheduling of pavement maintenance and allocation of resources to improve efficiency and mitigate traffic congestion.
It is expected that the outcomes of the project will benefit the state departments of transportation by way of minimizing the labor costs associated with pavement survey through implementing neural networks for processing publicly available images.
“The developed framework will allow the concerned departments to prioritize the resurfacing and repair of roads’ sections that experience heavy-traffic and high percentage of trucks,” he said.
For more information, contact Dr. Muhammad M. Sherif at email@example.com.