A review on pavement data acquisition and analytics tools using autonomous vehicles
Source abstract
Abstract
Nowadays, road maintenance is a crucial planning task for all road authorities across the world, making them spend vast amounts of money on identification and rehabilitation programmes every year. Thus, many researchers, road engineers, and decision-makers have turned to a system called pavement management system, the critical step of which is pavement inspection. So far, several methods have been proposed for pavement distress data collection and evaluation. These methods have also evolved with the advancement of technology and intelligent transportation systems. Today, researchers have acknowledged autonomous vehicles as a sophisticated tool monitoring right of way for appropriate operating; however, little attention has been paid to using collected pavement condition data for pavement management. This study reviews the technologies and algorithms proposed so far to investigate the feasibility of using the data regularly collected by these vehicles to evaluate pavement conditions. We hope our paper paves the way for further research.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Infrastructure Maintenance and Monitoring · Traffic Prediction and Management Techniques · Asphalt Pavement Performance Evaluation
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran
Department of Civil and Environmental Engineering, Amirkabir University of Technology, Tehran, Iran
Civil and Infrastructure Engineering Discipline, School of Engineering, RMIT University, Melbourne, Australia
Chang’an-Dublin International College of Transportation, Chang’an University, Xi’an, People’s Republic of China
References (100+)
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