Advancements in pothole detection techniques: a comprehensive review and comparative analysis

Potholes are a major issue for road infrastructure, leading to vehicle damage, higher maintenance expenses, and safety risks for road users. Prompt and precise detection of potholes is necessary for maintaining road quality and ensuring safety. In past few years, various techniques have been developed for pothole detection, utilizing technologies such as computer vision, sensors, machine learning (ML), and crowdsourcing. This review offers a detailed examination of these pothole detection methods, assessing their advantages, drawbacks, and potential uses. Extensive research has been conducted in this area, encompassing an analysis of more than a hundred research papers in the field. Various techniques and their accuracies and processing times are mentioned to determine the best technique while considering all the aspects. The review discusses the pothole detection and provide a comprehensive analysis of pothole formation mechanisms and the various techniques applied for their detection. The study evaluates different pothole detection techniques and presents a comparative analysis of various automated pothole detection methods. This study highlights the strengths and limitations of various pothole detection techniques, providing valuable insights for researchers, practitioners, and policymakers. By grasping the strengths and limitations of these methods, stakeholders can make well-informed choices about selecting and applying suitable detection strategies for the maintenance and safety of road infrastructure.