International roughness index: The quick way to the assessment of road quality; [Internationaler Rauheits-index: Der schnelle Weg zur Bewertung der Straßenqualität]

Abstract

This article discusses the International Roughness Index as a practical measure for assessing road quality. Road surfaces influence driving comfort, vehicle operation, maintenance requirements and overall transport safety. Because road networks cover large areas, authorities need efficient methods for identifying sections that require inspection or improvement. The International Roughness Index provides a standardized way to describe surface unevenness and can therefore support comparison between different road sections. The article focuses on the value of a quick and objective approach to road-condition assessment. Measurements collected through suitable surveying systems can be processed to produce an indicator that helps maintenance teams understand where road conditions may require attention. Combining such measurements with geographic information can make the results easier to visualize and relate to specific locations. Spatial databases and GIS can support the management of road-condition information over time, allowing authorities to compare measurements, identify recurring problem areas and plan interventions. The approach can also contribute to more systematic maintenance strategies instead of relying only on visual inspection or isolated reports. Although the roughness index provides useful information, road quality is influenced by several factors, so the indicator should be considered as part of a broader assessment process. The article shows how a relatively simple measurement concept can provide practical support for road management. Linking road-quality indicators with geospatial information can make infrastructure monitoring more efficient and help decision-makers prioritize maintenance activities. This perspective is also relevant for organizations that are planning long-term digital transformation and need practical information rather than technology in isolation. It shows how geospatial methods can connect operational needs with clearer, evidence-based decisions.