Floating Car Data for Road Roughness: An Innovative Approach to Optimize Road Surface Monitoring and Maintenance

This study investigates the potential of Floating Car Data (FCD) collected from Volkswagen Group vehicles since 2022 for monitoring pavement conditions along two Italian road stretches. While such data are primarily gathered to analyze vehicle dynamics and mechanical behaviour, here, they are repurposed to support road network assessment through the estimation of the International Roughness Index (IRI). Daily aggregated datasets provided by NIRA Dynamics were analyzed to evaluate their reliability in detecting spatial and temporal variations in surface conditions. The results show that FCD can effectively identify critical sections requiring maintenance, track IRI variations over time, and assess the performance of surface rehabilitation, with high consistency on single-lane roads. On multi-lane roads, limitations emerged due to data aggregation across lanes, leading to reduced accuracy. Nevertheless, FCD proved to be a cost-efficient and continuously available source of information, particularly valuable for identifying temporal changes and supporting the evaluation of maintenance interventions. Further calibration is needed to enhance alignment with high-performance measurement systems, considering data density at the section level. Overall, the findings highlight the suitability of FCD as a scalable solution for real-time monitoring and long-term maintenance planning, contributing to more sustainable management of road infrastructure.