The Relevance of Heterogeneous Floating Car Data for Macroscopic Fundamental Diagram Analysis

ABSTRACT Floating car data (FCD) are becoming an increasingly important source of information for macroscopic traffic monitoring. Unlike traditional fixed sensors, FCD allow direct measurement of travel times, speeds and delays, which are key indicators in the Highway Capacity Manual ( HCM ). This study investigates the applicability of heterogeneous FCD for capacity and performance analyses, with particular attention to the challenges of data noise, unstable traffic flows and varying vehicle composition. The methodology combines clustering techniques, specifically K‐means, to separate stable and unstable traffic states, along with a conversion of traffic volumes to passenger car equivalents (PCE). The results demonstrate that FCD can serve as a reliable supplementary data source on highways and major arterial roads, where measured values showed strong agreement with theoretical curves defined in HCM. However, the reliability decreases when the share of heavy vehicles exceeds 25 %, as PCE adjustments no longer fully correct the distortion. The findings confirm that FCD can be validated as a complementary input for traffic planning and decision‐making. Properly processed, these data offer valuable insights for local authorities. Future research should focus on estimating real traffic volumes from FCD to enable full integration with HCM methodologies, including the level of service evaluation.