floatingcardata

Floating Car Data, often abbreviated as FCD, refers to traffic information derived from GPS traces and other location data collected from moving vehicles acting as probes. Each vehicle contributes samples that typically include a timestamp, position, speed, and sometimes heading. The data are usually anonymized and aggregated to protect privacy, and shared at varying temporal and spatial resolutions.

Processing involves map matching to align GPS points with the road network, followed by speed estimation on road segments, travel-time calculations, and the creation of real-time speed maps and historical traffic patterns. Data are commonly combined with other sources, such as fixed sensors or map data, to improve accuracy.

Applications of floating car data include real-time traffic information services, route planning and dynamic navigation, congestion monitoring, incident detection, and travel-time forecasting. It also supports urban planning, transportation research, and the evaluation of traffic management policies.

Advantages of FCD include broad geographic coverage without the need for extensive fixed sensor infrastructure, high temporal resolution, and the ability to reflect actual driving conditions across diverse road networks. Limitations include sampling bias due to uneven vehicle penetration, varying data quality and GPS accuracy, privacy concerns, and potential data latency. Sparse coverage in rural areas can reduce reliability, and effective use often requires sophisticated data fusion and quality-control procedures.

Historically, floating car data emerged with the rise of telematics and GPS-equipped vehicles in the late 20th century and has since become a core data source for commercial navigation services and academic traffic studies. It is commonly considered a form of probe data derived from mobile platforms.