floatingcar

Floating car data (FCD) refers to traffic information derived from the movement of individual vehicles equipped with positioning devices, notably GPS. In this context, a "floating car" acts as a moving probe that reveals speeds and travel times on road segments, enabling estimation of network performance without relying solely on fixed sensors.

Data sources include taxi fleets, delivery and courier vehicles, fleet telematics, ride-hailing services, and consumer smartphones. Each observation provides a time-stamped position and speed, which are map-matched to roads and aggregated over defined intervals to produce segment speeds, travel times, or flow estimates. FCD complements traditional sensors.

Applications encompass real-time traffic monitoring, congestion detection, travel-time reliability analysis, incident detection, route planning, and calibration of transportation models. It is widely used in intelligent transportation systems and urban mobility studies, particularly in areas with sparse fixed sensing.

Limitations involve sampling biases toward equipped or smartphone users, privacy and regulatory concerns, data quality issues such as GPS error and inconsistent sampling rates, and potential gaps in coverage. Proper data processing and privacy-preserving techniques are essential when handling floating car data.

Originating in the late 20th century as researchers explored probe-vehicle methods for traffic measurement, the floating-car concept has grown with mobile devices and connected vehicles, becoming a central source of dynamic traffic information alongside traditional fixed sensors and crowd-sourced reports.