Floating car data for urban traffic flow analysis: a case study of Olomouc

Abstract

This paper examines the potential and limitations of floating car data for the spatiotemporal assessment of urban traffic congestion in a medium-sized city. Using traffic flow data obtained from the HERE Traffic API, the study analyses congestion patterns in Olomouc, Czechia, with a focus on daily trends, hourly variations, changes on selected specific days, and the spatial distribution of congestion across road segments. The data were collected at 15-minute intervals and aggregated to identify recurring traffic patterns and deviations associated with holidays, school-related changes, and pandemic restrictions. The results show that aggregated floating car data provide a robust basis for identifying recurrent congestion patterns, peak periods, and problematic road sections within the city. At the same time, the analysis demonstrates that single-day anomalies are often difficult to interpret without additional contextual information. The study confirms that floating car data are a useful source for medium-scale urban traffic monitoring, logistics planning, and comparative assessment of congestion, although their explanatory value is constrained by limited transparency in the underlying data generation process and by the absence of direct traffic counts.