Visualization of traffic congestion based on Floating Taxi Data

Abstract

Floating Car Data (FCD) are rich data sources collected from GPS-equipped vehicles for analyzing and modelling traffic information and human mobility. Due to the large amount of these movement data, we need visual analysis methods that enable users to inspect traffic situations. This paper investigates two visualization techniques for FCD: (1) three-dimensional representations of both average speed and average density derived from Floating Car Data (FCD) based on road segments and (2) two-dimensional maps representing qualitative traffic congestion inferred from the average speed and density. We propose a selection circle visualization method showing average speeds and average densities within a selected area. This information is represented in a 3-D extrusion projected onto the two-dimensional street network map. A test FCD set from Shanghai is used to evaluate the visualization technique. We can compare the visualization results at different time windows and detect spatio-temporal changes of the traffic situation in Shanghai. This helps to understand the general movement patterns.