In this project, we develope an interactive system for visual analysis of urban traffic congestion based on GPS trajectories. For these trajectories we develop strategies to extract and derive traffic jam information. After cleaning the trajectories, they are matched to a road network. Subsequently, traffic speed on each road segment is computed and traffic jam events are automatically detected. Spatially and temporally related events are concatenated in, so-called, traffic jam propagation graphs. These graphs form a high-level description of a traffic jam and its propagation in time and space. Our system provides multiple views for visually exploring and analyzing the traffic condition of a large city as a whole, on the level of propagation graphs, and on road segment level. Case studies with 24 days of taxi GPS trajectories collected in Beijing demonstrate the effectiveness of our system.
Zuchao Wang, Min Lu, Xiaoru Yuan, Junping Zhang, and Huub van de Wetering.
Visual Traffic Jam Analysis Based on Trajectory Data.
IEEE Transactions on Visualization and Computer Graphics (VAST'13), 19(12):2159-2168, 2013.
Zuchao Wang, Min Lu, Xiaoru Yuan.
Beijing Traffic Congestion Map.
Beijing Design Week, GeoCity Smart City-International Information Design Exhibition, Beijing, China, September 26-Octobor 13, 2013. (In Chinese 中文)
Different speed patterns of roads in Beijing
The path and temporal delay of a traffic jam propagation