Zuchao Wang, Tangzhi Ye, Min Lu, Xiaoru Yuan, Huamin Qu, Jacky Yuan, Qianliang Wu
Sparse Traffic Trajectory, Traffic Visualization, Dynamic Graph Visualization, Traffic Congestion \
In this paper, we present a visual analysis system to explore sparse traffic trajectory data recorded by transportation cells. \ Such data contains the movements of nearly all moving vehicles on the major roads of a city. Therefore it is very suitable for macro- \ traffic analysis. However, the vehicle movements are recorded only when they pass through the cells. The exact tracks between two \ consecutive cells are unknown. To deal with such uncertainties, we first design a local animation, showing the vehicle movements \ only in the vicinity of cells. Besides, we ignore the micro-behaviors of individual vehicles, and focus on the macro-traffic patterns. We \ apply existing trajectory aggregation techniques to the dataset, studying cell status pattern and inter-cell flow pattern. Beyond that, \ we propose to study the correlation between these two patterns with dynamic graph visualization techniques. It allows us to check \ how traffic congestion on one cell is correlated with traffic flows on neighbouring links, and with route selection in its neighbourhood. \ Case studies show the effectiveness of our system. \
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