Data-Driven Insights Into Urban Intersections: Visual Analytics of High-Value Scene.

Abstract

In this article, we propose TraVis, an interactive system that allows users to explore and analyze complex traffic trajectory data at urban intersections. Trajectory data contain a large amount of spatio-temporal information, and while previous studies have mainly focused on the macroscopic aspects of traffic flow, TraVis employs visualization methods to investigate and analyze microscopic traffic events (i.e., high-value scenes in trajectory data). TraVis contains a novel view design and provides multiple interaction modalities to offer users the most intuitive insights into high-value scenes. With this system, users can gain a better understanding of urban intersection traffic information, identify different types of high-value scenes, explore the reasons behind their occurrence, and gain deeper insights into urban intersection traffic. Through two case studies, we illustrate how to use the system and validate its effectiveness.