ICE--visual analytics for transportation incident datasets

Abstract

Transportation systems are being monitored at an unprecedented scope resulting in tremendously detailed traffic and incident databases. While the transportation community emphasizes developing standards for storing this incident data, little effort has been made to design appropriate visual analytics tools to explore the data, extract meaningful knowledge, and represent results. Analyzing these large multivariate geospatial datasets is a non-trivial task. A novel, web-based, visual analytics tool called ICE (incident cluster explorer) is proposed as an application that affords sophisticated yet user-friendly analysis of transportation incident datasets. Interactive maps, histograms, two-dimensional plots and parallel coordinates plots are four visualizations that are integrated together to allow users to simultaneously interact with and see relationships between multiple visualizations. Accompanied by a rich set of filters, users can create custom conditions to filter data and focus on a smaller dataset. Due to the multivariate nature of the data, a rank-by-feature framework has been expanded to quantify the strength of relationships between the different fields.