Optimal viewpoint finding for 3D visualization of spatio-temporal vehicle trajectories on caution crossroads detected from vehicle recorder big data
Masahiko Itoh, Daisaku Yokoyama, Masashi Toyoda, Masaru Kitsuregawa · 2017
Traffic accidents are still troubling our society. The number of drive recorders sold has increased, and therefore we can collect large-scale vehicle recorder data to be used to support traffic safety. We have developed a system for detecting potentially risky crossroads on the basis of vehicle recorder data, road shapes, and weather information. Visualization combining space and time in a single display called a “space time cube (STC)” helps us to understand and analyze spatio-temporal mobility data on caution crossroads. The STC enables us to simultaneously explore not only shapes and positions of vehicle trajectories but also their temporal distributions. However, it is difficult for users to manually find good viewpoints for understanding such characteristics of trajectories. In this paper, we propose an optimal viewpoint selection method for visualizing spatio-temporal characteristics of vehicle trajectories on a large set of crossroads using an STC. Major contributions of this paper are as follows: (1) We provide an algorithm based on viewpoint entropy weighted by angles of trajectories with a horizontal line as a measure of a viewpoint quality on a projected 2D image. (2) We demonstrate our solution can be adapted to crossroads with different trajectory shapes. We also extend the proposed method to find an optimal viewpoint for multiple crossroads. (3) We verify the proposed method through users' evaluations. (4) We construct an overviewing catalog of potentially risky crossroads detected from real vehicle recorder big data to discuss and analyze them with stakeholders.