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%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2017/08.21.17.31
%2 sid.inpe.br/sibgrapi/2017/08.21.17.31.23
%T Interactive Visualization of Traffic Dynamics Based on Trajectory Data
%D 2017
%A Gomes, George Allan Menezes,
%A Santos, Emanuele,
%A Vidal, Creto A.,
%@affiliation Federal University of Ceará, Fortaleza, Brazil
%@affiliation Federal University of Ceará, Fortaleza, Brazil
%@affiliation Federal University of Ceará, Fortaleza, Brazil
%E Torchelsen, Rafael Piccin,
%E Nascimento, Erickson Rangel do,
%E Panozzo, Daniele,
%E Liu, Zicheng,
%E Farias, Mylène,
%E Viera, Thales,
%E Sacht, Leonardo,
%E Ferreira, Nivan,
%E Comba, João Luiz Dihl,
%E Hirata, Nina,
%E Schiavon Porto, Marcelo,
%E Vital, Creto,
%E Pagot, Christian Azambuja,
%E Petronetto, Fabiano,
%E Clua, Esteban,
%E Cardeal, Flávio,
%B Conference on Graphics, Patterns and Images, 30 (SIBGRAPI)
%C Niterói, RJ
%8 Oct. 17-20, 2017
%S Proceedings
%I IEEE Computer Society
%J Los Alamitos
%K interactive visualization, traffic visualization, traffic patterns, spatiotemporal, visual exploration.
%X Urbanization is accelerating worldwide, giving rise to serious traffic problems. Traffic wave, known as stop-and-go traffic or phantom intersection, is one of the most significant traffic oscillation patterns studied in Traffic Engineering. Usually these studies are numerical experiments that investigate specific places, such as a crossroad or a highway section, and their findings cannot, therefore, be easily applied to sensing device data in a systematic computational approach. In this regard, visual analytics can help by combining automated analysis with interactive visualization for effective understanding, reasoning, and decision-making. In this paper, we present a novel approach for visualizing traffic oscillation patterns by visualizing the objects' movement in space over time, inspired by vector field visualization. We propose an algorithm to control and synchronize the visualization time; a systematic stepwise methodology for exploring sensing device data; and a visualization tool that computes the trajectory data in parallel on the GPU at interactive frame rates. Moreover, our approach is designed to support both batch-processed and streaming data applications. We also present the benefits and limitations of our visualization proposal based on domain expert feedback. Finally, we present performance tests with very encouraging results to support our approach.
%@language en
%3 PID4959881.pdf


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