Sensing technologies, social media, and large-scale computing infrastructures have produced a variety of traffic and transportation data, e.g., human mobility, mobile trajectories, mobile phone calls, traffic, and geographical data. Despite the wealth of research on intelligent transportation systems, contemporary analytical tools are often inadequate for handling the data with the character of large volume, sparseness, and heterogeneity, let alone for supporting interactive visual analysis for data-intensive applications. Visual analytics can build bridges between the capability of data processing and human intelligence to promote addressing various transportation problems. On one hand, by employing visual channels to represent datasets and transforming various types of data into appropriate visual components, visualization can enhance understanding and analysis. On the other hand, an interactive interface allows users to investigate and directly access selected data points or features, discover interesting patterns or events, and engage in visual reasoning that allows users to gain insights, e.g., it is desirable to only show the most relevant portions of a dataset while giving directions for potential exploration.
Guest Editorial Introduction to the Special Issue on Visual Analysis for ITS
IEEE Transactions on Intelligent Transportation Systems ; 18 , 8 ; 2229-2231
2017-08-01
465266 byte
Article (Journal)
Electronic Resource
English
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