Result: Visual exploratory data analysis of traffic volume
Department of Geography, University of Tennessee, Knoxville, TN 37996-0925, United States
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Computer science; theoretical automation; systems
Further Information
Beijing has deployed Intelligent Transportation System (ITS) monitoring devices along selected major roads in the core urban area in order to help relieve traffic congestion and improve traffic conditions. The huge amount of traffic data from ITS originally collected for the control of traffic signals can be a useful source to assist in transportation designing, planning, managing, and research by identifying major traffic patterns from the ITS data. The importance of data visualization as one of the useful data mining methods for reflecting the potential patterns of large sets of data has long been recognized in many disciplines. This paper will discuss several comprehensible and appropriate data visualization techniques, including line chart, bi-directional bar chart, rose diagram, and data image, as exploratory data analysis tools to explore traffic volume data intuitively and to discover the implicit and valuable traffic patterns. These methods could be applied at the same time to gain better and more comprehensive insights of traffic patterns and data relationships hidden in the massive data set. The visual exploratory analysis results could help transportation managers, engineers, and planners make more efficient and effective decisions on the design of traffic operation strategies and future transportation planning scientifically.