Exploratory visualisation of congestion evolutions on urban transport networks

Visualisation is an effective tool for studying traffic congestion using massive traffic datasets collected from traffic sensors. Existing techniques can reveal where/when congested areas are formed, developed, and moved on one or several highway roads, but it is still challenging to visualise the evolution of traffic congestion on the whole road network, especially on dense urban networks. To address this challenge, this paper proposes three 3D exploratory visualisation techniques: the isosurface, the constrained isosurface, and the wall map. These three techniques have different advantages and should be combined to leverage their respective strong points. We present our visualisation techniques with the case of link travel time data from Automatic Number Plate Recognition (ANPR) in London.

[1]  Gennady L. Andrienko,et al.  Interactive analysis of event data using space-time cube , 2004, Proceedings. Eighth International Conference on Information Visualisation, 2004. IV 2004..

[2]  Tomoki Nakaya,et al.  Visualising Crime Clusters in a Space‐time Cube: An Exploratory Data‐analysis Approach Using Space‐time Kernel Density Estimation and Scan Statistics , 2010, Trans. GIS.

[3]  Alexei Pozdnoukhov,et al.  User-Centric Time-Distance Representation of Road Networks , 2010, GIScience.

[4]  Gary Higgs,et al.  Visualising space and time in crime patterns: A comparison of methods , 2007, Comput. Environ. Urban Syst..

[5]  P. F. Madzudzo,et al.  Exploratory Visualization of Temporal Events in Epidemiological Research Case Study of the Black Death , 2007 .

[6]  Dirk Helbing,et al.  Reconstructing the spatio-temporal traffic dynamics from stationary detector data , 2002 .

[7]  T. Cheng,et al.  Multi-Scale Visualisation of Inbound and Outbound Traffic Delays in London , 2010 .

[8]  Allan R. Wilks,et al.  Visualizing Network Data , 1995, IEEE Trans. Vis. Comput. Graph..

[9]  Torsten Hägerstraand WHAT ABOUT PEOPLE IN REGIONAL SCIENCE , 1970 .

[10]  Kerner,et al.  Experimental properties of complexity in traffic flow. , 1996, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[11]  Cláudio T. Silva,et al.  Software Infrastructure for exploratory visualization and data analysis: past, present, and future , 2008 .

[12]  Jeffrey Johnson,et al.  The Q-Analysis of Road Traffic Systems , 1981 .

[13]  Jacky Legrand How far can Q-analysis go into social systems understanding ? , 2002 .

[14]  Fritz Drury,et al.  Visualization Criticism , 2008, IEEE Computer Graphics and Applications.

[15]  Erwin Keeve,et al.  Efficient point-based isosurface exploration using the span-triangle , 2004, IEEE Visualization 2004.

[16]  Heidrun Schumann,et al.  Stacking-Based Visualization of Trajectory Attribute Data , 2012, IEEE Transactions on Visualization and Computer Graphics.

[17]  Jason Dykes,et al.  Using treemaps for variable selection in spatio-temporal visualisation , 2008, Inf. Vis..

[18]  Marc Levoy,et al.  Display of surfaces from volume data , 1988, IEEE Computer Graphics and Applications.

[19]  Anthony C. Gatrell,et al.  Distance and Space: A Geographical Perspective , 1983 .

[20]  Dirk Helbing,et al.  MASTER: macroscopic traffic simulation based on a gas-kinetic, non-local traffic model , 2001 .

[21]  Thomas K. Peucker,et al.  2. Algorithms for the Reduction of the Number of Points Required to Represent a Digitized Line or its Caricature , 2011 .

[22]  Shashi Shekhar,et al.  CubeView: a system for traffic data visualization , 2002, Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems.

[23]  Kirsi Virrantaus,et al.  Space–time density of trajectories: exploring spatio-temporal patterns in movement data , 2010, Int. J. Geogr. Inf. Sci..

[24]  Daniel A. Keim,et al.  Information Visualization and Visual Data Mining , 2002, IEEE Trans. Vis. Comput. Graph..

[25]  Yi Zhang,et al.  Spatial-temporal traffic data analysis based on global data management using MAS , 2004, IEEE Trans. Intell. Transp. Syst..

[26]  Rui Jiang,et al.  Spatiotemporal congested traffic patterns in macroscopic version of the Kerner–Klenov speed adaptation model , 2007 .

[27]  M J Lighthill,et al.  On kinematic waves II. A theory of traffic flow on long crowded roads , 1955, Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences.

[28]  B. Marchand,et al.  DEFORMATION OF A TRANSPORTATION SURFACE , 1973 .

[29]  D. Hennessy,et al.  The Influence of Traffic Congestion, Daily Hassles, and Trait Stress Susceptibility on State Driver Stress: An Interactive Perspective , 2000 .

[30]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[31]  Dirk Helbing,et al.  Numerical simulation of macroscopic traffic equations , 1999, Comput. Sci. Eng..

[32]  Gennady L. Andrienko,et al.  Exploratory analysis of spatial and temporal data - a systematic approach , 2005 .

[33]  R. Courant What is mathematics? : an elementary approach to ideas and methods / R. Courant, Herbert Robbins , 1941 .

[34]  Dirk Helbing,et al.  Empirical Features of Congested Traffic States and Their Implications for Traffic Modeling , 2007, Transp. Sci..

[35]  Abdullah Zawawi Talib,et al.  Dynamic Traffic Simulation for Traffic Congestion Problem Using an Enhanced Algorithm , 2008 .

[36]  Zhiheng Li,et al.  Network-Wide Traffic State Observation and Analysis Method Using Pseudo-Color Map , 2009 .

[37]  Tong Li,et al.  Nonlinear Dynamics of Traffic Jams , 2005, Second International Multi-Symposiums on Computer and Computational Sciences (IMSCCS 2007).

[38]  Tong Li,et al.  Nonlinear dynamics of traffic jams , 2005 .

[39]  Xiaoyan Zhang,et al.  Visualizing Loop Detector Data , 1999 .

[40]  Wen-Long Jin,et al.  The formation and structure of vehicle clusters in the Payne-Whitham traffic flow model , 2003 .

[41]  D. Wright,et al.  Marine and coastal geographical information systems , 1999 .

[42]  David H. Douglas,et al.  ALGORITHMS FOR THE REDUCTION OF THE NUMBER OF POINTS REQUIRED TO REPRESENT A DIGITIZED LINE OR ITS CARICATURE , 1973 .