Spatiotemporal analysis of critical transportation links based on time geographic concepts: a case study of critical bridges in Wuhan, China

Abstract Critical transportation infrastructure has been studied extensively in recent years. This paper presents a spatiotemporal analysis of critical transportation links based on time geographic concepts. With widespread adoption of information and communication technologies (ICT) and location-aware mobile devices, large tracking datasets have become readily available. This study uses a tracking dataset of approximately 12,000 taxis in Wuhan, China over 1 week to analyze spatiotemporal origin–destination (O–D) patterns of trips that use three critical bridges connecting the three districts of Wuchang, Hankou, and Hanyang separated by the Yangtze River and the Han River. We use the space–time prism concept to identify alternative space–time paths passing through different bridges that observe the spatial and temporal constraints between each O–D pair derived from the taxi trajectory data. This case study illustrates the feasibility and benefits of using the proposed time geographic approach to analyze spatiotemporal patterns of travel demands on the critical links and their alternative paths in a transportation system.

[1]  Hoyoung Jeung.  Pattern-Aware Prediction for Moving Objects , 2009 .

[2]  Hani S. Mahmassani,et al.  Dynamic origin-destination demand estimation using automatic vehicle identification data , 2006, IEEE Transactions on Intelligent Transportation Systems.

[3]  Seth D. Guikema,et al.  Natural disaster risk analysis for critical infrastructure systems: An approach based on statistical learning theory , 2009, Reliab. Eng. Syst. Saf..

[4]  Hongbo Yu,et al.  Potential effects of ICT on face-to-face meeting opportunities: a GIS-based time-geographic approach , 2011 .

[5]  Noam Shoval,et al.  Sequence Alignment as a Method for Human Activity Analysis in Space and Time , 2007 .

[6]  Mei-Po Kwan,et al.  Network-based constraints-oriented choice set formation using GIS , 1998 .

[7]  Mei-Po Kwan,et al.  Interactive geovisualization of activity-travel patterns using three-dimensional geographical information systems: a methodological exploration with a large data set , 2000 .

[8]  Tomas Hellström,et al.  Critical infrastructure and systemic vulnerability: Towards a planning framework , 2007 .

[9]  Glen M. D'Este,et al.  Application of Accessibility Based Methods for Vulnerability Analysis of Strategic Road Networks , 2006 .

[10]  Ki-Joune Li,et al.  Searching for Similar Trajectories on Road Networks Using Spatio-temporal Similarity , 2006, ADBIS.

[11]  Robert Weibel,et al.  Towards a taxonomy of movement patterns , 2008, Inf. Vis..

[12]  Hani S. Mahmassani,et al.  A structural state space model for real-time traffic origin–destination demand estimation and prediction in a day-to-day learning framework , 2007 .

[13]  Yue Yang.  Vehicle Travel Speed Estimation from Large Volume Floating Car Data:A Case Study of Wuhan , 2009 .

[14]  C. Bhat,et al.  Activity-Travel Patterns of Nonworkers in the San Francisco Bay Area: Exploratory Analysis , 2000 .

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

[16]  E. Jenelius.  Network structure and travel patterns: explaining the geographical disparities of road network vulnerability , 2009 .

[17]  J Peachman,et al.  THE JOYS AND TRIBULATIONS OF A CONTINUOUS SURVEY. IN: TRANSPORT SURVEY QUALITY AND INNOVATION , 2003 .

[18]  Johannes Bröcker,et al.  Assessing Spatial Equity and Efficiency Impacts of Transport Infrastructure Projects , 2010 .

[19]  Hongbo Yu,et al.  A Space‐Time GIS Approach to Exploring Large Individual‐based Spatiotemporal Datasets , 2008, Trans. GIS.

[20]  Michael A. P. Taylor,et al.  Transport Network Vulnerability: a Method for Diagnosis of Critical Locations in Transport Infrastructure Systems , 2007 .

[21]  Wei Tu,et al.  A multi-objective approach to scheduling joint participation with variable space and time preferences and opportunities , 2011 .

[22]  K Fallast,et al.  SELECTED RESULTS OF A STANDARDIZED SURVEY INSTRUMENT FOR LARGE-SCALE TRAVEL SURVEYS IN SEVERAL EUROPEAN COUNTRIES , 1985 .

[23]  Irene Eusgeld,et al.  "System-of-systems" approach for interdependent critical infrastructures , 2011, Reliab. Eng. Syst. Saf..

[24]  Andrew S. Harvey,et al.  Time-Space Diaries: Merging Traditions , 2003 .

[25]  Bart Kuijpers,et al.  Modeling uncertainty of moving objects on road networks via space–time prisms , 2009, Int. J. Geogr. Inf. Sci..

[26]  Kees Maat,et al.  Deriving and validating trip purposes and travel modes for multi-day GPS-based travel surveys: A large-scale application in the Netherlands , 2009 .

[27]  Gaetano Valenti,et al.  Traffic Estimation And Prediction Based On Real Time Floating Car Data , 2008, 2008 11th International IEEE Conference on Intelligent Transportation Systems.

[28]  William J. Tolone.  Interactive visualizations for critical infrastructure analysis , 2009, Int. J. Crit. Infrastructure Prot..

[29]  Pengcheng Zhang,et al.  A generalized modeling framework to analyze interdependencies among infrastructure systems , 2011 .

[30]  Fred Cohen,et al.  What makes critical infrastructures Critical? , 2010, Int. J. Crit. Infrastructure Prot..

[31]  Hongbo Yu,et al.  A GIS-based time-geographic approach of studying individual activities and interactions in a hybrid physical–virtual space , 2009 .

[32]  Robert Weibel,et al.  Discovering relative motion patterns in groups of moving point objects , 2005, Int. J. Geogr. Inf. Sci..

[33]  Yafeng Yin,et al.  A decomposition scheme for estimating dynamic origin–destination flows on actuation-controlled signalized arterials , 2010 .

[34]  Mei-Po Kwan,et al.  Geovisualization of Human Hybrid Activity‐Travel Patterns , 2007, Trans. GIS.

[35]  Ta Theo Arentze,et al.  A Position-Sensitive Sequence-Alignment Method Illustrated for Space–Time Activity-Diary Data , 2001 .

[36]  Harvey J. Miller,et al.  Modelling accessibility using space-time prism concepts within geographical information systems , 1991, Int. J. Geogr. Inf. Sci..

[37]  Darren M. Scott,et al.  Network Robustness Index : a new method for identifying critical links and evaluating the performance of transportation networks , 2006 .

[38]  Shih-Lung Shaw,et al.  Exploratory data analysis of activity diary data: a space-time GIS approach , 2011 .

[39]  Scott A. Bridwell,et al.  A Field-Based Theory for Time Geography , 2009 .

[40]  Roberto Setola,et al.  Critical infrastructure dependency assessment using the input-output inoperability model , 2009, Int. J. Crit. Infrastructure Prot..

[41]  Harvey J. Miller,et al.  Computational Tools for Measuring Space-Time Accessibility within Transportation Networks with Dynamic Flow , 2001 .

[42]  Shih-Lung Shaw,et al.  Exploring potential human activities in physical and virtual spaces: a spatio‐temporal GIS approach , 2008, Int. J. Geogr. Inf. Sci..

[43]  Luis G. Willumsen,et al.  ESTIMATION OF AN O-D MATRIX FROM TRAFFIC COUNTS - A REVIEW , 1978 .

[44]  Gennady L. Andrienko,et al.  Spatio-temporal aggregation for visual analysis of movements , 2008, 2008 IEEE Symposium on Visual Analytics Science and Technology.

[45]  Stephen Greaves,et al.  Household travel surveys: Where are we going? , 2007 .

[46]  A. M. Lockwood,et al.  Exploratory Analysis of Weekend Activity Patterns in the San Francisco Bay Area, California , 2005 .

[47]  Tijs Neutens,et al.  A three-dimensional network-based space–time prism , 2008, J. Geogr. Syst..

[48]  Adrian V. Gheorghe,et al.  System of Systems , 2012 .

[49]  Randall Guensler,et al.  Elimination of the Travel Diary: Experiment to Derive Trip Purpose from Global Positioning System Travel Data , 2001 .

[50]  James P. Peerenboom,et al.  Identifying, understanding, and analyzing critical infrastructure interdependencies , 2001 .

[51]  Tetsuo Kobayashi.  An interactive visualization tool for mobile objects , 2010 .

[52]  Rabindra Bista,et al.  Spatio-temporal Similarity Measure Algorithm for Moving Objects on Spatial Networks , 2007, ICCSA.

[53]  Pavlos S. Kanaroglou,et al.  A GIS toolkit for exploring geographies of household activity/travel behavior , 2006 .

[54]  Li Qingquan.  Huge Volume Floating Car Data Express Processing Based on Vector Road Map Rasterization , 2010 .

[55]  Koos van der Bruggen,et al.  Critical infrastructures and responsibility: A conceptual exploration , 2008 .

[56]  Hai Yang,et al.  Estimation of origin-destination matrices from link traffic counts on congested networks , 1992 .