Uncertainty Propagation and Sensitivity Analysis During Calibration of an Integrated Land Use and Transport Model

In this work, propagation of uncertainty during calibra- tion process of TRANUS, an integrated land use and transport model (ILUTM), has been investigated. It has also been examined, through a sensitivity analysis, which input parameters affect the variation of the outputs the most. Moreover, a probabilistic verification methodology of calibration process, which equates the observed and calculated production, has been proposed. The model chosen as an application is the model of the city of Grenoble, France. For sensitivity analysis and uncertainty propagation, Monte Carlo method was employed, and a statistical hypothesis test was used for verification. The parameters of the induced demand function in TRANUS, were assumed as uncertain in the present case. It was found that, if during calibration, TRANUS converges, then with a high probability the calibration process is verified. Moreover, a weak correlation was found between the inputs and the outputs of the calibration process. The total effect of the inputs on outputs was investigated, and the output variation was found to be dictated by only a few input parameters.

[1]  Andrea Saltelli,et al.  From screening to quantitative sensitivity analysis. A unified approach , 2011, Comput. Phys. Commun..

[2]  M Echenique AN INTEGRATED LAND USE AND TRANSPORT MODEL , 1977 .

[3]  Kara M. Kockelman,et al.  Highway Improvement Project Rankings due to Uncertain Model Inputs: Application of Traditional Transportation and Land Use Models , 2010 .

[4]  B Pérez,et al.  TRANUS-J: Putting Large Models into Small Computers , 1984 .

[5]  P. Waddell UrbanSim: Modeling Urban Development for Land Use, Transportation, and Environmental Planning , 2002 .

[6]  Robert A. Johnston,et al.  Multivariate Uncertainty Analysis of an Integrated Land Use and Transportation Model: MEPLAN , 2006 .

[7]  Magnello Me Karl Pearson's Gresham lectures: W. F. R. Weldon, speciation and the origins of Pearsonian statistics. , 1996 .

[8]  Austin Troy,et al.  Integrated Land-Use, Transportation and Environmental Modeling: Validation Case Studies , 2010 .

[9]  Adrian E. Raftery,et al.  Uncertain benefits: Application of Bayesian melding to the Alaskan Way Viaduct in Seattle , 2011 .

[10]  John Douglas Hunt,et al.  Theory and Application of an Integrated Land-Use and Transport Modelling Framework , 1993 .

[11]  Pierre Dardenne,et al.  Validation and verification of regression in small data sets , 1998 .

[12]  Kara M. Kockelman,et al.  Propagation of Uncertainty in Transportation Land Use Models: Investigation of DRAM-EMPAL and UTPP Predictions in Austin, Texas , 2003 .

[13]  Kara M. Kockelman,et al.  Uncertainty Propagation in an Integrated Land Use-Transportation Modeling Framework: Output Variation via UrbanSim , 2002 .

[14]  Phil Edwards,et al.  INTEGRATED LAND USE AND TRANSPORT MODELLING. DECISION CHAINS AND HIERARCHIES , 1989 .

[15]  Joseph A. C. Delaney Sensitivity analysis , 2018, The African Continental Free Trade Area: Economic and Distributional Effects.

[16]  M. Wegener Overview of Land Use Transport Models , 2004 .

[17]  Hani S. Mahmassani,et al.  Uncertainty in transportation systems evaluation: issues and approaches , 1984 .

[18]  David M Levinson,et al.  Models of Transportation and Land Use Change: A Guide to the Territory , 2008 .

[19]  Saltelli Andrea,et al.  Global Sensitivity Analysis: The Primer , 2008 .

[20]  Karl Pearson's Gresham lectures: W. F. R. Weldon, speciation and the origins of Pearsonian statistics , 1996, The British Journal for the History of Science.

[21]  Richard E. Klosterman,et al.  Planning Support Systems: Integrating Geographic Information Systems,Models,and Visualization Tools , 2001 .

[22]  K. Miyamoto,et al.  EVALUATION SYSTEM OF POLICY MEASURE ALTERNATIVES FOR A METROPOLIS BASED ON TRANUS FROM THE VIEW POINT OF SUSTAINABILITY , 2005 .

[23]  Kaja Bahor Integrated Land Use and Transport modelling , 2014 .

[24]  Kara M. Kockelman,et al.  The propagation of uncertainty through travel demand models: An exploratory analysis , 2000 .

[25]  M. Hesse Handbook of Transport Geography and Spatial Systems , 2005 .

[26]  P. Cochat,et al.  Et al , 2008, Archives de pediatrie : organe officiel de la Societe francaise de pediatrie.

[27]  Wilson H. Tang,et al.  Probability concepts in engineering planning and design , 1984 .

[28]  P. Waddell Integrated Land Use and Transportation Planning and Modelling: Addressing Challenges in Research and Practice , 2011 .

[29]  Adrian E. Raftery,et al.  Assessing Uncertainty in Urban Simulations Using Bayesian Melding , 2007 .