How uncertainty in input and parameters influences transport model :output A four-stage model case-study

If not properly quantified, the uncertainty inherent to transport models makes analyses based on their output highly unreliable. This study investigated uncertainty in four-stage transport models by analysing a Danish case-study: the Naestved model. The model describes the demand of transport in the municipality of Naestved, located in the southern part of Zealand. The municipality has about 80,000 inhabitants and covers an area of around 681km2. The study was implemented by using Monte Carlo simulation and scenario analysis and it focused on how model input and parameter uncertainty affect the base-year model outputs uncertainty. More precisely, this study contributes to the existing literature on the topic by investigating the effects on model outputs uncertainty deriving from the use of (i) different probability distributions in the sampling process, (ii) different assignment algorithms, and (iii) different levels of network congestion. The choice of the probability distributions shows a low impact on the model output uncertainty, quantified in terms of coefficient of variation. Instead, with respect to the choice of different assignment algorithms, the link flow uncertainty, expressed in terms of coefficient of variation, resulting from stochastic user equilibrium and user equilibrium is, respectively, of 0.425 and 0.468. Finally, network congestion does not show a high effect on model output uncertainty at the network level. However, the final uncertainty of links with higher volume/capacity ratio showed a lower dispersion around the base uncertainty value.

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

[2]  James Odeck,et al.  Do Planners Get it Right? : The Accuracy of Travel Demand Forecasting in Norway , 2011 .

[3]  Peter Nijkamp,et al.  (Un)predictability in Traffic and Transport Decision Making , 1999 .

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

[5]  C. Xie,et al.  Integrated Equilibrium Travel Demand Model with Nested Logit Structure , 2011 .

[6]  Søren L. Buhl,et al.  Inaccuracy in Traffic Forecasts , 2006 .

[7]  David J. Ashley.  Uncertainty in the context of highway appraisal , 1980 .

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

[9]  R. Bain,et al.  Traffic forecasting risk: study update 2004 , 2004 .

[10]  Ram M. Pendyala,et al.  Stochastic Variability in Microsimulation Modeling Results and Convergence of Corridor-Level Characteristics , 2011 .

[11]  David M Levinson,et al.  Post-Construction Evaluation of Traffic Forecast Accuracy , 2009 .

[12]  B. Flyvbjerg.  Measuring Inaccuracy in Travel Demand Forecasting: Methodological Considerations Regarding Ramp Up and Sampling , 2005, 1303.7401.

[13]  Otto Anker Nielsen,et al.  A Stochastic Route Choice Model for Car Travellers in the Copenhagen Region , 2002 .

[14]  Chao Yang,et al.  Sensitivity-based Uncertainty Analysis of a Combined Travel Demand Model , 2011 .

[15]  W. Walker,et al.  Defining Uncertainty: A Conceptual Basis for Uncertainty Management in Model-Based Decision Support , 2003 .

[16]  R Bain,et al.  Traffic forecasting risk study update 2005: through ramp-up and beyond , 2005 .

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

[18]  Yosef Sheffi,et al.  Urban Transportation Networks: Equilibrium Analysis With Mathematical Programming Methods , 1985 .

[19]  A M Boyce,et al.  RISK ANALYSIS FOR PRIVATELY FUNDED TRANSPORT SCHEMES , 1999 .

[20]  Davy Janssens,et al.  Uncertainty in forecasts of complex rule-based systems of travel demand: Comparative analysis of the Albatross/Feathers model system , 2012 .

[21]  Anna Matas,et al.  Traffic forecasts under uncertainty and capacity constraints , 2009 .

[22]  Hjp Harry Timmermans,et al.  Uncertainty in travel demand forecasting models: literature review and research agenda , 2012 .

[23]  Andrew Daly,et al.  Uncertainty in traffic forecasts: literature review and new results for The Netherlands , 2007 .

[24]  Hjp Harry Timmermans,et al.  Probabilistic forecasting of time-dependent origin–destination matrices by a complex activity-based model system: effects of model uncertainty , 2013 .

[25]  E. Kroes.  SOME ISSUES IN TRAFFIC FORECASTING FOR PRIVATELY FINANCED INFRASTRUCTURE , 1996 .