The Introduction of Dynamic Features in a Random-Utility-Based Multiregional Input-Output Model of Trade, Production, and Location Choice

Tian, Hongyu; Kockelman, Kara M.

doi:10.5399/osu/jtrf.47.1.1061

Cited by 5 publications

(8 citation statements)

References 13 publications

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“…Figure 1b. The integrated approach is rerun, similarly as in other research works (26), with the updated GTC L,R through an iterative feedback process until convergence is achieved. (29).…”

Section: Road Network Modelmentioning

confidence: 99%

“…RUBMRIO analysis has been performed on well-known land use models involving spatial economics (23). Existing RUBMRIO applications of transport cover different ex ante topics such as construction of transportation corridors, changes in travel times, transport investments, operational cost variations, fuel taxes, road charging, trade pattern changes, and regional transport conditions [for more details, see Du and Kockelman (24), Cascetta et al (25), Huang and Kockelman (26), Guzman and Vassallo (27), and Zhao and Kockelman (28)]. Although these applications have identified important indirect effects of transport policies at the regional level on various macroeconomic aggregate indicators, most of these applications did not calculate direct effects on the transportation system (e.g., congestion reduction, time savings, traffic deviation, pollution, and reduction of emissions).…”

Section: Rubmrio Modelmentioning

confidence: 99%

“…These O-D matrices corresponding to each economic sector are assigned to the road transport network to determine traffic volumes in the links, which enable one to update costs according to the new TTime L as shown in Figure 1b. The integrated approach is rerun, similarly as in other research works (26), with the updated GTC L,R through an iterative feedback process until convergence is achieved. (29).…”

Section: Model Integration and Solution Proceduresmentioning

confidence: 99%

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Impact of Introducing Longer and Heavier Vehicles on Regional Consumer Price Index and Spanish Road Freight Transport System

Guzmán

Vassallo

2014

Transportation Research Record

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the estimation of transportation costs and effects from transportation policies are well documented. Impact assessment has shown a strong linkage between transportation costs and economic development, but a direct measurement [using, for example, the consumer price index (CPI)] of how changes in the weighted average for the price of a basket of consumer goods and services reflect the transportation policies by region is still scarce [see, e.g., Banister and Berechman (4) and Rephann (5)].The current research aims at filling that gap by addressing the effect of transport policies on transportation costs, commodity prices, CPI, and changes in the transportation system performance. For that purpose, an integrated model approach including a random utility-based multiregional input-output (RUBMRIO) model and a road transport network model has been applied to study the effect of introducing longer and heavier vehicles (LHVs) in a selected road transport network of Spain [9,799 km (6,089 mi) in length]. Results come from a comparison between the base case scenario and the case study.This paper is organized as follows. A brief overview of the research is first provided. Next, the methodology proposed and its limitations are discussed. A detailed description of the case study is then offered, followed by an analysis of results in regard to regional CPI changes and the transportation system. Finally, the most relevant conclusions and suggestions about the implementation of policies as well as possible future developments are presented.The Freight Transportation Planning and Logistics Committee peer-reviewed this paper.

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“…Figure 1b. The integrated approach is rerun, similarly as in other research works (26), with the updated GTC L,R through an iterative feedback process until convergence is achieved. (29).…”

Section: Road Network Modelmentioning

confidence: 99%

Section: Rubmrio Modelmentioning

confidence: 99%

Section: Model Integration and Solution Proceduresmentioning

confidence: 99%

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Impact of Introducing Longer and Heavier Vehicles on Regional Consumer Price Index and Spanish Road Freight Transport System

Guzmán

Vassallo

2014

Transportation Research Record

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“…Ruiz-Juri and extended the RUBMRIO model to recognize land use constraints on production (and residence), to incorporate domestic demands by other U.S. states, estimate vehicle trips resulting from monetary trades, and capture the effects of the network congestion on trade and production decisions. Based on the above work, Huang and Kockelman (2008) extended the RUBMRIO model to characterize near-term production and trade patterns based on current settlement and earnings patterns, and to introduce dynamic features, which forecast the evolution of a region's trade patterns -from a state of short-term disequilibrium to longer-run scenarios. Du and Kockelman (2012) extended work by Kockelman et al (2005) to a U.S.-level RUBMRIO model for trade patterns among the nation's 3,109 contiguous counties (excluding Hawaii and Alaska), across 20 socio-economic sectors, and two transportation modes.…”

Section: Introductionmentioning

confidence: 99%

Local Sensitivity Analysis of Forecast Uncertainty in a Random-Utility-Based Multiregional Input-Output Model

Wang¹,

Kockelman²

2016

J Transp Res Forum

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Transportation systems are critical to regional economies and quality of life. The Random-Utility-Based Multiregional Input-Output Model (RUBMRIO) for trade and travel choices is used here to appreciate the distributed nature of commodity flow patterns across the United States’ 3,109 contiguous counties and 12 industry sectors, for rail and truck operations. This paper demonstrates the model’s sensitivity to various inputs using the method of local sensitivity analysis with interactions (LSAI). This work simulates both individual effects as well as interaction effects of model inputs on outputs by providing sensitivity indices of model outputs to variations of inputs under two scenarios. Model outputs include predictions of domestic and export trade flows, value of goods produced, labor expenditures, and household and industry consumption levels across the counties in the United States. The LSAI technique allows transportation system operators to appreciate the roles of any model input and the associated uncertainty of outputs.

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“…Particularly Kockelman et al have used the model extensively to forecast land use and transportation scenarios in Texas and United States (Du and Kockelman, 2012;Ruiz Juri and Kockelman, 2006). They have also suggested variants of the original RUBMRIO model, in order to accommodate various objectives (Huang and Kockelman, 2010;Zhao and Kockelman, 2004;Juri and Kockelman, 2004). However, a methodology for inverse solution of the RUBMRIO model, where inputs are designed based on desired output values is missing from the literature.…”

Section: Introductionmentioning

confidence: 99%

Inverse identification of inputs of a random utility based model using optimal control

Dutta

2014

Computers, Environment and Urban Systems

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To cite this version:Parikshit Dutta. Inverse identification of inputs of a random utility based model using optimal control. Computers, Environment and Urban Systems, Elsevier, 2014, 46, pp.1 -11. <10.1016/j.compenvurbsys.2014 AbstractThe random utility based multiregional input-output (RUBMRIO) model is used by several integrated land use and transportation models (ILUTMs) to forecast commodity flows in a region and for spatial allocation of production activities. It makes use of multiregional input-output models which are based on random utility theory. In this work, we use optimal control techniques to find optimal final demand and transportation costs of a RUBMRIO model, that would lead to a desired level of commodity flow and production costs. At first, the RUBMRIO model is formulated as a discrete time dynamical system. It is shown, using Lyapunov argument, that the fixed point of the dynamical system is input-to-state stable (ISS). Then, a discrete time optimal control problem is formulated with states as commodity flows and production costs, and the final demand and transportation costs as control inputs. An optimization problem is then solved to obtain control inputs that would lead to desired commodity flows and production costs.Further, the proposed methodology is applied to a numerical example. It is shown that the optimal control based method can achieve user specified commodity flows and production costs up to an acceptable accuracy level.

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The Introduction of Dynamic Features in a Random-Utility-Based Multiregional Input-Output Model of Trade, Production, and Location Choice

Abstract: This study introduces dynamic features into the random-utility-based multiregional input-output

Cited by 5 publications

References 13 publications

Impact of Introducing Longer and Heavier Vehicles on Regional Consumer Price Index and Spanish Road Freight Transport System

Impact of Introducing Longer and Heavier Vehicles on Regional Consumer Price Index and Spanish Road Freight Transport System

Local Sensitivity Analysis of Forecast Uncertainty in a Random-Utility-Based Multiregional Input-Output Model

Inverse identification of inputs of a random utility based model using optimal control

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