JTLU Volume 4, No. 1 (2011)

Persistent link for this collection

https://hdl.handle.net/11299/170171
Table of Contents:
  • Introduction: The Journal of Transport and Land Use Enters Year Four, pp. 1-3
  • Agglomeration economies, accessibility, and the spatial choice behavior of relocating firms, pp. 5-24
  • ‘New urbanism’ or metropolitan-level centralization? A comparison of the influences of metropolitan-level and neighborhood-level urban form characteristics on travel behavior, pp. 25-44
  • An application of the node place model to explore the spatial development dynamics of station areas in Tokyo, pp. 45-58
  • Defining land use intensity based on roadway level-of-service targets, pp. 59-69
  • Impacts of ethanol plants on highway networks , pp. 71-81
  • Book Review: Gridlock: Why We're Stuck in Traffic and What to Do About It, pp. 83-85

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    Browsing JTLU Volume 4, No. 1 (2011) by Subject "Transportation"

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      Defining land use intensity based on roadway level of service targets
      (Journal of Transport and Land Use, 2011) Iravani, Hamid; Mirhoseini, Arash; Rasoolzadeh, Maziar
      Traditionally, master planners develop an initial land use scenario for an undeveloped site, which is then forwarded to transportation planners for modeling purposes. On the basis of travel demand forecast, several alternatives are provided to master planners and, accordingly, different land use proposals are examined until, finally, a preferred option is chosen. Such trial and error process is inherently cumbersome, time consuming and an optimal outcome is rarely achieved. Usually, by increasing land use intensity, roads will be overly congested, beyond acceptable levels, and under-utilized when lower levels of land use intensity is planned. Hence, defining optimum land use intensity to target traffic level of service on roads is never achieved. The aim of this paper is to introduce an innovative approach, based on a “reverse engineering” process, to define final land use intensity based on desired target volume on roads. This method significantly reduces the number of model runs required for “what if” analysis. It also brings the results of travel demand forecast models closer to the desired outcome.
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      Impacts of ethanol plants on highway networks
      (Journal of Transport and Land Use, 2011) Mitra, Subhor; Dybing, Alan; Tolliver, Denver
      This paper describes the impacts of the ethanol industry on existing highway infrastructure in the vicinity of an ethanol production plant. To determine the impacts of plant location, the corn and soybean draw areas are estimated on the basis of crop prices. Crop production data are extracted from satellite imagery of the crop data layer produced by National Agricultural Statistics Service and the United States Department of Agriculture. The increase in truck traffic attributable to the ethanol plant is estimated for the changed flow of feedstock. A model is run for two scenarios: i) existing corn and soybean production; and, ii) increased corn and soybean production. Based on existing pavement condition and incremental traffic changes, the funds required to maintain the affected roads at their present service levels are quantified.