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TRANUS-J: Putting Large Models into Small Computers

Author

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  • T de la Barra
  • B Pérez
  • N Vera

Abstract

Traditionally, large integrated land-use and transport models require considerable amounts of computer resources, restricting their use to a small number of metropolitan or regional planning authorities and to an elite of consultancy firms. The increasing availability of microcomputers should be able to extend the use of models to a much larger community of planners. However, even the most efficient packages existing today cannot be fitted into the standard desk-top machines. The purpose of this paper is to describe a package for land-use and transport simulation for microcomputers, showing that this is not only possible, but also that there is no need to sacrifice detail or accuracy. Furthermore, the need to produce highly compact and efficient models has forced the research team to look for completely new algorithms and even new theoretical developments. In designing the models, economy of resources was also extended to data requirements, calibration, and evaluation, and considerable attention was devoted to making the models easy to handle and the results easy to interpret. The authors begin by describing the theoretical base of the models, briefly covering random utility, decision chains, and hierarchies. Next, a summary of the mathematical formulation is presented, finishing with a description of the operative characteristics of the computer programs and complementary features.

Suggested Citation

  • T de la Barra & B Pérez & N Vera, 1984. "TRANUS-J: Putting Large Models into Small Computers," Environment and Planning B, , vol. 11(1), pages 87-101, March.
  • Handle: RePEc:sae:envirb:v:11:y:1984:i:1:p:87-101
    DOI: 10.1068/b110087
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    Cited by:

    1. Zhong, Shaopeng & Bushell, Max, 2017. "Built environment and potential job accessibility effects of road pricing: A spatial econometric perspective," Journal of Transport Geography, Elsevier, vol. 60(C), pages 98-109.
    2. Zhong, Shaopeng & Bushell, Max, 2017. "Impact of the built environment on the vehicle emission effects of road pricing policies: A simulation case study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 235-249.
    3. Johnston, Robert A., 1994. "The Evaluation of Multimodal Transportation Systems for Economic Efficiency and Other Impacts," University of California Transportation Center, Working Papers qt4f87125z, University of California Transportation Center.
    4. Tong Wu & Lina Tang & Huaxiang Chen & Ziyan Wang & Quanyi Qiu, 2017. "Application of Source-Sink Landscape Influence Values to Commuter Traffic: A Case Study of Xiamen Island," Sustainability, MDPI, vol. 9(12), pages 1-14, December.
    5. Lefèvre, Benoit, 2009. "Long-term energy consumptions of urban transportation: A prospective simulation of "transport-land uses" policies in Bangalore," Energy Policy, Elsevier, vol. 37(3), pages 940-953, March.
    6. Johnston, Robert A. & de la Barra, Tomas, 2000. "Comprehensive regional modeling for long-range planning: linking integrated urban models and geographic information systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(2), pages 125-136, February.
    7. Zhong, Shaopeng & Wang, Shusheng & Jiang, Yao & Yu, Bo & Zhang, Wenhao, 2015. "Distinguishing the land use effects of road pricing based on the urban form attributes," Transportation Research Part A: Policy and Practice, Elsevier, vol. 74(C), pages 44-58.

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