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Evaluation of transfer methods for spatial travel demand models

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  • Karasmaa, Nina

Abstract

The main goal of the research was to compare alternative methods of spatial transfer as a function of sample size. The study was based on the mobility surveys conducted in the Helsinki Metropolitan Area in 1995 and in the Turku region in 1997. The Helsinki Metropolitan Area data base was used to estimate the models that were to be transferred. The data base in the Turku region represents the application context to which the estimated Helsinki Metropolitan Area models are transferred. The transfer procedures examined were Bayesian updating, combined transfer estimation, transfer scaling, and joint context estimation procedures. To explore the impact of sample size on transferring performance, model transferability was tested using six different sample sizes. The model transferability was examined by comparing the transferred models to the models estimated using the entire set of the data which can be regarded as the best estimate representing "the real situation". The results indicated that joint context estimation gives the best prediction performance in almost all cases. In particular, the method is useful if the difference in the true parameters between the two contexts is large or only some of the model coefficients are precise. The applicability of joint context estimation can be improved by viewing the coefficients as variable-oriented and emphasizing precise and imprecise coefficients differently.

Suggested Citation

  • Karasmaa, Nina, 2007. "Evaluation of transfer methods for spatial travel demand models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(5), pages 411-427, June.
    • Handle: RePEc:eee:transa:v:41:y:2007:i:5:p:411-427
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    References listed on IDEAS

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    1. McCarthy, Patrick S., 1982. "Further evidence on the temporal stability of disaggregate travel demand models," Transportation Research Part B: Methodological, Elsevier, vol. 16(4), pages 263-278, August.
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    1. Balla, Bhavani Shankar & Sahu, Prasanta K., 2023. "Assessing regional transferability and updating of freight generation models to reduce sample size requirements in national freight data collection program," Transportation Research Part A: Policy and Practice, Elsevier, vol. 175(C).
    2. Agnivesh Pani & Prasanta K. Sahu & Furqan A. Bhat, 2021. "Assessing the Spatial Transferability of Freight (Trip) Generation Models across and within States of India: Empirical Evidence and Implications for Benefit Transfer," Networks and Spatial Economics, Springer, vol. 21(2), pages 465-493, June.
    3. Franco Chingcuanco & Eric Miller, 2014. "A meta-model of vehicle ownership choice parameters," Transportation, Springer, vol. 41(5), pages 923-945, September.
    4. Chenfeng Xiong & Di Yang & Jiaqi Ma & Xiqun Chen & Lei Zhang, 2020. "Measuring and enhancing the transferability of hidden Markov models for dynamic travel behavioral analysis," Transportation, Springer, vol. 47(2), pages 585-605, April.
    5. Siuhi, Saidi & Mwakalonge, Judith L. & Perkins, Judy, 2013. "Spatial Transferability: Analysis of the Regional Automobile-Specific Household-Level Carbon Dioxide (CO2) Emissions Models," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 52(2).

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