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The development of a policy for road tax in Turkey, using a genetic algorithm approach for demand estimation

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  • Haldenbilen, Soner
  • Ceylan, Halim

Abstract

This study deals, first, with estimation of transport demand based on Genetic Algorithm (GA) approach, and then deals with the evaluation of the road tax system in Turkey. It proposes an alternative road tax policy. The total transport demand is estimated based on population, Gross Domestic Product per Capita (GDPPC), and vehicle-number. Three forms of the Genetic Algorithm Transport Demand Estimation for Tax Revenues (GATDETR) are developed, of which one is linear, and the second and third are exponential forms of the mathematical expressions. The best-fit GATDETR model in terms of total minimum relative average errors between observed and estimated values are selected for future demand estimation. The evaluation of the road tax system and policy proposal is made based on estimated demand. The Distance-Based-Taxation (DBT) system is proposed in order to control highway transport. With the DBT system, some road users may wish to use railway. Thus, we re-organize the railways in order to meet the demand, but this requires new fund. The DBT system may help to create to this fund. It may also help to develop fair-taxation for the road users. Results show that the GA can be used to model transport demand and hence income tax in future transports planning. This study also suggests that planning the taxation in highway transport may help to ease funding problem of railway system.

Suggested Citation

  • Haldenbilen, Soner & Ceylan, Halim, 2005. "The development of a policy for road tax in Turkey, using a genetic algorithm approach for demand estimation," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(10), pages 861-877, December.
    • Handle: RePEc:eee:transa:v:39:y:2005:i:10:p:861-877
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    References listed on IDEAS

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    1. Ozturk, Harun Kemal & Ceylan, Halim & Hepbasli, Arif & Utlu, Zafer, 2004. "Estimating petroleum exergy production and consumption using vehicle ownership and GDP based on genetic algorithm approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 8(3), pages 289-302, June.
    2. Haldenbilen, Soner & Ceylan, Halim, 2005. "Genetic algorithm approach to estimate transport energy demand in Turkey," Energy Policy, Elsevier, vol. 33(1), pages 89-98, January.
    3. Ceylan, Halim & Bell, Michael G. H., 2005. "Genetic algorithm solution for the stochastic equilibrium transportation networks under congestion," Transportation Research Part B: Methodological, Elsevier, vol. 39(2), pages 169-185, February.
    4. Ceylan, Halim & Bell, Michael G. H., 2004. "Traffic signal timing optimisation based on genetic algorithm approach, including drivers' routing," Transportation Research Part B: Methodological, Elsevier, vol. 38(4), pages 329-342, May.
    5. Hensher, David A. & Houghton, Erne, 2004. "Performance-based quality contracts for the bus sector: delivering social and commercial value for money," Transportation Research Part B: Methodological, Elsevier, vol. 38(2), pages 123-146, February.
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    1. Ozan, Cenk & Haldenbilen, Soner & Ceylan, Halim, 2011. "Estimating emissions on vehicular traffic based on projected energy and transport demand on rural roads: Policies for reducing air pollutant emissions and energy consumption," Energy Policy, Elsevier, vol. 39(5), pages 2542-2549, May.

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