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An Economic Calibration Method for Fuel Consumption Model in HDM4

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An Erratum to this article was published on 05 August 2016

Abstract

HDM4 developed by Worldbank is the calculation software which is widely used in estimating various costs such as highway construction cost and vehicle operating cost (VOC). The necessary data such as weather condition, traffic volume, running speed, road curvature and road gradient should be input to calculate fuel consumption in HDM4. In conventional HDM4 calibration, calibration factors are determined by the average fuel consumption which has been measured for various vehicles for long period. The vehicles which are released after the calibration factors are determined or those with new technology could be low in terms of fuel consumption. This paper has proposed a fuel consumption testing method for quick and easy determination of the calibration factors in HDM4 VOC calculation. The calibration for the fuel consumption of HDM4 is performed by measuring fuel consumption for round trips on two flat and straight roads at several steady speeds for a short period. By this calibration method the factors for driving resistance ranged from 0.13 to 0.30. Latest cars are lower than HDM4 models in terms of tractive resistance and power loss with more efficient fuel economy. Therefore, it appears that the calibration factors would further decrease over time. In case of HDM4, however, separate calibration factors are not provided for aerodynamic resistance. Therefore, it is reasonable to regard that the difference in aerodynamic resistance has been reflected to the two calibration factors.

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References

  1. Bennett, C. R., & Greenwood, I. D. (2003). Volume 5: HDM-4 calibration reference manual. In ISOHDM World Road Association (PIARC) (pp. 174–181).

  2. Odoki, J. B., & Kerali, H. G. (2000). HDM-4 volume four: Analytical framework and model descriptions. In HDM-4: Highway Development and Management, the Highway Development and Management Series, World Road Association (PIARC) (pp. 245–255).

  3. Hussain, R., Rezaeifar, Z., & Oh, H. (2015). A paradigm shift from vehicular ad hoc networks to VANET-based clouds. Wireless Personal Communications, 83(2), 1131–1158.

    Article  Google Scholar 

  4. Greenwood, D., Dunn, R. C., & Raine, M. R. R. (2007). Estimating the effects of traffic congestion on fuel consumption and vehicle emissions based on acceleration noise. Journal of Transportation Engineering, 133(2), 124–126.

    Article  Google Scholar 

  5. Barrachina, J., Garrido, P., Fogue, M., Martinez, F. J., Cano, J., Calafate, C. T., et al. (2015). A V2I-based real-time traffic density estimation system in urban scenarios. Wireless Personal Communications, 83(1), 259–280.

    Article  Google Scholar 

  6. Kurmis, M., Andziulis, A., Dzemydiene, D., Jakovlev, S., Voznak, M., & Gricius, G. (2015). Cooperative context data acquisition and dissemination for situation identification in vehicular communication networks. Wireless Personal Communications, 85(1), 49–62.

    Article  MATH  Google Scholar 

  7. Lee, S. H., & Kim, Y. S. (2004). Observation of climate change in korea during the past four decades. Journal of Korea Atmospheric Engineering, 506–512.

  8. Hasan, S. F., Siddique, N. H., & Chakraborty, S. (2014). Developments and constraints in 802.11-based roadside-to-vehicle communications. Wireless Personal Communications, 69(4), 1261–1287.

    Article  Google Scholar 

  9. Lecointe, B., & Monnier, G. (2003). Downsizing a gasoline engine using turbocharging with direct injection. Transaction of SAE, Issue 2003-01-0542, 211–222.

  10. Odoki, J. B., & Akena, R. (2008). Energy balance framework for appraising road projects. Proceedings of the ICE Transport, 161(1), 23–35.

    Google Scholar 

  11. Altamira, A., de Solminihac, H., Harrison, R., & Covarrubias, J. P. (2004). Calibration of fuel consumption model in HDM-4 model: An application to observed consumption in Canada and Chile. In Proceedings of transportation research board conference (pp. 124–135).

  12. Bennett, C. R., & Paterson, W. D. O. (2002). Volume V: A guide to calibration and adaptation. HDM-4 Manual (Version 1.3) (pp. 524–529).

  13. Okubo, K., Sato, M., & Xing, J. (2003). Adapting the HDM-4 to expressways in Japan. In Proceedings of XXIInd PIARC world road congress (pp. 524–529).

  14. Jacobsen, R. H., & Mikkelsen, S. A. (2014). Infrastructure for intelligent automation services in the smart grid. Wireless Personal Communications, 76(2), 125–147.

    Article  Google Scholar 

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Correspondence to Byung-Koo Moon.

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Ko, KH., Moon, BK., Lee, TW. et al. An Economic Calibration Method for Fuel Consumption Model in HDM4. Wireless Pers Commun 89, 959–975 (2016). https://doi.org/10.1007/s11277-016-3353-2

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