Transactions on Transport Sciences 2021, 12(2):5-15 | DOI: 10.5507/tots.2021.016

Household travel survey method for vehicle kilometers travel estimations: A case study in a developing country

Sarala Gunathilakaa, Niranga Amarasinghaa, Sunanda Dissanayakeb, Malika Lakmalic
a Department of Civil Engineering, Sri Lanka Institute of Information Technology, New Kandy Road, Malabe, Sri Lanka.
b Department of Civil and Environmental Engineering, Kennesaw State University, USA.
c Faculty of Humanities & Sciences, Sri Lanka Institute of Information Technology, New Kandy Road, Malabe, Sri Lanka.

Vehicle Kilometers Travelled (VKT) represents number of kilometers travelled by vehicles during a specific period of time in a specific area of concern. Transportation planners, policy makers, urban planners, and estimators of vehicle emission, energy consumption and fuel-price encourage the calculation of VKT for various analytical purposes. However, in most of the developing countries VKT is not estimated due to data challenges. This study aimed at proposing a household travel survey method for estimating VKT in developing countries where timely VKT data are not available. Also, estimating Personal Kilometers Travelled (PKT) seems important in developing countries, since the majority is using public and non-motorized transport modes rather than personal vehicles in those countries. This proposed method allows to collect data that are needed for estimating both VKT and PKT together with socio demographic information. A case study was conducted in three different regions; Northern, Eastern and Southern areas of Sri Lanka, which is a developing country. Questions were asked regarding to trips in a typical week, trips in holidays, special seasons or vacations, number of passengers travelled, travel modes and, socio demography of the respondent. Pilot surveys were conducted prior to the actual surveys to verify the efficiency of developed questionnaire. Samples were taken satisfying all the selected socio demographic categories within the community. Collected data through surveys were aggregated to annual level and, weighted using relevant census and population data. Weighted VKT and PKT estimates were obtained under each selected socio demographic category. Also, VKT estimates were statistically compared for studying the travel behavior of people across different regions. ANOVA and Post Hoc tests were employed for statistical comparisons. These findings can efficiently be used for transport planning, policy making activities, emission calculations, energy consumption estimations etc. by transport and environmental agencies of the country. The case study revealed the experience of utilizing the household travel survey method in Sri Lanka, making it possible to be replicated in other developing countries as well.

Keywords: Vehicle Kilometers Travelled; Developing Countries; Household Travel Survey; Personal Kilometers Travelled; Transportation Planners.

Received: April 19, 2021; Revised: June 16, 2021; Accepted: July 12, 2021; Prepublished online: July 12, 2021; Published: November 16, 2021  Show citation

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Gunathilaka, S., Amarasingha, N., Dissanayake, S., & Lakmali, M. (2021). Household travel survey method for vehicle kilometers travel estimations: A case study in a developing country. Transactions on Transport Sciences12(2), 5-15. doi: 10.5507/tots.2021.016
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References

  1. Abdi, H., & Williams, L.J. (2010). Tukey's Honestly Significant Difference (HSD) Test. In Neil Salkind (Ed.), Encyclopedia of Research Design, Thousand Oaks, CA: Sage.
  2. Amarasingha, N., & Balasayanthan, V. (2018). Travel Characteristics and Vehicle Kilometers Travelled in Jaffna, Sri Lanka. Proceeding of the 6th International Symposium on Advances in Civil and Environmental Engineering Practices for Sustainable Development (ACEPS), 15 Mar., Galle, Sri Lanka.
  3. Ayuso, M., Guillén, M., & Marìn, A.M.P. (2016). Using GPS data to analyze the distance travelled to the first accident at fault in pay-as-you-drive insurance. Transportation Research Part C, 68, 160-167.Bajracharaya, I., & Bhattarai, N. (2016). Road Transportation Energy Demand and Environmental Emission: A Case of Kathmandu Valley. Hydro Nepal, 18. Go to original source...
  4. Bajracharaya, I., & Bhattarai, N. (2016). Road Transportation Energy Demand and Environmental Emission: A Case of Kathmandu Valley. Hydro Nepal, 18. Go to original source...
  5. Bansal, P., Kockelman, K. M., Schievelbein, W., & Schauer-West, S. (2018). Indian vehicle ownership and travel behaviour: A case study of Bengaluru, Delhi and Kolkata. Research in Transportation Economics, 71, 2-8. Go to original source...
  6. Bäumer, M., Hautzinger, H., Kuhnimhof, T., & Pfeiffer, M. (2018). The German Vehicle Mileage Survey 2014: Striking the balance between methodological innovation and continuity. Transportation Research Procedia, 32, 329-338. Go to original source...
  7. Black, K. (2009). Business Statistics: Contemporary Decision Making. The 6th edition, John Wiley & Sons.
  8. Boarnet, M.G., Burinskiy, E., Deadrick, L., Gullen, D., & Ryu, N. (2017). The Economic Benefits of Vehicle Miles Travelled (VMT) - Reducing Placemaking: Synthesizing a New View, A National Center for Sustainable Transportation Research Report.
  9. Cervero, R., & Murakami, J. (2010). Effects of built environments on vehicle miles travelled: evidence from 370 US urbanized areas. Environmental and Planning A 2010, 42, 400-418. Go to original source...
  10. Chi, G., & Stone, B. (2005). Sustainable Transport Planning: Estimating the Ecological Footprint of Vehicle Travel in Future Years. Journal of Urban Planning and Development, 131(3), 170-180. Go to original source...
  11. Choi, K., Jiao, J., & Zhang, M. (2017). Reducing Vehicle Travel for the Next Generation: Lessons from the 2001 and 2009 National Household Travel Surveys. Journal of Urban Planning and Development, 143(4): 04017017. Go to original source...
  12. Choo, S., Mokhtarian, P.L., & Salomon, I. (2005). Does telecommuting reduce vehicle-miles travelled? An aggregate time series analysis for the U.S. Transportation, 32, 37-64. Go to original source...
  13. Fu, M., Kelly, A., & Clinch, P. (2017). Estimating annual average daily traffic and transport emissions for a national road network: A bottom-up methodology for both nationally-aggregated and spatially-disaggregated results. Journal of Transport Geography, 58, 186-195. Go to original source...
  14. Henao, A., & Marshall, W.E. (2019). The impact of ride-hailing on vehicle miles travelled. Transportation, 46(6), 2173-2194. Go to original source...
  15. Hou, C., Wang, H., & Ouyang, M. (2013). Survey of daily vehicle travel distance and impact factors in Beijing. 7th IFAC Symposium on Advances in Automotive Control, September 4-7, Tokyo, Japan. Go to original source...
  16. Hu, L., & He, S. Y. (2016). Association between Telecommuting and Household Travel in the Chicago Metropolitan Area. Journal of Urban Planning and Development, 04016005. Go to original source...
  17. Huo, H., Zhang, Q., He, K., Yao, Z., & Wang, M. (2012). Vehicle - use intensity in China: Current status and future trend. Energy Policy, 43, 6-16. Go to original source...
  18. Jamal, S., Habib, M.A., & Khan, N.A. (2017). Does the Use of Smartphone Influence Travel Outcome? An Investigation on the Determinants of the Impact of Smartphone Use on Vehicle Kilometers Travelled. Transportation Research Procedia, 25C, 2694-2708. Go to original source...
  19. Jamroz, K., & Wachnicka, J. (2018). Macro Models of Vehicle Kilometres Travelled. Gdansk University of Technology, Poland.
  20. Jung, S., Kim, J., Kim, J., Hong, D., & Park, D. (2017). An estimation of vehicle kilometer travelled and on-road emissions using the traffic volume and travel speed on road links in Incheon City. Journal of Environmental Sciences. Go to original source...
  21. Kim, J. (2015). Vehicle fuel-efficiency choices, emission externalities, and urban sprawl. Economics of Transportation, Article in Press. Go to original source...
  22. Krebs, C.J. (2013). Chapter 07 Sampling and experimental design. ver.4, University of British Columbia.
  23. Li, Z., Jiang, S., Dong, J., Wang, S., Ming, Z., & Li, L. (2016). Battery capacity design for electric vehicles considering the diversity of daily vehicle miles travelled. Transportation Research Part C, 72, 272-282. Go to original source...
  24. Majid, M.R., Nordin, A.N., & Medugu, I.N. (2014). Influence of housing development designs on household vehicle miles travelled: A case of Iskandar Malaysia. Transportation Research Part D, 33, 63-73. Go to original source...
  25. Mendes, M., & Akkartal, E. (2010). Comparison of ANOVA F and WELCH Tests with Their Respective Permutation Versions in Terms of Type I Error Rates and Test Power. Kafkas Univ Vet Fak Derg,16(5), 711-716.
  26. Munyon, V.V., Bowen, W.M., & Holcombe, J. (2018). Vehicle fuel economy and vehicle miles travelled: An empirical investigation of Jevon's Paradox. Energy Research and Social Science, 38, 19-27. Go to original source...
  27. Noland, R. B., & Cowart, W.A. (2000). Analysis of Metropolitan Highway Capacity and the growth in vehicle miles of travel. Transportation, 27, 363-390. Go to original source...
  28. Osama, A., Sayed, T., & Bigazzi, A.Y. (2017). Models for estimating zone-level bike kilometers travelled using bike network, land use and, road facility variables. Transportation Research Part A, 96, 14-28. Go to original source...
  29. Rafter, J.A., Abell, M.L., & Braselton, J.P. (2002). Multiple Comparison Methods for Means. Society for Industrial and Applied Mathematics, 44, 2, 259-278. Go to original source...
  30. Renne, J.L., & Tolford, T. (2018). A planning tool for evaluating vehicles miles travelled and traffic safety forecasts of growth management scenarios: A case study of Baton Rouge and New Orleans. Transportation Research Part D, 59, 237-245. Go to original source...
  31. Small, K.A. (2012). Valuation of travel time. Economics of Transportation, 1, 2-14. Go to original source...
  32. Seethaler, R., & Rose, G. (2009). Using odometer readings to assess VKT changes associated with a voluntary travel behavior change program. Transport Policy, 16, 325-334. Go to original source...
  33. Starkey, P., & Hine, J. (2014). Poverty and sustainable transport: How transport affects poor people with policy implications for poverty reduction. UN-Habitat, Overseas Development Institute, SLoCaT.
  34. Sullivan, L. (2019). Hypothesis Testing-Analysis of Variance (ANOVA), Boston University School of Public Health. Retrieved from http://sphweb.bumc.bu.edu/otlt/MPHModules/BS/BS704_HypothesisTestingANOVA/BS704_HypothesisTesting-Anova_print.html.
  35. Tirachini, A. & Gómez-Lobo, A. (2020). Does ride-hailing increase or decrease vehicle kilometers travelled (VKT)? A simulation approach for Santiago de Chile. International Journal of Sustainable Transportation, 14(3), 187-204. Go to original source...
  36. Weerasekera, T.D., & Amarasingha, N. (2017). Estimation of vehicle kilometers travelled in southern province, Sri Lanka. 6th National Conference on Technology and Management (NCTM), Malabe, 40-45. Go to original source...
  37. Williams, T.A., Chigoy, B., Borowiec, J., & Glover, B. (2016). Methodologies Used to Estimate and Forecast Vehicle Miles Travelled (VMT): Final Report. Policy Research Center, Texas A & M Transportation Institute.
  38. Yoshimoto, R., & Nemoto, T. (2005). The impact of information and communication technology on road freight transportation. the computerization of transportation: Sophisticated Systems Incorporating IT in the Mobility of People and Goods, IATSS Research, 29 (1), 16-21. Go to original source...

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