Abstract
Travel surveys in cities remain the main source of information for obtaining people’s trip characteristics and developing transport models that serve to predict the performance indicators of transport systems. Despite the large number of travel surveys that have been conducted, there is still no universal methodology for survey design and no strict instructions for choosing a certain methodology for a particular case. Moreover, existing guidelines for sample size definition do not provide any estimates of the accuracy of obtained results. A new approach is proposed for determining the number of sample observations necessary for obtaining travel characteristics—such as travel time or distance—with a given precision. It takes into account the probabilistic nature of sample estimates and does not depend on the trip characteristic being studied. An example of the application of this approach demonstrated that existing guidelines for sample size definition allow trip characteristics to be defined with an error of 20–40%. Additionally, it was determined that while maintaining an average error below 30%, there is a possibility to decrease the required number of observations by up to 56% compared to the number recommended in the Handbook of Transport Modelling (HTM). The study also shows that it is possible to significantly decrease the sample size when the distribution law of the trip characteristic being investigated is known. Another outcome of the study was a substantiated reference size for a pilot survey sample.
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References
Ahrens, G.A.: Travel Behaviour Survey and Modal Split Analysis—City of Pardubice (Central MeetBike proj. rep.) (2013)
Ahrens, G.A., Wittwer, R., Hubrich, S., Wittig, S., Ließke, F., 2015. Mobilität in Städten—SrV 2013: Stadtgruppe: Große, SrV-Vergleichsstädte (Sonderauswertung zum Forschungsprojekt). https://tu-dresden.de/bu/verkehr/ivs/srv/ressourcen/dateien/2013/uebersichtsseite/SrV2013_Stadtgruppe_GrosseSrV-Vergleichsstaedte.pdf?lang=en.
Aultman-Hall, L. Dowds, J.: Designing the All-in-One Vermont Transportation Survey (Final Rep.) (2017). https://www.uvm.edu/sites/default/files/media/UVM-TRC-17-004.pdf.
Australian Transport Assessment and Planning (ATAP): Australian Transport Assessment and Planning Guidelines. (2016) https://www.atap.gov.au/tools-techniques/travel-demand-modelling/files/T1_Travel_Demand_Modelling.pdf.
Axhausen, K.W., Schmid, B.: Predicting response rates of all and recruited respondents: A first attempt. Transport Findings (2019). https://transportfindings.org/article/7827-predicting-response-rates-of-all-and-recruited-respondents-a-first-attempt.
Basarić, V., Vujičić, A., Mitrović-Simić, J., Bogdanović, V., Saulić, N.: Gender and age differences in the travel behaviora—Novi Sad case study. Transp. Res. Procedia 14, 4324–4333 (2016)
Berggren, U., Johnsson, C., Svenssona, H., Wretstrand, A.: Exploring waiting times in public transport through a semi-automated dedicated smartphone app survey. Travel Behav. Soc. 15, 1–14 (2019)
Bhat, C., Sen, S.: Household vehicle type holdings and usage: an application of the multiple discrete-continuous extreme value (MDCEV) model. Transp. Res. Part B Methodol. 40, 35–53 (2006)
Bolbol, A., Cheng, T., Tsapakis, I., Chow, A.: Sample size calculation for studying transportation modes from GPS data. Proc. Soc. Behav. Sci. 48, 3040–3050 (2012)
Bonnel, P., Munizaga, M.A.: Transport survey methods—in the era of big data facing new and old challenges. Transp. Res. Procedia 32, 1–15 (2018). https://www.sciencedirect.com/science/article/pii/S2352146518301522.
Cools, M., Moons, E., Wets, G.: Assessing the quality of origin-destination matrices derived from activity travel surveys: results from a monte carlo experiment. Transp. Res. Rec. 2183(1), 49–59 (2010). https://doi.org/10.3141/2183-06
Department of Economic and Social Affairs of the United Nations Secretariat (DESA UNS): Household Sample Surveys in Developing and Transition Countries (U. N. Publication Ser. F No. 96). (2005) https://unstats.un.org/unsd/hhsurveys/pdf/Household_surveys.pdf.
Evans, J.: NCHRP 716 Travel demand forecasting: parameters and techniques. presentation to north carolina model users group meeting. (2015) https://connect.ncdot.gov/projects/planning/TPB%20Model%20User%20Groups/NCMUG_2015Apr29_Presentation_1_NCHRP_Report716_JayEvans_CSI_Apr15.pdf.
Federal State Statistic Service (FSSS): Meтoдoлoгичecкиe paзpaбoтки Poccтaтa [The Rosstat Methodology]. (2010). https://www.gks.ru/bgd/free/meta_2010/Main.htm.
Forbes, C., Evans, M., Hastings, N., Peacock, B.: Statistical Distributions, 4th edn. Wiley, Hoboken, NJ (2011)
Gnedenko, B.V., Ushakov, I.A.: Probabilistic Reliability Engineering, Falk, J.A. (Ed.). Wiley, New York (1995).
Gnedenko, B.V., Belyayev, Yu.K., Solovyev, A.D.: Mathematical Methods of Reliability Theory, Birnbaum, Z.W., Lukacs, E. (Ed.). Academic Press, New York, London (1969). https://doi.org/https://doi.org/10.1016/C2013-0-12300-8.
Golob, T.F., Wissen, L.: A joint household travel distance generation and car ownership model. Transp. Res. Part B: Methodological 23, 471–491 (1989)
Griffiths, R., Richardson, A.J., Lee-Gosselin, M.E.H., 2000, January. Travel Surveys. Paper presented at the Transportation Research Board Standing Committees “Transportation in the New Millennium: State of the Art and Future Directions”, Washington, DC. http://onlinepubs.trb.org/onlinepubs/millennium/00135.pdf.
Habib, K.N., El-Assi, W.: How Large is too Large? The Issue of Sample Size Requirements of Regional Household Travel Surveys, the Case of the Transportation Tomorrow Survey in the Greater Toronto and Hamilton Area. Paper presented at the 95th Annual Meeting of Transportation Research Board, Washington, DC (2016) https://www.researchgate.net/publication/284452108_How_Large_is_too_Large_The_Issue_of_Sample_Size_Requirements_of_Regional_Household_Travel_Surveys_the_Case_of_the_Transportation_Tomorrow_Survey_in_the_Greater_Toronto_and_Hamilton_Area.
Handbook of transport modelling (HTM). In: D.A. Hensher & K.J. Button (Ed.). Pergamon, Amsterdam, New York (2005).
Hess, S., Daly, A., Dekker, T., Cabral, O.C., Batley, R.: A framework for capturing heterogeneity, heteroskedasticity, non-linearity, reference dependence and design artefacts in value of time research. Transp. Res. Part B Methodol. 96, 126–149 (2017)
Horbachov, P., Svichynskyi, S.: Dependence of trip length frequency distribution on characteristics of route network elements. Arch. Transp. 30(2), 21–30 (2014). https://doi.org/10.5604/08669546.1146974
Horbachov, P., Svichynskyi, S.: Theoretical substantiation of trip length distribution for home-based work trips in urban transit systems. J. Transp. Land Use 11(1), 593–632 (2018). https://doi.org/10.5198/jtlu.2018.916
Kish, L.: Survey Sampling. Wiley, New York, London (1965)
Kolmogorov, A.N.: Foundations of the Theory of Probability. Chelsea Publishing Company, New York (1956)
Kulpa, T., Szarata, A.: Analysis of household survey sample size in trip modelling process. Transp. Res. Procedia 14, 1753–1761 (2016)
Kurth, D., & Rossi, T., 2012. NCHRP 8–61 Travel Demand Forecasting: Parameters and Techniques. Presentation to Tennessee Model Users Group, Knoxville. http://web.utk.edu/~tnmug08/misc/2012/NCHRP_TNMug.pdf.
Lagutin, M.B.: Haгляднaя мaтeмaтичecкaя cтaтиcтикa [Visual Mathematical Statistics], 2nd edn. BINOM Knowledge Laboratory, Moscow (2009)
McGuckin, N.: Trips, Chains, and Tours—Using an Operational Definition. Paper presented at the FHWA and the NHTS Conference, Washington, DC, USA. (2004) http://www.trb.org/conferences/nhts/mcguckin.pdf.
Molenberghs, G.: Survey Methods & Sampling Techniques. Leuven: The Centre for Sociological Research at the KU Leuven (2010). https://soc.kuleuven.be/ceso/historischedemografie/resources/pdf/ML/survey10.pdf.
Mooney, R., Healy, S., Dulat, E., 2018. National Household Travel Survey 2017 (Final Rep.). https://www.nationaltransport.ie/wp-content/uploads/2019/01/National_Household_Travel_Survey_2017_Report_-_December_2018.pdf.
Morency, C., 2014. Recent development and analysis on Household Travel Surveys, Quebec. Presentation at the Toronto Workshop “Mobilité”. https://uttri.utoronto.ca/files/2014/10/6-Morency-Recent-development-and-analysis-on-Household-Travel-Surveys-in-Quebec.pdf.
Morency, C., & Valiquette, F.: Trip chaining and its impact on travel behaviour. Paper presented at the 12th World Conference on Transp. Res. Soc. (WCTRS), Lisbon, Portugal. (2010) http://www.wctrs-society.com/wp-content/uploads/abstracts/lisbon/selected/02499.pdf.
National Academies of Sciences, Engineering, and Medicine (NASEM): Travel Demand Forecasting: Parameters and Techniques. The Natl. Acad. Press, Washington, DC, (2012) https://doi.org/https://doi.org/10.17226/14665.
National Household Travel Survey (NHTS): U.S. Department of Transportation, Federal Highway Administration. (2009) Retrieved from http://nhts.ornl.gov.
National Household Travel Survey Analysis Package (NHTSAP), 2010. Whitehouse Group Inc., Fort Lauderdale, FL, USA.
Ortuzar, J.D., Willumsen, L.G.: Modelling Transport, 4th edn. Wiley, Chichester (2011)
Ramachandran, K.M., Tsokos, C.P.: Mathematical Statistics with Applications. Elsevier, London, UK (2015)
Richardson, A., Ampt, E.S., Meyburg, A.H.: Survey Methods for Transport Planning. Eucalyptus, Parkville, Vic (1995)
Roddis, S., Winter, S., Zhao, F., Kutadinata, R.: Respondent preferences in travel survey design: An initial comparison of narrative, structured and technology-based travel survey instruments. Travel Behaviour and Society 16, 1–12 (2019). Paper available at https://www.sciencedirect.com/science/article/pii/S2214367X18301108.
Sacramento area council of governments (SACOG), 2018. Sacramento regional transportation study (Analysis Rep.). https://www.sacog.org/sites/main/files/file-attachments/sacramento_regional_transportation_study_2018.pdf?1547157602.
Schiffer, R.G., Yuan, Q., 2012. Transferable Model Parameters: NCHRP 8–61 and NCHRP 8–84. Presentation to Southeast Florida Model Users Group. http://www.fsutmsonline.net/images/uploads/southeastfloridafsutms/NCHRP_8-61_8-84_SEFUG_6-1-12x.pdf.
Seo, T., Kusakabe, T., Goto, H., Asakura, Y.: Interactive online machine learning approach for activity-travel survey. Transp. Res. Part B Methodol 123, 362–373 (2019)
Sevarts, P., 2007. The Dutch Travel Survey. Presentation of the AVV Transport Research Centre, Finnish Transport Infrastructure Agency. https://vayla.fi/documents/20473/149651/The_Dutch_Travel_Survey.pdf.
Sherman, L.: Household Surveys, Trip Purposes, and Travel Time. (2016) https://hapaforhayward.files.wordpress.com/2016/09/hd-surveys-trip-purposes-travel-time.docx.
Smith, M.E.: Design of small-sample home-interview travel surveys. Transp. Res. Record 701, 29–35 (1979)
Stopher, P., Wilmot, C., Stecher, C., Alsnih, R., 2003. Standards for household travel surveys-some proposed ideas. Paper presented at the 10th International Conference on Travel Behavior Research, Lucerne, Switzerland. https://pdfs.semanticscholar.org/2b16/d9afd65ad4c63e470d31842237f718cd71ef.pdf.
Stopher, P.R., Kockelman, K., Greaves, S.P., Clifford, E.: Reducing burden and sample sizes in multi-day household Travel surveys. Transp. Res. Record 2064, 12–18 (2008). https://doi.org/10.3141/2064-03
Sturgess, H.A.: The choice of classic intervals. J. Am. Stat. Assoc. 21(153), 65–66 (1926)
Sun, L., Axhausen, K.W.: Understanding urban mobility patterns with a probabilistic tensor factorization framework. Transp. Res. Part B: Methodological 91, 511–524 (2016)
National Research Center (NRC), 2007. Trip Diary Survey of Community Travel Patterns (Rep. of Results). https://www.flagstaff.az.gov/DocumentCenter/View/6402/Flagstaff-Trip-Diary-Survey-2006?bidId=.
National Research Center (NRC), 2018. Flagstaff Trip Diary Survey of Community Travel Patterns (Rep. of Results). https://www.flagstaff.az.gov/DocumentCenter/View/60331/Flagstaff-Trip-Diary-Survey---2018.
Cambridge Systematics (CS): Travel Survey Manual (TMIP Rep. FHWA-PL-96–029). (1996) https://trid.trb.org/view/465304.
Texas Transportation Institute (TTI), 2012. Positive Feedback: Exploring Current Approaches in Iterative Travel Demand Model Implementation (Rep. No. FHWA/TX-12/0–6632–1). https://texashistory.unt.edu/ark:/67531/metapth281765/m2/1/high_res_d/txcs-0007.pdf.
Transportation Research Board (TRB), 2008. Standardized procedure for personal travel surveys (NCHRP Rep. 571). DOI: https://doi.org/10.17226/13805.
Transportation Research Board (TRB), 2014. Analytical Travel Forecasting Approaches for Project-Level Planning and Design (NCHRP Rep. 765). http://www.trb.org/Publications/Blurbs/170900.aspx.
National Household Travel Survey (NHTS), 2017. U.S. Department of Transportation, Federal Highway Administration. Retrieved from http://nhts.ornl.gov.
Wittwer, R., Hubrich, S.: Nonresponse in household surveys: A survey of nonrespondents from the repeated cross-sectional study “Mobility in Cities – SrV” in Germany. Transp. Res. Procedia 11, 66–84 (2015). https://www.sciencedirect.com/science/article/pii/S2352146515002987?via%3Dihub.
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Horbachov, P., Makarichev, O., Svichynskyi, S. et al. Framework for designing sample travel surveys for transport demand modelling in cities. Transportation 49, 115–136 (2022). https://doi.org/10.1007/s11116-021-10168-6
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DOI: https://doi.org/10.1007/s11116-021-10168-6