Skip to main content

Travel Behavior and Demand Analysis and Prediction

  • Reference work entry
  • First Online:
Book cover Complex Dynamics of Traffic Management
  • Originally published in
  • R. A. Meyers (ed.), Encyclopedia of Complexity and Systems Science, © Springer-Verlag 2009

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 279.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 379.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Bibliography

  • Adler T, Ben-Akiva M (1979) A theoretical and empirical model of trip chaining behavior. Transp Res B 13:243–257

    Article  Google Scholar 

  • Alam BS (1998) Dynamic emergency evacuation management system using GIS and spatio-temporal models of behavior. MS Thesis, Department of Civil and Environmnetal Engineering, The Pennsylvania State University, University Park

    Google Scholar 

  • Alam BS, Goulias KG (1999) Dynamic emergency evacuation management system using GIS and spatio-temporal models of behavior. Transp Res Rec 1660:92–99

    Article  Google Scholar 

  • Anas A (1982) Residential location markets and urban transportation: economic theory, econometrics and policy analysis with discrete choice models. Academic, New York

    Google Scholar 

  • Arentze T, Timmermans H (2000) ALBATROSS – a learning based transportation oriented simulation system. European Institute of Retailing and Services Studies (EIRASS), Technical University of Eindhoven, Eindhoven

    Google Scholar 

  • Arentze T, Timmermans H, Janssens D, Wets G (2006) Modeling short-term dynamics in activity-travel patterns: from aurora to feathers. Presented at the innovations in travel modeling conference, Austin, 21–23 May 2006

    Google Scholar 

  • Avineri E, Prashker Y (2003) Sensitivity to uncertainty: the need for a paradigm shift. CD-TRB ROM proceedings, paper presented at the 82nd annual transportation research board meeting, 12–16 January 2003, Washington, DC

    Google Scholar 

  • Becker GS (1976) The economic approach to human behavior. The University of Chicago Press, Chicago

    Book  Google Scholar 

  • Ben-Akiva ME, Lerman SR (1985) Discrete choice analysis: theory and application to travel demand. MIT Press, Cambridge

    Google Scholar 

  • Ben-Akiva ME, Morikawa T (1989) Estimation of mode switching models from revealed preferences and stated intentions. Paper presented at the international conference on dynamic travel behavior at Kyoto University Hall, Kyoto

    Google Scholar 

  • Ben-Akiva M, Bowman JL, Gopinath D (1996) Travel demand model system for the information era. Transportation 23:241–266

    Google Scholar 

  • Ben-Akiva ME, Walker J, Bernardino AT, Gopinath DA, Morikawa T, Polydoropoulou A (2002) Integration of choice and latent variable models. In: Mahmassani HS (ed) In perceptual motion: travel behavior research opportunities and application challenges. Pergamon, Amsterdam

    Google Scholar 

  • Bergstrom TC (1995) A survey of theories of the family. Department of Economics, University of California Santa Barbara, Paper 1995D. http://repositories.cdlib.org/ucsbecon/bergstrom/1995D/

  • Bhat CR (2000) Flexible model structures for discrete choice analysis. In: Hensher DA, Button KJ (eds) Handbook of transport modelling. Pergamon, Amsterdam, pp 71–89

    Google Scholar 

  • Bhat C (2001) A comprehensive and operational analysis framework for generating the daily activity-travel pattern of workers. Paper presented at the 78th annual meeting of the transportation research board, Washington, DC, 10–14 January 2001

    Google Scholar 

  • Bhat CR (2003) Random utility-based discrete choice models for travel demand analysis. In: Goulias KG (ed) Transportation systems planning: methods and applications. CRC Press, Boca Raton, pp 10-1–10-30

    Google Scholar 

  • Bhat CR, Koppelman F (1999) A retrospective and prospective survey of time-use research. Transportation 26(2):119–139

    Article  Google Scholar 

  • Bhat CR, Singh SK (2000) A comprehensive daily activitytravel generation model system for workers. Transp Res A 34(1):1–22

    Article  Google Scholar 

  • Bhat CR, Guo J, Srinivasan S, Sivakumar A (2003) Center for Transportation Research, Austin

    Google Scholar 

  • Bockenholt U (2002) Comparison and choice: analyzing discrete preference data by latent class scaling models. In: Hagenaars JA, McCutcheon AL (eds) Applied latent class analysis. Cambridge University Press, Cambridge, pp 163–182

    Chapter  Google Scholar 

  • Borgers AWJ, Hofman F, Timmermans HJP (1997) Activitybased modelling: prospects. In: Ettema DF, Timmermans HJP (eds) Activity-based approaches to travel analysis. Pergamon, Oxford, pp 339–351

    Google Scholar 

  • Borgers AWJ, Timmermans AH, van der Waerden P (2002) Patricia: predicting activity-travel interdependencies with a suite of choice-based, interlinked analysis. Transp Res Rec 1807:145–153

    Article  Google Scholar 

  • Bowman JL, Bradley M, Shiftan Y, Lawton TK, Ben-Akiva M (1998) Demonstration of an activity-based model system for Portland. Paper presented at the 8th world conference on transport research, Antwerp, June 1998

    Google Scholar 

  • Bradley M, Bowman J (2006) A summary of design features of activity-based microsimulation models for US MPOs. Conference on innovations in travel demand modeling, Austin, 21–23 May 2006

    Google Scholar 

  • Brög W, Erl E (1980) Interactive measurement methods – theoretical bases and practical applications. Transp Res Rec 765:1–6

    Google Scholar 

  • Bryk AS, Raudenbush SW (1992) Hierarchical linear models. Sage, Newberry Park

    Google Scholar 

  • Chandrasekharan B, Goulias KG (1999) Exploratory longitudinal analysis of solo and joint trip making in the Puget Sound transportation panel. Transp Res Rec 1676:77–85

    Article  Google Scholar 

  • Chapin FS Jr (1974) Human activity patterns in the city: things people do in time and space. Wiley, New York

    Google Scholar 

  • Chung J, Goulias KG (1997) Travel demand forecasting using microsimulation: initial results from a case study in Pennsylvania. Transp Res Rec 1607:24–30

    Article  Google Scholar 

  • Creighton RL (1970) Urban transportation planning. University of Illiniois Press, Urbana

    Google Scholar 

  • Cullen I, Godson V (1975) Urban networks: the structure of activity patterns. Progr Plan 4(1):1–96

    Article  Google Scholar 

  • Dijst M, Vidakovic V (1997) Individual action space in the city. In: Ettema DF, Timmermans HJP (eds) Activity-based approaches to travel analysis. Elsevier Science, New York, pp 117–134

    Google Scholar 

  • Dillman DA (2000) Mail and internet surveys: the tailored design method, 2nd edn. Wiley, New York

    Google Scholar 

  • Doherty S (2003) Interactive methods for activity scheduling processes. In: Goulias KG (ed) Transportation systems planning: methods and applications. CRC Press, Boca Raton, pp 7-1–7-25

    Google Scholar 

  • Doherty ST, Noel N, Lee M-G, Sirois C, Ueno M (2001) Moving beyond observed outcomes: global positioning systems and interactive computer-based travel behavior surveys. Transportation research circular, E-C026, March 2001. Transportation Research Board, Washington DC

    Google Scholar 

  • Ettema DF, Timmermans HJP (1997) Activity-based approaches to travel analysis. Elsevier Science, New York, p xiii

    Google Scholar 

  • Ettema DF, Borgers AWJ, Timmermans HJP (1995) Competing risk hazard model of activity choice, timing, sequencing and duration. Transp Res Rec 1439:101–109

    Google Scholar 

  • Ettema DF, Borgers AWJ, Timmermans H (1996) SMASH (simulation model of activity scheduling heuristics): some simulations. Transp Res Rec 1551:88–94

    Article  Google Scholar 

  • Ettema DF, Daly A, de Jong G, Kroes E (1997) Towards an applied activity-based travel demand model. Paper presented at the IATBR conference, Austin, 21–25 September 1997

    Google Scholar 

  • Ettema DF, de Jong K, Timmermans H, Bakema A (2006) PUMA: multi-agent modeling of urban systems. 2006 Transportation Research Board CD-ROM

    Google Scholar 

  • Fellendorf M, Haupt T, Heidl U, Scherr W (1997) PTV vision: activity based demand forecasting in daily practice. In: Ettema DF, Timmermans HJP (eds) Activity-based approaches to travel analysis. Elsevier Science, New York, pp 55–72

    Google Scholar 

  • Fosgerau M (2002) PETRA – an activity-based approach to travel demand analysis. In: Lundquist L, Mattsson L-G (eds) National transport models: recent developments and prospects. Royal Institute of Technology/Springer, Stockholm/Berlin

    Google Scholar 

  • Gärling T, Brannas K, Garvill J, Golledge RG, Gopal S, Holm E, Lindberg E (1989) Household activity scheduling. In: Transport policy, management and technology towards 2001. Selected proceedings of the fifth world conference on transport research, vol 4. Western Periodicals, Ventura, pp 235–248

    Google Scholar 

  • Gärling T, Kwan M, Golledge R (1994) Computational-process modeling of household travel activity scheduling. Transp Res Part B 25:355–364

    Article  Google Scholar 

  • Gärling T, Laitila T, Westin K (1998) Theoretical foundations of travel choice modeling: an introduction. In: Garling T, Laitila T, Westin K (eds) Theoretical foundations of travel choice modeling. Pergamon, Elsevier, Amsterdam, pp 1–30

    Google Scholar 

  • Garrett M, Wachs M (1996) Transportation planning on trial. The clean air act and travel forecasting. Sage, Thousand Oaks

    Book  Google Scholar 

  • Gliebe JP, Koppelman FS (2002) A model of joint activity participation. Transportation 29:49–72

    Article  Google Scholar 

  • Goldstein H (1995) Multilevel statistical models. Edward Arnold, London/New York

    MATH  Google Scholar 

  • Golledge RG, Gärling T (2003) Spatial behavior in transportation modeling and planning. In: Goulias KG (ed) Transportation systems planning: methods and applications. CRC Press, Boca Raton, pp 1–27

    Google Scholar 

  • Golledge RG, Gärling T (2004) Cognitive maps and urban travel. In: Hensher D, Button K, Haynes K, Stopher P (eds) Handbook of transport geography and spatial systems, vol 5. Elsevier, Amsterdam, pp 501–512

    Chapter  Google Scholar 

  • Golledge RG, Stimpson RJ (1997) Spatial behavior: a geographic perspective. Guilford Press, New York

    Google Scholar 

  • Golledge RG, Smith TR, Pellegrino JW, Doherty S, Marshall SP (1985) A conceptual model and empirical analysis of children’s acquisition of spatial knowledge. J Environ Psychol 5(2):125–152

    Article  Google Scholar 

  • Golob TF (2001) Travelbehaviour.com: activity approaches to modeling the effects of information technology on personal travel behaviour, in travel behavior research. In: Hensher D (ed) The leading edge. Elsevier Science/Pergamon, Kidlington/Oxford, pp 145–184

    Google Scholar 

  • Golob TF, McNally M (1997) A model of household interactions in activity participation and the derived demand for travel. Transp Res B 31:177–194

    Article  Google Scholar 

  • Golob TF, Kitamura R, Long L (eds) (1997) Panels for transportation planning: methods and applications. Kluwer, Boston

    Google Scholar 

  • Goodman LA (2002) Latent class analysis: the empirical study of latent types, latent variables, and latent structures. In: Hagenaars JA, McCutcheon AL (eds) Applied latent class analysis. Cambridhe University Press, Cambridge, pp 3–55

    Chapter  Google Scholar 

  • Goulias KG (1999) Longitudinal analysis of activity and travel pattern dynamics using generalized mixed Markov latent class models. Transp Res B 33:535–557

    Article  Google Scholar 

  • Goulias KG (2001) A longitudinal integrated forecasting environment (LIFE) for activity and travel forecasting. In: Villacampa Y, Brebbia CA, Uso J-L (eds) Ecosystems and sustainable development III. WIT Press, Southampton, pp 811–820

    Google Scholar 

  • Goulias KG (2002) Multilevel analysis of daily time use and time allocation to activity types accounting for complex covariance structures using correlated random effects. Transportation 29(1):31–48

    Article  Google Scholar 

  • Goulias KG (2003) Transportation systems planning. In: Goulias KG (ed) Transportation systems planning: methods and applications. CRC Press, Boca Raton, pp 1-1 to 1-45

    Google Scholar 

  • Goulias KG, Kim T (2003) A longitudinal analysis of the relationship between environmentally friendly modes, weather conditions, and information-telecommunications technology market penetration. In: Tiezzi E, Brebbia CA, Uso JL (eds) Ecosystems and sustainable development, vol 2. WIT Press, Southampton, pp 949–958

    Google Scholar 

  • Goulias KG, Kim T (2005) An analysis of activity type classification and issues related to the with whom and for whom questions of an activity diary. In: Timmermans H (ed) Progress in activity-based analysis. Elsevier, Amsterdam, pp 309–334

    Google Scholar 

  • Goulias KG, Kitamura R (1992) Travel demand analysis with dynamic microsimulation. Transp Res Rec 1607:8–18

    Google Scholar 

  • Goulias KG, Kitamura R (1997) Regional travel demand forecasting with dynamic microsimulation models. In: Golob T, Kitamura R, Long L (eds) Panels for transportation planning: methods and applications. Kluwer, Boston, pp 321–348

    Chapter  Google Scholar 

  • Goulias KG, Litzinger T, Nelson J, Chalamgari V (1993) A study of emission control strategies for Pennsylvania: emission reductions from mobile sources, cost effectiveness, and economic impacts. Final report to the low emissions vehicle commission. PTI 9403. The Pennsylvania Transportation Institute, University Park

    Google Scholar 

  • Goulias KG, Kim T, Pribyl O (2003) A longitudinal analysis of awareness and use for advanced traveler information systems. Paper to be presented at the European Commission workshop on behavioural responses to ITS – 1–3 April 2003, Eindhoven

    Google Scholar 

  • Goulias KG, Zekkos M, Eom J (2004) CentreSIM3 scenarios for the South Central Centre County transportation study. CentreSIM3 report submitted to McCormick Taylor Associates and the Mid-Atlantic Universities Transportation Center, April 2004, University Park

    Google Scholar 

  • Goulias KG, Blain L, Kilgren N, Michalowski T, Murakami E (2007) Catching the next big wave: are the observed behavioral dynamics of the baby boomers forcing us to rethink regional travel demand models? Paper presented at the 86th transportation research board annual meeting, 21–25 January 2007, Washington, DC and included in the CD ROM proceedings

    Google Scholar 

  • Greene WH (1997) Econometric analysis, 3rd edn. Prentice Hall, Upper Saddle River

    Google Scholar 

  • Grieving S, Kemper R (1999) Integration of transport and land use policies: state of the art. Deliverable 2b of the project TRANSLAND, 4th RTD Framework Programme of the European Commission

    Google Scholar 

  • Haab TC, Hicks RL (1997) Accounting for choice set endogeneity in random utility models of recreation demand. J Environ Econ Manag 34:127–147

    Article  MATH  Google Scholar 

  • Hagerstrand T (1970) What about people in regional science? Pap Reg Sci Assoc 10:7–21

    Google Scholar 

  • Hato E (2006) Development of behavioral context addressable loggers in the shell for travel activity analysis. Paper presented at the IATBR conference, Kyoto

    Google Scholar 

  • Hayes-Roth B, Hayes-Roth F (1979) A cognitive model of planning. Cogn Sci 3:275–310

    Article  Google Scholar 

  • Henson K, Goulias KG (2006) Preliminary assessment of activity and modeling for homeland security applications. Transportation Research Record: J Transportation Research Board, No. 1942. Transportation Research Board of the national academies, Washington, DC, pp 23–30

    Google Scholar 

  • Henson K, Goulias KG, Golledge R (2006) An assessment of activity-based modeling and simulation for applications in operational studies, disaster preparedness, and homeland security. Paper presented at the IATBR conference, Kyoto

    Google Scholar 

  • Horowitz JL (1991) Modeling the choice of choice set in discrete-choice random-utility models. Environ Plan A 23:1237–1246

    Article  Google Scholar 

  • Horowitz JL, Louviere JJ (1995) What is the role of consideration sets in choice modeling? Int J Res Marketing 12:39–54

    Article  Google Scholar 

  • Huigen PPP (1986) Binnen of buiten bereik?: Een sociaal-geografisch onderzoek in Zuidwest-Friesland, Nederlandse Geografische Studies 7. University of Utrecht, Utrecht

    Google Scholar 

  • Hutchinson BG (1974) Principles of urban transport systems planning. Scripta, Washington, DC

    Google Scholar 

  • JHK & Associates, Clough, Harbour & Associates, Pennsylvania Transportation Institute, Bogart Engineering (1996) Scranton/Wilkes-Barre area strategic deployment plan. Final report. Prepared for Pennsylvania Department of Transportation District 4-0. August 1996, Berlin

    Google Scholar 

  • Joh C-H, Arentze T, Timmermans H (2004) Activity-travel scheduling and rescheduling decision processes: empirical estimation of aurora model. Transp Res Rec 1898:10–18

    Article  Google Scholar 

  • Jones PM, Dix MC, Clarke MI, Heggie IG (1983) Understanding travel behaviour. Gower, Aldershot

    Google Scholar 

  • Jones P, Koppelman F, Orfeuil J (1990) Activity analysis: state of-the-art and future directions. In: Jones P (ed) Developments in dynamic and activity-based approaches to travel analysis. A compendium of papers from the 1989 Oxford conference. Avebury, Gower-Aldershot, pp 34–55

    Google Scholar 

  • Jonnalagadda N, Freedman J, Davidson WA, Hunt JD (2001) Development of microsimulation activity-based model for San Francisco. Transp Res Rec 1777:25–35

    Article  Google Scholar 

  • Kahneman D, Tversky A (1979) Prospect theory: an analysis of decisions under risk. Econometrica 47(2):263–291

    Article  MATH  Google Scholar 

  • Kawakami S, Isobe T (1989) Development of a travel-activity scheduling model considering time constraint and temporal transferability test of the model. In: Transport policy, management and technology towards 2001: selected proceedings of the fifth world conference on transport research, vol 4. Western Periodicals, Ventura, pp 221–233

    Google Scholar 

  • Kharoufeh JP, Goulias KG (2002) Nonparametric identification of daily activity durations using kernel density estimators. Transp Res B Methodol 36:59–82

    Article  Google Scholar 

  • Kitamura R (1988) An evaluation of activity-based travel analysis. Transportation 15:9–34

    Article  Google Scholar 

  • Kitamura R (1997) Applications of models of activity behavior for activity based demand forecasting. In: Engelke LJ (ed) Activity-based travel forecasting conference: summary, recommendations and compendium of papers. Report of the travel model improvement program. Texas Transportation Institute, Arlington, pp 119–150

    Google Scholar 

  • Kitamura R (2000) Longitudinal methods. In: Hensher DA, Button KJ (eds) Handbook of transport modelling. Pergamon, Amsterdam, pp 113–128

    Google Scholar 

  • Kitamura R, Fujii S (1998) Two computational process models of activity-travel choice. In: Garling T, Laitila T, Westin K (eds) Theoretical foundations of travel choice modeling. Pergamon, Elsevier, Amsterdam, pp 251–279

    Google Scholar 

  • Kitamura R, Pas EI, Lula CV, Lawton TK, Benson PE (1996) The sequenced activity simulator (SAMS): an integrated approach to modeling transportation, land use and air quality. Transportation 23:267–291

    Article  Google Scholar 

  • Kitamura R, Chen C, Pendyala RM (1997) Generation of synthetic daily activity-travel patterns. Transp Res Rec 1607:154–162

    Article  Google Scholar 

  • Koppelman FS, Sethi V (2000) Closed-form discrete-choice models. In: Hensher DA, Button KJ (eds) Handbook of transport modelling. Pergamon, Amsterdam, pp 211–225

    Google Scholar 

  • Krizek KJ, Johnson A (2003) Mapping of the terrain of information and communications technology (ICT) and household travel. Transportation Research Board annual meeting CDROM, Washington, DC

    Google Scholar 

  • Kuhnau JL (2001) Activity-based travel demand modeling using spatial and temporal models in the urban transportation planning system. MS Thesis, Department of Civil and Environmental Engineering, The Pennsylvania State University, University Park

    Google Scholar 

  • Kuhnau JL, Goulias KG (2002) Centre SIM: hour-by-hour travel demand forecasting for mobile source emission estimation. In: Brebbia CA, Zannetti P (eds) Development and application of computer techniques to environmental studies IX. WIT Press, Southampton, pp 257–266

    Google Scholar 

  • Kuhnau JL, Goulias KG (2003) Centre SIM: first-generation model design, pragmatic implementation, and scenarios. In: Goulias KG (ed) Transportation systems planning: methods and applications. CRC Press, Boca Raton, pp 16-1–16-14

    Google Scholar 

  • Kulkarni A, McNally MG (2001) A microsimulation of daily activity patterns. Paper presented at the 80th annual meeting of the Transportation Research Board, Washington, DC, 7–11 January 2001

    Google Scholar 

  • Kwan M-P (1994) A GIS-based model for activity scheduling in intelligent vehicle highway systems (IVHS). Unpublished PhD, Department of Geography, University of California Santa Barbara, Santa Barbara

    Google Scholar 

  • Kwan M-P (1997) GISICAS: an activity-based travel decision support system using a GIS-interfaced computational-process model. In: Ettema DF, Timmermans HJP (eds) Activity based approaches to travel analysis. Elsevier Science, New York, pp 263–282

    Google Scholar 

  • Lenntorp B (1976) Paths in space-time environment: a time geographic study of possibilities of individuals. Lund Studies in Geography, Series B Human Geography, vol 44. The Royal University of Lund, Department of Geography, Lund

    Google Scholar 

  • Lomborg B (2001) The skeptical environmentalist: measuring the real state of the world. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Longford NT (1993) Random coefficient models. Clarendon Press, Oxford

    MATH  Google Scholar 

  • Los Alamos National Laboratory (2003) TRANSIMS: Transportation analysis system (Version 3.1). LA-UR-00-1725

    Google Scholar 

  • Loudon WR, Dagang DA (1994) Evaluating the effects of transportation control measures. In: Wholley TF (ed) Transportation planning and air quality II. American Society of Civil Engineers, New York

    Google Scholar 

  • Louviere JJ, Hensher DA, Swait JD (2000) Stated choice methods: analysis and application. Cambridge University Press, Cambridge

    Book  MATH  Google Scholar 

  • Ma J (1997) An activity-based and micro-simulated travel forecasting system: a pragmatic synthetic scheduling approach. Unpublished PhD Dissertation, Department of Civil and Environmental Engineering, The Pennsylvania State University, University Park

    Google Scholar 

  • Mahmassani HS, Herman R (1990) Interactive experiments for the study of tripmaker behaviour dynamics in congested commuting systems, In: Developments in dynamic and activity-based approaches to travel analysis. A compendium of papers from the 1989 Oxford Conference. Avebury

    Google Scholar 

  • Mahmassani HS, Jou R-C (1998) Bounded rationality in commuter decision dynamics: incorporating trip chaining in departure time and route switching decisions. In: Garling T, Laitila T, Westin K (eds) Theoretical foundations of travel choice modeling. Pergamon, Elsevier, Amsterdam

    Google Scholar 

  • Manheim ML (1979) Fundamentals of transportation systems analysis, vol 1: Basic concepts. MIT Press, Cambridge

    Google Scholar 

  • Marker JT, Goulias KG (2000) Framework for the analysis of grocery teleshopping. Transp Res Rec 1725:1–8

    Article  Google Scholar 

  • McFadden D (1998) Measuring willingness-to-pay for transportation improvements. In: Garling T, Laitila T, Westin K (eds) Theoretical foundations of travel choice modeling. Pergamon, Elsevier, Amsterdam, pp 339–364

    Google Scholar 

  • McNally MG (2000) The activity-based approach. In: Hensher DA, Button KJ (eds) Handbook of transport modelling. Pergamon, Amsterdam, pp 113–128

    Google Scholar 

  • Meyer MD, Miller EJ (2001) Urban transportation planning, 2nd edn. McGraw Hill, Boston

    Google Scholar 

  • Miller EJ (2003) Land use: transportation modeling. In: Goulias KG (ed) Transportation systems planning: methods and applications. CRC Press, Boca Raton, pp 5-1 to 5-24

    Google Scholar 

  • Miller EJ (2006) Resource paper on integrated land use-transportation models. IATBR, Kyoto

    Google Scholar 

  • Miller JS, Demetsky MJ (1999) Reversing the direction of transportation planning process. ASCE J Transp Eng 125(3):231–237

    Article  Google Scholar 

  • Miller EJ, Roorda MJ (2003) A prototype model of household activity/travel scheduling. Transp Res Rec 1831:114–121

    Article  Google Scholar 

  • Mokhtarian PL (1990) A typology of relationships between telecommunications and transportation. Transp Res A 24(3):231–242

    Article  Google Scholar 

  • National Cooperative Highway Research Program (2000) Report 446. Transp Res Board, Washington, DC

    Google Scholar 

  • Newell A, Simon HA (1972) Human problem solving. Prentice Hall, Englewood Cliffs

    Google Scholar 

  • Niemeier DA (2003) Mobile source emissions: an overview of the regulatory and modeling framework. In: Goulias KG (ed) Transportation systems planning: methods and applications. CRC Press, Boca Raton, pp 13-1–13-28

    Google Scholar 

  • Ortuzar JD, Willumsen LG (2001) Modelling transport, 3rd edn. Wiley, Chichester

    Google Scholar 

  • Paaswell RE, Rouphail N, Sutaria TC (eds) (1992) Site impact traffic assessment. Problems and solutions. ASCE, New York

    Google Scholar 

  • Patten ML, Goulias KG (2001) Test plan: motorist survey – evaluation of the Pennsylvania turnpike advanced travelers information system (ATIS) project, phase III PTI-2001-23-I. April 2001. University Park

    Google Scholar 

  • Patten ML, Hallinan MP, Pribyl O, Goulias KG (2003) Evaluation of the Smartraveler advanced traveler information system in the Philadelphia metropolitan area. Technical memorandum. PTI 2003–33. March 2003. University Park

    Google Scholar 

  • Payne JW, Bettman JR, Johnson EJ (1993) The adaptive decision maker. Cambridge University Press, Cambridge

    Book  Google Scholar 

  • Pendyala R (2003) Time use and travel behavior in space and time. In: Goulias KG (ed) Transportation systems planning: methods and applications. CRC Press, Boca Raton, pp 2-1–2-37

    Google Scholar 

  • Pendyala RM, Kitamura R, Kikuchi A, Yamamoto T, Fujii S (2005) The Florida activity mobility simulator (FAMOS): an overview and preliminary validation results. Presented at the 84th annual transportation research board conference and CD-ROM

    Google Scholar 

  • Pribyl O (2004) A microsimulation model of activity patterns and within household interactions. PhD dissertation, Department of Civil and Environmental Engineering, The Pennsylvania State University, University Park

    Google Scholar 

  • Pribyl O (2007) Computational intelligence in transportation: short user-oriented guide. In: Goulias KG (ed) Transport science and technology. Elsevier, Amsterdam, pp 37–54

    Google Scholar 

  • Pribyl O, Goulias KG (2003) On the application of adaptive neuro-fuzzy inference system (ANFIS) to analyze travel behavior. Paper presented at the 82nd transportation research board meeting and included in the CDROM proceedings and accepted for publication in the Transportation Research Record, Washington DC, January 2003

    Google Scholar 

  • Pribyl O, Goulias KG (2005) Simulation of daily activity patterns. In: Timmermans H (ed) Progress in activity-based analysis. Elsevier Science, Amsterdam, pp 43–65

    Google Scholar 

  • Ramadurai G, Srinivasan KK (2006) Transportation Research Board of the National Academies, Washington, DC, pp 43–52

    Google Scholar 

  • Recker WW (1995) The household activity pattern problem: general formulation and solution. Transp Res B 29:61–77

    Article  Google Scholar 

  • Recker WW, McNally MG, Root GS (1986a) A model of complex travel behavior: part I – theoretical development. Transp Res A 20(4):307–318

    Article  Google Scholar 

  • Recker WW, McNally MG, Root GS (1986b) A model of complex travel behavior: part II – an operational model. Transp Res A 20(4):319–330

    Article  Google Scholar 

  • Richardson A (1982) Search models and choice set generation. Transp Res Part A 16(5–6):403–416

    Article  Google Scholar 

  • Robinson J (1982) Energy backcasting: a proposed method of policy analysis. Energ Policy 10(4):337–344

    Article  Google Scholar 

  • Rubinstein A (1998) Modeling bounded rationality. MIT Press, Cambridge

    Google Scholar 

  • Sadek AW, El Dessouki WM, Ivan JI (2002) Deriving land use limits as a function of infrastructure capacity. Final report, project UVMR13-7, New England Region One University Transportation Center. MIT, Cambridge

    Google Scholar 

  • Salomon I (1986) Telecommunications and travel relationships: a review. Transp Res A 20(3):223–238

    Article  Google Scholar 

  • Salvini P, Miller EJ (2003) ILUTE: an operational prototype of a comprehensive microsimulation model of urban systems. Paper presented at the 10th international conference on travel behaviour research, Lucerne, August 2003

    Google Scholar 

  • Savage LJ (1954) The foundations of statistics. Reprinted version in 1972 by Dover Publications, New York

    Google Scholar 

  • Searle SR, Casella G, McCulloch CE (1992) Variance components. Wiley, New York

    Book  MATH  Google Scholar 

  • Simma A, Axhausen KW (2001) Within-household allocation of travel-The case of Upper Austria. Transportation Research Record: J Transportation Research Board, No. 1752, TRB, National Research Council, Washington, DC 69–75

    Google Scholar 

  • Simon HA (1983) Alternate visions of rationality. In: Simon HA (ed) Reason in human affairs. Stanford University Press, Stanford, pp 3–35

    Google Scholar 

  • Simon HA (1997) Administrative behavior, 4th edn. The Free Press, New York

    Google Scholar 

  • Southworth F (2003) Freight transportation planning: models and methods. In: Goulias KG (ed) Transportation systems planning: methods and applications. CRC Press, Boca Raton, pp 4.1–4.29

    Google Scholar 

  • Sparmann U (1980) Ein verhaltensorientiertes Simulationsmodell zur Verkehrsprognose. Schriftenreihe des Instituts für Verkehrswesen 20. Universität (TH) Karlsruhe, Karlsruhe

    Google Scholar 

  • Stefan KJ, McMillan JDP, Hunt JD (2005) An urban commercial vehicle movement model for Calgary. Paper presented at the 84th transportation research board meeting, Washington, DC

    Google Scholar 

  • Stopher PR (1994) Predicting TCM responses with urban travel demand models. In: Wholley TF (ed) Transportation planning and air quality II. American Society of Civil Engineers, New York

    Google Scholar 

  • Stopher PR, Meyburg AH (eds) (1976) Behavioral travel-demand models. Lexington Books, Lexington

    Google Scholar 

  • Stopher PR, Hartgen DT, Li Y (1996) SMART: simulation model for activities, resources and travel. Transportation 23:293–312

    Article  Google Scholar 

  • Sundararajan A, Goulias KG (2002) Demographic microsimulation with DEMOS 2000: design, validation, and forecasting. In: Goulias KG (ed) Transportation systems planning: methods and applications. CRC Press, Boca Raton, pp 14-1–14-23

    Google Scholar 

  • Swait J, Ben-Akiva M (1987a) Incorporating random constraints in discrete models of choice set generation. Transp Res Part B 21(2):91–102

    Article  Google Scholar 

  • Swait J, Ben-Akiva M (1987b) Empirical test of a constrained choice discrete model: mode choice in Sao Paolo, Brazil. Transp Res Part B 21(2):103–115

    Article  Google Scholar 

  • Teodorovic D, Vukadinovic K (1998) Traffic control and transport planning: a fuzzy sets and neural networks approach. Kluwer, Boston

    Book  MATH  Google Scholar 

  • Thill J (1992) Choice set formation for destination choice modeling. Progr Human Geogr 16(3):361–382

    Article  Google Scholar 

  • Tiezzi E (2003) The end of time. WIT Press, Southampton

    Google Scholar 

  • Timmermans H (2003) The saga of integrated land use-transport modeling: how many more dreams before we wake up? Conference keynote paper at the Moving through net: the physical and social dimensions of travel. 10th international conference on travel behaviour research, Lucerne, 10–15, August 2003. In: Proceedings of the meeting of the International Association for Travel Behevaior Research (IATBR). Lucerne

    Google Scholar 

  • Timmermans H (2006) Analyses and models of household decision making processes. Resource paper in the CDROM proceedings of the 11th IATBR international conference on travel behaviour research, Kyoto

    Google Scholar 

  • Timmermans H, Arentze T, Joh C-H (2001) Modeling effects of anticipated time pressure on execution of activity programs. Transp Res Rec 1752:8–15

    Article  Google Scholar 

  • Train KE (2003) Discrete choice methods with simulation. Cambridge University Press, Cambridge

    Book  MATH  Google Scholar 

  • Transportation Research Board (1999) Transportation, energy, and environment. Policies to promote sustainability. Transportation research circular 492. TRB, Washington, DC

    Google Scholar 

  • Transportation Research Board (2002) Surface transportation environmental research: a long-term strategy. Transportation Research Board, Washington, DC

    Book  Google Scholar 

  • Tversky A (1969) Intransitivity of preferences. Psychol Rev 76:31–48

    Article  Google Scholar 

  • Tversky A (1972) Elimination by aspects: a theory of choice. Psychol Rev 79:281–299

    Article  Google Scholar 

  • Tversky A, Kahneman D (1992) Advances in prospect theory: cumulative representation of uncertainty. J Risk Uncertain 9:195–230

    MATH  Google Scholar 

  • US Government (2006) Analytical perspectives. Budget of the United States Government, Fiscal year 2007. US Government printing Office, Washington, DC

    Google Scholar 

  • Van der Hoorn T (1997) Practitioner’s future needs. Paper presented at the conference on transport surveys, raising the standard. Grainau, Germany, May 24–30

    Google Scholar 

  • Van Middelkoop M, Borgers AWJ, Timmermans H (2004) Merlin. Transp Res Rec 1894:20–27

    Article  Google Scholar 

  • Vause M (1997) A rule-based model of activity scheduling behavior. In: Ettema DF, Timmermans HJP (eds) Activity-based approaches to travel analysis. Elsevier Science, New York, pp 73–88

    Google Scholar 

  • Veldhuisen J, Timmermans H, Kapoen L (2000) RAMBLAS: a regional planning model based on the microsimulation of daily activity travel patterns. Transp Res A 32:427–443

    Google Scholar 

  • Vovsha P, Petersen E (2005) Escorting children to school: statistical analysis and applied modeling approach. Transp Res Rec: J Transp Res Board 1921. Transportation Research Board of the National Academies, Washington, DC, pp 131–140

    Google Scholar 

  • Vovsha P, Peterson EJ, Donnelly R (2002) Microsimulation in travel demand modeling: lessons learned from the New York best practice mode. Transp Res Rec 1805:68–77

    Article  Google Scholar 

  • Vovsha P, Peterson EJ, Donnelly R (2003) Explicit modeling of joint travel by household members: statistical evidence and applied approach. Transp Res Rec 1831:1–10

    Article  Google Scholar 

  • Waddell P, Ulfarsson GF (2003) Dynamic simulation of real estate development and land prices within an integrated land use and transportation model system. Presented at the 82nd annual meeting of the transportation research board, 12–16 January 2003, Washington, DC. Also available in http://www.urbansim.org/papers/. Accessed April 2003

  • Wang D, Timmermans H (2000) Conjoint-based model of activity engagement, timing, scheduling, and stop pattern formation. Transp Res Rec 1718:10–17

    Article  Google Scholar 

  • Weiland RJ, Purser LB (2000) Intelligent transportation systems. In: Transportation in the new millennium. State of the art and future directions. Perspectives from transportation research board standing committees. Transportation Research Board. National Research Council. The National Academies, Washington, DC, p 6. Also in http://nationalacademies.org/trb/

    Google Scholar 

  • Wen C-H, Koppelman FS (2000) A conceptual and methodological framework for the generation of activity-travel patterns. Transportation 27:5–23

    Article  Google Scholar 

  • Williams HCWL, Ortuzar JD (1982) Behavioral theories of dispersion and the mis-specification of travel demand models. Transp Res B 16(3):167–219

    Article  Google Scholar 

  • Wilson EO (1998) Consilience, the unity of knowledge. Vintage Books, New York

    Google Scholar 

  • Wolf J, Guensler R, Washington S, Frank L (2001) Use of electronic travel diaries and vehicle instrumentation packages in the year 2000. Atlanta regional household travel survey. Transportation research circular, E-C026, March 2001. Transportation Research Board, Washington, DC

    Google Scholar 

  • Zhang J, Timmermans HJP, Borgers AWJ (2005) A model of household task allocation and time use. Transp Res B 39:81–95

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Goulias, K.G. (2009). Travel Behavior and Demand Analysis and Prediction. In: Kerner, B. (eds) Complex Dynamics of Traffic Management. Encyclopedia of Complexity and Systems Science Series. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-8763-4_565

Download citation

Publish with us

Policies and ethics