A Panel-Based Evaluation of the San Diego I-15 Carpool Lanes Project

  • Thomas F. Golob
  • Ryuichi Kitamura
  • Janusz Supernak
Part of the Transportation Research, Economics and Policy book series (TRES)

Abstract

The operation of reversible high-occupancy vehicle (HOV) lanes on Interstate 15 north of San Diego, California, has been monitored by an annual panel survey of commuters in the region and by traffic flow observations. The panel survey, initiated in 1988, collected mode choice, travel time, and attitudinal data in one wave prior to the opening of the lanes and in two waves after the opening of the lanes. These data are used to model the causes of changes in four variables at three points in time: (1) choice of ride-sharing versus solo driving, (2) travel time, (3) perceptions of traffic conditions on the I-15 mixed-flow lanes, and (4) attitudes concerning the HOV lanes. The model involves simultaneous equations with mixed discrete-choice, ordinal-scale and continuous variables, estimated by probit sub-models and distribution-free generalized least squares. An important feature is the use of individual-specific constant terms, which take advantage of repeated measurements on the same individuals to account for population heterogeneity. Results show mutual cause and effects among mode choice, travel times, and attitudes.

Keywords

Travel Time Structural Equation Model Endogenous Variable Traffic Condition Mode Choice 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Ashford, J.R. (1959) An approach to the analysis of data for semi-quantal responses in biological response. Biometrics 15, 573–581.CrossRefGoogle Scholar
  2. Arrchlson, J. and S. Silvey (1957) The generalization of probit analysis to the case of multiple responses. Biometrica 44, 131–140.Google Scholar
  3. Bentler, P.M. (1983) Simultaneous equation systems as moment structure models. Journal of Econometrics, 22, 13–42.CrossRefGoogle Scholar
  4. Bollen, K.A. (1989) Structural Equations with Latent Variables. New York: Wiley.Google Scholar
  5. Browne, M.W. (1982) Covariance structures. In D.M. Hawkins, ed. Topics in Multivariate Analysis, Cambridge: Cambridge University Press, pp. 72–141.CrossRefGoogle Scholar
  6. Browne, M.W. (1984) Asymptotic distribution free methods in analysis of covariance structures. British Journal of Mathematical and Statistical Psychology, 37, 62–83.CrossRefGoogle Scholar
  7. Gown, T.F. (1990) The dynamics of household travel time expenditures and car ownership decisions. Transportation Research, 24A, 443–463.Google Scholar
  8. Gam, T.F. and L. Van Wissen (1989) A joint household travel distance generation and car ownership model. Transportation Research, 23B, 471–491.CrossRefGoogle Scholar
  9. Jörfskog, K.G. and D. Sörbom (1993a) L/SREL 8 User’s Reference Guide. Scientific Software, Chicago.Google Scholar
  10. Jöreskog, K.G. and D. Sörbom (1993b) PRELIS 2 User’s Reference Guide. Scientific Software, Chicago.Google Scholar
  11. Krramura, R. and P.H.L. Bovy (1987) Analysis of attrition biases and trip reporting errors for panel data. Transportation Research, 21A, 287–302Google Scholar
  12. Kitamura, R., K.G. Goulias and R.M. Pendyala (1993) Weighting methods. for choice based panels with correlated attrition and initial choice. In C.F. Daganzo, ed., Transportation and Traffic Theory, Amsterdam: Elsevier, pp. 275–294.Google Scholar
  13. Kirk, D.D. (1973) On the numerical approximation of the bivariate normal (tetrachoric) correlation coefficient. Psychometrika, 38, 259–268.CrossRefGoogle Scholar
  14. Maddala, G.S. (1983) Limited-dependent and Qualitative Variables in Econometrics. New York: Cambridge University Press.Google Scholar
  15. Mutinn, B. (1983) Latent variable structural equation modeling with categorical data. Journal of Econometrics, 22, 43–65.CrossRefGoogle Scholar
  16. Mumen, B. (1984) A general structural equations model with dichotomous, ordered categorical and continuous latent variable indicators. Psychometrika, 49, 115–132.CrossRefGoogle Scholar
  17. Olsson, U. (1979) Maximum likelihood estimation of the polychoric correlation coefficient. Psychometrika, 44, 443–360.CrossRefGoogle Scholar
  18. Olsson, U., F. Drasgow and N. J. Dorans (1982) The polyserial correlation coefficient. Psychometrika, 47, 337–347.CrossRefGoogle Scholar
  19. Pendyala, R.M. and R. Krramura (1997) Weighting methods for attrition in choice-based samples. Chapter Nine in this volume.Google Scholar
  20. Pendyala, R.M., K.G. Goulias, R. Kitamura and E. Murakaaii (1993) An analysis of a choice-based panel travel survey sample: Results from the Puget Sound Transportation Panel. Transportation Research, 27A (6), 477–492.Google Scholar
  21. Supernak, J. (1991) Assessment of the Effectiveness of the Reversible Roadway for High Occupancy Vehicles on Interstate Route 15, Final Report. Department of Civil Engineering, San Diego State University for the California Department of Transportation.Google Scholar
  22. Van Wissen, L. and T.F. Gown (1992) A dynamic model of car fuel-type choice and mobility. Transportation Research, 26B, 77–96.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  • Thomas F. Golob
    • 1
  • Ryuichi Kitamura
    • 2
  • Janusz Supernak
    • 3
  1. 1.Institute of Transportation StudiesUniversity of CaliforniaIrvineUSA
  2. 2.Department of Transportation EngineeringKyoto UniversitySakyo-ku, Kyoto, 606Japan
  3. 3.Department of Civil EngineeringSan Diego State UniversitySan DiegoUSA

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