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Transportation

, Volume 29, Issue 2, pp 193–220 | Cite as

Revisiting the notion of induced traffic through a matched-pairs study

  • Patricia L. Mokhtarian
  • Francisco J. Samaniego
  • Robert H. Shumway
  • Neil H. Willits
Article

Abstract

In investigating the question of the existence of "induced demand" in connection with highway expansion projects, Hansen et al. (1993) studied eighteen California state highway segments whose capacities had been improved in the early 1970s. For the present study, these segments were paired with control segments that matched the improved segments to unimproved ones with regard to facility type, region, approximate size, and initial volumes and congestion levels. Taking annual data for average daily traffic (ADT) and design-hour-traffic-to-capacity (DTC) ratios during the 21 years 1976–1996, three approaches were used to compare growth rates between the improved and unimproved segments: overall growth comparisons for the matched pairs, repeated measures analysis, and analysis of matched mean profiles. We found the growth rates between the two types of segments to be statistically and practically indistinguishable, suggesting that the capacity expansions, in and of themselves, had a negligible effect on traffic growth over the period studied. Reasons for the differences between these results and those of aggregate cross-sectional models finding a significant induced demand effect are discussed. Our analyses suggest that the aggregate models may overestimate induced traffic due to the attribution of at least a fraction of the observed traffic growth to "induced demand" rather than to some of the confounding factors which were not controlled for in such studies. At the same time, it is noted that the traffic induced by capacity expansion may in certain circumstances be larger than that observed in the present study, with the effect of new highway construction on traffic growth being a prime candidate for scrutiny in this regard. The results of this study nonetheless suggest that, for existing facilities, the size of the induced-traffic effect that can be attributed to capacity enhancements may be sufficiently small that its detection in a case-control study would be difficult, if not impossible, without a substantially larger sample size.

highway capacity induced demand induced travel latent demand repeated measures time series analysis Wilcoxon test 

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References

  1. Barr L (2000) Testing for the significance of induced highway travel demand in metropolitan areas. Transportation Research Record 1706: 1-8.Google Scholar
  2. Chu X (2000) Highway capacity and area-wide congestion. Paper no. 00-1506 on the CD-ROM for the 2000 Annual Meeting of the Transportation Research Board, Washington DC, January.Google Scholar
  3. Cohen HS (1995) Review of empirical studies of induced traffic. Appendix B of Special Report 245, Expanding metropolitan highways: Implications for air quality and energy use. National Academy Press, Washington, DC, 295-309.Google Scholar
  4. Dawid AP (2000) Causal inference without counterfactuals. Journal of the American Statistical Association 95: 407-424.Google Scholar
  5. DeCorla-Souza P (2000) Induced highway travel: Transportation policy implications for congested metropolitan areas. Transportation Quarterly 54: 13-30.Google Scholar
  6. Fulton LM, Meszler DJ, Noland RB & Thomas JV (2000) A statistical analysis of induced travel effects in the US mid-Atlantic region. Journal of Transportation and Statistics 3(1): 1-14.Google Scholar
  7. Golob TF, Beckmann MJ & Zahavi Y (1981) A utility theory travel demand model incorporating travel budgets. Transportation Research B 15: 375-389.Google Scholar
  8. Goodwin PB (1996) Empirical evidence on induced traffic: A review and synthesis. Transportation 23(1): 35-54.Google Scholar
  9. Hansen M, Gillen D, Dobbins A, Huang Y & Puvathingal M (1993) The air quality impacts of urban highway capacity expansion: Traffic generation and land use change. Report no. UCBITS-RR-93-5. Institute of Transportation Studies, University of California, Berkeley.Google Scholar
  10. Hansen M & Huang Y (1997) Road supply and traffic in California urban areas. Transportation Research A 31(3): 205-218.Google Scholar
  11. Harvey AC (1991) Forecasting structural time series models and the Kalman filter. Cambridge, UK: Cambridge University Press.Google Scholar
  12. Heanue K (1998) Highway capacity and induced travel: Issues, evidence, and implications. Highway Capacity Expansion and Induced Travel: Evidence and Implications. Transportation Research Circular 481 (February), Transportation Research Board, 33-45.Google Scholar
  13. Huynh H & Feldt LS (1976) Estimation of the Box correction for degrees of freedom from sample data in the randomized block and split plot designs. Journal of Educational Statistics 1: 69-82.Google Scholar
  14. Kroes E, Daly A, Gunn H & van der Hoorn T (1996) The opening of the Amsterdam Ring Road: A case study on short-term effects of removing a bottleneck. Transportation 23(1): 71-82.Google Scholar
  15. Marshall NL (2000) Evidence of induced demand in the Texas Transportation Institute's Urban Roadway Congestion Study data set. Paper no. 00-0181 on the CD-ROM for the 2000 Annual Meeting of the Transportation Research Board, Washington DC, January.Google Scholar
  16. Mauchly JW (1940) Significance test for sphericity of a normal n-variate distribution. Annals of Mathematical Statistics 11: 204-209.Google Scholar
  17. Noland RB (2001) Relationships between highway capacity and induced vehicle travel. Transportation Research A 35(1): 47-72.Google Scholar
  18. Noland RB & Cowart WA (2000) Analysis of metropolitan highway capacity and the growth in vehicle miles of travel. Transportation 27(4): 363-390.Google Scholar
  19. Rodier CJ, Abraham JE & Johnston RA (2000) Anatomy of induced travel using an integrated land use and transportation model. Chapter 4 of CJ Rodier, Uncertainty in travel and emissions models: A case study in the Sacramento region. PhD dissertation, Ecology Graduate Group, University of California, Davis.Google Scholar
  20. Samaniego FJ, Azari R, Mokhtarian PL, Shumway R & Willits N (1999) Final report on the statistical analysis of traffic generation in California: Another look at the question of “induced traffic” following highway capacity improvements. Prepared by the Statistical Laboratory, University of California, Davis, pursuant to Interagency Agreement No. 43A0014 between the California Department of Transportation and the University of California, Davis, Task Order No. 22. December.Google Scholar
  21. Shumway RH and Stoffer DS (2000) Time series analysis and its applications, Chapter 4. New York: Springer-Verlag.Google Scholar
  22. Transportation Research Board (1995) Special Report 245, Expanding metropolitan highways: Implications for air quality and energy use. National Academy Press, Washington, DC.Google Scholar

Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  • Patricia L. Mokhtarian
    • 1
  • Francisco J. Samaniego
    • 2
  • Robert H. Shumway
    • 2
  • Neil H. Willits
    • 2
  1. 1.Department of Civil and Environmental Engineering and Institute of Transportation StudiesUniversity of CaliforniaDavisUSA
  2. 2.Department of Statistics and The Statistical LaboratoryUniversity of CaliforniaDavisUSA

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