Advertisement

Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

The importance of being early

Abstract

This research quantifies the relationship between the cost of earliness and lateness by empirically observing commute trips from two different sources. The first empirical analysis uses individual level travel survey data from six metropolitan regions while the second analysis uses traffic data from the Twin Cities freeway network. The analysis conducted in this research provides a method to estimate the ratio of the costs of earliness to lateness for different datasets. This can be a useful tool for traffic engineers and planners, to assist them in the development and implementation of improved control strategies for congested cities. The results also corroborates the hypothesis of earliness being less expensive than lateness and show that the finding holds steady over time and across different regions and levels.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Notes

  1. 1.

    The Minnesota Traffic Observatory (MTO) maintains a repository of actual freeway traffic data extracted from the loop detectors on the Twin Cities freeway network, available for download at http://data.dot.state.mn.us/datatools/.

References

  1. Arnott, R.J., De Palma, A., Lindsey, R.: Departure time and route choice for the morning commute. Transp. Res. B Methodol. 24B, 209–228 (1990)

  2. Cassidy, M., Windover, J.: Methodology for assessing dynamics of freeway traffic flow. Transp. Res. Rec. Natl. Res. Counc. 1484, 73–79 (1995)

  3. Daganzo, C.: Urban gridlock: macroscopic modeling and mitigation approaches. Transp. Res. B 41, 49–62 (2007)

  4. Geroliminis, N., Daganzo, C.: Macroscopic modeling of traffic in cities. In: 86th Annual Meeting of the Transportation Research Board, pp. 07-0413. Washington, DC (2007)

  5. Geroliminis, N., Daganzo, C.: Existence of urban-scale macroscopic fundamental diagrams: some experimental findings. Transp. Res. B 42, 759–770 (2008)

  6. Geroliminis, N., Levinson, D.: Cordon pricing consistent with the physics of overcrowding. In: Proceedings of the 18th International Symposium on Transportation and Traffic Theory (2009)

  7. Hendrickson, C., Plank, E.: The flexibility of departure time for work trips. Transp. Res. A 18, 25–36 (1984)

  8. Hollander, Y.: Direct versus indirect models for the effects of unreliability. Transp. Res. A 40, 699–711 (2006)

  9. Jou R.C., Kitamura R., Weng M.C., Chen C.C.: Dynamic commuter departure time choice under uncertainty. Transp. Res. A 42, 774–783 (2008)

  10. Levinson, D., Harder, K., Bloomfield, J., Carlson, K.: Waiting tolerance: ramp delay vs. freeway congestion. Transp. Res. F 9, 1–13 (2006)

  11. Levinson, D., Krizek, K.: Planning for Place and Plexus: Metropolitan Land Use and Transport. Routledge, New Yrok (2008)

  12. Levinson, D., Zofka, E.: The metropolitan travel survey archive: a case study in archiving. In: Stopher P., Stecher C. (eds.) Travel Survey Methods: Quality and Future Directions, Proceedings of the 5th Intenational Conference on Travel Survey Methods, pp. 223–238. Emerald Group Pub Ltd, Bingley (2006)

  13. Metropolitan Council of the Twin Cities Area: 2000 Travel behavior inventory home interview survey: data and methodology. Metropolitan Council, St. Paul, MI (2003)

  14. Muñoz, J., Daganzo, C., Center, T., University of California (System): Fingerprinting traffic from static freeway sensors. University of California Transportation Center, University of California, California (2000)

  15. Noland, R., Small, K., Koskenoja, P., Chu, X.: Simulating travel reliability. Reg. Sci. Urban Econ. 28, 535–564 (1998)

  16. Regional Transportation Management Center: http://www.dot.state.mn.us/tmc/tmctools.html. Accessed October 2008

  17. Sarvi, M., Horiguchi, R., Kuwahara, M., Shimizu, Y., Sato, A., Sugisaki, Y.: A methodology to identify traffic condition using intelligent probe vehicles. In: Proceedings of 10th ITS World Congress, Madrid, pp. 17–21 (2003)

  18. Small, K.: The scheduling of consumer activities: work trips. Am. Econ. Rev. 72, 467–479 (1982)

  19. Tilahun, N., Levinson, D.: A moment of time: valuing reliability using stated preference. J. Intell. Transp. Syst. (2006, in press)

  20. University of Minnesota: Metropolitan Travel Survey Archive. http://www.surveyarchive.org (2003). Accessed Oct 2008

  21. Vickrey, W.: Pricing in urban and suburban transport. Am. Econ. Rev. JSTOR 53, 452–465 (1963)

  22. Vickrey, W.: Congestion theory and transport investment. Am. Econ. Rev. 59, 251–260 (1969)

  23. Wu, X., Levinson, D., Liu, H.: Perception of waiting time at signalized intersections. Transp. Res. Rec. 2135, 52–59 (2009)

Download references

Author information

Correspondence to Pavithra Parthasarathi.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Parthasarathi, P., Srivastava, A., Geroliminis, N. et al. The importance of being early. Transportation 38, 227–247 (2011). https://doi.org/10.1007/s11116-010-9301-1

Download citation

Keywords

  • Earliness to lateness
  • Congestion pricing
  • Macroscopic traffic model