Unexpected versus expected network disruption: Effects on travel behavior

Adam Danczyk, Xuan Di, Henry X. Liu, David M. Levinson

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


This paper discusses the observed evolution of traffic in the Minneapolis-St Paul (Twin Cities) region road network following the unexpected collapse of the I-35W Bridge over the Mississippi River. The observations presented within this paper reveal that traffic dynamics are potentially different when a prolonged and unexpected network disruption occurs rather than a preplanned closure. Following the disruption from the I-35W Bridge's unexpected collapse, we witnessed a unique trend: an avoidance phenomenon after the disruption. More specifically, drivers are observed to drastically avoid areas near the disruption site, but gradually return after a period of time following the collapse. This trend is not observed in preplanned closures studied to date. To model avoidance, it is proposed that the tragedy generated a perceived travel cost that discouraged commuters from using these sections. These perceived costs are estimated for the Twin Cities network and found to be best described as an exponential decay cost curve with respect to time. After reinstituting this calibrated cost curve into a mesoscopic simulator, the simulated traffic into the discouraged areas are found to be within acceptable limits of the observed traffic on a week-by-week basis. The proposed model is applicable to both practitioners and researchers in many traffic-related fields by providing an understanding of how traffic dynamics will evolve after a long-term, unexpected network disruption.

Original languageEnglish (US)
Pages (from-to)68-78
Number of pages11
JournalTransport Policy
StatePublished - Jul 2017

Bibliographical note

Funding Information:
This research was partially funded by the National Science Foundation (CMMI 0825768). The views are those of the authors alone.

Publisher Copyright:
© 2017 Elsevier Ltd


  • Avoidance phenomenon
  • Perceived cost evolution
  • Traffic dynamic, I-35W Bridge collapse
  • Unexpected network disruption


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