Skip to main content
Intended for healthcare professionals
Free access
Research article
First published online January 1, 2011

Selection of Source and Use of Traffic Information in Emergency Situations

Abstract

The access and the use of advanced traveler information systems (ATISs) by drivers during normal commuting have been extensively assessed and analyzed. Emergency managers and transportation officials have extended the results of studies of ATIS use under routine conditions to emergency scenarios under the assumption that drivers' responses to information under emergency conditions mimic those seen under normal driving conditions. A recent survey of potential hurricane evacuees suggests the need to revisit this assumption. Results indicate that although commercial radio reports and variable message signs continue to be the sources of traffic information cited the most frequently, other information sources (mobile phones, in-car systems such as Global Positioning System devices, and the Internet) have significantly increased in importance. Rapid growth in user rates and the relatively low cost of implementation suggest that a revision of plans for emergency transportation information communications may be warranted. Better, more effective use of ATISs during emergency situations, especially when traffic incidents occur, may lead to improved and more reliable travel times and improved safety and emergency response. With the use of factor analysis, four driver personalities are identified, with each one characterized by the proclivity for and response to traffic information. This information will be of interest to developers and users of ATISs and to those responsible for emergency management and transportation planning.

References

1. Dow K., and Cutter S. L. Public Orders and Personal Opinions: Household Strategies for Hurricane Risk Assessment. Global Environmental Change Part B: Environmental Hazards, Vol. 2, No. 4, 2000, pp. 143–155.
2. Prater C. S., Wenger D., and Grady K. Hurricane Bret Post Storm Assessment: A Review of the Utilization of Hurricane Evacuation Studies and Information Dissemination. Texas A&M University Hazard Reduction and Recovery Center, College Station, 2000. http://archone.tamu.edu/hrrc/Publications/researchreports/index.html. Accessed June 16, 2009.
3. Wolshon B., Hamilton E. U., Levitan M., and Wilmot C. Review of Policies and Practices for Hurricane Evacuation. II. Traffic Operations, Management, and Control. Natural Hazards Review, Vol. 6, No. 3, 2005, pp. 143–161.
4. Mehndiratta S. R., Kemp M. A., Lappin J. E., and Nierenberg E. Likely Users of Advanced Traveler Information Systems: Evidence from the Seattle Region. In Transportation Research Record: Journal of the Transportation Research Board, No. 1739, TRB, National Research Council, Washington, D.C., 2000, pp. 15–24.
5. Goulias K. G., Kim T.-G., and Pribyl O. A Longitudinal Analysis of Awareness and Use for Advanced Traveler Information Systems. Journal of Intelligent Transportation Systems, Vol. 8, No. 1, 2004, pp. 3–17.
6. Khattak A. J., Schofer J. L., and Koppelman F. S. Factors Influencing Commuters' En Route Diversion Behavior in Response to Delay. In Transportation Research Record 1318, TRB, National Research Council, Washington, D.C., 1991, pp. 125–136.
7. Khattak A., Polydoropoulou A., and Ben-Akiva M. Modeling Revealed and Stated Pretrip Travel Response to Advanced Traveler Information Systems. In Transportation Research Record 1537, TRB, National Research Council, Washington, D.C., 1996, pp. 46–54.
8. Khattak A. J., Pan X., Williams B. M., Rouphail N. M., and Fan Y. Traveler Information Delivery Mechanisms: Impact on Consumer Behavior. In Transportation Research Record: Journal of the Transportation Research Board, No. 2069, Transportation Research Board of the National Academies, Washington, D.C., 2008, pp. 77–84.
9. Scheisel R., and Demetsky M. J. Evaluation of Traveler Diversion Due to En-Route Information. Mid-Atlantic Universities Transportation Center Report UVA/29472/CE00/103. Virginia Department of Transportation and U.S. Department of Transportation, Charlottesville, 2000.
10. Levinson D., and Huo H. Effectiveness of VMS Using Empirical Loop Detector Data. Presented at 82nd Annual Meeting of the Transportation Research Board, Washington, D.C., 2003.
11. Maier-Speredelozzi V., Wang J.-H., Collyer C., Thomas N., Clark A., Severson J., and Chaparro K. S. Disseminating Information with Variable Message Signs During Natural or Human-Caused Disasters. European Conference of Transport Research Institutes, Young Researchers Seminar, May 27–30, 2007, Brno, Czech Republic. www.ectri.org/YRS07/Papiers/Session-15/Mayer-Speredelozi.pdf. Accessed July 29, 2010.
12. Ye Z., Chaudhari J., Booth J., and Posadas B. Evaluation of the Use of Rural Transportation Infrastructure in Evacuation Operations. Journal of Transportation Safety and Security, Vol. 2, No. 2, 2010, pp. 88–101.
13. Robinson R. M., and Khattak A. Route Change Decision Making by Hurricane Evacuees Facing Congestion. In Transportation Research Record: Journal of the Transportation Research Board, No. 2196, Transportation Research Board of the National Academies, Washington, D.C., 2010, pp. 168–175.
14. Robinson R. M. Modeling Decision Making Related to Incident Delays During Hurricane Evacuations. PhD dissertation. Old Dominion University, Norfolk, Va., 2010.
15. Yim Y., Khattak A. J., and Raw J. Traveler Response to New Dynamic Information Sources: Analyzing Corridor and Areawide Behavioral Surveys. In Transportation Research Record: Journal of the Transportation Research Board, No. 1803, Transportation Research Board of the National Academies, Washington, D.C., 2002, pp. 66–75.
16. Pett M. A., Lackey N. R., and Sullivan J. J. Making Sense of Factor Analysis. Sage Publications, Thousand Oaks, Calif., 2003.

Cite article

Cite article

Cite article

OR

Download to reference manager

If you have citation software installed, you can download article citation data to the citation manager of your choice

Share options

Share

Share this article

Share with email
EMAIL ARTICLE LINK
Share on social media

Share access to this article

Sharing links are not relevant where the article is open access and not available if you do not have a subscription.

For more information view the Sage Journals article sharing page.

Information, rights and permissions

Information

Published In

Article first published online: January 1, 2011
Issue published: January 2011

Rights and permissions

© 2011 National Academy of Sciences.
Request permissions for this article.

Authors

Affiliations

R. Michael Robinson
Virginia Modeling, Analysis, and Simulation Center, Old Dominion University, Suffolk, VA 23435.
Asad Khattak
Department of Civil and Environmental Engineering, 135 Kaufmann Hall, Old Dominion University, Norfolk, VA 23529.

Notes

Metrics and citations

Metrics

Journals metrics

This article was published in Transportation Research Record: Journal of the Transportation Research Board.

VIEW ALL JOURNAL METRICS

Article usage*

Total views and downloads: 119

*Article usage tracking started in December 2016


Altmetric

See the impact this article is making through the number of times it’s been read, and the Altmetric Score.
Learn more about the Altmetric Scores



Articles citing this one

Receive email alerts when this article is cited

Web of Science: 0

Crossref: 5

  1. Ten Takeaways from the COVID-19 Pandemic for Transportation Planners
    Go to citation Crossref Google ScholarPub Med
  2. ITS Technologies for Decision Making during Evacuation Operations: A R...
    Go to citation Crossref Google Scholar
  3. Online optimization with look-ahead for freeway emergency vehicle disp...
    Go to citation Crossref Google Scholar
  4. Awareness and Utilization of Advanced Traveler Information by Active S...
    Go to citation Crossref Google Scholar
  5. Generic Incident Model for Investigating Traffic Incident Impacts on E...
    Go to citation Crossref Google Scholar

Figures and tables

Figures & Media

Tables

View Options

View options

PDF/ePub

View PDF/ePub

Get access

Access options

If you have access to journal content via a personal subscription, university, library, employer or society, select from the options below:


Alternatively, view purchase options below:

Purchase 24 hour online access to view and download content.

Access journal content via a DeepDyve subscription or find out more about this option.