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Red-light cameras at intersections: Estimating preferences using a stated choice model

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  • Egbendewe-Mondzozo, Aklesso
  • Higgins, Lindsey M.
  • Shaw, W. Douglass

Abstract

Red-light cameras placed at intersections have the potential to increase safety, but they are often viewed as an invasion of privacy. Preferences for these cameras were explored using a stated choice model that presents key attributes of camera placements. Stated choice models involve careful experimental design, akin to experimental control in laboratory settings. A variety of design approaches were used, settling on a composition of the choice sets people face in the survey. To illustrate the approach, an internet survey was used with a convenience sample containing a high percentage of college students. The results show that while not the case independently, as the number of cameras and fines for violators are simultaneously increased, the preferences for one particular red light cameras program are likely to improve.

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Bibliographic Info

Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

Volume (Year): 44 (2010)
Issue (Month): 5 (June)
Pages: 281-290

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Handle: RePEc:eee:transa:v:44:y:2010:i:5:p:281-290

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Related research

Keywords: Red-light traffic cameras Stated choice models Random parameters logit;

References

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  1. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, October.
  2. Obeng, Kofi & Burkey, Mark, 2008. "Explaining crashes at intersections with red light cameras: A note," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(5), pages 811-817, June.
  3. Greg Chen & Rebecca N. Warburton, 2006. "Do speed cameras produce net benefits? Evidence from British Columbia, Canada," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 25(3), pages 661-678.
  4. Yang, Jianguo & Deng, Wen & Wang, Jinmei & Li, Qingfeng & Wang, Zhaoan, 2006. "Modeling pedestrians' road crossing behavior in traffic system micro-simulation in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(3), pages 280-290, March.
  5. Alexander Shapiro & Jos Berge, 2002. "Statistical inference of minimum rank factor analysis," Psychometrika, Springer, vol. 67(1), pages 79-94, March.
  6. Hossain, M., 2001. "Estimation of saturation flow at signalised intersections of developing cities: a micro-simulation modelling approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(2), pages 123-141, February.
  7. Siikamaki, Juha & Layton, David F., 2007. "Discrete choice survey experiments: A comparison using flexible methods," Journal of Environmental Economics and Management, Elsevier, vol. 53(1), pages 122-139, January.
  8. Al-Madani, Hashim M. N., 2003. "Dynamic vehicular delay comparison between a police-controlled roundabout and a traffic signal," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(8), pages 681-688, October.
  9. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
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