Table of Contents
International Journal of Vehicular Technology
Volume 2012, Article ID 532568, 8 pages
http://dx.doi.org/10.1155/2012/532568
Research Article

StopWatcher: A Mobile Application to Improve Stop Sign Awareness for Driving Safety

Department of Computer Science and Engineering, New Mexico Institute of Mining and Technology, Socorro, NM 87801, USA

Received 30 June 2012; Accepted 30 November 2012

Academic Editor: Nandana Rajatheva

Copyright © 2012 Carl Tucker et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. U.S. Department of Transportation Federal Highway Administration, “Low-cost safety improvements can improve safety at stop sign controlled intersections,” 2002, http://safety.fhwa.dot.gov/intersection/resources/casestudies/fhwasa09010/stop_article.cfm.
  2. Visiting My Councilor, 2008, http://harrumpher.com/?cat=6.
  3. Hidden snow stop sign, 2011, http://peicanada.com/snow_bound_west_prince_pei/image/hidden_snow_stop_sign.
  4. J. Curiel, “Mill Valley: Stop sign obscured by foliage,” 2009, http://articles.sfgate.com/2009-07-08/bay-area/17216162_1_sign-stop-intersection.
  5. J. Sena, “Frequently ignored stop sign leads to close calls,” 2008, http://www.santafenewmexican.com/Local%20News/Downtown-dilemma.
  6. S. Xu, “Robust traffic sign shape recognition using geometric matching,” IET Intelligent Transport Systems, vol. 3, no. 1, pp. 10–18, 2009. View at Publisher · View at Google Scholar · View at Scopus
  7. A. De la Escalera, J. M. Armingol, and M. Mata, “Traffic sign recognition and analysis for intelligent vehicles,” Image and Vision Computing, vol. 21, no. 3, pp. 247–258, 2003. View at Publisher · View at Google Scholar · View at Scopus
  8. C. Y. Fang, C. S. Fuh, P. S. Yen, S. Cherng, and S. W. Chen, “An automatic road sign recognition system based on a computational model of human recognition processing,” Computer Vision and Image Understanding, vol. 96, no. 2, pp. 237–268, 2004. View at Publisher · View at Google Scholar · View at Scopus
  9. X. Gao, L. Podladchikova, D. Shaposhnikov, K. Hong, and N. Shevtsova, “Recognition of traffic signs based on their colour and shape features extracted using human vision models,” Journal of Visual Communication and Image Representation, vol. 17, no. 4, pp. 675–685, 2006. View at Publisher · View at Google Scholar · View at Scopus
  10. S. H. Hsu and C. L. Huang, “Road sign detection and recognition using matching pursuit method,” Image and Vision Computing, vol. 19, no. 3, pp. 119–129, 2001. View at Publisher · View at Google Scholar · View at Scopus
  11. P. Jimenez, S. Arroyo, H. Moreno, F. Ferreras, and S. Bascon, “Traffic sign shape classification evaluation II: FFT applied to the signature of blobs,” in Proceedings of the IEEE Intelligent Vehicles Symposium, pp. 607–612, Las Vegas, Nev, USA, June 2005.
  12. P. Mohan, V. N. Padmanabhan, and R. Ramjee, “Nericell: rich monitoring of road and traffic conditions using mobile smartphones,” in Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems (SenSys '08), pp. 323–336, Raleigh, NC, USA, November 2008. View at Publisher · View at Google Scholar
  13. J. Dai, J. Teng, X. Bai, Z. Shen, and D. Xuan, “Mobile phone based drunk driving detection,” in Proceedings of the 4th International Conference on Pervasive Computing Technologies for Healthcare, pp. 1–8, March 2010. View at Publisher · View at Google Scholar · View at Scopus
  14. M. Fazeen, B. Gozick, R. Dantu, M. Bhukhiya, and M. C. Gonzalez, “Safe driving using mobile phones,” IEEE Transactions on Intelligent Transportation Systems, vol. 13, no. 3, pp. 1462–1468, 2012. View at Publisher · View at Google Scholar
  15. “Manual on uniform traffic control devices (MUTCD),” 2003, http://mutcd.fhwa.dot.gov/pdfs/2003/pdf-index.htm.
  16. http://dev.mysql.com/doc/refman/5.1/en/data-types.html.
  17. E. Ben-Joseph, “Residential street standards & neighborhood traffic control: a survey of cities' practices and public officials' attitudes,” Institute of Urban and Regional Planning, University of California at Berkeley, 1995, http://web.mit.edu/ebj/www/Official%20final.pdf.