Program Overview

Often, the most cost-effective way to solve a problem related to transportation is to manage demand. Transportation demand management (TDM) focuses on helping people change their travel behavior—to meet their travel needs by using different modes, traveling at different times, making fewer trips or shorter trips, or taking different routes. Through the nation’s largest and most comprehensive TDM research program, CUTR’s diverse research portfolio ranges from guidance for integrating TDM into the transportation planning process to developing the TRIMMS(tm) tool for estimating impact of TDM to developing patented technologies for global positioning system-enabled mobile phones to track travel behavior. Our technical assistance efforts include managing Best Workplaces for Commuters, which recognizes and supports employer-provided transportation services; operating the Florida TDM Clearinghouse and the National TDM and Telework Clearinghouse, including its online support center; producing netconferences; administering a 2,550+ member TRANSP-TDM listserv to foster peer-to-peer exchanges; advancing safety by conducting targeted bicycle and pedestrian safety educational outreach programs to community groups; facilitating Safe Routes to Schools; and offering a nationally recognized Commuter Choice Certificate and Social Marketing in Transportation Certificate training programs.

Sean Barbeau, Ph.D.

Principal Mobile Software Architect for R&D; USF Associate Director Technology Transfer Traffic Demand Management
Phone: 813-974-7208
Photo of Sean Barbeau, Ph.D.

Biography

Education:

Ph.D, Computer Science & Engineering (Mobile Computing) and Minor in Geographic Information Systems, University of South Florida, 2012

M.S., Computer Science, University of South Florida, 2009

B.S., Computer Science with Minor in Electronic Music, University of South Florida, 2003

 

Bio:

I’m the Principal Mobile Software Architect for R&D in CUTR at the University of South Florida.  I’m part of the CUTR Transportation Demand Management group, and I lead a group of software engineers in our Location-Aware Information Systems lab to create prototype location-based services and intelligent mobile apps as part of government and industry-sponsored research.  My research interests include intelligent location-based services for cell phones, lightweight data communication frameworks for mobile devices, and mobile application optimization to conserve battery life.

 

Representative Experience:

Principal Mobile Software Architect for R&D                                              Aug 2008 – Present

Center for Urban Transportation Research, College of Engineering, University of South Florida

  • Lead team of software engineers to implement prototype mobile software applications
  • Served as the principal mobile software architect for research projects at the Location-Aware Information Systems Lab
  • Developed, directed, and managed research projects as PI or Co-PI

 

Visiting Research Associate                                                         Aug 2004 – Aug 2008

Center for Urban Transportation Research, College of Engineering, University of South Florida

  • Developed, directed, and managed research projects as PI or Co-PI
  • Served as the principal mobile software engineer for research projects at the Location-Aware Information Systems Lab

 

Research Assistant                                                                        Aug 1999 – Aug 2004

College of Engineering, University of South Florida

  • Served as a software engineer for research project collaborations between the Department of Computer Science & Engineering and the Center for Urban Transportation Research

 

Publications:

  1. Sean J. Barbeau, Rafael A. Perez, Miguel A. Labrador, Alfredo J. Perez, Philip L. Winters, Nevine Labib Georggi,  http://www.locationaware.usf.edu/wp-content/uploads/2011/10/Barbeau-et-al.-A-Location-Aware-Framework-for-Intelligent-Real-Time-Mobile-Applications-mpc2011030058-final-print.pdf,” IEEE Pervasive Computing, vol. 10, no. 3, pp. 58-67, July-Sept. 2011.
  2. Paul A. Zandbergen and Sean J. Barbeau.  “Positional Accuracy of Assisted GPS Data from High-Sensitivity GPS-enabled Mobile Phones,” The Journal of Navigation, volume 64, issue 03, pp. 381-399.  July 2011.
  3. Sean J. Barbeau, Miguel A. Labrador, Nevine L. Georggi, Philip L. Winters, Rafael A. Perez.  “The Travel Assistance Device:  Utilizing GPS-enabled Mobile Phones to Aid Transit Riders with Special Needs,” Institution of Engineering and Technology (IET) Intelligent Transportation Systems, 2010, Vol. 4, Iss. 1, pp. 12–23. doi: 10.1049/iet-its.2009.0028. © The Institution of Engineering and Technology 2010.
  4. Sean J. Barbeau, Miguel A. Labrador, Nevine L. Georggi, Philip L. Winters, Rafael A. Perez.  “TRAC-IT: A Software Architecture Supporting Simultaneous Travel Behavior Data Collection and Real-Time Location-Based Services for GPS-Enabled Mobile Phones,” Proceedings of the National Academy of Sciences’ Transportation Research Board 88th Annual Meeting, Paper #09-3175.  January, 2009.
  5. Sean J. Barbeau, Nevine L. Georggi, Philip L. Winters.  “Global Positioning System Integrated with Personalized Real-Time Transit Information from Automatic Vehicle Location,” Transportation Research Record: Journal of the Transportation Research Board, Transit 2010 Vol 1, No. 2143, pp. 168-176, October 2010.
  6. Sean J. Barbeau, Miguel A. Labrador, Philip L. Winters, Rafael Perez, Nevine Labib Georggi, http://www.locationaware.usf.edu/wp-content/uploads/2011/09/Barbeau-Location-API-2.0-for-J2ME-COMCOM3573.pdf Computer Communications, Volume 31, Issue 6, Advanced Location-Based Services, 18 April 2008, Pages 1091-1103.
  7. Sean J. Barbeau, Miguel A. Labrador, Philip Winters, Rafael Perez and Nevine Labib Georggi, “A General Architecture in Support of Interactive, Multimedia, Location-based Mobile Applications”, IEEE Communications Magazine, Vol. 44, No. 11, pp. 156-163, November 2006. © 2006 IEEE.
  8. U.S. Patent # 8,036,679 – Optimizing performance of location-aware applications using state machines – Dynamically adjusts GPS sampling rates to allow high resolution tracking while moving and conservation of battery energy when  stopped.  Issued October 11, 2011, U.S. Patent and Trademark Office.
  9. U.S. Patent # 8,249,807 – Method for Determining Critical Points in Location Data Generated by Location-Based Applications – Reduces the amount of location data sent over a wireless network by pre-filtering the data on-board a mobile device and eliminating “non-critical” points that aren’t needed to recreate the device’s path.  Reduced data tranmissions result in reduced battery energy consumption and reduced data costs.  Issued August 21, 2012.

 

 

For more information on patents and publications, please see:

http://www.locationaware.usf.edu/publications/

 

For information on research projects, please see:

http://www.locationaware.usf.edu/

 

 

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