New Technology Sources for Origin-Destination (O-D) Data: Overview and Lessons Learned (May 12, 2016)

Recording: https://connectdot.connectsolutions.com/p56hpehft1q/

Date: May 12, 2016

Description: This webinar will provide potential users of O-D data sourced from cell, GPS, and Bluetooth technologies current information and guidance on the uses and applications of these new passive data sources. It will clarify what the data from each technology represent, provide a better understanding of the current capabilities and limitations of each source, and provide information on the use of these technologies for different types of O-D studies.

The webinar will provide lessons learned and key takeaways from 1) O-D studies using cell, third-party GPS, and/or Bluetooth over the past six years and 2) researchers with many years of hands-on experience in scoping these studies, processing and analyzing the data, and working with private sector data aggregators to develop and refine their O-D data for transportation planning and modelling. It will include summary findings on how new technology O-D data compare to model results as well as how they compare in relation to different types and categories of trips.

The webinar will begin with a high level overview of new technology O-D data for managers and policy-types and then proceed into more technical detail and ‘how-to’s for analysts and modelers.

Presenters: Ed Hard is a Research Scientist and Manager of the Transportation Planning Program of the Texas A&M Transportation Institute in College Station, Texas. He has over 25 years of experience as a transportation planner, including 14 years as a TTI researcher, and over 11 years as a practitioner in the public and private sectors. Mr. Hard leads applied research and project development in new and emerging methods/technologies for collection of O-D data for travel surveys and studies. In 2014, he led an external O-D study in Tyler, TX that compared O-D results between cellular, third-party GPS and Bluetooth and he is currently leading a similar project in the Dallas-Ft. Worth region of Texas He is also leading a study for the Arizona DOT to assess new technology O-D data and develop an implementation plan for statewide O-D data collection. Ed serves as TTI’s manager for the development and design of travel surveys as part of TxDOT’s robust statewide travel survey program. He is a member of TRB’s Travel Survey Methods (ABJ40) and Transportation and Land Development (ADD30) committees.

Byron Chigoy is an Associate Research Scientist with the Texas A&M Transportation Institute in Austin, Texas. Mr. Chigoy has ten years of experience in transportation planning and data analytics. He is a lead researcher at TTI in the analysis of passive data collected through a variety of means including Bluetooth, Cellular, GPS, and Automated License Plate Recorder (ALPR). Mr. Chigoy has extensive experience in data analysis and GIS conflation techniques to evaluate state and national travel behavior data. These data include the NHTS, Commodity Flow Survey, Longitudinal Employer-Household Dynamics/ Origin-Destination Employment Statistics, USACE Waterborne Commerce, US Census, BLS Employment data, Highway Performance and Monitoring System, and various other local and regional data. Mr. Chigoy has an expertise in the use of RDMS, including PostgreSQL/PostGIS, for geospatial analytics and data mining of large data sets. Additional software expertise includes ArcGIS, TransCAD, Cube Software Suite, SQL, SPSS, and QGIS. Prior to joining TTI, Mr. Chigoy was in consulting for eight years developing traffic data for micro-simulation studies of sub-areas and corridors.

Praprut Songchitruksa is an Associate Research Engineer with the Texas A&M Transportation Institute in College Station, Texas. Dr. Songchitruksa has 16 years of experience as a professional engineer, a researcher, and an educator. His expertise includes traffic simulation, statistical computing, and connected vehicles. He has extensive experience with large-scale data analytics and spatio-temporal data mining for transportation planning applications. His recent projects include the FHWA Urban Partnership Agreement evaluation project, the software for analyzing GPS-based travel surveys, the OD data mining from private-sector GPS data, the Tyler OD comparison study, and the real-time traffic forecasting system for smart work zones. In addition, he is a lead simulation engineer for an ongoing FHWA project to develop an advanced platform for connected/automated vehicle simulation. Dr. Songchitruksa is well versed in a variety of programming languages and data analytics platforms including C++, Python, VB .Net, R, and ArcGIS. He was the recipient of the TRB Best Paper Award for Young Researchers in 2014. He received his doctoral degree in Civil Engineering from Purdue University and is a registered professional engineer in the State of Texas.