Training

June 12, 2024 | 11:00 a.m. - 12:30 p.m.

MS Teams Webinar Recording

Travel Demand Models are a common method for forecasting traffic flows on the transportation system using current travel behavior to predict future travel patterns. To many, they are complicated and surrounded with a bit of mystery, but they do not have to be. Models can be a valuable source of information into long range planning, traffic impact analysis, and project development. Join us on June 12 as a panel shares their expertise and insights into practical applications of travel demand models.

September 11, 2024 I 11:00 a.m. - 12:30 p.m.

MS Teams Webinar -  Recording

This webinar will dive into the critical role of microsimulation in informing transportation decision-making. Participants will:

• Categorize traffic study types as outlined in the FDOT Traffic Analysis Handbook.
• Explore the application of microsimulation to generate valuable insights for transportation planning.
• Gain a comprehensive understanding of various simulation tools and their suitability for different project requirements.
• Acquire a basic understanding of microsimulation model development, calibration, and validation.
• Identify the strengths, limitations, and emerging trends in microsimulation modeling.
  

Presenters:

• Sunil Doddapaneni, PE, IMSA III
• Govardhan Muthyalagari, PE, PTOE

August 21, 2024 I 1:00 p.m. - 2:30 p.m.

LTAP Webinar - Recording

This webinar will explore travel forecasting models tailored specifically for planners and decision-makers in Florida. It will provide participants with a high-level overview of travel models, highlighting their significance in informing planning initiatives and decision-making. From understanding how modeling fits in the overall planning process and their practical applications, attendees will gain valuable insights into the connection between planning and travel demand modeling.

This course provides a basic introduction on the use of Python for transportation planning and modeling. It includes a brief review of the fundamentals of writing code in Python, as well as modules on tabular data analysis, visualizations, geographic analysis, and discrete choice modeling. The course assumes that students are already somewhat familiar with the methodologies and mathematical tools of transportation modeling in general, and focuses exclusively on the how these tools and models are constructed and used within Python.

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Python Training Recordings

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As part of the D1RPM 2.0 webinar series, these recorded webinars provide details about the District One Regional Planning Model (version 2.0), a four-step, trip-based FSUTMS model beginning the change from PSWAADT TO AADT and continuing on with in-depth discussions of each model processes. We discuss the model's special features: airport trip distribution, the heavy truck procedure and connected and automated vehicles (CAV) modeling procedure.

This workshop is designed for managers and non-modelers to gain a better understanding of the travel demand forecasting process. It provides an overview of the transportation planning process, traveling demand forecasting methodologies, and FSUTMS modules under Cube. Participants will learn the underlying theories of modeling and see the benefits of Cube's abilities to produce presentation graphics for reports and meetings.

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• FSUTMS Data Mining Presentation
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