Fundamentals of Data Analytics and AI for Engineers


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Fundamentals of Data Analytics and AI for Engineers

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Data Analytics and Artificial Intelligence in Transportation Engineering

  • Session 1: March 2, 2022 | 10:00 am – 2:00 pm Eastern Time
  • Session 2: March 9, 2022 | 10:00 am – 2:00 pm Eastern Time
  • Session 3: March 16, 2022 | 10:00 am – 2:00 pm Eastern Time
  • Virtual sessions via Zoom | Registration includes access to all three sessions. 

Preview

Agenda

Session 1

Introduction to Artificial Intelligence and Applications | Dr. Xilei Zhao
  • Intelligent Transportation Systems (ITS) and its relationship with data analytics
  • Data lifecycle, data pipelines, and data infrastructure for ITS
  • Foundation to data analytics for ITS
  • Fundamentals of transit service supply and demand
  • Public transit data resources: GTFS, AFC, and smart-card data analytics
  • Methods and algorithms for transit trip interference

Session 2

Apply Artificial Intelligence to Produce Visual Products| Dr. Jacob Yan 
  • Geospatial big data analytics in transportation
  • Workflow to automate downloading, mapping, and analysis of U.S. Census data
  • Basic spatial operations in R: spatial join
  • Develop maps in R
  • Transportation Applications: 1) spatiotemporal analysis of the relationship between shared micromobility and transit 2) analysis of crash data

Session 3

Artificial Intelligence for Traffic Engineering Applications | Dr. Sanjay Ranka
  • Data Mining, Machine Learning and Data Visualization 
  • Classification of transportation data
  • Clustering subsets of data by population, trips, mobility type, etc.
  • Identify outliers in transportation datasets
  • Apply deep learning techniques in transportation
  • Understand traffic signal performance through data analysis
  • Analyze data to detect traffic flow interruptions
  • Objective based transportation data visualization

Course Description

  • Applications using artificial intelligence offers solutions to existing transportation challenges as well as opening the door to the next generation of transportation developments. As more sensors are added to roadway infrastructure and vehicles themselves, opportunities are created to advance traffic signal timing efficiency and enhance safety applications for traditional vehicles as well as for connected and autonomous vehicles (CAVs). With the influx of high-resolution datasets and the need to process real-time and the necessity to integrate into existing systems a new toolbox of data methods is warranted. Data acquisition, management, and processing has and will continue to affect every aspect of the transportation system.
  • These methods are being tested and validated on the I-STREET Testbed in Gainesville, Florida--a collaboration of UFTI, the City of Gainesville, and the Florida Department of Transportation. I-STREET is a living laboratory for development of new transportation technologies that operates on City of Gainesville and University of Florida campus roadways.
  • Artificial Intelligence in Transportation Engineering will be presented by UFTI faculty who are at the forefront of techniques needed to manage, analyze, and visualize transportation data for the future. 

Audience

  • Artificial Intelligence in Transportation Engineering is ideal for transportation professionals and project managers who work with data-driven processes and systems. 

Professional Development Hours (PDH)

  • 9.0 PDH