Fundamentals of Data Analytics and AI for Engineers
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.
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
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
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
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.
Artificial Intelligence in Transportation Engineering is ideal for transportation professionals and project managers who work with data-driven processes and systems.