Although the first applications of artificial intelligence (AI) to travel modeling and forecasting date to the early 1990s in academic research and the first applications in adopted agency models have only appeared in the past several years, its adoption is accelerating, and over the next decade AI has the potential to truly revolutionize travel modeling the way it has revolutionized other disciplines like computer vision and natural language processing.
FHWA undertook the project, Enhancing Travel Forecasting Practices and Effective Use of Travel Forecasts in Long Range Transportation Planning Through the Application of Artificial Intelligence and Big Data (TOPR HEPP240005PR), in order to, “Investigate the role artificial intelligence (AI) could play in enhancing travel forecasting,” and “Develop a prototype / playbook for incremental improvement to travel forecasting.” This webinar is the first in a series of TMIP webinars on artificial intelligence (AI) in travel modeling being organized as part of this project and will introduce both the webinar series and the project of which it is a part as well as serve as an introduction to basic topics in AI for travel modeling and forecasting.
Vince Bernardin, PhD, Vice President at Caliper Corporation, is one of the nation’s foremost experts on the incorporation of both big data and AI in the practice of travel modeling. He was the first to use big data for statewide modeling (2010) and activity-based modeling (2016), and the first to incorporate machine learning/AI methods including boosting (2017) and decision trees (2021). He is serving as Project Manager/Principal Investigator for this project.
Rama Balakrishna, PhD, is a Principal Transportation Scientist at Caliper, where he works on cutting-edge data analytics, travel demand and traffic simulation modeling approaches. He is an expert on machine learning (ML) algorithms and routinely grapples with the role of Artificial Intelligence (AI) in the modeling process. Dr. Balakrishna holds multiple certifications on ML and AI, and taught the graduate course “Behavioral Science, Artificial Intelligence and Mobility” at MIT last Fall. He is scheduled to teach it again this year.