Overview
This webinar provides information for enhancing Active Transportation and Demand Management (ATDM) applications using advanced and emerging technologies and data sources. These include decision support system technologies, vehicle technologies, sensor technologies, connected vehicle/traveler data, connected infrastructure data, and map technologies. It first discussed the emerging technologies and data sources, along with how they can be paired with ATDM applications. It provides information on planning, organizing, designing, implementing, operating, and maintaining, new and enhanced ATDM deployments. A number of case studies are also discussed.
Target Audience: State and local transportation agencies
Learning Objectives: Webinar attendees will understand the opportunities and challenges of enhancing ATDM applications with advanced and emerging technologies and data sources.
Instructors
Moderator:
David Hale (Leidos): Dr. David Hale is a certified Project Management Professional with 25 years of experience in traffic analysis tools and traffic control strategies. Dr. Hale has conducted innovative research for FHWA on ATM strategies, and co-authored the ATDM chapters of the Highway Capacity Manual.
Presenters:
James Colyar (FHWA): James Colyar is a Transportation Specialist with the Federal Highway Administration (FHWA), Office of Operations. He has been with FHWA for over 15 years and has worked in offices in Arizona, Virginia, Washington D.C., and Washington state. He has experience in traffic engineering, traffic analysis and modeling, intelligent transportation systems, and transportation systems management and operations.
Daniel Lukasik (Parsons): Daniel Lukasik works at Parsons and is the principal investigator for FHWA’s project on Enhancing ATDM with Advanced and Emerging Technologies and Data Sources. Dan is also Co-Chair of the TRB Active Traffic Management Subcommittee and as lead of the Parsons ITS Sector, has overseen the deployment of over 40 ATDM projects/strategies.
Jiaqi Ma (University of Cincinnati): Jiaqi Ma is the Director of Advanced Transportation Collaborative at the University of Cincinnati. He has led research projects covering areas such as vehicle-highway automation, Intelligent Transportation Systems, connected vehicles, shared mobility, simulation modeling, travel behavior modeling, and artificial intelligence.