T3 Webinar Overview

Adapting to Climate Change Using Intelligent Transportation Systems

Date:   Tuesday, May 10, 2016
Time:  1:00 PM – 2:30 PM ET
Cost:  All T3 webinars are free of charge
PDH:  1.5   View PDH Policy

T3 Webinars are brought to you by the Intelligent Transportation Systems (ITS) Professional Capacity Building (PCB) Program of the U.S. Department of Transportation's (U.S. DOT) ITS Joint Program Office (JPO). References in this webinar to any specific commercial products, processes, or services, or the use of any trade, firm, or corporation name is for the information and convenience of the public, and does not constitute endorsement, recommendation, or favoring by the U.S. DOT.

Background

Within the national framework for addressing climate change, Intelligent Transportation Systems (ITS) is an important strategy for meeting the growing need for climate resiliency and adaption. ITS uses a variety of sensors to monitor the highway network such as traffic volume and speed detectors, cameras, pavement, and weather monitoring systems. All sensors are designed to communicate continuously with a centralized Transportation Management Center (TMC). This sensor data, when integrated with construction and incident reports, are used by TMC operators to create real time situational awareness of the highway system for the benefit of travelers, public safety, emergency responders, and transportation managers.

Climate change has and will result in the increased frequency and severity of disrupting weather events. These events require a proactive response across the traffic, maintenance, and emergency management communities. New sensor technology and applications are being developed to help identify vulnerable regions and transportation routes that are subject to flooding, fog, smoke from wildfires or other harmful pollutants, high winds, ice, damaged pavement, and bridge weight restrictions. This approach will not only require new sensing capability from the field, but also a means of identifying alternate routes and/or alternate transportation modes. The following speakers will touch on all of these components in order to illustrate new approaches to building transportation resiliency and adapting to climate change.

Agenda

Dr. Matthew J. Barth will review current efforts to use localized air quality sensing and modeling to change transportation mode and trip routing behavior. Topics will include new distributed routing algorithms that will allow a city to better adapt to severe events and dynamic low emission zones to minimize localized pollutant emissions.

Dr. Erin Bell will describe new sensor technology that will transform the Memorial Bridge in New Hampshire into a “living” bridge by installing sensors that will provide engineers and the public with real time status data that will include information on the bridge's structural health, traffic conditions, weather conditions, and changes in sea level and tidal flow.

Mr. Connor McKay and Mr. Keith Bynum will discuss the City of Boston's efforts to incorporate real time social media feedback into their operations in order to improve traffic signal timings and to create a greater situational awareness of traffic flows throughout the downtown transportation network.

Target Audience

Anyone interested in climate change, Intelligent Transportation Systems, Transportation System Management and Operations (TSM&O); Bridge Engineers, City Planners, Emergency and Public Safety Managers, and academic and research staff.

Learning Objectives

• Gain a better understanding of the need for expanded transportation system monitoring to keep up with severe weather disruptions associated with climate change.
• Learn the latest technologies associated with Intelligent Transportation Systems (ITS) that monitor the transportation network and critical infrastructure.
• Gain a clearer understanding of how Transportation System Managers and Transportation Management Centers (TMCs) are using new sensor technology to improve their operations.
• Gain an understanding of how to plan for climate change using ITS.

The webinar will conclude with an online question and answer session.

Host

Mr. Paul Pisano, Team Leader of the Road Weather and Work Zone Management Team, Federal Highway Administration (FHWA), Office of Transportation Operations

Mr. Pisano will serve as host and briefly introduce current U.S. DOT efforts to improve environmental sensing and the corresponding capability of transportation system managers to counter severe weather and climate change impacts. Pisano has worked for the FHWA for over 31 years, and in his current capacity he is responsible for two programs: addressing the effects of weather on transportation safety and operations, and improving transportation safety and mobility in and around work zones. He is the recipient of the 2016 Kenneth C. Spengler Award from the American Meteorological Society, and his education is in Civil Engineering, holding Bachelor of Science and Master of Science degrees from the University of Maryland.

Presenters

Dr. Matthew J. Barth is the Yeager Families Professor at the College of Engineering, University of California-Riverside (UCR)

Dr. Barth is part of the Intelligent Systems faculty in Electrical Engineering and is also serving as the Director for the Center for Environmental Research and Technology (CE-CERT), UCR's largest multi-disciplinary research center. He received his B.S. degree in Electrical Engineering/Computer Science from the University of Colorado in 1984, and M.S. (1985) and Ph.D. (1990) degrees in Electrical and Computer Engineering from the University of California, Santa Barbara. Dr. Barth joined the University of California-Riverside in 1991, conducting research in Intelligent Systems. Dr. Barth's research focuses on applying engineering system concepts and automation technology to Transportation Systems, and in particular how it relates to energy and air quality issues. His current research interests include ITS and the Environment, Transportation/Emissions Modeling, Vehicle Activity Analysis, Advanced Navigation Techniques, Electric Vehicle Technology, and Advanced Sensing and Control.

Dr. Erin Bell, Department Chair, Assistant Professor of Civil and Environmental Engineering, University of New Hampshire

Dr. Bell is an associate professor and chair of the Department of Civil and Environmental Engineering at the University of New Hampshire in Durham, NH. She earned her Bachelor of Science in Civil Engineering from the Georgia Institute of Technology and her master's and doctoral degrees from Tufts University. She is also a registered professional engineer in New Hampshire and Massachusetts. Her research is related to the use of instrumentation and modeling for bridge management.

Mr. Connor McKay, Data Scientist at City of Boston - Department of Innovation and Technology

Mr. McKay works as a Data Scientist to transform raw civic data into actionable insights and visualizations for Boston's Citywide Analytics Team. Mr. McKay works in close collaboration with Boston's Transportation Department (BTD) and the Public Works Department. He is also the lead on Boston's data sharing relationship with the navigation application, Waze. His research interests and areas of practice encompass machine learning, traffic studies, intervention analyses, public policy, and text mining. Mr. McKay holds a BS degree in Political Science with a concentration in Public Policy from Northeastern University in Boston.

Mr. Keith Bynum, Senior Traffic Engineer, Boston Transportation Department (BTD)

Mr. Bynum has over 20 years of experience in urban traffic operations at various locations including Seattle, Providence, and the Central Artery/Tunnel project in Boston. He currently serves as the afternoon/evening supervisor of BTD's Traffic Management Center where he is responsible for BTD's traffic signal retiming program, developing and analyzing new traffic signal sequences and patterns, and attending community meetings regarding traffic signal issues. Mr. Bynum holds a Bachelor of Civil Engineering and EIT from the Georgia Institute of Technology.