When you drive to work, school, the grocery store, a doctor’s appointment or meet your friends for lunch or a golf outing, did you ever stop to think about all the various factors involved with your travel?
Do you travel alone, or do you drop someone off along the way? What time do you leave the house and what route are you likely to take? And how do you travel?
Pima Association of Governments is looking to better understand the answers to those travel demand questions through the transition from a trip-based model to a new activity-based model (ABM). The ABM, which offers the latest in modeling technology capabilities, will be used to predict how, when and where people travel in the greater Tucson region.
This advanced, simulating model technology which focuses on travel demand provides greater analytical details for modelers to have a clearer understanding of daily travel patterns of individuals and households, such as departure times, to inform PAG’s long-term transportation planning efforts.
“This work will help PAG establish a better understanding of finer-resolution travel behavior that is more representative of travel in our region,” said Paul Casertano, PAG’s Transportation Planning Director. “Additionally, the PAG ABM development will support alignment with the greater Phoenix region and activity-based modeling done by Maricopa Association of Governments. This will allow us to improve how we prepare for and manage future growth and expanding transportation needs through the Sun Corridor mega region.”
Household travel survey data is also used in the model. That data is reviewed to ensure it closely matches observed behavior in the greater Tucson region and is validated through other sources of data.
Some of the other inputs for the activity-based model include building a representative population for the greater Tucson region, which is now over 1 million residents, and a representative employer database. The region has approximately 400,000 employees, including from major employers such as Raytheon, Davis-Monthan Air Force Base, the University of Arizona and Banner University Medical Center.
Geographic inputs include information about the local jurisdictions, as well as the major highways of Interstates 10 and 19. Information on how roadways are configured, such as the roadway network having 80% of arterial roads, is input to help assess traffic congestion.
The activity-based model also can forecast new mobility impacts, such as connected and autonomous vehicles, ridesharing and home delivery services generated through e-commerce. Service providers, for example, would be TuSimple, Waymo, Lyft, Uber or Amazon.
The goal is for the activity-based model is to better represent changing travel options and behaviors to support regional transportation planning efforts. “The ABM enhances our overall modeling capabilities, and the combined data gives us new tools to deliver better products and services,” Casertano said.