“Information on how roadways are configured, such as the roadway network having 80% of arterial roads, is input to help assess traffic congestion,” PAG said.
Another goal is to use the model to better represent residents’ changing travel options and behaviors to ensure better regional transportation planning efforts.
The activity-based model can better forecast new mobility impacts, such as autonomous vehicles, ride-sharing and home delivery services, which have grown through online shopping. Some of these providers are companies such as TuSimple, Lyft, Uber or Amazon, PAG said.
“Autonomous vehicles might be a major transportation mode in 2045. The behavior of a family with autonomous vehicles would be different from another family without autonomous vehicles,” PAG said.
“A family could change the ownership of vehicles from two normal cars to one autonomous vehicle. This change would impact the daily activities of the family. This will affect the transportation demand on the network.”
An influx of these vehicles could be addressed by examining not only the daily activity changes but an impact to other transportation modes in the region.
The activity-based model will also be used to expand out of the region, said Paul Casertano, PAG’s transportation planning director in a statement.