Overview
Travel demand modeling is a crucial component of transportation planning and system management. Unfortunately, creating an accurate model of network traffic patterns can be difficult and time consuming. The calibration and validation of travel demand modeling requires the use of extensive datasets that describe the travel characteristics of people in the modeling area. This study investigates the potential use of connected and automated vehicle (CAV) data for both statewide and regional-level modeling. While there are related privacy and data management issues to overcome, the data collected from CAVs holds great promise for supporting travel forecasting modeling, transportation system management and planning.