Evaluating Fuzzed Connected Vehicle Data to Support Travel Demand Modeling

About the project:

VDOT is currently developing a method to use connected vehicle (CV) data to support the development of travel demand models. The work includes estimating nuanced information about trip time, trip distance, and path patterns with fine geographic and temporal resolution. Recently, CV trajectory data providers in the U.S. started to “fuzz” the raw vehicle trajectory data for privacy reasons. These data-fuzzing algorithms may affect the feasibility, accuracy, and robustness of VDOT’s application of CV data for planning purposes. This project assesses the impact of data fuzzing algorithms used by two different CV trajectory data providers, Streetlight and Compass IoT, on potential VDOT application scenarios related to calibration and validation of transportation planning models. This research will further assess the potential of using Compass IoT data to support the development of truck ODs, and if feasible, a valuable enhancement to the current VDOT truck origin-destination (OD) estimation procedure.

Project Team

Principal Investigators

Co-Principal Investigators

Project Manager

Project Monitor

Members

Other Investigators