Vehicular ad-hoc networks (VANETs) allow vehicles to communicate with infrastructure as well as with one another, which allows for navigation of autonomous vehicles (AVs) and improved safety and traffic management. However, these networks are susceptible to passive attackers who aim to ascertain and misuse vehicles’ location data through eavesdropping. In order to ensure location privacy, it is necessary to utilize macroscopic location privacy without sacrificing safety and quality of service for the user (in this case, the passenger of the AV). We aim to use the pre-defined k-anonymity protocol in a simulated environment to test optimal mix-zone locations, the incorporation of dummy trajectories, and alternate/redirected paths, in order to maximize privacy throughout the AV’s entire trajectory.