Post-Frontiers Conference 2019

An orderly, lawful populace is essential to any functioning democracy.

How do we balance the 1st Amendment’s rights to assembly and free speech with this imperative? In this paper, we present a possibility for safe crowd control via automated vehicles. Through supervised learning based on training data of herding, we develop a spatial algorithm that can be implemented in self-driving vehicles. With a baseline algorithm, further testing can be performed in the field — after sporting events, during parades, and amidst demonstrations — in order to determine the efficacy of the algorithm, particular with respect to safety for law enforcement officers.

Our research group operates out of the Kalanick Center for Automation at Carnegie Mellon University, with additional funding from Governor Peduto’s PA Tech Forward initiative and the Department of Homeland Security.