Christopher Gojcz's thesis
– Executive Summary –
No clear guidance outlines how to use force or which type of force might be reasonable in confrontations with autonomous vehicles, leaving law enforcement without clear parameters to guide their interdiction decisions. This lack of guidance could lead to delayed and inconsistent responses, improper use of force, or inaction, all of which could cause the loss of life. An analysis of the interactions between law enforcement and autonomous vehicles reveals the degree to which current use-of-force models do, and do not, apply to situations requiring force to interdict an autonomous vehicle. There is scant research on whether law enforcement agencies should adopt a policy for using force to interdict autonomous drones, cars, buses, trucks, or vessels. Rather, the prevailing scholarship addresses models and guidelines based strictly on the human-versus-human context. The narrow perspective associated with current use of force in the human-versus-human context has created significant gaps in the literature relating to law enforcement’s eventual need to use force on an autonomous vehicle.
This project utilized case studies and a focus group to examine the necessity and importance of communication between law enforcement and a subject. The incorporation of qualitative research, case study analysis, and a focus group consisting of law enforcement professionals confirms that current use-of-force models or policies are not entirely transferable to autonomous vehicle situations. Research, including a review of law enforcement interactions with autonomous cars, supports this conclusion.
The application of current use-of-force models and policies to situations involving autonomous vehicles deprives law enforcement of the ability to communicate, thus hampering its ability to identify, interact with, and interdict an autonomous vehicle. Furthermore, there is no way for law enforcement to determine whether the vehicle is operating according to its intended programming, or malfunctioning, or being remotely monitored or controlled by a human operator. These uncertainties surrounding the interactions between law enforcement and autonomous vehicles can increase the probability of an adverse outcome.
The research suggests that the potential to inadvertently harm someone inside an autonomous vehicle or cause second-order effects in the form of collateral damage requires a separate decision-making framework. Such a new decision-making framework for interdicting autonomous vehicles should emphasize continuous assessments of the situation. Furthermore, based on the Graham standards relating to objective reasonableness and the force used to perform the interdiction, as well as any collateral damage, each situation involving autonomous vehicles should be judged on the totality of the circumstances available to the officer at that time.
 Natalie Todak and Lois James, “A Systematic Social Observation Study of Police De-escalation Tactics,” Police Quarterly 21, no. 4 (December 2018): 512–13, https://doi.org/10.1177/1098611118784007.
 Graham v. Connor, 490 U.S. 386, 396–97 (1989).