skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: The Intersection Between Societal and Ethical Laws and the Use of Autonomous Vehicles (AVs)
This report discusses a variety of societal and ethical laws with respect to autonomous vehicles and their gradual deployment across the United States of America. With companies like Tesla deploying weapons that’ve already being legally faulted with being the cause of tragic road accidents, a deeper analysis of the timeline for deployment is imperative. This report will present the evolution of autonomous vehicles, societal challenges they’ve faced while operating, ethical challenges faced in developing optimal AV algorithms and software, as well as a synopsis of how U.S. citizens feel about these weapons. The findings of this research may suggest the following: most U.S. citizens feel safer inside of an AV as opposed to outside of one, most U.S. citizens feel that AVs pose great threat to their communities, further deployment of these vehicles will require a revamp of traffic laws and regulation, and manufacturers will not take accountability for faulty vehicles.  more » « less
Award ID(s):
1458729
PAR ID:
10301436
Author(s) / Creator(s):
Date Published:
Journal Name:
The ADMI Symposium 2021
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. The United States Department of Defense (DoD) designs, constructs, and deploys social and autonomous robots and robotic weapons systems. Military robots are designed to follow the rules and conduct of the professions or roles they emulate, and it is expected that ethical principles are applied and aligned with such roles. The application of these principles appear paramount during the COVID-19 global pandemic, wherein substitute technologies are crucial in carrying out duties as humans are more restrained due to safety restrictions. This article seeks to examine the ethical implications of the utilization of military robots. The research assesses ethical challenges faced by the United States DoD regarding the use of social and autonomous robots in the military. The authors provide a summary of the current status of these lethal autonomous and social military robots, ethical and moral issues related to their design and deployment, a discussion of policies, and the call for an international discourse on appropriate governance of such systems. 
    more » « less
  2. null (Ed.)
    Teaching autonomous systems is challenging because it is a rapidly advancing cross-disciplinary field that requires theory to be continually validated on physical platforms. For an autonomous vehicle (AV) to operate correctly, it needs to satisfy safety and performance properties that depend on the operational context and interaction with environmental agents, which can be difficult to anticipate and capture. This paper describes a senior undergraduate level course on the design, programming and racing of 1/10th-scale autonomous race cars. We explore AV safety and performance concepts at the limits of perception, planning, and control, in a highly interactive and competitive environment. The course includes an ethics-centered design philosophy, which seeks to engage the students in an analysis of ethical and socio-economic implications of autonomous systems. Our hypothesis is that $1/10th-scale autonomous vehicles sufficiently capture the scaled dynamics, sensing modalities, decision making and risks of real autonomous vehicles, but are a safe and accessible platform to teach the foundations of autonomous systems. We describe the design, deployment and feedback from two offerings of this class for college seniors and graduate students, open-source community development across 36 universities, international racing competitions, student skill enhancement and employability, and recommendations for tailoring it to various settings. 
    more » « less
  3. null (Ed.)
    In this paper we provide a proof of principle of a new method for addressing the ethics of autonomous vehicles (AVs), the Data-Theories Method, in which vehicle crash data is combined with philosophical ethical theory to provide a guide to action for AV algorithm design. We use this method to model three scenarios in which an AV is exposed to risk on the road, and determine possible actions for the AV. We then examine how different philosophical perspectives on agent partiality, or the degree to which one can act in one’s own self-interest, might address each scenario. This method shows why modelling the ethics of AVs using data is essential. First, AVs may sometimes have options that human drivers do not, and designing AVs to mimic the most ethical human driver would not ensure that they do the right thing. Second, while ethical theories can often disagree about what should be done, disagreement can be reduced and compromises found with a more complete understanding of the AV’s choices and their consequences. Finally, framing problems around thought experiments may elicit preferences that are divergent with what individuals might prefer once they are provided with information about the real risks for a scenario. Our method provides a principled and empirical approach to productively address these problems and offers guidance on AV algorithm design. 
    more » « less
  4. Escalante, Hugo Jair; Hadsell, Raia (Ed.)
    The deployment and evaluation of learning algorithms on autonomous vehicles (AV) is expensive, slow, and potentially unsafe. This paper details the F1TENTH autonomous racing platform, an open-source evaluation framework for training, testing, and evaluating autonomous systems. With 1/10th-scale low-cost hardware and multiple virtual environments, F1TENTH enables safe and rapid experimentation of AV algorithms even in laboratory research settings. We present three benchmark tasks and baselines in the set- ting of autonomous racing, demonstrating the flexibility and features of our evaluation environment. 
    more » « less
  5. null (Ed.)
    The deployment and evaluation of learning algorithms on autonomous vehicles (AV) is expensive, slow, and potentially unsafe. This paper details the F1TENTH autonomous racing platform, an open-source evaluation framework for training, testing, and evaluating autonomous systems. With 1/10th-scale low-cost hardware and multiple virtual environments, F1TENTH enables safe and rapid experimentation of AV algorithms even in laboratory research settings. We present three benchmark tasks and baselines in the setting of autonomous racing, demonstrating the flexibility and features of our evaluation environment. 
    more » « less