Standardized Autonomous Vehicle Evaluation and Deployment (SAVED) Framework

Autonomous vehicles are rapidly expanding on U.S. roads, but oversight has not kept pace. Today’s patchwork of federal guidance and state-by-state rules leaves uneven safety expectations, inconsistent reporting, and public trust problems. This memo proposes the Standardized Autonomous Vehicle Evaluation and Deployment (SAVED) framework: a national safety baseline with state flexibility. SAVED establishes enforceable federal performance standards for safety and cybersecurity, requires independent pre-deployment evaluation (including simulation and controlled on-road testing within the vehicle’s operating domain), and creates standardized incident reporting to a national database. It also authorizes time-limited state “sandbox zones” for tightly monitored pilots and builds in equity and accessibility expectations so benefits and risks are not concentrated in only a few communities. This policy memo was originally submitted to Dr. Cynthia Bailey's CS 121: Equity and Governance for Artificial Intelligence

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Publication Details

Journal
Stanford OJS Journals
Published
2025-10-01
DOI
https://doi.org/10.60690/g64gh055
Primary Topic
Human-Automation Interaction and Safety
Type
article
Field-Weighted Citation Impact
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article

Standardized Autonomous Vehicle Evaluation and Deployment (SAVED) Framework

Andrew Bempong
Stanford OJS Journals
Human-Automation Interaction and Safety
article

Standardized Autonomous Vehicle Evaluation and Deployment (SAVED) Framework

Andrew Bempong
article en

Abstract

Autonomous vehicles are rapidly expanding on U.S. roads, but oversight has not kept pace. Today’s patchwork of federal guidance and state-by-state rules leaves uneven safety expectations, inconsistent reporting, and public trust problems. This memo proposes the Standardized Autonomous Vehicle Evaluation and Deployment (SAVED) framework: a national safety baseline with state flexibility. SAVED establishes enforceable federal performance standards for safety and cybersecurity, requires independent pre-deployment evaluation (including simulation and controlled on-road testing within the vehicle’s operating domain), and creates standardized incident reporting to a national database. It also authorizes time-limited state “sandbox zones” for tightly monitored pilots and builds in equity and accessibility expectations so benefits and risks are not concentrated in only a few communities. This policy memo was originally submitted to Dr. Cynthia Bailey's CS 121: Equity and Governance for Artificial Intelligence

Stanford OJS Journals
Stanford University (US)
Openalex Percentile: Top 22%
Human-Automation Interaction and Safety
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