most citedBenchmarks for Retrospective Automated Driving System Crash Rate Analysis Using Police-Reported Crash Data

20 citations · 37 across the 4 of their papers we have counts for

collaborators

5 papers

cs.SE2025

Assessing a Safety Case: Bottom-up Guidance for Claims and Evidence Evaluation

Scott Schnelle, Francesca Favaro, Laura Fraade-Blanar +3

As Automated Driving Systems (ADS) technology advances, ensuring safety and public trust requires robust assurance frameworks, with safety cases emerging as a critical tool toward…

cs.SE2025

Determining Absence of Unreasonable Risk: Approval Guidelines for an Automated Driving System Deployment

Francesca Favaro, Scott Schnelle, Laura Fraade-Blanar +6

This paper provides an overview of how the determination of absence of unreasonable risk can be operationalized. It complements previous theoretical work published by existing deve…

cs.CY2025★ 2 cited

Being good (at driving): Characterizing behavioral expectations on automated and human driven vehicles

Laura Fraade-Blanar, Francesca Favarò, Johan Engstrom +4

For over a century, researchers have wrestled with how to define good driving behavior, and the debate has surfaced anew for automated vehicles (AVs). We put forth the concept of D…

cs.RO2023★ 20 cited

Benchmarks for Retrospective Automated Driving System Crash Rate Analysis Using Police-Reported Crash Data

John M. Scanlon, Kristofer D. Kusano, Laura A. Fraade-Blanar +3

With fully automated driving systems (ADS; SAE level 4) ride-hailing services expanding in the US, we are now approaching an inflection point, where the process of retrospectively…

cs.CY2023★ 15 cited

Building a Credible Case for Safety: Waymo's Approach for the Determination of Absence of Unreasonable Risk

Francesca Favaro, Laura Fraade-Blanar, Scott Schnelle +6

This paper presents an overview of Waymo's approach to building a reliable case for safety - a novel and thorough blueprint for use by any company building fully autonomous driving…