Waymo's Safety Methodologies and Safety Readiness Determinations
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Abstract (arXiv)
Waymo's safety methodologies, which draw on well established engineering processes and address new safety challenges specific to Automated Vehicle technology, provide a firm foundation for safe deployment of Waymo's Level 4 ADS, which Waymo also refers to as the Waymo Driver. Waymo's determination of its readiness to deploy its AVs safely in different settings rests on that firm foundation and on a thorough analysis of risks specific to a particular Operational Design Domain. Waymo's process for making these readiness determinations entails an ordered examination of the relevant outputs from all of its safety methodologies combined with careful safety and engineering judgment focused on the specific facts relevant for a particular determination. Waymo will approve when it determines the ADS is ready for the new conditions without creating any unreasonable risks to safety. This paper explains Waymo's methodologies as applied to the three layers of its technology: hardware, ADS behavior, and operations, and also explains Waymo's safety governance. Waymo will continue to apply and adapt those methodologies, and to learn from the important contributions of others in the AV industry, as Waymo continues to build an ever safer and more able ADS.
Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Oct 2020.
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Citing papers per year: 2021: 3; 2022: 2; 2023: 3; 2024: 3; 2025: 2; 2026: 3.
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- 2023Learning Realistic Traffic Agents in Closed-loopcited by 24
- 2023What Truly Matters in Trajectory Prediction for Autonomous Driving?cited by 17
- 2024Pedestrian Trajectory Prediction with Missing Data: Datasets, Imputation, and Benchmarkingcited by 8
- 2021The missing link: Developing a safety case for perception components in automated drivingcited by 7
- 2025DriveGen: Towards Infinite Diverse Traffic Scenarios with Large Modelscited by 7
- 2024Few-Shot Scenario Testing for Autonomous Vehicles Based on Neighborhood Coverage and Similaritycited by 2
- 2021Agent-aware State Estimation in Autonomous Vehiclescited by 1
- 2024Savvy: Trustworthy Autonomous Vehicles Architecturecited by 1
- 2021Future Intelligent Autonomous Robots, Ethical by Design. Learning from Autonomous Cars Ethicscited by 0
- 2022Taking the Intentional Stance Seriously, or "Intending" to Improve Cognitive Systemscited by 0
- 2022Exiting the Simulation: The Road to Robust and Resilient Autonomous Vehicles at Scalecited by 0
- 2023Finding Needles in Haystack: Formal Generative Models for Efficient Massive Parallel Simulationscited by 0
4 more
- 2025Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM)cited by 0
- 2026A Five-Layer MLOps Architecture for Connected Automated Drivingcited by 0
- 2026Guiding Neuro-Symbolic Scenario Generation with Spatio-Temporal Logiccited by 0
- 2026LLM-Assisted Dynamic Threat Analysis for Attacker-Reachable Software Weaknesses in Autonomous Vehiclescited by 0
- 2026LLM-Assisted Dynamic Threat Analysis for Attacker-Reachable Software Weaknesses in Autonomous Vehicles13 Aug 2026
- 2026Guiding Neuro-Symbolic Scenario Generation with Spatio-Temporal Logic18 May 2026
- 2026A Five-Layer MLOps Architecture for Connected Automated Driving12 May 2026
- 2025DriveGen: Towards Infinite Diverse Traffic Scenarios with Large Models4 Mar 2025
- 2025Systems Engineering for Autonomous Vehicles; Supervising AI using Large Language Models (SSuperLLM)18 Jan 2025
- 2024Pedestrian Trajectory Prediction with Missing Data: Datasets, Imputation, and Benchmarking31 Oct 2024
- 2024Savvy: Trustworthy Autonomous Vehicles Architecture8 Feb 2024
- 2024Few-Shot Scenario Testing for Autonomous Vehicles Based on Neighborhood Coverage and Similarity2 Feb 2024
- 2023Learning Realistic Traffic Agents in Closed-loop2 Nov 2023
- 2023What Truly Matters in Trajectory Prediction for Autonomous Driving?27 Jun 2023
- 2023Finding Needles in Haystack: Formal Generative Models for Efficient Massive Parallel Simulations3 Jan 2023
- 2022Exiting the Simulation: The Road to Robust and Resilient Autonomous Vehicles at Scale19 Oct 2022
4 more
- 2022Taking the Intentional Stance Seriously, or "Intending" to Improve Cognitive Systems21 Sep 2022
- 2021The missing link: Developing a safety case for perception components in automated driving30 Aug 2021
- 2021Agent-aware State Estimation in Autonomous Vehicles1 Aug 2021
- 2021Future Intelligent Autonomous Robots, Ethical by Design. Learning from Autonomous Cars Ethics16 Jul 2021
- 2023Learning Realistic Traffic Agents in Closed-loopcited by 24
- 2023What Truly Matters in Trajectory Prediction for Autonomous Driving?cited by 17
- 2024Pedestrian Trajectory Prediction with Missing Data: Datasets, Imputation, and Benchmarkingcited by 8
- 2021The missing link: Developing a safety case for perception components in automated drivingcited by 7
- 2025DriveGen: Towards Infinite Diverse Traffic Scenarios with Large Modelscited by 7
- 2024Few-Shot Scenario Testing for Autonomous Vehicles Based on Neighborhood Coverage and Similaritycited by 2
- 2021Agent-aware State Estimation in Autonomous Vehiclescited by 1
- 2024Savvy: Trustworthy Autonomous Vehicles Architecturecited by 1
- 2021Future Intelligent Autonomous Robots, Ethical by Design. Learning from Autonomous Cars Ethicscited by 0
- 2022Taking the Intentional Stance Seriously, or "Intending" to Improve Cognitive Systemscited by 0
- 2022Exiting the Simulation: The Road to Robust and Resilient Autonomous Vehicles at Scalecited by 0
- 2023Finding Needles in Haystack: Formal Generative Models for Efficient Massive Parallel Simulationscited by 0
12 most cited of 15 All 15 (JSON)
- 2026LLM-Assisted Dynamic Threat Analysis for Attacker-Reachable Software Weaknesses in Autonomous Vehicles13 Aug 2026
- 2026Guiding Neuro-Symbolic Scenario Generation with Spatio-Temporal Logic18 May 2026
- 2026A Five-Layer MLOps Architecture for Connected Automated Driving12 May 2026
- 2025DriveGen: Towards Infinite Diverse Traffic Scenarios with Large Models4 Mar 2025
- 2024Pedestrian Trajectory Prediction with Missing Data: Datasets, Imputation, and Benchmarking31 Oct 2024
- 2024Savvy: Trustworthy Autonomous Vehicles Architecture8 Feb 2024
- 2024Few-Shot Scenario Testing for Autonomous Vehicles Based on Neighborhood Coverage and Similarity2 Feb 2024
- 2023Learning Realistic Traffic Agents in Closed-loop2 Nov 2023
- 2023What Truly Matters in Trajectory Prediction for Autonomous Driving?27 Jun 2023
- 2023Finding Needles in Haystack: Formal Generative Models for Efficient Massive Parallel Simulations3 Jan 2023
- 2022Exiting the Simulation: The Road to Robust and Resilient Autonomous Vehicles at Scale19 Oct 2022
- 2022Taking the Intentional Stance Seriously, or "Intending" to Improve Cognitive Systems21 Sep 2022
12 newest of 15 All 15 (JSON)