CLAIMBOUND / SOURCE-PUBLICATION EVIDENCE
Autonomous vehicles
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1. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 4
Narrow public claim
Three of these generic features were selected to further support the development of an example of a testing framework for ADS (L3 Conditional Automated Traffic Jam Drive, L3 Conditional Automated Highway Drive, and L4 Highly Automated Vehicle/TNC).
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
What this card does not prove
It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
- Primary source
- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
- Section locator
PDF page 4- Captured
- 2026-08-04
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59350cbebe58dd7a98f60a14658a5db572f831b902b178a7b70fdead7cb3d65e- Reproduction
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Three of these generic features were selected to further support the development of an example of a testing framework for ADS (L3 Conditional Automated Traffic Jam Drive, L3 Conditional Automated Highway Drive, and L4 Highly Automated Vehicle/TNC).
2. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 5
Narrow public claim
OEDR refers to the subtasks of the DDT that include monitoring the driving environment (detecting, recognizing, and classifying objects and events and preparing to respond as needed) and executing an appropriate response to such objects and events (i.e., as needed to complete the DDT and/or DDT fallback; (SAE International, 2016).
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
What this card does not prove
It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
- Primary source
- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
- Section locator
PDF page 5- Captured
- 2026-08-04
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59350cbebe58dd7a98f60a14658a5db572f831b902b178a7b70fdead7cb3d65e- Reproduction
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OEDR refers to the subtasks of the DDT that include monitoring the driving environment (detecting, recognizing, and classifying objects and events and preparing to respond as needed) and executing an appropriate response to such objects and events (i.e., as needed to complete the DDT and/or DDT fallback; (SAE International, 2016).
3. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 6
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This representative ADS is described by a functional architecture under development by SAE International (Underwood, 2016).
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
What this card does not prove
It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
- Primary source
- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
- Section locator
PDF page 6- Captured
- 2026-08-04
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59350cbebe58dd7a98f60a14658a5db572f831b902b178a7b70fdead7cb3d65e- Reproduction
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This representative ADS is described by a functional architecture under development by SAE International (Underwood, 2016).
4. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 18
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Since 1975, the first year that the Fatality Analysis Reporting System began collecting data, the rate of traffic fatalities per 100 million miles traveled in the United States has decreased by 66 percent, according to the National Highway Traffic Safety Administration’s Traffic Safety Facts data (NHTSA, 2017b).
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
What this card does not prove
It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
- Primary source
- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
- Section locator
PDF page 18- Captured
- 2026-08-04
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59350cbebe58dd7a98f60a14658a5db572f831b902b178a7b70fdead7cb3d65e- Reproduction
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Since 1975, the first year that the Fatality Analysis Reporting System began collecting data, the rate of traffic fatalities per 100 million miles traveled in the United States has decreased by 66 percent, according to the National Highway Traffic Safety Administration’s Traffic Safety Facts data (NHTSA, 2017b).
5. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 18
Narrow public claim
The worldwide automotive industry has recognized driver performance (e.g., error and choice) as a key factor that impacts safety and has begun to introduce systems that complement the driver in terms of enhanced perception with 360-degree vehicle views and rear video systems.
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
What this card does not prove
It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
- Primary source
- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
- Section locator
PDF page 18- Captured
- 2026-08-04
- Source SHA-256
59350cbebe58dd7a98f60a14658a5db572f831b902b178a7b70fdead7cb3d65e- Reproduction
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The worldwide automotive industry has recognized driver performance (e.g., error and choice) as a key factor that impacts safety and has begun to introduce systems that complement the driver in terms of enhanced perception with 360-degree vehicle views and rear video systems.
6. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 20
Narrow public claim
OEDR refers to “the subtasks of the dynamic driving task (DDT) that include monitoring the driving environment (detecting, recognizing, and classifying objects and events and preparing to respond as needed) and executing an appropriate response to such objects and events (i.e., as needed to complete the DDT and/or DDT fallback (SAE International, 2016).
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
What this card does not prove
It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
- Primary source
- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
- Section locator
PDF page 20- Captured
- 2026-08-04
- Source SHA-256
59350cbebe58dd7a98f60a14658a5db572f831b902b178a7b70fdead7cb3d65e- Reproduction
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python scripts/verify_primary_public_claim_group.py artifacts/cb7k_dom006_t01_primary_claims.json --source-file <local-raw-pdf>Exact source quote
OEDR refers to “the subtasks of the dynamic driving task (DDT) that include monitoring the driving environment (detecting, recognizing, and classifying objects and events and preparing to respond as needed) and executing an appropriate response to such objects and events (i.e., as needed to complete the DDT and/or DDT fallback (SAE International, 2016).
7. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 22
Narrow public claim
Most of the research described in this report was conducted before ADS 2.0 was published, and therefore relies on the information contained in the 2016 FAVP document.
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
What this card does not prove
It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
- Primary source
- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
- Section locator
PDF page 22- Captured
- 2026-08-04
- Source SHA-256
59350cbebe58dd7a98f60a14658a5db572f831b902b178a7b70fdead7cb3d65e- Reproduction
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python scripts/verify_primary_public_claim_group.py artifacts/cb7k_dom006_t01_primary_claims.json --source-file <local-raw-pdf>Exact source quote
Most of the research described in this report was conducted before ADS 2.0 was published, and therefore relies on the information contained in the 2016 FAVP document.
8. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 22
Narrow public claim
OEDR refers to the subtasks of the DDT that include monitoring the driving environment (detecting, recognizing, and classifying objects and events and preparing to respond as needed) and executing an appropriate response to such objects and events (i.e., as needed to complete the DDT and/or DDT fallback) (SAE International, 2016).
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
What this card does not prove
It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
- Primary source
- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
- Section locator
PDF page 22- Captured
- 2026-08-04
- Source SHA-256
59350cbebe58dd7a98f60a14658a5db572f831b902b178a7b70fdead7cb3d65e- Reproduction
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python scripts/verify_primary_public_claim_group.py artifacts/cb7k_dom006_t01_primary_claims.json --source-file <local-raw-pdf>Exact source quote
OEDR refers to the subtasks of the DDT that include monitoring the driving environment (detecting, recognizing, and classifying objects and events and preparing to respond as needed) and executing an appropriate response to such objects and events (i.e., as needed to complete the DDT and/or DDT fallback) (SAE International, 2016).
9. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 23
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The workshop was held immediately after the conclusion of the Automated Vehicles Symposium2 in San Francisco, California, in July 2017.
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
What this card does not prove
It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
- Primary source
- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
- Section locator
PDF page 23- Captured
- 2026-08-04
- Source SHA-256
59350cbebe58dd7a98f60a14658a5db572f831b902b178a7b70fdead7cb3d65e- Reproduction
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The workshop was held immediately after the conclusion of the Automated Vehicles Symposium2 in San Francisco, California, in July 2017.
10. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 24
Narrow public claim
This analysis is focused on SAE Levels 3-5 ADS, such as Google’s self-driving car project (i.e., Waymo), and others like it that focus on next-generation automation.
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
What this card does not prove
It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
- Primary source
- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
- Section locator
PDF page 24- Captured
- 2026-08-04
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59350cbebe58dd7a98f60a14658a5db572f831b902b178a7b70fdead7cb3d65e- Reproduction
- Maintainer run only; no independent operator rerun is registered.
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python scripts/verify_primary_public_claim_group.py artifacts/cb7k_dom006_t01_primary_claims.json --source-file <local-raw-pdf>Exact source quote
This analysis is focused on SAE Levels 3-5 ADS, such as Google’s self-driving car project (i.e., Waymo), and others like it that focus on next-generation automation.
11. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 24
Narrow public claim
A four-stage approach was followed to identify ADS features: (1) review the literature, (2) define a framework for discussing ADS features, (3) define features and behaviors, and (4) categorize the features.
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
What this card does not prove
It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
- Primary source
- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
- Section locator
PDF page 24- Captured
- 2026-08-04
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59350cbebe58dd7a98f60a14658a5db572f831b902b178a7b70fdead7cb3d65e- Reproduction
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A four-stage approach was followed to identify ADS features: (1) review the literature, (2) define a framework for discussing ADS features, (3) define features and behaviors, and (4) categorize the features.
12. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 25
Narrow public claim
USDOT, such as the Crash Avoidance Metrics Partnership Automated Vehicle Research for Enhanced Safety (Christensen et al., 2015; NHTSA, 2016c), which details functional descriptions for on-road driving automation levels, was also used.
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
What this card does not prove
It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
- Primary source
- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
- Section locator
PDF page 25- Captured
- 2026-08-04
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59350cbebe58dd7a98f60a14658a5db572f831b902b178a7b70fdead7cb3d65e- Reproduction
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USDOT, such as the Crash Avoidance Metrics Partnership Automated Vehicle Research for Enhanced Safety (Christensen et al., 2015; NHTSA, 2016c), which details functional descriptions for on-road driving automation levels, was also used.
13. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 25
Narrow public claim
SAE J3016 defines an ADS feature as “a driving automation system’s design-specific functionality at a specific level of driving automation within a particular Operational Design Domain.” Referring to this definition, each feature can be described in terms of the following.
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
What this card does not prove
It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
- Primary source
- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
- Section locator
PDF page 25- Captured
- 2026-08-04
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59350cbebe58dd7a98f60a14658a5db572f831b902b178a7b70fdead7cb3d65e- Reproduction
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SAE J3016 defines an ADS feature as “a driving automation system’s design-specific functionality at a specific level of driving automation within a particular Operational Design Domain.” Referring to this definition, each feature can be described in terms of the following.
14. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 26
Narrow public claim
The remaining DDT elements 1, 2, 5, and 6 are discussed in this chapter, and are loosely described as “tactical and operational maneuvers.” That term would typically include aspects of OEDR, but OEDR is covered in Chapter 4.
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
What this card does not prove
It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
- Primary source
- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
- Section locator
PDF page 26- Captured
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59350cbebe58dd7a98f60a14658a5db572f831b902b178a7b70fdead7cb3d65e- Reproduction
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The remaining DDT elements 1, 2, 5, and 6 are discussed in this chapter, and are loosely described as “tactical and operational maneuvers.” That term would typically include aspects of OEDR, but OEDR is covered in Chapter 4.
15. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 26
Narrow public claim
Levels of Driving Automation SAE International, the Bundesanstalt für Straßenwesen, Organisation Internationale des Constructeurs d’Automobiles, and UNECE WP.29 have agreed upon common definitions for levels of driving automation, which are described in SAE J3016.
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
What this card does not prove
It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
- Primary source
- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
- Section locator
PDF page 26- Captured
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59350cbebe58dd7a98f60a14658a5db572f831b902b178a7b70fdead7cb3d65e- Reproduction
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Levels of Driving Automation SAE International, the Bundesanstalt für Straßenwesen, Organisation Internationale des Constructeurs d’Automobiles, and UNECE WP.29 have agreed upon common definitions for levels of driving automation, which are described in SAE J3016.
16. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 28
Narrow public claim
SAE International Autonomous Mode Functional Architecture Flow Diagram (Underwood, 2016) The SAE International draft functional architecture (Figure 3) was adapted to describe system components (i.e., sensors, environment [ODD], perception, plan, act, etc.) and their interactions in relation to the technical analysis in this project.
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
What this card does not prove
It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
- Primary source
- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
- Section locator
PDF page 28- Captured
- 2026-08-04
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59350cbebe58dd7a98f60a14658a5db572f831b902b178a7b70fdead7cb3d65e- Reproduction
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SAE International Autonomous Mode Functional Architecture Flow Diagram (Underwood, 2016) The SAE International draft functional architecture (Figure 3) was adapted to describe system components (i.e., sensors, environment [ODD], perception, plan, act, etc.) and their interactions in relation to the technical analysis in this project.
17. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 33
Narrow public claim
The 2017 Audi A4 and Q7, which contain an early version of this feature (SAE International L2), follow the vehicle ahead and automatically operate the accelerator and brake within the limits of the system so the vehicle is kept in lane.
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
What this card does not prove
It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
- Primary source
- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
- Section locator
PDF page 33- Captured
- 2026-08-04
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59350cbebe58dd7a98f60a14658a5db572f831b902b178a7b70fdead7cb3d65e- Reproduction
- Maintainer run only; no independent operator rerun is registered.
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The 2017 Audi A4 and Q7, which contain an early version of this feature (SAE International L2), follow the vehicle ahead and automatically operate the accelerator and brake within the limits of the system so the vehicle is kept in lane.
18. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 33
Narrow public claim
The future version of the feature is expected to achieve L3 driving automation, and to be commercially available on the Audi A8.
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
What this card does not prove
It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
- Primary source
- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
- Section locator
PDF page 33- Captured
- 2026-08-04
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59350cbebe58dd7a98f60a14658a5db572f831b902b178a7b70fdead7cb3d65e- Reproduction
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The future version of the feature is expected to achieve L3 driving automation, and to be commercially available on the Audi A8.
19. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 34
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X Category 3, L4 Highly Automated Low-Speed Shuttle Feature L4 Highly Automated Low Speed Shuttle is an automated shuttle that drives along a predetermined route.
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
What this card does not prove
It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
- Primary source
- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
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PDF page 34- Captured
- 2026-08-04
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59350cbebe58dd7a98f60a14658a5db572f831b902b178a7b70fdead7cb3d65e- Reproduction
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X Category 3, L4 Highly Automated Low-Speed Shuttle Feature L4 Highly Automated Low Speed Shuttle is an automated shuttle that drives along a predetermined route.
20. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 34
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For example, Olli (Local Motors, 2017) is a self-driving electric vehicle that has been tested in several locations in the United States and is currently deployed in Germany.
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
What this card does not prove
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- Primary source
- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
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PDF page 34- Captured
- 2026-08-04
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For example, Olli (Local Motors, 2017) is a self-driving electric vehicle that has been tested in several locations in the United States and is currently deployed in Germany.
21. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 35
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CityMobil2 (CityMobil2, 2017) piloted a platform for automated road transport systems, which was implemented in several urban environments across Europe.
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
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PDF page 35- Captured
- 2026-08-04
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CityMobil2 (CityMobil2, 2017) piloted a platform for automated road transport systems, which was implemented in several urban environments across Europe.
22. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 35
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A fleet of six Robosoft vehicles drove at a speed of about 12.5 mph along a 1.5-mile itinerary that was integrated into the main city road network.
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
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PDF page 35- Captured
- 2026-08-04
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A fleet of six Robosoft vehicles drove at a speed of about 12.5 mph along a 1.5-mile itinerary that was integrated into the main city road network.
23. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 36
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X X X Category 4, L4 Highly Automated Valet Parking Feature L4 Highly Automated Valet Parking involves a car, potentially unoccupied, that can find a parking spot and park itself.
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
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PDF page 36- Captured
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X X X Category 4, L4 Highly Automated Valet Parking Feature L4 Highly Automated Valet Parking involves a car, potentially unoccupied, that can find a parking spot and park itself.
24. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 37
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Category 5, L4 Highly Automated Emergency Takeover In the event a driver is in impending danger, Emergency Takeover assumes control of the vehicle and guides it to a safe stop.
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PDF page 37- Captured
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Category 5, L4 Highly Automated Emergency Takeover In the event a driver is in impending danger, Emergency Takeover assumes control of the vehicle and guides it to a safe stop.
25. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 37
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Toyota’s Guardian system is distinct from other ADS features and operates in parallel with a human rather than in series (Goreham, 2017).
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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PDF page 37- Captured
- 2026-08-04
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Toyota’s Guardian system is distinct from other ADS features and operates in parallel with a human rather than in series (Goreham, 2017).
26. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 38
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X Category 7, L4 Highly Automated Vehicle/Transportation Network Company (TNC) Feature L4 Highly Automated Vehicle/TNC enables the vehicle to pick up passengers or goods and drive to a destination without the need for an onboard driver.
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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PDF page 38- Captured
- 2026-08-04
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X Category 7, L4 Highly Automated Vehicle/Transportation Network Company (TNC) Feature L4 Highly Automated Vehicle/TNC enables the vehicle to pick up passengers or goods and drive to a destination without the need for an onboard driver.
27. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 38
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However, confirmation has not yet been provided that these features will operate in all ODDs, and thus they are categorized as L4 as opposed to full driving automation (L5).
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
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- NHTSA A Framework for Automated Driving System Testable Cases and Scenarios
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PDF page 38- Captured
- 2026-08-04
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However, confirmation has not yet been provided that these features will operate in all ODDs, and thus they are categorized as L4 as opposed to full driving automation (L5).
28. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 40
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For L3 systems, conditional automated traffic jam drive is expected in 2018, while conditional automated highway drive is not expected until 2020.
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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PDF page 40- Captured
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For L3 systems, conditional automated traffic jam drive is expected in 2018, while conditional automated highway drive is not expected until 2020.
29. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 41
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ADS Feature Timeline by Level of Driving Automation (SAE International, 2016) The ADS features described in this chapter provide the basis for identifying ODD attributes in Chapter 3, OEDR capabilities in Chapter 4, test cases in Chapter 5, and FS/FO mechanisms in Chapter 6.
What this card proves
The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
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PDF page 41- Captured
- 2026-08-04
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ADS Feature Timeline by Level of Driving Automation (SAE International, 2016) The ADS features described in this chapter provide the basis for identifying ODD attributes in Chapter 3, OEDR capabilities in Chapter 4, test cases in Chapter 5, and FS/FO mechanisms in Chapter 6.
30. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 42
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Over 50 literature sources were reviewed, including OEM websites, press releases, USDOT documents, including NHTSA pre-crash scenario analysis and FHWA managed lane use case, as well as technical and international publications, including proceedings of the 2015 and 2016 automated vehicles symposiums.
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
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PDF page 42- Captured
- 2026-08-04
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Over 50 literature sources were reviewed, including OEM websites, press releases, USDOT documents, including NHTSA pre-crash scenario analysis and FHWA managed lane use case, as well as technical and international publications, including proceedings of the 2015 and 2016 automated vehicles symposiums.
31. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 42
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Additionally, the NHTSA fiscal year 2017 Budget Request to Congressional Appropriations Committees (NHTSA, 2016b) identifies several ADS use cases that were considered when defining the ODD for this analysis.
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
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PDF page 42- Captured
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Additionally, the NHTSA fiscal year 2017 Budget Request to Congressional Appropriations Committees (NHTSA, 2016b) identifies several ADS use cases that were considered when defining the ODD for this analysis.
32. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 44
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Automated Driving Systems 2.0 – A Vision for Safety The USDOT definition of ODD is given in Federal guidance and is adopted for the purposes of this report.
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
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PDF page 44- Captured
- 2026-08-04
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Automated Driving Systems 2.0 – A Vision for Safety The USDOT definition of ODD is given in Federal guidance and is adopted for the purposes of this report.
33. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 44
Narrow public claim
The ODD would include the following information at a minimum to define each ADS’s capability limits/boundaries: Roadway types (interstate, local, etc.) on which the ADS is intended to operate safely; Geographic area (city, mountain, desert, etc.); Speed range; Environmental conditions in which the ADS will operate (weather, daytime/nighttime, etc.); and other domain constraints (NHTSA, 2017a).
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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PDF page 44- Captured
- 2026-08-04
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The ODD would include the following information at a minimum to define each ADS’s capability limits/boundaries: Roadway types (interstate, local, etc.) on which the ADS is intended to operate safely; Geographic area (city, mountain, desert, etc.); Speed range; Environmental conditions in which the ADS will operate (weather, daytime/nighttime, etc.); and other domain constraints (NHTSA, 2017a).
34. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 45
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For example, the National Society of Professional Engineers (Austin, 2016) commented that: The operational design domains proposed in SAE J3016 are overly broad and do not adequately reflect the myriad of subdomains a vehicle may be required to enter and exit in the course of a single route within an overall domain (e.g., toll roads).
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
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PDF page 45- Captured
- 2026-08-04
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For example, the National Society of Professional Engineers (Austin, 2016) commented that: The operational design domains proposed in SAE J3016 are overly broad and do not adequately reflect the myriad of subdomains a vehicle may be required to enter and exit in the course of a single route within an overall domain (e.g., toll roads).
35. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 45
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SAE J3016 is currently working on an update to the document in conjunction with ISO that will clarify several points, including concepts that relate to ODDs.
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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PDF page 45- Captured
- 2026-08-04
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SAE J3016 is currently working on an update to the document in conjunction with ISO that will clarify several points, including concepts that relate to ODDs.
36. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 46
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In support of the California policy, California PATH conducted an analysis (University of California PATH Program, 2016) that gathered expert feedback on “areas of operation,” which were defined as Rural, Urban, and Freeway/Highway.
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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PDF page 46- Captured
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In support of the California policy, California PATH conducted an analysis (University of California PATH Program, 2016) that gathered expert feedback on “areas of operation,” which were defined as Rural, Urban, and Freeway/Highway.
37. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 47
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NASA’s missions operate in a limited domain that help to constrain design; for example, missions that are restricted to specific geographic areas or types of objects that may be encountered (Wang & Hussein, 2012).
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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PDF page 47- Captured
- 2026-08-04
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NASA’s missions operate in a limited domain that help to constrain design; for example, missions that are restricted to specific geographic areas or types of objects that may be encountered (Wang & Hussein, 2012).
38. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 47
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For automated flight systems, there are certain domain considerations, such as air traffic, hazardous weather, terrain, and other obstructions and safety maneuvers (Hayhurst, Maddalon, Miner, DeWalt, & McCormick, 2006).
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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PDF page 47- Captured
- 2026-08-04
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For automated flight systems, there are certain domain considerations, such as air traffic, hazardous weather, terrain, and other obstructions and safety maneuvers (Hayhurst, Maddalon, Miner, DeWalt, & McCormick, 2006).
39. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 49
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Subcategories of the main physical infrastructure elements are listed below; illustrative photos are provided in Figure 11.
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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PDF page 49- Captured
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Subcategories of the main physical infrastructure elements are listed below; illustrative photos are provided in Figure 11.
40. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 55
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There are several other types of zones that are important to consider as potential elements of an ODD (see text below and Figure 16).
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There are several other types of zones that are important to consider as potential elements of an ODD (see text below and Figure 16).
41. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 55
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Geo-fencing (Crosbie, 2017) • Central business districts, school campuses, and retirement communities (for example, CityMobil2 is fixed route and includes < 20 mph (CityMobil2, 2013) routes both onroad and off-road on pedestrian walkways).
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Geo-fencing (Crosbie, 2017) • Central business districts, school campuses, and retirement communities (for example, CityMobil2 is fixed route and includes < 20 mph (CityMobil2, 2013) routes both onroad and off-road on pedestrian walkways).
42. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 57
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An excerpt of the checklist for L3 Conditional Traffic Jam Drive is shown in Table 11, with the other ODD categories presented in the Appendix.
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An excerpt of the checklist for L3 Conditional Traffic Jam Drive is shown in Table 11, with the other ODD categories presented in the Appendix.
43. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 58
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A figure showing the significance of ODD relative to levels of driving automation from SAE J3016 is reproduced in Figure 18.
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A figure showing the significance of ODD relative to levels of driving automation from SAE J3016 is reproduced in Figure 18.
44. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 59
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Illustrates the Significance of ODD Relative to the Levels of Driving Automation (SAE International, 2016) There are several aspects to consider to expand upon the defined ODD characteristics.
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Illustrates the Significance of ODD Relative to the Levels of Driving Automation (SAE International, 2016) There are several aspects to consider to expand upon the defined ODD characteristics.
45. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 60
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OEDR refers to “the subtasks of the DDT that include monitoring the driving environment (detecting, recognizing, and classifying objects and events and preparing to respond as needed) and executing an appropriate response to such objects and events (i.e., as needed to complete the DDT and/or DDT fallback”; SAE International, 2016).
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OEDR refers to “the subtasks of the DDT that include monitoring the driving environment (detecting, recognizing, and classifying objects and events and preparing to respond as needed) and executing an appropriate response to such objects and events (i.e., as needed to complete the DDT and/or DDT fallback”; SAE International, 2016).
46. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 60
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ADS, which are the focus of this report, range from SAE International L3 through L5, which means that the ADS feature is completing all aspects of monitoring the driving environment.
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ADS, which are the focus of this report, range from SAE International L3 through L5, which means that the ADS feature is completing all aspects of monitoring the driving environment.
47. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 61
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Using these selected conceptual ADS features from Chapter 2 and the notional ODDs identified in Chapter 3 and expanded upon in Chapter 7.Appendix A for the selected features, this chapter will review the process undertaken to identify notional capabilities for OEDR for ADS.
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Using these selected conceptual ADS features from Chapter 2 and the notional ODDs identified in Chapter 3 and expanded upon in Chapter 7.Appendix A for the selected features, this chapter will review the process undertaken to identify notional capabilities for OEDR for ADS.
48. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 62
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For example, Vendor A designs and develops an L3 Traffic Jam Drive feature that can only operate on limited access highways where there are no pedestrians or pedalcyclists; while Vendor B designs an L3 Traffic Jam Drive feature with similar control capabilities but that also works on arterials and urban streets where pedestrians and pedalcyclists may be present.
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For example, Vendor A designs and develops an L3 Traffic Jam Drive feature that can only operate on limited access highways where there are no pedestrians or pedalcyclists; while Vendor B designs an L3 Traffic Jam Drive feature with similar control capabilities but that also works on arterials and urban streets where pedestrians and pedalcyclists may be present.
49. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 63
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Prior work conducted by California PATH to define behavioral competencies (Nowakowski, Shladover, Chan, & Tan, 2015) informed this evaluation of driving scenarios.
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Prior work conducted by California PATH to define behavioral competencies (Nowakowski, Shladover, Chan, & Tan, 2015) informed this evaluation of driving scenarios.
50. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 64
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The prioritization was based on frequency of occurrence and severity (number resulting in injuries or fatalities) (Najm, Smith, & Yanagisawa, 2007).
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The prioritization was based on frequency of occurrence and severity (number resulting in injuries or fatalities) (Najm, Smith, & Yanagisawa, 2007).
51. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 64
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These actions are seated in the tactical maneuver behaviors identified in Chapter 2 and PATH behavioral competencies reproduced in Table 12 above.
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These actions are seated in the tactical maneuver behaviors identified in Chapter 2 and PATH behavioral competencies reproduced in Table 12 above.
52. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 65
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Institute of Standards and Technology 4D/RCS Reference Model Architecture for Unmanned Vehicle Systems was leveraged (Barbera, Horst, Schlenoff, & Aha, 2004) for this analysis.
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Institute of Standards and Technology 4D/RCS Reference Model Architecture for Unmanned Vehicle Systems was leveraged (Barbera, Horst, Schlenoff, & Aha, 2004) for this analysis.
53. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 66
Narrow public claim
L3 Conditional Automated Traffic Jam Drive Feature For the L3 Conditional Automated Traffic Jam Drive feature, a notional operational use case of a driver on a limited-access highway or urban arterial road encountering slow, stop-and-go traffic that is expected to persist for a period of time was considered.
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L3 Conditional Automated Traffic Jam Drive Feature For the L3 Conditional Automated Traffic Jam Drive feature, a notional operational use case of a driver on a limited-access highway or urban arterial road encountering slow, stop-and-go traffic that is expected to persist for a period of time was considered.
54. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 67
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L3 TJD Baseline ODD - Zones ODD Elements Examples Regions/States Adhere to State/local laws School/Construction Construction zones L3 Conditional Automated Highway Drive Feature For the L3 Conditional Automated Highway Drive feature, a notional use case of a driver on a limited access highway encountering nominal, free-flow traffic conditions allowing for highspeed driving was considered.
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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L3 TJD Baseline ODD - Zones ODD Elements Examples Regions/States Adhere to State/local laws School/Construction Construction zones L3 Conditional Automated Highway Drive Feature For the L3 Conditional Automated Highway Drive feature, a notional use case of a driver on a limited access highway encountering nominal, free-flow traffic conditions allowing for highspeed driving was considered.
55. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 68
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L3 HWD Baseline ODD - Zones ODD Elements Examples Regions/States Adhere to State/local laws School/Construction Construction zones Interference Urban canyons L4 Highly Automated Vehicle/TNC Feature For the L4 Highly Automated Vehicle/TNC feature, a use case of an unmanned TNC vehicle being hailed by a passenger in a dense urban area was considered.
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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It does not independently establish the underlying model capability, safety, comparison, or real-world truth. This is a retrospective single-maintainer source-publication audit.
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L3 HWD Baseline ODD - Zones ODD Elements Examples Regions/States Adhere to State/local laws School/Construction Construction zones Interference Urban canyons L4 Highly Automated Vehicle/TNC Feature For the L4 Highly Automated Vehicle/TNC feature, a use case of an unmanned TNC vehicle being hailed by a passenger in a dense urban area was considered.
56. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 73
Narrow public claim
As previously mentioned, several other attempts have been made to develop similar sets of behaviors and conditions that are important, including the California PATH program behavioral competency analysis (Nowakowski, Shladover, Chan, & Tan, 2015) and NHTSA precrash scenario analysis (Najm, Smith, & Yanagisawa, 2007).
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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As previously mentioned, several other attempts have been made to develop similar sets of behaviors and conditions that are important, including the California PATH program behavioral competency analysis (Nowakowski, Shladover, Chan, & Tan, 2015) and NHTSA precrash scenario analysis (Najm, Smith, & Yanagisawa, 2007).
57. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 74
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V2V and V2I communications capability, via DSRC or other technology, can also support detection and recognition in some capacity.
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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V2V and V2I communications capability, via DSRC or other technology, can also support detection and recognition in some capacity.
58. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 74
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If available, SAE J2735 Basic Safety Messages include information on vehicle position, speed, and heading that could supplement or augment measurements taken by an ADS’s onboard perception sensors.
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If available, SAE J2735 Basic Safety Messages include information on vehicle position, speed, and heading that could supplement or augment measurements taken by an ADS’s onboard perception sensors.
59. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 83
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These challenges were broken down into two main categories: (1) challenges associated with developing tests and metrics, and (2) challenges associated with test execution.
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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These challenges were broken down into two main categories: (1) challenges associated with developing tests and metrics, and (2) challenges associated with test execution.
60. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 86
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Alternatively, a real heavy-duty vehicle pneumatic brake actuation system could be installed on a static stand and tied into the simulator (Salaani, Mikesell, Boday, & Elsasser, 2016).
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Alternatively, a real heavy-duty vehicle pneumatic brake actuation system could be installed on a static stand and tied into the simulator (Salaani, Mikesell, Boday, & Elsasser, 2016).
61. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 86
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Alternatively, virtual scenarios and objects could be injected into a real-world test environment, with the actual ADS running on a track and reacting to the virtual scenarios (Kallweit, Prescher, & Butenuth, 2017).
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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Alternatively, virtual scenarios and objects could be injected into a real-world test environment, with the actual ADS running on a track and reacting to the virtual scenarios (Kallweit, Prescher, & Butenuth, 2017).
62. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 90
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Several entities are actively testing prototype ADS in public, open-road settings to support ongoing development and refinement (General Motors, 2016), (Krok, 2017), (Guardian, 2015), (Lomas, 2017).
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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Several entities are actively testing prototype ADS in public, open-road settings to support ongoing development and refinement (General Motors, 2016), (Krok, 2017), (Guardian, 2015), (Lomas, 2017).
63. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 91
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Notional ADS Open-Road Testing Architecture Efforts have been, and currently are, underway to provide guidance to developing organizations on the safe testing and validation of ADS, including in public-road settings (SAE International, 2015; NHTSA, 2016a).
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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Notional ADS Open-Road Testing Architecture Efforts have been, and currently are, underway to provide guidance to developing organizations on the safe testing and validation of ADS, including in public-road settings (SAE International, 2015; NHTSA, 2016a).
64. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 91
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Some States have investigated similar guidance or, in some cases, legislation that governs the testing and deployment of ADS on public roads within their State boundaries (Nowakowski, Shladover, Chan, & Tan, 2015).
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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Some States have investigated similar guidance or, in some cases, legislation that governs the testing and deployment of ADS on public roads within their State boundaries (Nowakowski, Shladover, Chan, & Tan, 2015).
65. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 92
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Test scenarios can be composed of one or more elements of each of these core components, visualized as the individual dimensions of the multidimensional test matrix in Figure 27.
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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Test scenarios can be composed of one or more elements of each of these core components, visualized as the individual dimensions of the multidimensional test matrix in Figure 27.
66. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 92
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ADS Test Scenario Matrix For example, a sample ADS test scenario for the L4 Highly Automated Vehicle/TNC feature may be notionally described by the items indicated in Table 54.
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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ADS Test Scenario Matrix For example, a sample ADS test scenario for the L4 Highly Automated Vehicle/TNC feature may be notionally described by the items indicated in Table 54.
67. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 93
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General test procedures were modeled on prior tests conducted by NHTSA for CV technology, specifically a test for an FCW system for commercial vehicles (Howe, Xu, Hoover, Elsasser, & Barickman, 2016).
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The exact quoted statement occurred in the named official PDF fetched on 2026-08-04, and the complete PDF matched the recorded SHA-256.
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General test procedures were modeled on prior tests conducted by NHTSA for CV technology, specifically a test for an FCW system for commercial vehicles (Howe, Xu, Hoover, Elsasser, & Barickman, 2016).
68. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 94
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Each of these scenarios was generated for one of the selected generic features by identifying the elements of the proposed test matrix in Figure 27.
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Each of these scenarios was generated for one of the selected generic features by identifying the elements of the proposed test matrix in Figure 27.
69. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 94
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There are numerous relevant scenarios related to an ADS performing a low-speed merge, some of which are shown in Figure 28, as well as most of the other behaviors.
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There are numerous relevant scenarios related to an ADS performing a low-speed merge, some of which are shown in Figure 28, as well as most of the other behaviors.
70. NHTSA A Framework for Automated Driving System Testable Cases and Scenarios · PDF page 95
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This section builds off prior work to identify several key challenges associated with testing ADS (Koopman & Wagner, 2016).
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This section builds off prior work to identify several key challenges associated with testing ADS (Koopman & Wagner, 2016).