Concretize: A Model-Driven Tool for Scenario-Based Autonomous Vehicle Testing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To achieve rigorous certification of autonomous vehicles (AVs), testing approaches must handle all possible, practically relevant traffic scenarios. This is achievable through the handling of relevant abstractions within the scenario specification language and throughout the scenario generation process. While many scenario generation approaches exist, they are often limited to generating instances of a fixed (pre-defined) scenario and lack tool support. In this paper, we introduce Concretize, a model-driven AV testing framework. It (1) allows users to define scenario specifications using an abstract domain-specific language, and (2) generates conforming concrete (exact) scenarios, which are (3) visualized via a user-friendly web interface. Scenarios are also (4) executed in simulation, in which case Concretize (5) auto-generates figures depicting the monitored safety behavior of the AV-under-test wrt. scenario components at various abstraction levels.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it