Design and Development of the Artemis Autonomous Vehicle for the SAE/GM AutoDrive Challenge II Year 2
Bibliographic record
Abstract
Following the groundbreaking success of the original four-year AutoDrive Challenge that ended in 2021, SAE and General Motors renewed this international collegiate design competition, the AutoDrive Challenge Series II, for another four years. The goal of the competition is to develop and demonstrate a Level 4 autonomous vehicle, capable of navigating urban driving environment. Team aUToronto is the University of Toronto’s competition team that has participated in this challenge since the beginning and achieved Overall 1st place in Series I. In Series II Year 1, aUToronto designed a stand-alone multi-modal perception system with all new sensors. The Series II Year 2 competition focuses on integrating the perception system with a brand-new Chevrolet Bolt EUV and turning it into a self-driving car. This thesis describes the team’s vehicle entry for the Year 2 competition, named Artemis, in its design and development. It elucidates the design decisions and details each autonomy subsystem architecture. Additionally, this thesis provides a detailed analysis and discussion of Artemis’ performance in the Year 2 competition.
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.
How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".