SWADAPT2: benefits of a collision avoidance assistance for powered wheelchair users in driving difficulty
Bibliographic record
Abstract
Purpose In France, tens of thousands of people use a wheelchair. Driving powered wheelchairs (PWCs) present risks for users and their families. The risk of collision in PWC driver increases with severity of disability and may reduce their independence to drive. The European ADAPT project has developed a robotic assistance add-on for PWCs to prevent collisions and improve their driving performance.Materials and methods The aim of the SWADAPT2 study is to assess the benefit of this robotic assistance add-on arranged on a Standard Quickie Salsa M2 PWC in a population of PWC drivers with neurological disorders and driving difficulties. Eighteen (18) participants tested the system on three circuits of increasing difficulty, with and without the robotic assistance add-on.Results The benefit of the robotic assistance add-on was important especially on the more difficult circuits without impacting cognitive load or driving speed. The number of collisions was significantly reduced when using robotic assistance add-on from 2.16 to 0.36 on circuit 2 (p = 0.009) and from 7.3 to 1.33 on circuit 3 (p = 0.0009). Task load demand was not increased with the assistance.Conclusion Finally, this system seems to be indicated to assist and improve driving safety for PWC drivers in driving difficulty. Evaluation was performed in controlled environments; therefore, further evaluation in real-world scenarios is needed to reach technology readiness.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".