Advantages of training with an adaptive driving device on a driving simulator compared to training only on the road
Bibliographic record
Abstract
Purpose To compare the advantages of training on a driving simulator versus on the road, when learning to drive with new assistive technologies (AT) in individuals with motor impairments.Method An experimental group (EXP = 16) that trained on a driving simulator was compared to a comparison group (CMP = 16) that received training only on the road. A post-training road test assessed driving performance. Analysis included proportion of participants who successfully completed the on-road driving test, number of training sessions, level of satisfaction, simulator sickness, advantages and discomforts.Results EXP and CMP were comparable for age (48 ± 17 years), sex (13 M, 3 F), and AT (3 steering wheel knobs with integrated switches, 4 left accelerators, 9 hand controls and steering wheel knobs). No significant difference was observed between groups in the proportion of participants who were found to be fit to drive (EXP: 9/16; CMP: 13/16; p = 0.126) or in the number of sessions completed (EXP: 4.3; CMP: 3.2; p = 0.061). For 6 of the 9 satisfaction variables, participants reported being satisfied/very satisfied with training on a simulator with driving assistive technologies 76% to 100% of the time. EXP was satisfied to have been able to use simulator sessions before going on the road (100%). Participants determined to be fit to drive on an on-road test following simulator training showed no significant difficulty continuing with the training. EXP reported temporary discomfort on the simulator during the initial session (88%).Conclusion Simulators provide some advantages for training drivers with adaptive aids in a safe context.IMPLICATIONS FOR REHABILITATIONAmong individuals with motor impairments who used to drive: All participants reported a high level of satisfaction training on the simulator with assistive technologies.The simulator proved to be an interesting tool for initiating training with new driving AT in a safe environment at no cost to individuals.The few discomforts reported during the first session resolved over time when participants continued with the driving simulator protocol.Occupational therapists noticed that the difficulties observed on the simulator were the same as those observed during on-road testing.The simulator allowed participants to begin to learn how to operate a vehicle with new assistive technology in a safe context.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".