The effectiveness of driving simulator training on driving skills and safety in young novice drivers: A systematic review of interventions
Bibliographic record
Abstract
INTRODUCTION: This systematic review evaluated the effectiveness of driving simulator training on simulated/on-road driving skills and safety in young novice drivers. METHOD: Searches were performed in Embase, Global Health, Medline, Scopus, and Web of Science databases, and on Google advanced, Google Scholar, and the Transport Research International Documentation websites. A total of 1,630 unique sources (titles and abstracts) were screened by two reviewers independently with 99 full-text articles reviewed for inclusion. Studies were included if they were a primary driving simulator intervention study that consisted of a randomized controlled trial, quasi-experimental, prospective cohort, and case-control design, published in English between January 1, 2010 and January 26, 2024. RESULTS: The review included 15 studies published in 2010-2022 (study sample size ranged from 30 to 183,197). Findings showed that driving simulator training (compared to control conditions) can immediately improve simulated driving skills (e.g., adjustment to stimuli, lane maintenance, and speed regulation), although it was unclear whether simulator training can improve on-road driving skills or safety, immediately or longitudinally. Studies showed low quality of evidence with increased risks of selection bias, confounding factors, and type I errors influencing findings. PRACTICAL APPLICATIONS: Since it is not known whether driving simulator training has short-term or long-term benefits on drivers' real-world driving skills or safety, it should not replace any training offered in driver education programs. However, driving simulator training can be included in driver education programs to supplement the in-class and on-road training. CONCLUSIONS: The quality of evidence in this review shows low confidence on whether findings accurately reflect true effects on driving skills or safety. Further research should enhance the quality of evidence and demonstrate the transfer effects of driving simulator training to valid measures of real-world driving before recommending any integration of simulator training into standard practice.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".