Can Three-Dimensional Multiple Object Tracking Training Be Used to Improve Simulated Driving Performance? A Pilot Study in Young and Older Adults
DOI: 10.1007/s41465-023-00260-3
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Summary
This pilot study investigated whether training in three-dimensional multiple object tracking (3D-MOT) could improve simulated driving performance in young and older adults. Driving relies heavily on perceptual-cognitive abilities, such as visual attention and processing speed, which decline with age and predict driving safety. While previous research established that 3D-MOT performance correlates with driving ability, no study had previously tested if training this specific dynamic attention task transfers to improved driving outcomes. The authors aimed to determine the feasibility of using 3D-MOT training to enhance driver safety, particularly regarding reaction to dangerous events. The study employed a randomized controlled design with 34 participants: 20 young adults (23–33 years) and 14 older adults (65–76 years). Participants were assigned to either an experimental group or an active control group. The experimental group underwent ten 30-minute sessions of 3D-MOT training using NeuroTracker™, a task requiring the simultaneous tracking of four moving targets amidst distractors. The control group performed a perceptual discrimination task and played the puzzle game 2048. Driving performance was assessed before and after training using a high-fidelity driving simulator featuring a rural scenario with seven skill-testing events involving hazards. Key metrics included braking intensity, distance at maximum braking, steering changes, and near-crash occurrences. The Useful Field of View (UFOV) test was also used to measure changes in attention and processing speed. Results replicated known age-related differences, with older adults driving slower and exhibiting more abrupt steering and braking maneuvers. The primary finding indicated a possible trend for the 3D-MOT trained group, particularly younger adults, to increase the distance at which they applied maximum braking in response to hazards. This earlier braking was associated with less extreme braking forces, suggesting more controlled and deliberate stops. The study also found that baseline 3D-MOT performance was significantly correlated with driving measures, such as steering range and braking distance. However, the study did not report statistically significant improvements in crash rates or UFOV scores, likely due to the small sample size necessitated by early termination during the pandemic. The authors conclude that 3D-MOT training shows preliminary promise for transferring to driving performance by facilitating quicker detection or reaction to dangerous events. The observed trend toward earlier, more controlled braking suggests that enhancing dynamic attention and processing speed may improve driver safety behaviors. Despite limitations regarding sample size and ecological validity, the findings provide a rationale for larger-scale replication studies to confirm whether cognitive training can effectively mitigate age-related declines in driving performance.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-06-25 |
| archive | success | canonical_url | — | — | 1 | 2026-06-26 |
| extract | success | cached | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-25 |
| chunk | success | chunk | — | — | 1 | 2026-06-25 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-25 |
| promote | success | — | — | — | 1 | 2026-06-25 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-25 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
Topics
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- hazard perception training
- simulator training transfer
- cognitive capacity variation
- useful field of view
- mci dementia driving
- hazard perception
Information type
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- Empirical Findings: behavioral performance data
- Methodological Resource: tool software
- Theoretical Contribution: computational model