Effect of Auditory Road Safety Alerts on Brake Response Times of Younger and Older Male Drivers
Bibliographic record
Abstract
In-vehicle technology is increasingly being implemented to assist drivers. These technologies could improve driver safety or, conversely, introduce distractions that reduce safety. The purpose of this study was to evaluate the effectiveness of a newly developed, commercially available road safety device (Otto Driving Companion, Persen Technologies Inc.) that provides drivers with auditory alerts based on position and velocity data acquired via the Global Positioning System. Auditory alarms warn of situations such as speeding, crosswalks, and red light cameras. To study emergency braking situations, simulated driving was used (STISIM Driving Simulator). Younger male drivers (30 to 50 years old, n = 16) and older male drivers (70+, n = 14) participated in two sessions. In the first session, they were tested for underlying driving abilities, and they practiced driving on the simulator. In the second session, they were refamiliarized with the simulator and then drove two blocks of 10 trials, with and without auditory alerts. Braking events in each trial were either expected (e.g., person crossing at a crosswalk) or unexpected (e.g., person jaywalking). The presentation of auditory alerts resulted in faster brake response times with expected events for both groups (p < .01), and they resulted in even faster response times for the older subjects for unexpected events (p < .05). The auditory alerts also reduced the proportion of events with crashes for the older subjects (from 25.3 ± 21.7% to 10.8 ± 11.9%, p < .05). In conclusion, this simulator study demonstrated that there may be road safety benefits associated with auditory alerts.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".