Examining Distracted Drivers' Underestimation of Time and Overestimation of Speed
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Summary
This study investigates how cognitive workload from secondary tasks affects drivers' perception of time and speed, addressing a gap in literature regarding speed perception under distraction. While previous research suggests high cognitive load leads to time underestimation, this experiment aimed to quantify how visual (map) and audio distractions alter these perceptions compared to a control condition. The researchers hypothesized that distracted drivers would underestimate time and overestimate speed, potentially impacting safety during re-engagement with driving tasks. The experiment utilized a full-cab driving simulator at the University of Massachusetts Amherst. Thirty-four licensed drivers participated, each completing two drives: one control drive with no distractions and one drive with either an audio task (verbal sentence analysis) or a visual map task (locating streets). The study employed a prospective paradigm, where participants knew they would estimate speed and time duration. To prevent external cues, speedometers and clocks were obscured, and personal devices were removed. The virtual environment consisted of a rural two-lane road with curves and intersections. Data on actual and perceived speeds and times were collected at five checkpoints. Contrary to expectations, participants overestimated time and underestimated their speed across all conditions. On average, drivers perceived their speed as 5.6 mph lower than actual speeds. The authors attribute this to the open, rural environment lacking visual flow, which typically aids speed perception. The map task resulted in significantly lower actual speeds than the control or audio tasks, indicating higher cognitive workload. Notably, nine participants crashed the virtual vehicle at a horizontal curve due to excessive speed. Analysis revealed that drivers who crashed in their second drive had significantly worse time perception (greater overestimation) during their first drive compared to non-crashing drivers. The findings suggest that current time perception may serve as a predictor for future speed selection and crash risk. Drivers who perceived longer time intervals, possibly due to finding the task unstimulating or "boring," were more likely to engage in risky speed selection later. The study highlights that environmental factors, such as roadside vegetation density, significantly influence speed perception, potentially overriding the effects of cognitive load. These results imply that safety interventions must account for environmental stimulation levels, as low-stimulation environments may lead to inaccurate speed judgments and increased crash likelihood, even when drivers are engaged in secondary tasks.
Key finding
Participants overestimated time and underestimated speed, and those with poorer time perception in the first drive were significantly more likely to crash in the second drive.
Methodology
simulator
Sample size: 34
Provenance
The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | rosap | — | — | 2 | 2026-05-23 |
| archive | success | — | — | — | 1 | 2026-05-23 |
| extract | success | cached | — | — | 2 | 2026-06-10 |
| clean | success | — | — | — | 1 | 2026-06-01 |
| chunk | success | — | — | — | 1 | 2026-06-01 |
| embed | success | — | — | — | 1 | 2026-06-02 |
| enrich | success | — | — | — | 1 | 2026-05-23 |
| promote | success | — | — | — | 1 | 2026-05-23 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 3 | 2026-06-10 |
| tag | success | vector_similarity | — | — | 19 | 2026-06-11 |
| verify | success | — | — | — | 2 | 2026-06-10 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.
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- Empirical Findings: behavioral performance data, observational prevalence
- Theoretical Contribution: theory or model