Analysis of the Influence of Vehicle Color on Speed Perception and Estimation
archive: archived pipeline: cataloged verified
Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)
Summary
This study investigates the influence of vehicle color on drivers' speed perception and estimation, addressing a critical gap in traffic safety research. While previous literature suggests that vehicle color affects crash risk—with yellow vehicles showing the lowest accident probability and dark colors like black showing higher risks—few studies have empirically examined how color specifically alters speed perception. The research aims to determine if statistically significant differences exist in how drivers estimate the speed of passenger vehicles based on their color, using a driving simulator to control for environmental variables. The experimental design involved 81 participants who completed eight tasks on a driving simulator under night-time conditions. Participants were asked to verbally estimate the speed of a Renault Megane vehicle presented in four colors: white, yellow, blue, and black. Each color was tested at two speeds: 30 km/h and 50 km/h. The order of presentation was randomized for each participant to prevent bias. Data collection included demographic information, driving experience, and history of traffic accidents. Statistical analysis employed One Sample tests to compare estimated speeds against actual speeds and Paired Sample T-tests to identify significant differences between color conditions. The results revealed systematic biases in speed estimation dependent on both speed and color. At 30 km/h, participants consistently overestimated the speed of vehicles regardless of color. Conversely, at 50 km/h, participants underestimated the speed for all colors. The magnitude of error varied by color: the smallest estimation error at 30 km/h occurred for black vehicles (mean estimate 34.714 km/h), while the largest error occurred for yellow vehicles (mean estimate 36.565 km/h). At 50 km/h, white vehicles had the smallest error (mean estimate 47.323 km/h), and black vehicles had the largest error (mean estimate 45.025 km/h). Statistically significant differences in perception were found between black and yellow vehicles, as well as between yellow and blue vehicles, at 30 km/h. At 50 km/h, significant differences were observed between black and white vehicles. These findings confirm that vehicle color significantly influences speed perception, with implications for traffic safety and infrastructure design. The study supports the notion that visual factors, including color contrast and visibility, play a crucial role in driver decision-making. The results suggest that lighter colors, particularly yellow, may lead to different perceptual outcomes compared to darker colors, potentially affecting reaction times and maneuver planning. This evidence reinforces the importance of considering visual factors, such as vehicle color and road infrastructure contrast, in traffic safety assessments and the design of emergency vehicle livery.
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.
| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-06-07 |
| archive | success | canonical_url | — | — | 1 | 2026-06-09 |
| extract | success | pdftotext | — | — | 2 | 2026-06-09 |
| clean | success | clean | — | — | 1 | 2026-06-09 |
| chunk | success | chunk | — | — | 1 | 2026-06-09 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-09 |
| promote | success | — | — | — | 1 | 2026-06-07 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-09 |
| tag | success | vector_similarity | — | — | 8 | 2026-06-11 |
| verify | success | — | — | — | 1 | 2026-06-09 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-09; verification: verified.
Topics
Ranked by relevance to this paper. Hover a topic for its definition.