Bibliographic record
Abstract
The process of navigating a roundabout involves acquiring and processing information from the geometry of the road, from pavement markings, and from signs. All three elements should be designed and located in order to minimize detection, reading and processing time, and maximize comprehension and ability for motorists to perform the tasks of navigation, guidance and vehicle control. Signs at all roundabouts should aid in detecting the presence of the roundabout ahead, deciding on a destination or exit leg, and slowing to an appropriate speed. Signs at multi-lane roundabouts should also aid in deciding on the correct entry lane. In the United States sign use is regulated through the federal Manual on Uniform Traffic Control Devices (MUTCD) and its state supplements. In Canada, the Canadian MUTCD and various provincial guides such as the Ontario Traffic Manual (OTM) regulate sign use. While these documents detail the application of regulatory and warning signs, they do not yet provide much guidance on specific signs exclusively used for roundabouts, in particular guide signs. This paper proposes that the principles used in designing guide signs in countries where roundabouts are more widespread than in North America be employed. This takes advantage of international expertise while still complying with regulatory and warning signs in the MUTCD. In particular, guide signing practice in the United Kingdom (U.K.) is referenced. The U.K. has pioneered the use of roundabouts, and has more complex, multi-lane designs on high-speed approaches than any other country. The roundabout guide signs discussed in this paper are the: 1. Map-Type Roundabout sign, 2. Lane Assignment sign, and 3. Flag-Type Exit sign. With use of these guide signs, this paper also makes recommendations concerning other signs currently being used at roundabouts: ROUNDABOUT AHEAD, YIELD AHEAD, YIELD, KEEP RIGHT, and ONE-WAY signs. Finally, this paper lists locations for advance signs for roundabouts, including multi-lane roundabouts.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.086 | 0.044 |
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".