Comparison of Macroscopic and Microscopic Simulation Models in Modern Roundabout Analysis
Bibliographic record
Abstract
Modern roundabouts are more and more widely used at both urban and rural intersections in North America. The results of traffic operations analysis at roundabouts often depend on the software used and parameters adopted. For an evaluation of types of traffic analysis tools on roundabout operations, a macroscopic traffic analysis software (SIDRA) and a microscopic simulation package (VISSIM) were used to analyze a two-lane roundabout at the intersection of two rural arterial highways in Alberta, Canada. A full range of traffic flow rates and left-turn proportions was loaded to the roundabout to compare the two traffic analysis tools and to evaluate the effects of different factors on the roundabout performance. Average control delay and 95% queue length were used as measures of effectiveness. Factors such as total traffic flow rate and left-turn vehicle proportion in each approach were analyzed to evaluate the sensitivity of the roundabout performance at different factor levels. The results showed that there was no significant difference for the delays predicted by VISSIM simulation and SIDRA at medium-to-high traffic flow rates and at all left-turn proportion levels. The 95% queue length predicted by VISSIM was longer than those predicted by SIDRA. Good correlation existed between predicted delays and 95% queue length from the two types of software. Both types of software needed parameter calibration for local traffic conditions. Roundabout capacity could also be estimated from a delay curve obtained from the method presented in this study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".