Performance Analysis of a Roundabout and a 3 leg Intersection Under Heterogeneous Traffic
Bibliographic record
Abstract
This paper addresses the analysis of the operational performance of a roundabout and a 3-legged intersection located in quite a busy area of the Aligarh city. The city has an urban population of around 0.9 million people. The roundabout and 3-legged intersection are located in the close proximity of busy commercial areas and schools. Roundabout that has been taken under consideration is un-signalized and 3-legged intersection is priority controlled. The Current study has been undertaken analyze the operational execution of the two intersections and to pave the way for forthcoming investigations related to improvement of the intersections in the Aligarh District region. Traffic data was accumulated on weekdays during peak periods (5:30 pm to 6:30 pm). Video recording was taken in consideration to accomplish this task. The traffic was categorized in 3 classes; light vehicles, heavy vehicles and bicycles. To execute the evaluation of functioning performance of both intersections, SIDRA INTERSECTION software has been used. Results have shown that both the roundabout and 3-legged intersection are operating nearly at their maximum capacities and Level of Service (LOS) is not adequate for such amount of traffic influx into both the intersections. Volume to capacity (v/c) ratio has revealed that both the roundabout and 3-legged intersection are in an unstable state and roundabout condition is worse than the 3-legged intersection as the heavy vehicle volume influx is quite higher for the roundabout.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".