Operational performance comparison of four unconventional intersection designs using micro‐simulation
Bibliographic record
Abstract
SUMMARY Several unconventional intersection designs have been proposed as an innovative approach to mitigate congestion at heavily congested at‐grade signalized intersections. Many of these unconventional designs were shown to outperform conventional intersections in terms of the average control delay and the overall intersection capacity. Little research has been conducted to compare the performance of these unconventional intersections to each other under different volume conditions. This study evaluated and compared the operational performance of four unconventional intersection schemes: the crossover displaced left‐turn (XDL), the upstream signalized crossover (USC), the double crossover intersection (DXI) (i.e., half USC), and the median U‐turn (MUT). The micro‐simulation software vissim (PTV Planung Transport Verkehr AG, Karlsruhe, Germany) was used to model and analyze the four unconventional intersections as well as a counterpart conventional one. The results showed that the XDL intersection constantly exhibited the lowest delays at nearly all tested balanced and unbalanced volume levels. The operational performance of both the USC and the DXI was similar in most volume conditions. The MUT design, on the other hand, was unable to accommodate high approach volumes and heavy left‐turn traffic. The capacity of the XDL intersection was found to be 99% higher than that of the conventional intersection, whereas the capacity of the USC and the DXI intersections was about 50% higher than that of the conventional intersection. The results of this study can provide guidance on choosing among alternative unconventional designs according to the prevailing traffic conditions at an intersection. Copyright © 2012 John Wiley & Sons, Ltd.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".