The Effect of the Number of Right-Turn and Left-Turn Lanes on the Performance of Undersaturated Signalized Intersections
Bibliographic record
Abstract
Vehicle traffic flow channelizing can significantly contribute to fewer collisions and smooth traffic flow in isolated signalized intersection design. Therefore, this study investigates the effect of changes in the number of right-turn lanes with splitter islands and left-turn storage bays for different volume approaches on intersection performance. This study aims to provide an accurate analysis to estimate the effect of such changes on signalized intersections, which can improve intersection performance. Furthermore, the delay parameter derived from HCM2016 and simulation was evaluated for different scenarios. For this purpose, simulation was performed using Synchro software. In this study, a symmetrical, 90-degree, undersaturated (volume per capacity lower than 1, V/C < 1), and four-leg intersection were considered according to AASHTO Green Book 2018 suggestions. HCM2016 results indicated the delay parameter was less sensitive to the undersaturated condition than the right-turn volume variation for both single and dual-lane bays. However, the simulation results indicated that the delay parameter was not constant, depending on the number of right-turn lanes and volumes. On the other hand, there was a significant difference in delay parameters between the single and dual left-turn lanes for both simulation and HCM cases estimated 77.4% and 59.7%, respectively. Overall, this study can provide a vision for traffic engineers to modify the geometry of the four-leg signalized intersections, if the right-turn or left-turn demand volume of an undersaturated signalized intersection is larger than the through approach.
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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 | 0.000 | 0.000 |
| 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".