Evaluation of Level-of-Service Measures for Two-Lane Highways with a Simulation Model
Bibliographic record
Abstract
Most highway capacity guidelines use two main traffic measures to establish the level of service for two-lane highways: average travel speed (ATS) and percentage of time spent following (PTSF). In the Highway Capacity Manual (HCM), directional ATS is related to volume by using a linear expression with a single coefficient for volume in both directions (travel and opposing), whereas in other capacity guides such as those in Germany, Finland, and Brazil, a nonlinear form of expression is used; some of these expressions use different coefficients for travel and opposing volumes. In the HCM, directional PTSF is related to volume by using an exponential expression. Other models use a slightly different exponential form of model with different coefficients. The purpose of this research is to use a newly developed and calibrated two-lane microsimulation model to investigate the relationship between traffic volume and directional ATS and PTSF. New expressions are suggested and subsequently compared with those of the HCM and of a number of existing European and South American models. The simulation results show that, unlike the HCM expression, ATS versus volume has a nonlinear convex shape especially at low volume in the travel direction. This finding is in accordance with German, Finnish, and Brazilian models. A new nonlinear exponential expression is suggested to replace the current linear expression for ATS versus volume in the HCM. The HCM PTSF model structure, however, was found to be in accordance with simulation results. Hence, model coefficients were updated for PTSF only.
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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 | 0.007 | 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 | 0.001 | 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".