Dynamic Evolution of Traveler’s Bounded-Rational Route Choice Behavior
Bibliographic record
Abstract
Travelers’ route choice shows bounded-rationality because of different perceptions of route attributes. Based on the bounded-rationality, the paper proposes the dynamic evolution rules and route choice model, and simulation method is applied to study the evolution process and results. The model includes three parameters reflecting the bounded-rationality of travelers. First, simulation results show that the bounded-rationality affects the evolution process. The switching threshold or the perception deviance is larger, convergence rate is faster, and shorter time is needed to reach equilibrium state. Also, fewer perfect rational travelers will lead to similar results. Second, the system can reach equilibrium and the final equilibrium volume of every route is almost unaffected by bounded-rationality. The equilibrium volume of every route is an approximately fixed value under all simulation scenes. At last, it is found that equilibrium volume of every route obeys normal distribution. That is, bounded-rationality affects the equilibrium convergence rate, but volume equilibrium results will not be influenced.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".