Disaggregate Model on Drivers' Route Choice Behavior under Traffic State Information
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
When reviewing on route choice models, most literature supposes that all drivers share the same standards of understanding and assessing the traffic conditions and have a homogeneous route choice behavior reacting to the same real-time traffic state information. But there is a great dissimilarity between the real traffic system and this hypothesis. In this paper the authors considered the above dissimilarity and adopted a logit model to describe the drivers' route choice behavior under real-time traffic state information. When modeling, each driver's characteristics are taken into account. These characteristics include gender, age, income, familiarity with the road network, trip purpose and so on. Finally, by analyzing SP and RP survey data in the Shanghai urban expressway A20, the authors proved the validity and rationality of the established logit model.
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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 it