Whether to enter expressway or not? The impact of new variable message sign information
Bibliographic record
Abstract
Summary This study develops a random effect panel data logit model that identifies the factors that influence expressway users' decision behavior under a new arterial road variable message sign information service. The new information service provides travel time of both an expressway route and an alternate arterial road route. It is based on the data collected from a stated preference survey of Shanghai drivers. Correlations within repeated choices by the same respondent were addressed. The results show that the random effect model performs well in addressing repeated observations and evidences the existence of common unobserved random factors affecting route choice behaviors of the same respondent. It is shown that drivers' decisions can be significantly influenced by the new information service. Driving experience, travel time saving, and occurrence of expressway accidents serve as positive factors whereas number of traffic lights on the arterial road serves as a negative factor in choosing the arterial road. Private car drivers, employer‐provided car drivers, and taxi drivers value number of traffic lights in a different way. Female drivers are more sensitive to expressway delays. Drivers with rich driving experience and female drivers are more sensitive to number of traffic lights. Copyright © 2014 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".