Evaluating Traveler Preferences, Values, and Behaviors Associated with Public Rest Areas
Bibliographic record
Abstract
How travelers select and value public rest areas was investigated. A comprehensive survey was conducted at 15 public rest areas throughout Michigan; a similar survey was performed at two large commercial travel centers for comparison purposes. The primary objectives of this survey were to (a) identify the reasons motorists stop at public rest areas versus commercial service facilities, (b) estimate the value of services provided by public rest areas, and (c) determine the probable action taken by motorists in the event that a public rest area was unavailable. Results of the survey indicated that patrons at both public rest areas and commercial service facilities generally preferred rest areas for basic services (e.g., restroom use, short break) primarily because of the convenient freeway access. The median patron-reported value of services at standard public rest areas was $1.68 per stop compared with $2.21 per stop at rest areas that included a traveler information center. Even though drivers of commercial vehicles were the most frequent users of public rest areas, they tended to be less satisfied and gave a lower value to services provided. Had a particular public rest area not been available, approximately two-thirds of travelers in private vehicles would have diverted off the freeway to a commercial service facility, whereas one-quarter would have continued to the next rest area along the route. Commercial truck drivers were equally likely to continue to the next rest area as to divert off the freeway.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".