Charging for Road Use When Road Systems Have Multiple Independent Road Owners
Bibliographic record
Abstract
The dedicated, unindexed fuel taxes commonly used to charge for road use in the United States and Canada are generally considered to be unsatisfactory because, with falling fuel consumption, they do not raise sufficient revenues. They are also unsatisfactory because they cannot function as effective prices for road use, which prevents roads from becoming part of the market economy. This paper reviews the ways in which flexible, autonomous charging methods and technologies can operate within a single, interoperating charging system, permitting road-use charging on any configuration of private, state, regional or municipal road, with minimal roadside infrastructure. Payments by road users would be made to “Payment Operators” who would aggregate the amounts payable for the use of specific road segments and credit the individual road owners with the amounts due to them. After setting out some essential criteria for national (even international) mileage-based user fee (MBUF) systems, the paper describes “thick” and “thin” “autonomous” road use metering. It concludes that only thick, autonomous systems can meet these criteria, and that, to reduce their costs, MBUF systems should be offered in conjunction with benefits desired by road users, such as insurance premiums based on distance travelled. The paper also suggests that such new charging methods should be introduced on a voluntary basis, giving road users the choice of using one of them before the existing one (fuel taxes) is replaced, and that private firms should be invited to offer these new payment systems in conjunction with appropriate incentives.
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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 | 0.010 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".