Probabilistic Methodology to Quantify User Delay Costs for Urban Arterial Work Zones
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Bibliographic record
Abstract
The total cost of road construction comprises direct costs paid by agencies and indirect costs paid by road users. In densely populated urban areas, work zone instigated user costs could outweigh direct costs and therefore need to be considered in project alternative selection. This paper develops and applies a probabilistic methodology for quantifying user delay cost (UDC) for urban arterial work zones. The methodology incorporates traffic microsimulation and Monte Carlo simulation to establish a distribution of UDCs, which supports risk-based optimization of work zone configuration, justification of accelerated construction methods, and establishment of contractual incentives and disincentives. The paper demonstrates the development of the methodology through a bridge rehabilitation case study in Calgary, Alberta, Canada. The results revealed that every hour of work zone operation during the morning peak resulted in 169.2 h of network-wide vehicle delay and a mean UDC of CAD 2,816 (in 2016 Canadian dollars). To further demonstrate the applicability of the methodology, a second case study examined three work zone configurations and concluded that the traditional work zone configuration instigated the lowest UDC.
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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) | 0.001 | 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