Design and Development of a Methodology to Estimate Urban Container Truck Traffic
Bibliographic record
Abstract
This paper describes a methodology to estimate container truck traffic volume to help understand the effects of this traffic on transportation engineering and planning issues in urban inland ports within the Canadian Prairie Region. The methodology is sensitive to the unique characteristics of container truck traffic and is intended to assist transportation engineers and planners reveal issues that should be considered in defining, evaluating, and choosing among alternative options to improve urban container freight transportation. There is an increasing demand for freight forecasts for long-term infrastructure planning; however, forecasts are weakened unless there is data representing current conditions. Therefore, methodologies are required to accurately estimate current container truck traffic volume. The methodology discussed in this paper is based on research currently being conducted to develop a container truck model in Winnipeg using 348 hours of truck classification counts at various locations on the truck network. From this preliminary analysis three important findings are revealed: (1) container truck traffic exhibits different temporal characteristics than other articulated truck traffic; (2) geographic distribution of container truck traffic differs from other articulated truck traffic; and (3) there is a significant difference between the container truck and other articulated truck axle configurations. For the covering asbtract of this conference see ITRD number E217481.
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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 | 0.000 |
| 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 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".