Development of a speed limit model for two-lane rural highways
Bibliographic record
Abstract
Two-lane rural highways usually have to face the traffic volumes generated by small villages that developed along their path. These roads were normally capable to ensure uninterrupted flow that provides a high level of mobility with high speed limits. The increase in lateral road occupation and some shortcomings in land planning along these roads have led to a rethink in the methodologies and criteria used to define the speed limits namely in stretches that have systematic variations in the surrounding environment. In fact, up until the mid 1980's the approach used for rural and interurban road design tended to put the emphasis on standardized geometric solutions with little consideration being given to its integration with the surrounding environment. By that time, however, in many European countries but also in the United States, Canada and Australia, the emphasis started to shift towards traffic safety and, progressively, even more in environmental and quality of life related issues, particularly during the crossing of small urban areas or towns. At present there is a widely accepted understanding that only an integrated approach is capable of taking into consideration in a coherent way the interests and needs of all the stakeholders. These are, on the one hand, the vehicles' drivers and passengers who mainly want a rapid and safe, route, and on the other hand, they are the needs and aspirations of the other road users and residents of the surrounding areas, and, finally, those of the society as a all. In the case of two lane roads with regional or national importance where the road tends to cross over many different environments, from the pure rural ones with very little marginal access and interactions, passing through suburban ones where there is a non-negligible level of lateral occupancy by human activities, to pure urban ones. So there is still some work to be done in the development of strategies and solutions which are at the same time efficient and can be applied in a standardized, widespread and systematic way. One of the basic problems related with this question is the one related to the selection of the adequate speed limits for the different surrounding environments, and functional and physical characteristics of the roads. Xlimits and USlimits (from Australia and United States respectively) are examples of the types of software that enable the estimation of speed limits according to a set of conditions related to the infrastructure, land use, operational conditions and local accident rates. These models are, however, adapted to their origin countries' main conditions and require some inputs that are not always available. The development of more detailed analytical models capable of supporting this selection process through the production of objective estimates for the speed limits, based on the quantification of simple explanatory variables representing these aspects, is of significant relevance. In the present paper a linear multiple regression model capable of objectively supporting the process of defining the adequate speed limit levels throughout the full length of a regional or national single carriageway through road is presented. The model, which was developed using real life data, enables the production of estimates for the speed limits to be applied along the route based on the quantification of a small set of variables which describe the functional and physical characteristics of the different stretches of the road and its surrounding environment. In addiction the suitability of the application of logit models and fuzzy logic techniques to the problem is evaluated in an attempt to create discrete response models. This paper presents the methodological approach to this issue as well as the different modelling options assumed, particularly those related to the criteria for the selection of the relevant explanatory variables and of their adequate degree of aggregation.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".