Assessment of the transferability of European road safety inspection procedures and risk index model to Egypt
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Road safety is considered a worldwide issue, especially in developing countries where road fatalities are considered the top cause of death among youth. Generally, three main factors impact road safety including driver, vehicle, and road environment. Statistics show that driver behavior is the major contributory factor to crashes (65%); however, other factors may lead to higher severity crashes such as deteriorated infrastructure, unforgiving roadside design, etc. In this regard, extensive research work has been performed to analyze these crash-contributing factors and propose safety measures. For instance, in North America, researchers developed the Highway Safety Manual (HSM) which provides crash prediction models (CPM) and safety performance functions (SPFs) used in implementing effective safety measures. In the European Union (EU), crash data is complementary to road safety inspections as tools for the safety management of the road network in operation. This research investigates the potential of transferring the European experience, namely the Identification of Hazard Location (IASP) procedures, to Egypt. The analysis shows not only a significant similarity in the safety levels of infrastructure between Egypt and Italy but also in speed behavior. The transferability of the EU IASP procedure is validated by comparing the output of the Risk Index (RI) measure as a surrogate measure of safety with the expected crash frequency resulting from HSM’s SPFs. The comparison is assessed using Spearman’s rank correlation coefficient. This process is applied to a case study that examines a 6-km segment of a two-lane, two-way rural road connecting Faraskour and El Mansoura in Egypt, serving as an example of a hazardous rural road in Egypt. The results indicate that the relation between the RI outputs and the expected crash frequency at the majority of segments of the road section is significant based on Spearman’s rank correlation factor value of 0.75. Few limitations have been identified and presented in the study including the effect of access located on curves or hidden in vegetated areas.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 it