A Vehicle-Terrain Analysis on the Maximum Desirable Grades for the Residential Driveway Profiles
Bibliographic record
Abstract
Driveways, serving as the junction points between public roadway and private sites, play an important role in the safety and operational performance of roadways. The geometric design of the residential driveways, comprising of the horizontal alignment, vertical profile, and cross sections must accommodate the selected design vehicles in order to avoid any vehicle-terrain conflicts. These conflicts may lead to vehicle or infrastructure damages or unnecessary speed reductions affecting safety and capacity. Traditionally, the horizontal design (e.g. curb return radii and turning lane widths) can be checked by performing a vehicle swept path simulation or superimposing a two-dimensional (2D) turning template. The design would be adjusted to suit the vehicle’s turning characteristics and swept path clearance envelopes. As to the vertical design, design guidelines, such as the Geometric Design Guide for Canadian Roads (GDGCR) from the Transport Association of Canada (TAC), indicate maximum slopes and recommended profile designs. Although the ground clearances of design vehicles are not provided in the publication, it is assumed the recommended slopes have taken those values into consideration. With current technology, the driveway design can be easily modelled in three-dimension (3D) within a CAD environment, and 3D vehicle swept path analysis can be performed to determine if parts of the vehicle will come into contact with the ground. In this study, the authors analyzed the maximum recommended driveway profiles (i.e. uphill and downhill) from the GDGCR to reverse engineer the minimum allowable ground clearances for three of the TAC design vehicles (i.e. P, B12, LSU), two of the Low Clearance Vehicle (i.e. fire truck, and garbage truck) from the NCHRP Report 659 and an ambulance. Next, applying the calculated minimum allowable ground clearances for the selected vehicles, the authors performed 3D vehicle swept path simulations on the 3D surface of the driveway in CAD. Results from 3D driveway analysis highlighted vehicle-terrain conflicts that were not exposed in the 2D driveway profile analysis.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".