Bibliographic record
Abstract
The 11th International Conference on Mobility and Transport for Elderly and Disabled Persons (TRANSED 2007) was held June 18-22, 2007, at the Palais des congres de Montreal under the theme Benchmarking, Evaluation and Vision for the Future. The infrastructure of these various modes of transportation, without which they could not be accessible, was one of the issues raised at this conference. The rapidly aging population in industrialized societies must be taken into account when planning infrastructure and facilities. Therefore, several sessions dealt specifically with pedestrian accessibility, readability and clarity of signage, road markings and lighting, in the context of international experience. The suggested improvements focused on slower pedestrians, such as seniors, and consisted of changes to road infrastructure to calm traffic (narrowing the road, refuge islands, changes to the surface of the road, speed bumps), improve pedestrian visibility (flashing green light, large visible signs indicating pedestrian crossings, etc.) and simplify and extend the crossing phases (e.g. pedestrian detectors). Finally, extending the sidewalks at intersections to the edge of the parking spaces was suggested to make it easier for pedestrians to see and be seen, as well as decrease crossing time. New safety-based designs for audible signals for people who are blind or visually impaired were presented. These include on-site or remote user activation, a push-button audible location device, tactile repeaters, and a melodic audio signal (rich in harmonics). Other details, such as alternating the audio signal on either side of the intersection and installing the equipment on the poles closest to the corners, would also help pedestrians head in the right direction before and while crossing. In addition, lowering the curb to make it more accessible to people with reduced mobility creates an obstacle for people with visual impairments by making it more difficult for them to feel where the curb is. To compensate, changes in surface texture (tiles with textured lines, texture stamped into cement, different types of domes, etc.) are used as reference points by blind pedestrians; research into the effectiveness and safety of warning tiles in the winter, as well as which tiles work best in these conditions, is ongoing. In order to make it possible to safely cross at intersections without audible signals, the development of automated systems to assist people who are blind, visually impaired, or have reduced mobility, using information already available in the infrastructure (Pedestrian Information and Communication Systems (PICS), Visible Light Communication (VLC)) is very promising. Research is also being conducted on systems that integrate several types of data (GPS, mapping accessible points, etc.) in order to determine the best itinerary to follow. It was also shown that it is important to make designers, contractors, and maintenance workers aware that they should not neglect elements such as access to and choice of accessible parking spaces, temporary or permanent barriers (news stands, benches, snow, garbage, etc.), and the location and design of bus stops and shelters, which can also be a major barrier for elderly and disabled persons. This conference reviewed international advances in transportation mobility infrastructure and will help implement future solutions that will promote independence for all. For the covering abstract see ITRD E139491.
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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 | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.016 | 0.007 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.044 | 0.016 |
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".