Maintaining safe mobility for the ageing population - the role of the private car
Bibliographic record
Abstract
The UK's ageing population is having a fast growing impact on the provision of all services, including transport. Today 16 per cent of the UK's population is over the age of 65, and by 2033 it is predicted that older people will make up almost a quarter of all UK residents. This increase will be proportionately greater amongst the 'oldest old': those aged 85 and above. The effect of these changes on the nation's driving habits will be significant. There is no evidence to suggest that older people's desire to travel will decline at the same rate as their ability to drive or to find other options. In fact, a loss of independent mobility in old age can lead to mental and physical decline, which burdens both the individual and society. There is a great deal that can be achieved through vehicle design to improve the safety of older motorists, passengers and pedestrians. Changes may range from accounting for the greater frailty of the ageing population, through intelligent airbag and seatbelt designs, to making the physical and cognitive requirements of driving less demanding. Developments such as rear-view monitors, blind spot mirrors and automatic parking are also proving helpful. Ergonomic design, which allows easy access to vehicles for older drivers and their passengers, will be an increasingly important design consideration as the older market grows. Reducing headlight glare from new vehicles will also be needed as the number of older drivers with age-related eyesight concerns increases on UK roads. 'Self-explaining' roads which include perceptual cues are needed. For this to be achieved, guidance similar to that already available in the United States would need to be developed. Improvements that would specifically help reduce collisions involving older drivers include: _ traffic signals at junctions; _ clear and unambiguous signage; lower risk traffic control devices such as roundabouts at identified risky junctions; reduced speed limits on priority roads approaching high-risk junctions; high contrast white lines; increased luminance of signs; and larger road signs. If an older driver is no longer able to drive or decides to retire from driving, it is vital that the service delivery options and alternative transport modes are in place to support this change. Changes are also in progress for pension payments, which will encourage a large proportion of the population to work beyond the traditional retirement age. Today seven out of ten people travel to work by car. The implications of this working life change on transport are clear. The full text of this study may be found at: http://www.racfoundation.org/assets/rac_foundation/content/downloadables/maintaining%20safe%20mobility%20-%20rac%20foundation%20-%20140410%20-%20report.pdf
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.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".