The use of a naturalistic driving route for characterizing older drivers
Notice bibliographique
Résumé
Although the vast majority of older drivers are safe, there are some older drivers who are at risk of crashes due to health-related changes in functional status. For licensing agencies worldwide it is a challenge to identify unsafe older drivers. One form of older driver assessment that can be done conducted is an on-road test. Often this occurs in an unfamiliar vehicle and on roads that are not familiar to the older driver. This could be detrimental to their driving performance and lead to an overestimation of their crash risk. Purpose: The purpose of the current study is to determine whether the route used for the Driving Observation Schedule (DOS), a specific driving task designed to observe and record driving performance, is actually representative of older drivers’ everyday driving in Melbourne Australia. This is a sub-study of the Ozcandrive study, which is a partner study to Candrive. Methods: Older drivers (75+ years old) were asked to describe locations where they typically drive. A route was then devised to incorporate those locations, and the older driver was observed for their driving behaviours over this route. Older drivers’ vehicles were equipped with a device that monitored their driving locations by global positioning system (GPS) technology at 1 Hz. These same older drivers were followed over several months for their everyday driving using the same device. All trips made were compared for their location against the DOS route. These results were then expressed as a percentage of the trips that included a road from the DOS route, in order to determine how representative the DOS route was of each older drivers’ everyday driving. In addition to location, speed patterns were also compared between the DOS route and everyday driving. Results: The average distance of the DOS route was 13.8 ± 5.3 km, and on average it took 31.0 ± 7.6 minutes to drive, for the 23 older drivers that were included in the sample for this study. Over the 108 ± 18 days whereby the older drivers were monitored for their everyday driving, the older drivers drove 2384 ± 1504 km, and made 385 ± 155 trips. The roads that were part of the DOS route represented 9 ± 8 percent of roads that were used during the everyday driving trips. The DOS route and driving was similar to everyday driving in terms of speed limits of the roadways, exceeding the speed limit, and speed of driving. Drivers spent the majority of time driving on roadways that had speed limits of 50 and 60 km/hr (DOS = 80.4%, everyday = 74.1%). There was a slight trend for everyday driving to be on roadways with faster speed limits and have faster driving than DOS driving. Conclusions: These results suggest that a route can be formulated that will be representative of most of the everyday driving of older drivers. Use of such a route has promise for determining the performance of older drivers under conditions which are typical for their everyday driving. Future research that combines driving behaviour observation, crash data, naturalistic driving as well as health and functional testing for individual older drivers will do much to provide more definitive information about this growing cohort of drivers.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».