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The use of a naturalistic driving route for characterizing older drivers

2012· other· en· W7034692892 sur OpenAlex

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Notice bibliographique

RevueMspace (University of Manitoba) · 2012
Typeother
Langueen
DomaineSocial Sciences
ThématiqueInternational Relations and Autism
Établissements canadiensnon disponible
Organismes subventionnairesCanadian Institutes of Health ResearchState Government of VictoriaOttawa Hospital Research InstituteTransport Accident CommissionMonash UniversityLa Trobe UniversityU.S. Department of Justice
Mots-clésTRIPS architectureOlder peopleHuman factors and ergonomicsCrashPoison controlScheduleInjury preventionTask (project management)
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,529
Score d'incertitude au seuil0,999

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,034
Tête enseignante GPT0,248
Écart entre enseignants0,214 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle