Traffic injury prevention · 2026
Driver engagement in partial driving automation: Mediating pathways of personality and driving style through trust in the intention pathway.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Lee Joong Hee, Kim Wonjoon
Аннотация
OBJECTIVES: To examine how trust influences intention to use partial driving automation through TAM beliefs, and to examine how personality traits and driving styles influence trust and intention indirectly through these mechanisms. These mechanisms are relevant to safe engagement and traffic injury prevention by reducing misuse and disuse of partial automation.
METHODS: An offline, in-person survey was conducted in Korean with 600 licensed drivers who had experience using commercially available SAE Level 2 or Level 3 functions. A latent-variable structural equation model tested the hypothesized mediation pathways, with indirect effects decomposed from the model.
RESULTS: Attitude mediated the effects of perceived usefulness and perceived ease of use on intention to use, and trust affected intention indirectly through attitude and usefulness rather than directly. The model accounted for 72.1% of the variance in intention. Personality and three driving-style dimensions influenced trust and intention indirectly through the sequential cascade, with all constituent structural paths significant.
CONCLUSIONS: Integrating trust and individual differences into acceptance models helps explain heterogeneity in engagement with partial automation and informs design and communication strategies to calibrate trust for safe use. Trust-calibrating interventions may help mitigate misuse-related crash and injury risk.
METHODS: An offline, in-person survey was conducted in Korean with 600 licensed drivers who had experience using commercially available SAE Level 2 or Level 3 functions. A latent-variable structural equation model tested the hypothesized mediation pathways, with indirect effects decomposed from the model.
RESULTS: Attitude mediated the effects of perceived usefulness and perceived ease of use on intention to use, and trust affected intention indirectly through attitude and usefulness rather than directly. The model accounted for 72.1% of the variance in intention. Personality and three driving-style dimensions influenced trust and intention indirectly through the sequential cascade, with all constituent structural paths significant.
CONCLUSIONS: Integrating trust and individual differences into acceptance models helps explain heterogeneity in engagement with partial automation and informs design and communication strategies to calibrate trust for safe use. Trust-calibrating interventions may help mitigate misuse-related crash and injury risk.