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Acceptability of Driver State Monitoring
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Though widespread monitoring of driver states and behaviors appears to be imminent, research on perceived acceptability of driver state monitoring has lagged behind research on acceptance of automated driving per se. The current study used an original 29-item driver state monitoring acceptability scale to examine potential theoretical subdimensions of acceptability of driver state monitoring (DSM) systems with an exploratory factor analysis approach. The study used an online, U.S.-based sample. Three subdimensions of DSM acceptability emerged: (1) general acceptability of DSM; (2) concerns over DSM; and (3) perceived ease of use. Correlational analyses were conducted to investigate relationships of subdimensions of DSM acceptability with driving styles, accident concerns, perceived driving skill, tendency to speed, self-reported accident and violations history, and demographic variables. Results showed significant but weak relationships between subdimensions of DSM acceptability with a number of variables, including positive relationships with cautious driving styles, familiarity with advanced driver assistance technology (ADAS), and accidents and violations history. Negative relationships were found between acceptability and anxious driving styles, driving experience, and worries of being involved in car accidents. Female participants reported a lower level of acceptability than male participants, whereas current/previous DSM users reported a higher level of acceptability than non-users. Participants also were randomly assigned to receive descriptions indicating that DSM would occur during all driving periods or only during periods when automated systems were engaged. There were no significant differences in acceptability ratings for monitoring in the presence versus absence of automated driving.
Title: Acceptability of Driver State Monitoring
Description:
Though widespread monitoring of driver states and behaviors appears to be imminent, research on perceived acceptability of driver state monitoring has lagged behind research on acceptance of automated driving per se.
The current study used an original 29-item driver state monitoring acceptability scale to examine potential theoretical subdimensions of acceptability of driver state monitoring (DSM) systems with an exploratory factor analysis approach.
The study used an online, U.
S.
-based sample.
Three subdimensions of DSM acceptability emerged: (1) general acceptability of DSM; (2) concerns over DSM; and (3) perceived ease of use.
Correlational analyses were conducted to investigate relationships of subdimensions of DSM acceptability with driving styles, accident concerns, perceived driving skill, tendency to speed, self-reported accident and violations history, and demographic variables.
Results showed significant but weak relationships between subdimensions of DSM acceptability with a number of variables, including positive relationships with cautious driving styles, familiarity with advanced driver assistance technology (ADAS), and accidents and violations history.
Negative relationships were found between acceptability and anxious driving styles, driving experience, and worries of being involved in car accidents.
Female participants reported a lower level of acceptability than male participants, whereas current/previous DSM users reported a higher level of acceptability than non-users.
Participants also were randomly assigned to receive descriptions indicating that DSM would occur during all driving periods or only during periods when automated systems were engaged.
There were no significant differences in acceptability ratings for monitoring in the presence versus absence of automated driving.
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