Computer-implemented method for maintaining a driver's perceived trust level in an at least partially automated vehicle
A computer-implemented method for maintaining a driver's perceived trust level in an at least partially automated vehicle, comprising monitoring one or more parameters concerning the driver, the vehicle and/or a surrounding environment; predicting, based on the one or more parameters, a decrease in the perceived trust level; and carrying out one or more countermeasures to compensate for the predicted decrease in the perceived trust level.
1. A method for maintaining a driver's perceived trust level in an at least partially automated vehicle, comprising:
monitoring parameters concerning the driver, the parameters comprising information related to a driver profile, including stored driver preferences concerning vehicle dynamic outputs and human-machine interface outputs to the driver;
predicting, based on the parameters, a decrease in the perceived trust level;
carrying out one or more countermeasures to compensate for the predicted decrease in the perceived trust level;
updating the stored driver preferences in response to the predicted decrease in the perceived trust level;
detecting and monitoring contextual information indicating misbehavior of another driver that contributes to the decrease in the perceived trust level, the misbehavior including zigzagging.
2. The method according to claim 1 , wherein the parameters concerning the driver further comprise information related to one or more of vehicle specifications, traffic, weather and/or road conditions, and a driver state.
3. The method according to claim 2 , wherein the information related to the vehicle specifications includes information concerning inherent attributes of the vehicle with a potential impact on the perceived trust level.
4. The method according to claim 2 , wherein the information related to the traffic, weather and/or road conditions include stored itinerary information and/or information received from one or more vehicle sensors.
5. The method according to claim 4 , wherein the one or more vehicle sensors include one or more of a radar, a LIDAR, a camera, an acoustic sensor, a rain sensor and a motion sensor.
6. The method according to claim 2 , wherein the information related to the driver state comprises physiological information received from one or more driver sensors.
7. The method according to claim 6 , wherein the physiological information includes one or more of the driver's electrodermal activity, pulse rate and eye activity.
8. The method according to claim 2 , wherein the information related to the human-machine interface outputs to the driver includes information concerning one or more of purpose, method and sensory channel of one or more current and/or upcoming human-machine interface outputs to the driver.
9. The method according to claim 1 , wherein the information related to the driver profile includes information related to one or more of driver's propensity to trust the vehicle and driver's familiarity with the vehicle.
10. The method according to claim 1 , wherein the stored driver preferences concerning the vehicle dynamic outputs relate to current and/or upcoming steering, acceleration and/or braking of the vehicle.
11. The method according to claim 1 , wherein the one or more countermeasures comprise adjusting one or more of the vehicle dynamic outputs and the human-machine interface outputs to the driver.
12. A vehicle control system adapted to carry out the method of claim 1 .
13. An at least partially automated vehicle comprising the vehicle control system according to claim 12 .
14. The method according to claim 1 , further comprising adjusting, in response to the monitoring of the contextual information, the vehicle dynamic outputs so as to adjust a distance relative to the another driver.
15. The method according to claim 14 , further comprising notifying, via the human-machine interface outputs, the driver that the misbehavior has been detected.
16. The method according to claim 1 , further comprising notifying that a countermeasure is being undertaken in response to the detection of the misbehavior.
17. The method according to claim 1 , wherein the contextual information is received from one or more vehicle sensors, a positioning system, a wireless communication system, and a data storage unit.
18. A non-transitory computer-readable data storage medium comprising a set of instructions that, when carried out by a computer, cause it to perform:
monitoring parameters concerning a driver, the parameters comprising information related to a driver profile, including stored driver preferences concerning vehicle dynamic outputs and human-machine interface outputs to the driver;
predicting, based on the parameters, a decrease in a perceived trust level;
carrying out one or more countermeasures to compensate for the predicted decrease in the perceived trust level;
updating the stored driver preferences in response to the predicted decrease in the perceived trust level; and
detecting and monitoring contextual information indicating misbehavior of another driver that contributes to the decrease in the perceived trust level, the misbehavior including zigzagging.
19. The non-transitory computer-readable data storage medium according to claim 18 , wherein the set of instructions, when carried out by the computer, further cause the computer to perform adjusting, in response to the monitoring of the contextual information, the vehicle dynamic outputs so as to adjust a distance relative to the another driver.
20. The non-transitory computer-readable data storage medium according to claim 19 , wherein the set of instructions, when carried out by the computer, further cause the computer to perform notifying, via the human-machine interface outputs, the driver that the misbehavior has been detected.