US 12,073,734 B2
Automatic teaching device
Andreas U. Kuehnle, Villa Park, CA (US); Andre Tokman, San Clemente, CA (US); and Shaun M. Howard, Irvine, CA (US)
Assigned to Bendix Commercial Vehicle Systems LLC, Elyria, OH (US)
Filed by RM ACQUISITION, LLC, Chicago, IL (US)
Filed on Aug. 17, 2021, as Appl. No. 17/404,137.
Prior Publication US 2023/0057393 A1, Feb. 23, 2023
Int. Cl. G09B 19/16 (2006.01); G09B 5/06 (2006.01)
CPC G09B 19/167 (2013.01) [G09B 5/065 (2013.01)] 22 Claims
OG exemplary drawing
 
1. A system for monitoring a driver's operation of a vehicle and automatically providing a lesson to a driver based on the monitoring, comprising:
a processor;
a memory in communication with the processor, the memory storing a plurality of instructions executable by the processor to cause the system to:
receive input data generated by an onboard vehicle computing system specifying actions taken by the driver while operating the vehicle;
determine based on the input data whether a driving event, requiring the lesson to be output to the driver, has occurred during the driver's operation of the vehicle;
analyze the driving event based on threshold data stored in the memory; and
automatically output the lesson to the driver based on results of the analyzing of the driving event, wherein the lesson includes a plurality of event types; and
a display screen configured to provide the lesson to the driver;
wherein the processor is programmed to control movement of the vehicle based on the results of the analyzing of the driving event during a subsequent operation of the vehicle by the driver including providing a machine intervention by the vehicle prior to a time at which the driver should implement a driver movement of the vehicle and prior to outputting a warning to the driver to implement the driver movement, thereby prompting the driver to control the vehicle in a manner corresponding to the machine intervention, wherein the machine intervention is less than what is required for complete control of the movement of the vehicle, and a degree of the machine intervention is settable and decreases as driver performance improves;
wherein the lesson includes a video, including examples of correct and incorrect driver operation for the driving event, output to the driver on the display screen and a text output to the driver in sync with the video;
wherein the processor is programmed to select a plurality of different examples of the driving event based on a diversity constraint that ensures illustrative variation in the different examples output to the driver, the diversity constraint including at least two of day/night time, urban/non-urban environment, high/low speed, wet/dry road, and winter/summer; and
wherein the lesson further includes an audio narration output to the driver in sync with the video, at least one of the text and the audio narration including a statement indicating a particular driver action that should have occurred at a specific time during the driving event and outputting the statement at a time during the video corresponding to the specific time during the driving event when the driver should have initiated the particular driver action.