Granted Patent B2

US 12,521,052 · App. 18/665,458 · Granted Jan 13, 2026

Inventors: Akilesh Rajavenkatanarayanan (Macomb, MI); Manoj Kumar Sharma (Troy, MI); Jonathon Markowski (Royal Oak, MI); Tetyana Wasko (West Bloomfield, MI); Kiran Babu (Detroit, MI)

Assignee: GM GLOBAL TECHNOLOGY OPERATIONS LLC

A61B5/18B60K35/10G07C5/008H04W4/40

Abstract

Claims (60)

1 . A method comprising:

collecting, via one or more vehicle sensors, sensor data pertaining to a cognitive load of a driver of a vehicle, including by:

collecting, via one or more internal vehicle sensors, internal data as to circumstances within a cabin of each of a plurality of vehicles of a fleet that may affect the cognitive load; and

collecting, via one or more external vehicle sensors, external data as to circumstances outside the cabin of each of the plurality of vehicles of the fleet that may affect the cognitive load;

transmitting, via one or more transceivers, the sensor data, including the internal data and the external data, to a remote server that is physically remote from the plurality of vehicles, via a wireless communications network; and

determining, via one or more processors, the cognitive load for the driver based on the sensor data;

providing one or more actions with respect to a driver of the vehicle based on the cognitive load, in accordance with instructions provided by the one or more processors;

aggregating, via the one or more processors, the internal data and the external data for all of the plurality of vehicles in the fleet, generating aggregated fleet data; and

providing, via instructions provided by the one or more processors, one or more driver-related control actions for the plurality of vehicles of the fleet, based on the aggregated fleet data.

2 . The method of claim 1 , further comprising:

determining, via the one or more processors, one or more external events pertaining to the cognitive load for each of the plurality of vehicles in the fleet;

determining, via the one or more processors, one or more internal circumstances pertaining to the cognitive load for each of the plurality of vehicles in the fleet, including internal distractions that are likely to cause stress, distraction, or both for the driver; and

correlating, via the one or more processors, the one or more internal circumstances with the one or more external events for each of the plurality of vehicles in the fleet.

3 . The method of claim 2 , further comprising:

obtaining, via one or more input sensors, anonymous feedback from a driver of each of the plurality of vehicles of the fleet, including via the driver's interaction with a display screen, verbal feedback from the driver, or both;

wherein the correlating is performed via the one or more processors further using the anonymous feedback.

4 . The method of claim 2 , further comprising:

correlating, via the one or more processors, the one or more external events with the cognitive load, based on respective time stamps provided to the one or more external events and to the cognitive load via the one or more processors.

5 . The method of claim 4 , further comprising:

providing, via a display screen in accordance with instructions provided by the one or more processors, a display for a manger of the fleet, the display including information as to the one or more external events and the cognitive load, including a mapping of the one or more external events and the cognitive load along one or more routes taken by the plurality of vehicles in the fleet, and wherein the display includes a plurality of cognitive load notations corresponding to respective regions of interest along the one or more routes and their corresponding cognitive loads.

6 . The method of claim 2 , wherein the cognitive load is calculated using the internal data as obtained via one or more biometric sensors for the driver.

7 . The method of claim 6 , wherein the cognitive load is further calculated using operational data obtained via one or more vehicle sensors pertaining to the driver's operation of a respective one of the plurality of vehicles of the fleet.

8 . The method of claim 1 , wherein the method further comprises:

determining, via the processor based on the sensor data, whether the cognitive load of the driver was triggered by internal circumstances within the vehicle, or rather by external circumstances that are outside the vehicle; and

providing, via instructions provided by the processor, a notification as to the cognitive load and one or more causes thereof, including whether the cognitive load is believed to be caused by external or internal circumstances.

9 . A system comprising:

one or more vehicle sensors configured to collect sensor data pertaining to a cognitive load of a driver of a vehicle, the one or more vehicle sensors comprising:

one or more internal vehicle sensors configured to collect internal data as to circumstances within a cabin of each of a plurality of vehicles of a fleet that may affect the cognitive load; and

one or more external vehicle sensors configured to collect external data as to circumstances outside the cabin of each of the plurality of vehicles of the fleet that may affect the cognitive load;

one or more transceivers configured to transmit the sensor data, including the internal data and the external data, to a remote server that is physically remote from the plurality of vehicles, via a wireless communications network; and

one or more processors that are configured to at least facilitate:

aggregating the internal data and the external data for all of the plurality of vehicles in the fleet, generating aggregated fleet data; and

providing, via instructions provided by the one or more processors, one or more driver-related control actions for the plurality of vehicles of the fleet, based on the aggregated fleet data.

10 . The system of claim 9 , wherein the one or more processors are further configured to at least facilitate:

determining one or more external events pertaining to the cognitive load for each of the plurality of vehicles in the fleet;

determining one or more internal circumstances pertaining to the cognitive load for each of the plurality of vehicles in the fleet; and

correlating the one or more internal circumstances with the one or more external events for each of the plurality of vehicles in the fleet.

11 . The system of claim 10 , further comprising:

one or more input sensors configured to obtain anonymous feedback from a driver of each of the plurality of vehicles of the fleet, including via the driver's interaction with a display screen, verbal feedback from the driver, or both;

wherein the one or more processors are configured to perform the correlating further using the anonymous feedback.

12 . The system of claim 10 , wherein the one or more processors are further configured to at least facilitate correlating the one or more external events with the cognitive load, based on respective time stamps provided to the one or more external events and to the cognitive load via the one or more processors.

13 . The system of claim 12 , further comprising:

a display screen;

wherein the one or more processors are further configured to at least facilitate providing, via the display screen in accordance with instructions provided by the one or more processors, a display for a manger of the fleet, the display including information as to the one or more external events and the cognitive load, including a mapping of the one or more external events and the cognitive load along one or more routes taken by the plurality of vehicles in the fleet.

14 . The system of claim 13 , wherein the display includes information as to the one or more external events and the cognitive load, including a mapping of the one or more external events and the cognitive load along one or more routes taken by the plurality of vehicles in the fleet.

15 . The system of claim 10 , wherein the one or more processors are further configured to calculate the cognitive load using the internal data as obtained via one or more biometric sensors for the driver.

16 . The system of claim 15 , wherein the one or more processors are further configured to calculate the cognitive load using operational data obtained via one or more vehicle sensors pertaining to the driver's operation of a respective one of the plurality of vehicles of the fleet.

17 . The system of claim 9 , wherein the processor is further configured to at least facilitate:

determining, based on the sensor data, whether the cognitive load of the driver was triggered by internal circumstances within the vehicle, or rather by external circumstances that are outside the vehicle; and

providing a notification as to the cognitive load and one or more causes thereof, including whether the cognitive load is believed to be caused by external or internal circumstances.

18 . A system comprising:

a fleet comprising a plurality of vehicles, each vehicle of the plurality of vehicles including:

one or more internal vehicle sensors configured to collect internal data as to circumstances within a cabin of the vehicle pertaining to a cognitive load of a driver of the vehicle;

one or more external vehicle sensors configured to collect external data as to circumstances outside the cabin of the vehicle pertaining to the cognitive load of the driver of the vehicle;

one or more transceivers configured to transmit the internal data and the external data via a wireless communications network; and

a remote server that is physically remote from the plurality of vehicles and that comprises:

a transceiver configured to receive the internal data and the external data from each of the plurality of vehicles of the fleet, via the wireless communications network; and

one or more processors that are configured to at least facilitate:

aggregating the internal data and the external data for all of the plurality of vehicles in the fleet, generating aggregated fleet data; and

providing one or more driver-related control actions for the plurality of vehicles of the fleet, based on the aggregated fleet data and the cognitive load.

Assignments (1)

Continuity (1)

References Cited (11)