GB2592034A

GB2592034A - A cognitive overload sensing system and method for a vehicle

Info

Publication number: GB2592034A
Application number: GB2001962.6A
Authority: GB
Inventors: John Murray Andy; Gerhardt Torsten; Sutherland Wright Ian; Wright Christopher; Tauber Daniel
Original assignee: Ford Global Technologies LLC
Current assignee: Ford Global Technologies LLC
Priority date: 2020-02-13
Filing date: 2020-02-13
Publication date: 2021-08-18
Anticipated expiration: 2040-02-13
Also published as: GB202001962D0; GB2592034B; CN113246994A; DE102021101702A1

Abstract

A cognitive overload sensing system (10) for a vehicle (20), the vehicle comprising an autonomous driving system (30), wherein the cognitive overload sensing system comprises: at least one sensor (40); a processor (50) configured to determine a cognitive load parameter for a driver of the vehicle based at least on data from the at least one sensor; wherein the processor is further configured to: suppress notifications to the driver if the cognitive load parameter is determined to be above a first threshold value; and increase an autonomous driving level if the cognitive load parameter is determined to be above a second threshold value. The sensors may detect inside or outside of the vehicle and be able to determine cognitive load based on location data.

Description

A COGNITIVE OVERLOAD SENSING SYSTEM AND METHOD FOR A VEHICLE

Technical Field

The present disclosure relates to a cognitive overload sensing system and method and, particularly, although not exclusively, relates to a cognitive overload sensing system and method in which notifications are suppressed and an autonomous driving level is increased if a cognitive load parameter is determined to be above first and second thresholds respectively.

Background

Driving in certain environments can be cognitively very demanding for a driver of a vehicle. On such occasions, it is desirable to allow the driver to focus on driving the vehicle.

Statements of Invention

According to an aspect of the present disclosure, there is provided a cognitive overload sensing system for a vehicle, wherein the cognitive overload sensing system comprises: at least one sensor; and a processor configured to determine a cognitive load parameter for a driver of the vehicle based at least on data from the at least one sensor; wherein the processor is further configured to: suppress notifications to the driver if the cognitive load parameter is determined to be above a first threshold value.

The vehicle may comprise an autonomous driving system. The processor may be further configured to increase an autonomous driving level if the cognitive load parameter is determined to be above a second threshold value.

The cognitive load parameter may be indicative of the degree of concentration required by the driver to drive the vehicle. The cognitive load parameter may be a single parameter that represents the overall level of concentration required by the driver. The cognitive load parameter may be representative of actual events occurring at a particular point in time and that may be sensed by the driver (and thus the sensor). The cognitive load parameter may othenyise represent a predicted level of concentration required by the driver, e.g. based on a predicted level of concentration that may be required at a particular time of day and/or location In the latter case, the sensor may determine the location of the vehicle.

The sensor may sense at least one parameter that the driver may be capable of sensing and which the driver may process cognitively. The processor or another processor may use data from the sensor to determine the presence of distinct events or objects that the driver may need to process in order to safely drive the vehicle. The sensor may sense variables that influence the driving of the vehicle, for example potential hazards, such as other vehicles, pedestrians, cyclists, any other road users, road infrastnicture or any other variable external to the vehicle.

The sensor may also sense variables internal to the vehicle that may distract the driver. The sensor may comprise a camera, a LiDAR system, microphone, location determining system (e.g. a satellite navigation system) or any other sensor that is configured to detect or predict hazards external or internal to the vehicle.

The cognitive load parameter may be recorded and stored, e.g. on a server, together with time and location data. This data may be used to infer a cognitive load parameter for other road users at the same locations and/or times.

The second threshold value may be higher than the first threshold value, e.g. the driver experiences a greater cognitive load when the cognitive load parameter is at the second threshold value than at the first threshold value.

The processor may be further configured to allow notifications when the cognitive load parameter is determined to be above the second threshold value and the autonomous driving level has been increased.

The processor may be further configured to suppress notifications having a lower priority value and allow notifications having a higher priority value if the cognitive load parameter is determined to be above the first threshold value.

The processor may be further configured to delay notifications (e.g. those having a lower priority value) until the cognitive load parameter is determined to be below the first threshold value or above the second threshold value.

The processor may be further configured to reduce the autonomous driving level if the cognitive load parameter is determined to be below the second threshold value.

The at least one sensor may provide data for the autonomous driving system.

The cognitive load parameter may be at least partially a function of a parameter associated with (e.g. derived from or calculated by) the autonomous driving system. The cognitive load parameter may be a function of at least a computational power required by the autonomous driving system The sensor or one of the sensors may be configured to detect driver distractions within the vehicle, e.g. originating from within the vehicle cabin. The sensor or one of the sensors may be configured to detect hazards originating from outside the vehicle. The sensor or a plurality of sensors may detect both distractions from within the vehicle and hazards outside the vehicle.

The sensor or one of the sensors may be configured to detect a location of the vehicle. The processor may be configured to determine the cognitive load parameter based at least on the detected location. The processor may be configured to determine the cognitive load parameter based at least on a current time.

According to an aspect of the present disclosure there is provided a method for a vehicle, wherein the method comprises: receiving data from at least one sensor; determining a cognitive load parameter for a driver of the vehicle based at least on said data and suppressing notifications to the driver if the cognitive load parameter is determined to be above a first threshold value.

The vehicle may comprise an autonomous driving system. The method may further comprise increasing an autonomous driving level if the cognitive load parameter is determined to be above a second threshold value The method may further comprise allowing notifications when the cognitive load parameter is determined to be above the second threshold value and the autonomous driving level has been increased.

The method may further comprise suppressing notifications having a lower priority value and allowing notifications having a higher priority value if the cognitive load parameter is determined to be above the first threshold value.

The method may further comprise delaying notifications until the cognitive load parameter determined to be below the first threshold value or above the second threshold value.

The method may further comprise reducing the autonomous driving level if the cognitive load parameter is determined to be below the second threshold value.

The sensor or one of the sensors may provide data for the autonomous driving system.

The cognitive load parameter may be at least partially a function of a parameter associated with (e.g. derived from or calculated by) the autonomous driving system. The cognitive load parameter may be a function of at least a computational power required by the autonomous driving system The method may further comprise detecting driver distractions originating from within the vehicle with the sensor or one of the sensors.

The method may further comprise detecting hazards originating from outside the vehicle with the sensor or one of the sensors.

The method may further comprise detecting a location of the vehicle with die sensor or one of the sensors; and determining the cognitive load parameter based at least on the detected location.

The method may further comprise determining the cognitive load parameter based at least on a current time of day.

According to an aspect of the present disclosure, there is provided a cognitive overload sensing system for a vehicle, the vehicle comprising an autonomous driving system, wherein the cognitive overload sensing system comprises: at least one sensor; and a processor configured to determine a cognitive load parameter for a driver of the vehicle based at least on data from the at least one sensor; wherein the processor is fiirther configured to: suppress notifications to the driver if the cognitive had parameter is determined to be above a first threshold value; and the cognitive load parameter is at least partially a function of a parameter related to (e.g. derived or calculated from) the autonomous driving system. A corresponding method may also be provided.

The present disclosure also provides software, such as a computer program or a computer program product, and a computer readable medium having stored thereon a program. The software, when executed by a computing apparatus, may cause the computing apparatus to perform the above mentioned method. A computer program embodying the invention may be stored on a computer-readable medium, or it could, for example, be in the form of a signal such as a downloadable data signal provided from the Internet, or it could be in any other form.

Features described in respect of any of the aforementioned aspects of the present disclosure may equally apply to any of the other aspects.

To avoid unnecessary duplication of effort and repetition of text in the specification, certain features are described in relation to only one or several aspects or embodiments of the invention. However, it is to be understood that, where it is technically possible, features described in relation to any aspect or embodiment of the invention may also be used with any other aspect or embodiment of the invention.

Brief Description of the Drawings

For a better understanding of the present invention, and to show more clearly how it may be carried into effect, reference will now be made, by way of example, to the accompanying drawings, in which: Figure I is a block diagram depicting a cognitive overload sensing system for a vehicle according to arrangements of the present disclosure; and Figure 2 is a flowchart depicting a method for a vehicle according to arrangements of the present disclosure.

Detailed Description

With reference to Figure I, the present disclosure relates to a cognitive overload sensing system 10 for a vehicle 20. The vehicle 20 may comprise an autonomous driving system 30, which may control one or more driving parameters of the vehicle 20 (such as the steering, braking, acceleration and any other aspect of the vehicle) without driver input or with reduced driver input (e.g. providing safeguards in case of dangerous driving). The autonomous driving system 30 may have various levels of autonomous driving functionality, for example from driver assistance and partial automation to full automation. The autonomous driving levels may correspond to those defined by the Society of Automotive Engineers (SAE) in standard J3016.

As such a higher level autonomous driving level may indicate greater levels of autonomous driving control.

The cognitive overload sensing system 10 comprises at least one sensor 40 and a processor 50. The processor is configured to determine a cognitive load parameter for a driver of the vehicle based at least on data from the at least one sensor 40. The cognitive load parameter may be indicative of the degree of concentration required by the driver to drive the vehicle. The cognitive load parameter may be a single parameter that represents the overall level of concentration required by the driver. For example, a low cognitive parameter may be representative of a driving environment that requires lower levels of concentration, such as a road with little traffic and/or few pedestrians. By contrast, a high cognitive parameter may be representative of a driving environment in an urban setting with high traffic levels ancUor a greater variety of road users (e.g. cyclists etc.).

The processor 50 may be further configured to suppress notifications to the driver if the cognitive load parameter is determined to be above a first threshold value. All or only certain types of notifications may be suppressed by the processor 50. Notifications to the driver may comprises messages or indications from a dashboard display, information (e.g. infotainment) system, a device connected to the vehicle (wired or wirelessly) or any other notification system associated with the vehicle. The notifications may be visual and/or audible in form. By way of example, a notification may comprise a low fuel and/or battery level indication, an incoming phone call or message, a vehicle diagnostic indication and/or any other type of notification.

Each possible notification may be pre-assigned a priority value. When the cognitive load parameter is determined to be above the first threshold value, the processor 50 may suppress notifications having a lower priority value (e.g. being less important), but allow notifications having a higher priority value (e.g. being more important). For example, a notification indicating a low screen wash level may be suppressed when the cognitive load parameter is above the first threshold value, whereas a notification relating to an engine temperature may not be suppressed. The processor 50 may delay notifications (e.g. those having a lower priority value) until the cognitive load parameter is determined to be below the first threshold value (or above the second threshold value as will be described below).

The processor 50 may additionally be configured to increase an autonomous driving level if the cognitive load parameter is determined to be above a second threshold value. Likewise, the processor 50 may reduce the autonomous driving level if the cognitive load parameter is determined to be below the second threshold value. The second threshold value may be higher than the first threshold value, e.g. the driver experiences a greater cognitive load when the cognitive load parameter is at the second threshold value than at the first threshold value. Accordingly, if the cognitive load parameter is between the first and second threshold values, the notifications may be suppressed without an autonomous driving level having been increased.

The processor 50 may be further configured to allow notifications when the cognitive load parameter is determined to be above the second threshold value and the autonomous driving level has been increased. in this scenario, the processor 50 may determine that a lower level of concentration is required by the driver due to the increase in the autonomous driving level and notifications may resume. For example, any delayed notifications may occur once the autonomous driving level has increased.

The cognitive load parameter may be based on actual events occurring at a particular point in time and that may be sensed by the sensor 40 and/or driver. The cognitive load parameter may thus change in real-time and may react to events in the driving environment as they occur.

Alternatively, the cognitive load parameter may be based on a predicted level of concentration required by the driver, e.g. depending on the time of day and/or location of the vehicle. For example, it may be pre-determined that higher levels of driver concentration may be required or are desirable in urban environments, around particular locations (such as junctions, schools etc.), on certain roads or any other type of location. Additionally or alternatively, higher levels of driver concentration may be required or desirable at certain times of day, such as during peak times. Conversely, it may be pre-determined that lower levels of driver concentration are required at other locations and/or times of day. Accordingly, the sensor(s) 40 may determine the time of day and/or location of the vehicle 20 and from the time and/or location, the processor 50 may predict the cognitive load parameter by referring to a database of times/locations and cognitive load parameters. The database may be stored on the vehicle 20 and/or on a server outside the vehicle that the vehicle is in communication with.

In the case of the cognitive load parameter being based on actual events occurring, the sensor(s) 40 may sense at least one parameter that relates to events or objects in the driving environment which the driver may be capable of sensing and which the driver may process cognitively. The processor 50 (or another processor) may use data from the sensor(s) 40 to determine the presence of distinct events or objects that the driver may need to process in order to safely drive the vehicle 20. The sensor(s) 40 may sense variables that influence the driving of the vehicle, for example potential hazards, such as other vehicles, pedestrians, cyclists, any other road users, road infrastructure or any other variable external to the vehicle 20. The sensor(s) 40 may also sense variables internal to the vehicle that may distract the driver. The sensor(s) 40 may comprise a camera, a LiDAR system, microphone, location determining system (e.g. a satellite navigation system) and/or any other sensor that is configured to detect or predict hazards external or internal to the vehicle.

The sensor(s) 40 may be part of or separate from the autonomous driving system 30, in the former case, the sensor(s) 40 may provide data for the autonomous driving system 30 to assist in the automatic (or partially automatic) driving of the vehicle 20. Data from the sensor(s) 40 may be used to determine the cognitive load parameter and this determination may be separate from computations carried out by the autonomous driving system (e.g. even if the sensor(s) are part of the autonomous driving system 30). Alternatively, the cognitive load parameter may be at least partially derived from computational processes that are part of the autonomous driving system 30. For example, the cognitive load parameter may at least partially be a function of a computational performance parameter (such as computational time, power, calculations per second etc.) of the autonomous driving system 30 or other parameters resulting from routines or processes that are part of the autonomous driving system 30 and that may be indicative of the cognitive load required to drive the vehicle 20.

The autonomous driving system 30 may provide data to calculate the cognitive load parameter even if the autonomous driving system is not contributing to the driving of the vehicle at a particular time (e.g. the autonomous driving level may be zero). In other words, the autonomous driving system 30 may be receiving data from the sensor(s) 40 and processing said data as if it were controlling components of the vehicle, despite such components not actually being fully or partially controlled by the autonomous driving system 30. The autonomous driving system 30 may subsequently control such components of the vehicle, e.g if the autonomous driving level is increased.

The determined cognitive load parameter (e.g. resulting from external factors) may be recorded and stored, e.g. on a server, together with time of day and location data. This data may be used to infer and predict a cognitive load parameter for other vehicles at the same locations and/or times of day, for example as described above. In this way, vehicles with the appropriate sensor(s) 40 may help to build up information relating to cognitive load parameter required at certain locations and/or times of day and other vehicles without such sensor(s) may use this data to predict the cognitive load parameter.

In addition to detecting parameters outside the vehicle 20, it is also contemplated that the sensor (or at least one of the sensors) may be configured to detect driver distractions within the vehicle, e.g. originating from within the vehicle cabin. By way of example, the sensor(s) 40 may detect potential driver distractions from other occupants, information systems, entertainment systems, telecommunication devices or any other source of distraction from within the vehicle. The sensor(s) may detect sound within the vehicle cabin and may be configured to detect if the driver is being engaged in conversation (e.g. with another occupant or via a telecommunication system). The sensor(s) may deduce that the driver is engaged in conversation from detected sound signals or by determining that the telecommunication system is in use. The sensor(s) 40 may also detect if entertainment systems are in operation that may distract the driver. Data from one or more such sensors may be used to determine the cognitive load parameter.

it will thus be appreciated that the sensor(s) 40 may detect both distractions from within the vehicle and hazards outside the vehicle and data from the sensor(s) may be used by the processor 30 to determine the cognitive load parameter. For example, the processor 30 may calculate an overall cognitive load parameter by combining an internal cognitive load factor and an external cognitive load factor (e.g. by addition, multiplication or any other mathematical operation). The external cognitive load factor may be derived from data received from the sensor(s) detecting variables outside the vehicle (as described above) or the external cognitive load factor may be estimated based on the time of day and/or location of the vehicle (also as described above). The internal cognitive load factor may be derived from data received from the sensor(s) detecting variables inside the vehicle (as described above). The overall cognitive load parameter may be used to determine whether notifications should be suppressed or permitted and/or if the autonomous driving level should be changed.

With reference to Figure 2, the present disclosure also relates to a method 100 for the vehicle 20. The method comprises a first block 110 in which data from the at least one sensor 40 is received. In a second block 120 the cognitive load parameter for the driver of the vehicle based at least on said data is determined. In a third block 130, notifications to the driver are suppressed if the cognitive load parameter is determined to be above the first threshold value. In a fourth block 140, the autonomous driving level is increased if the cognitive load parameter is determined to be above the second threshold value. The method may also comprise additional steps that have been described above, e.g. in respect of Figure I. It will be appreciated by those skilled in the art that although the invention has been described by way of example, with reference to one or more examples, it is not limited to the disclosed examples and alternative examples may be constructed without departing from the scope of the invention as defined by the appended claims.

Claims

Claims A cognitive overload sensing system for a vehicle, the vehicle comprising an autonomous driving system, wherein the cognitive overload sensing system comprises: at least one sensor; a processor configured to determine a cognitive load parameter for a driver of the vehicle based at least on data from the at least one sensor; wherein the processor is further configured to: suppress notifications to the driver if the cognitive load parameter is determined to be above a first threshold value; and increase an autonomous driving level if the cognitive load parameter is determined to be above a second threshold value.
2. The cognitive overload sensing system of claim 1, wherein the processor is further configured to allow notifications when the cognitive load parameter is determined to be above the second threshold value and the autonomous driving level has been increased.
3. The cognitive overload sensing system of claim I or 2, wherein the processor is further configured to suppress notifications having a lower priority value and allow notifications having a higher priority value if the cognitive load parameter is determined to be above the first threshold value.
4. The cognitive overload sensing system of any of the preceding claims, wherein the processor is further configured to delay notifications until die cognitive load parameter is determined to be below the first threshold value or above the second threshold value.
5. The cognitive overload sensing system of any of the preceding claims, wherein the processor is further configured to reduce the autonomous driving level if the cognitive load parameter is determined to be below the second threshold value.
6. The cognitive overload sensing system of any of the preceding claims wherein the at least one sensor provides data for the autonomous driving system.
7. The cognitive overload sensing system of any of the preceding claims, wherein the cognitive load parameter is at least partially a function of a parameter associated with the autonomous driving system.
The cognitive overload sensing system of any of the preceding claims, wherein the sensor or one of the sensors is configured to detect driver distractions originating from within the vehicle.
9. The cognitive overload sensing system of any of the preceding claims, wherein the sensor or one of the sensors is configured to detect hazards originating from outside the vehicle.
10. The cognitive overload sensing system of any of the preceding claims, wherein the sensor or one of the sensors is configured to detect a location of the vehicle and the processor is configured to determine the cognitive load parameter based at least on the detected location.
11. The cognitive overload sensing system of any of the preceding claims, wherein the processor is configured to determine the cognitive load parameter based at least on a current time of day.
12. A cognitive overload sensing system for a vehicle, the vehicle comprising an autonomous driving system, wherein the cognitive overload sensing system comprises: at least one sensor; and a processor configured to determine a cognitive load parameter for a driver of the vehicle based at least on data from the at least one sensor; wherein the processor is thither configured to: suppress notifications to the driver if the cognitive load parameter is determined to be above a first threshold value; and the cognitive load parameter is at least partially a function of a parameter related to the autonomous driving system.
13. A method for a vehicle, the vehicle comprising an autonomous driving system, wherein the method comprises: receiving data from at least one sensor; determining a cognitive load parameter for a driver of the vehicle based at least on said data suppressing notifications to the driver if the cognitive load parameter is determined to be above a first threshold value; and increasing an autonomous driving level if the cognitive load parameter is determined to be above a second threshold value.
14. The method of claim 13 further comprising: allowing notifications when the cognitive load parameter is determined to be above the second threshold value and the autonomous driving level has been increased.
15. The method of claim 13 or 14, further comprising: suppressing notifications having a lower priority value and allowing notifications having a higher priority value if the cognitive load parameter is determined to be above the first threshold value.
16. The method of any of claims 13 to 15 further comprising delaying notifications until the cognitive load parameter is determined to be below the first threshold value or above the second threshold value.
17. The method of any of claims 13 to 16 further comprising: reducing the autonomous driving level if the cognitive load parameter is determined to be below the second threshold value.
18. The method of any of claims 13 to 17 further comprising: detecting driver distractions originating from within the vehicle with the sensor or one of the sensors.
19. The method of any of claims 13 to 18 further comprising: detecting hazards originating from outside the vehicle with the sensor or one of the 25 sensors.
20. The method of any of claims 13 to 19 further comprising: detecting a location of the vehicle with the sensor or one of the sensors; and determining the cognitive load parameter based at least on the detected location.
21. The method of any of claims 13 to 20 further comprising: determining the cognitive load parameter based at least on a current time of day.