Method and system for activating and adjusting one or more HMI of a vehicle according to an environment of the vehicle and to the attentiveness of a driver of the vehicle

Abstract

The invention relates to an activation and adjustment system (1) comprising an acquisition unit (2) for acquiring a representation of the environment and of the eye movements of the driver (DR), and a processor (PR) configured to determine an attention-level matrix (M) for the attentiveness of the driver (DR) for the environment, establish a list of the obstacles (OB) in the environment that are associated with a level of attentiveness of the driver (DR) and are likely to be passed by the vehicle (VE) from a digital model of the environment, determine a field of safe travel (FoST) observed by the driver (DR), activate a first HMI if an obstacle (OB) has an associated level of attentiveness less than or equal to a predetermined attention-level threshold, activate a second HMI if a parameter indicative of a difference between a predicted field of safe travel (PFoST) and a new field of safe travel both determined after the activation of the first HMI is greater than or equal to a predetermined difference threshold.

Description

Description Title of the invention: Method and system for activating and adjusting one or more HMIs of a vehicle according to the vehicle environment and the attention of a vehicle driver. technical field

[0001] The present invention relates to a method and system for activating and adjusting one or more human-machine interfaces (HMIs) in a vehicle, depending on the vehicle's environment and the driver's attention. The method and system according to the invention aim to make the driver aware of at least one obstacle when their level of attention to the obstacle appears insufficient. State of the art

[0002] Measuring a driver's situational awareness (also known as situational awareness) involves observing both the driver's behavior and the driving scene in which the vehicle is operating. This measurement ensures that the driver is correctly analyzing the elements of the driving scene. If so, the driver can make appropriate decisions while driving. If not, the use of human-machine interfaces (HMIs), referred to as HMIs hereafter, can draw the driver's attention to these elements. An HMI typically consists of audible, visual, or haptic signals emitted by the vehicle and designed to draw the driver's attention to, for example, an obstacle the vehicle might encounter.

[0003] One aim of the invention is to determine the driver's situational awareness of their surroundings, to compare this awareness with obstacles in their path, and to act, if necessary, by activating appropriate HMIs. Description of the invention

[0004] The present invention aims to provide a method and system for activating and adjusting one or more HMIs of a vehicle based on the vehicle environment and the driver's attention.

[0005] For this, it concerns a process of activating one or more HMIs of a vehicle based on the vehicle's environment and the driver's attention.

[0006] According to the invention, the method comprises the following steps implemented iteratively: - an acquisition step, implemented by the acquisition unit, to acquire at least one representation of the environment and the driver's eye movements; - a first determination step, implemented by the processor, to determine an attentional level matrix of the driver for the environment at least from the representation of the environment and the eye movements of the driver; - a listing step, implemented by the processor, to establish a list of environmental obstacles that the vehicle may encounter, based on the representation of the environment; - a second determination step, implemented by the processor, to determine a safe movement field observed by the driver from the attentional level matrix and the list of obstacles, the safe movement field comprising a grid containing the listed obstacles and their associated attentional level; - a first activation step, implemented by the processor, to activate a first HMI if at least one obstacle in the safe movement field has an associated attention level less than or equal to a predetermined attention level threshold; - a second activation step, implemented by the processor, to activate a second HMI if a difference parameter between, on the one hand, a safe displacement field predicted by the processor after activation of the first HMI and, on the other hand, a new safe displacement field determined by the processor after activation of the first HMI is greater than or equal to a predetermined difference threshold.

[0007] Thus, the process makes it possible to determine a safe current displacement field observed by the conductor, which allows the HMI to be precisely adapted to be activated.

[0008] Furthermore, the first step in activating the first HMI includes the following sub-steps: - a sub-step of determining the first HMI in a list of HMIs intended to increase the driver's attention towards at least one obstacle for which the associated attention level is less than or equal to the predetermined attention level threshold; - a sub-step for activating the first determined HMI.

[0009] Advantageously, the list of HMIs intended to increase driver attention is associated with the vehicle driver.

[0010] Furthermore, the acquisition step is implemented by the acquisition unit to also acquire at least some driver action parameters, The first determination step is implemented by the processor to determine the attentional level matrix further from the driver's action parameters.

[0011] Furthermore, the second activation step also includes the following sub-steps implemented iteratively by the processor if a first GUI has been activated: - a sub-step of predicting a safe movement field predicted as a function of the first HMI activated in the first activation step, the predicted safe movement field corresponding to a safe movement field that the driver is expected to observe after the first HMI has been activated; - an acquisition sub-step, implemented by the acquisition unit after activation of the first HMI, to acquire at least one representation of the environment and the driver's eye movements; - a first sub-step of determination, implemented by the processor, to determine an attentional level matrix of the driver for the environment at least from the representation of the environment and the eye movements of the driver; - a sub-step of listing, implemented by the processor, to establish the list of environmental obstacles that the vehicle may encounter, based on the representation of the environment; - a second sub-step of determining the new safe displacement field at the instant corresponding to the prediction of the prediction sub-step; - a substep comparing the predicted safe displacement field and the new safe displacement field to determine a difference parameter between the predicted safe displacement field and the new safe displacement field; - a sub-step to activate a second GUI if the difference parameter is greater than or equal to a predetermined difference threshold; - a sub-step of deactivating the first GUI if the difference parameter is strictly less than the predetermined difference threshold.

[0012] Furthermore, the predicted safe movement field is further predicted based on movement parameters of the environmental obstacle(s) provided by an environmental modeling system.

[0013] Furthermore, the activation substep includes the following substeps: - a sub-step of determining the second HMI in the list of HMIs intended to increase the driver's attention to at least one obstacle; - a sub-step for activating the second determined HMI.

[0014] Advantageously, the second HMI corresponds to a modulation of the first HMI.

[0015] The invention also relates to a system for activating one or more HMIs of a vehicle based on the vehicle environment and the driver's attention.

[0016] According to the invention, the determination system comprises: - an acquisition unit configured to acquire at least some representation of the environment and the driver's eye movements, and a processor configured to: - determine a matrix of the driver's attentional level for the environment at least from the representation of the environment and the driver's eye movements; - establish a list of environmental obstacles that the vehicle may encounter, based on the representation of the environment; - determine a safe movement field observed by the driver from the attentional level matrix and the list of obstacles, the safe movement field comprising a grid containing the listed obstacles and their associated attentional level; - activate a first HMI if at least one obstacle in the safe movement field has an associated attention level less than or equal to a predetermined attention level threshold; - activate a second HMI if a difference parameter between, on the one hand, a safe displacement field predicted by the processor after activation of the first HMI and, on the other hand, a new safe displacement field determined by the processor after activation of the first HMI is greater than or equal to the predetermined difference threshold.

[0017] Furthermore, to activate the first GUI, the processor is configured to: - determine the first HMI in a list of HMIs intended to increase the driver's attention towards at least one obstacle for which the associated attention level is less than or equal to the predetermined attention level threshold; - activate the first determined GUI.

[0018] Furthermore, the acquisition unit is configured to acquire at least some driver action parameters, and the processor is configured to determine the attentional level matrix further from the driver action parameters.

[0019] Furthermore, if a first GUI has been activated, in order to activate the second GUI, the processor is also configured to iteratively: - predict a safe travel field predicted as a function of the first activated HMI, the predicted safe travel field corresponding to a safe travel field that the driver is expected to observe after the first HMI has been activated; - acquire at least a representation of the environment and the driver's eye movements; - determine a matrix of the driver's attentional level for the environment at least from the representation of the environment and the driver's eye movements; - establish a list of environmental obstacles that the vehicle may encounter, based on the representation of the environment; - determine a new safe displacement field at the time of predicting the predicted safe displacement field; - compare the predicted safe displacement field and the safe displacement field to determine a difference parameter between the predicted safe displacement field and the new safe displacement field; - activate a second GUI if the difference parameter is greater than or equal to a predetermined difference threshold; - disable the first GUI if the difference parameter is strictly less than the predetermined difference threshold.

[0020] Furthermore, to activate the second GUI, the processor is configured to: - determine the second HMI in the list of HMIs intended to increase the driver's attention to at least one obstacle; - activate the second determined GUI.

[0021] Advantageously, the second HMI corresponds to a modulation of the first HMI.

[0022] The invention also relates to a vehicle comprising a system for activating and adjusting one or more vehicle HMIs according to the vehicle environment and the attention of a vehicle driver, as described above. Brief description of the figures

[0023] The attached figures will clearly illustrate how the invention can be implemented. In these figures, identical references designate similar elements.

[0024] Figure [1] schematically represents the activation system according to one embodiment.

[0025] Figure [Fig.2] schematically represents the activation process according to one embodiment.

[0026] Figure 3 schematically represents a vehicle including the activation system and driven by a driver.

[0027] Figure 4 represents a driver's gaze direction towards a region before the first HMI is activated.

[0028] Figure 5 represents the region including the obstacle towards which the driver's gaze is oriented a priori after the activation of the first HMI.

[0029] Figure 6 schematically represents the activation or not of a second HMI following the activation of the first HMI.

[0030] Figure [Fig. 7] represents an example of an attentional level matrix in the form of a heat map of driver DR's attention.

[0031] Figure [8] represents a schematic example of a safe displacement field.

[0032] Figure 9 represents an example of a safe displacement field determined by the processor before the first HMI was activated.

[0033] Figure 10 represents an example of a safe displacement field predicted after the activation of the first HMI.

[0034] [Fig.11] is an example of a safe displacement field determined by the processor after the first HMI was activated. Detailed description

[0035] The activation and adjustment system 1 (hereinafter referred to as "activation system 1") is shown in [Fig. 1] according to one embodiment. Activation system 1 corresponds to an activation system for one or more HMIs HMIs HMIs 1, HMIs 2 of an EV based on the environment of the EV and the attention of an EV driver.

[0036] Within the scope of the invention, an HMI (Human-Machine Interface) may consist of at least: an audible device in the EV capable of emitting an audible signal when activated, a visual device in the EV capable of emitting a visual signal when activated, or a haptic device in the EV capable of emitting a haptic signal when activated. The HMI is adapted to draw the driver's attention, for example, to an obstacle that the EV may encounter.

[0037] Figure 3 shows an EV corresponding to a car. However, the activation system 1 and the activation process shown in Figure 2 can be applied to any other vehicle, such as an aircraft or a boat.

[0038] Activation system 1 and the activation process can be used for autonomous vehicles, for example to estimate the moment of taking back control of the vehicle (highly automated (level 3) or fully automated (level 4) autonomous driving). They can also be used in driver assistance systems or advanced driver assistance systems (ADAS) or in various mobility services.

[0039] The EV vehicle includes the activation system 1 ([Fig.3]).

[0040] Figures 4, 5, and 6 present a non-limiting example of an HMI. In this example, the HMI consists of a strip of LEDs. The strip can be placed under the windshield of the vehicle. Depending on the position of the obstacle, the strip is activated by lighting up the LEDs opposite the obstacle, as shown in Figure 5.

[0041] The activation system 1 includes at least one acquisition unit 2 and one PR processor.

[0042] Acquisition unit 2 is configured to acquire at least one representation of the environment and eye movements of driver DR.

[0043] The environmental representation can be obtained from images of the environment captured by one or more cameras 10 mounted on the EV. The environmental images can be typical images of the environment as seen by the driver. Each camera 10 is configured to provide an electrical signal to the acquisition unit 2. This electrical signal is representative of the environmental images. Alternatively or complementarily, the environmental representation can be obtained or supplemented by measurements taken by one or more radars and / or lidars configured to transmit data to the acquisition unit 2. Eye movements can be captured by an eye tracker 11. The eye tracker 11 is configured to capture eye movements in the direction of the driver's gaze. The eye tracker 11 is configured to provide an electrical signal to the acquisition unit 2.This electrical signal is representative of the movements in the direction of the gaze 15 of the DR driver.

[0044] Acquisition unit 2 can also be configured to acquire at least physiological parameters of the DR driver and action parameters of the DR driver on the VE vehicle.

[0045] Physiological parameters can be measured using at least one sensor 3, 4. This sensor or these sensors 3, 4 are configured to provide an electrical signal to the acquisition unit 2. These electrical signals are representative of the physiological parameter for which the sensor 3 or 4 is configured. By way of exception, the acquisition unit 2 can receive electrical signals from a heart rate sensor 3 and an eye data sensor 4. The heart rate sensor 3 is configured to measure the heart rate of the DR driver and provide an electrical signal representative of the DR driver's heart rate. The eye data sensor 4 can include two sensors, one configured to measure the eyelid beat rate of the DR driver and the other configured to measure the DR driver's gaze angle. The data sensor The ocular sensor 4 is configured to provide an electrical signal representative of the blink rate and to provide an electrical signal representative of the driver's gaze angle. The acquisition unit 2 can also receive electrical signals from an electrodermal sensor 12. For example, this electrodermal sensor 12 can be integrated into the steering wheel 18 of the EV to measure the skin conductance of the driver.

[0046] The driver action parameters DR on the EV can be measured from sensors 6, 7, and 8 mounted on the EV. Each of these sensors 6, 7, and 8 provides an electrical signal to the acquisition unit 2. These electrical signals are representative of the action parameter for which the sensor 6, 7, or 8 is configured. By way of exception, the acquisition unit 2 can receive electrical signals from a speed sensor 6, an acceleration sensor 7, and a steering angle sensor 8. The speed sensor 6 is configured to measure a current EV speed and provide an electrical signal representative of a current EV speed. The acceleration sensor 7 is configured to measure a current EV acceleration and provide an electrical signal representative of a current EV acceleration.The steering angle sensor 8 is configured to measure a current steering angle 18 of the EV vehicle relative to a vertical and provide an electrical signal representative of a current steering angle 18 of the EV vehicle.

[0047] The PR processor is configured to determine an attentional level matrix M of the DR driver of the environment at least from the representation of the environment and the eye movements of the DR driver.

[0048] The PR processor can determine the attentional level matrix M from, in addition, the driver action parameters DR on the EV vehicle, by analyzing whether his behavior is in line with the consideration of elements of the environment, for example by observing the acceleration of the EV vehicle or the movements of the steering wheel 8. The attentional level can be established for example by the implementation of a previously trained machine learning algorithm.

[0049] The attentional level matrix M corresponds to a matrix in which a numerical level of driver DR's attention is given at each point of the environmental representation. Figure 7 shows an example of an attentional level matrix M in the form of a heat map. Region 13 of the heat map corresponds to a region where driver DR has high attention. Region 14 of the heat map corresponds to a region where driver DR has lower attention than in region 13.

[0050] This attentional level matrix M can be determined at a predetermined frequency. Without limitation, the predetermined frequency is equal to 2 seconds.

[0051] The PR processor is also configured to establish a list of OB obstacles in the environment that the VE vehicle may encounter. Obstacle detection can be done from the representation of the environment, for example from images acquired by the camera(s) 10, for example by implementing an image segmentation algorithm, and / or from information obtained from other on-board sensors of the vehicle (for example radar, lidar, ...).

[0052] The processor is further configured to determine an EoST (Eield of Safe Travel) observed by driver DR from the attentional level matrix M and the obstacle list OB. The EoST is modeled as a grid G ​​containing the listed obstacles OB and their associated attentional levels. The obstacles OB are placed on the grid G ​​according to their current position relative to driver DR. This is a well-known representation, also known as the "Gibson principle." Figure 8 shows an example of an EoST in which three obstacles OBI, OB2, and OB3 are represented. The EoST is a measure of driver DR's situational awareness.

[0053] The safe travel field (EoST) is modeled by the PR processor using the attentional level matrix M and the obstacle list OB. The attentional level matrix M assigns an average attention level of the driver DR to the obstacles OB in the world model. The higher the average attention level of an obstacle OB, the higher the driver DR's attention to that obstacle OB.

[0054] The PR processor is configured to activate the first HMI (HMI 1) if at least one listed obstacle (OB) has an associated attention level less than or equal to a predetermined attention level threshold. Activation of the first HMI (HMI 1) follows the determination of the safe movement field (EoST). The predetermined attention level threshold can be the same for every obstacle (OB), or it can vary depending on the type of obstacle (OB).

[0055] Advantageously, for each obstacle OB for which the associated attention level is less than or equal to the predetermined attention level threshold, the PR processor is configured to determine the first HMI IHM1 from a list of HMIs designed to increase driver DR's attention toward the obstacle OB and to activate the first HMI IHM1 determined by the PR processor. The list of HMIs can be stored in a database within the vehicle. The list of HMIs can be associated with the driver DR.

[0056] Determining the first HMI in the HMI list can be implemented by artificial intelligence such as a pre-trained machine learning algorithm.

[0057] The PR processor can also be configured to adapt / modulate the HMI based on the driver DR's consideration of obstacles OB. Thus, the processor is further configured to activate a second HMI IHM2 if a difference parameter between, on the one hand, a safe movement field predicted PFoST by the PR processor after activation of the first HMI IHM1 and, on the other hand, a new safe movement field FoST determined by the processor (PR) after activation of the first HMI IHM1 is greater than or equal to the predetermined difference threshold.

[0058] To achieve this, if a first HMI (HMI1) has been activated at time t, in order to activate the second HMI (HMI2), the PR processor can also be configured iteratively to: - predict a safe displacement field PFoST as a function of the first activated HMI IHM1, the predicted safe displacement field PFoST corresponding to a safe displacement field that the driver DR is supposed to observe at a time t+x after the first HMI IHM1 has been activated; - acquire at least a representation of the environment and the eye movements of the driver DR; - determine an attentional level matrix M of the driver DR for the environment at least from the representation of the environment and the eye movements of the driver DR; - establish the list of OB obstacles in the environment that the EV vehicle may encounter, based on the representation of the environment; - determine a new displacement field on FoST at time t+x; - compare the predicted safe displacement field PFoST and the safe displacement field FoST to determine a difference parameter between the predicted safe displacement field PFoST and the new safe displacement field FoST for each obstacle OB; - activate a second HMI IHM2 (and possibly deactivate the first HMI IHM1 if the difference parameter is greater than or equal to a predetermined difference threshold, which corresponds to a case where the activation of the HMI IHM1 did not have the expected effect on the driver's vigilance; - deactivate the first HMI IHM1 if the difference parameter is strictly less than the predetermined difference threshold.

[0059] Indeed, when an HMI (IHM1, IHM2) linked to an obstacle (OB) is activated, it is possible to predict what the safe travel field (PFoST) of the driver (DR) should be after taking into account the indication given by this HMI (IHM1, IHM2). It is then possible to verify the effectiveness of an HMI (IHM1, IHM2) by recalculating the safe travel field (FoST) (the new safe travel field). at the prediction time, and by measuring the difference between this safe displacement field FoST, and that predicted PFoST when the HMI IHM1 is activated.

[0060] The predicted safe travel field (PFoST) can be calculated using a prediction model by estimating the new safe travel field based on knowledge of the previous safe travel field(s) (FoST) and the previous HMI (Human-Machine Interface). The prediction model can be based on priors defined during the selection of an HMI implementation strategy, or on a machine learning algorithm trained on collected data, for example, from a driver database. The prediction model can also be customized based on historical data for a specific driver (DR).

[0061] Advantageously, the OB obstacles in the OB obstacle list can be analyzed and linked together by a WM environment modeling system of the "world model" type, designed to provide a representation of the vehicle's environment and to predict future developments. This model can be used to analyze obstacle movement in order to predict their position at the time of prediction of the predicted safe field PFoST. Thus, the predicted safe displacement field PFoST is further predicted based on displacement parameters of the OB obstacle(s) in the environment provided by the WM environment modeling system.

[0062] The second HMI (HMI2) can be of a different type than the first HMI (HMI1), or a variant of the first HMI (HMI1), for example, an audible alarm with a different volume or frequency, or a different LED color. This allows the alert to be varied according to the level of risk and its consideration by the HMIs.

[0063] Figures 4 and 5 illustrate a simple implementation of the invention. Figure 4 shows the gaze direction of conductor DR 15 before the first HMI IHM1 is activated. In Figure 4, conductor DR's gaze is directed towards the region 16 with hatching slanted to the right. Obstacle OB is not located in this region. In Figure 5, the first HMI IHM1 is activated to draw conductor DR's attention to obstacle OB. The activated (lit) LEDs are those with vertical hatching. The prediction model therefore predicts that conductor DR's gaze will be directed towards the region 17 with hatching slanted to the left.

[0064] The comparison of the predicted safe displacement field PFoST and the new effective safe displacement field FoST can be made by determining metrics such as the Kullback-Leibler divergence, which measures the dissimilarity between two distributions. This comparison allows us to determine the difference parameter. between the predicted safe displacement field PFoST and the new safe displacement field FoST.

[0065] Figure 6 represents an advantageous embodiment of the invention, in which, when the difference parameter between the predicted safe travel field PFoST and the new safe travel field FoST measured at the time corresponding to the prediction is greater than or equal to a predetermined difference threshold for an obstacle OB, corresponding to a case where the first HMI IHM1 did not have the expected effect on driver attention DR, a second HMI IHM2 is activated (Fig. 6, arrow pointing left). The purpose of HMI IHM2 is to increase the driver's awareness of the obstacle.

[0066] Conversely, if the difference between the predicted safe displacement field PFoST and the new safe displacement field FoST measured at the prediction time is strictly less than the predetermined difference threshold, the first HMI IHM1 is deactivated ([Fig. 6], arrow pointing to the right). Deactivating the first HMI IHM1 prevents overloading the driver's cognitive processes.

[0067] Figure 6 shows the LED strip 9. The activated (lit) LEDs are vertically hatched. In this embodiment, the second HMI IHM2 corresponds to a device designed to emit a sound signal when activated. Alternatively, both HMIs can correspond to a sound signal, with the second HMI IHM2 corresponding to a modulation (higher intensity, higher frequency) of the first HMI IHM1. Alternatively again, the second HMI 2 can be a modulation of the LED strip relative to the first HMI 1 (more intense light, different colors, higher number of illuminated LEDs).

[0068] The predetermined difference threshold can be associated with the DR driver.

[0069] The PR processor can be configured to determine the second HMI (IHM2) in the list of HMIs intended to increase driver DR's attention towards at least one obstacle (OB). The PR processor can be configured to activate the second determined HMI (IHM2).

[0070] Figure 9 represents an example of a safe travel field (FoST). In this Figure 9, driver DR's attention to obstacle OB2 is low compared to driver DR's attention to obstacle OBI. The height of obstacles OBI and OB2 is indeed representative of the level of attention paid to obstacle OBI or OB2.

[0071] Figure 10 shows an example of a predicted safe travel field (PFoST) after the first HMI (Homologation Module 1) has been activated. The predicted safe travel field (PFoST) shows an increase in attention level for obstacle OB2, as well as a slight decrease in attention level for obstacle OBI. Therefore, the driver (DR) should be attentive to both obstacles OBI and OB2 present on the road.

[0072] Figure 11 shows an example of a (new) safe travel field (FoST) recalculated after the first HMI (HCI) IHM1 was activated, at the time corresponding to the prediction in Figure 10. The FoST safe travel field shows that the attention level for obstacle OB2 is quite close to the predicted level. Therefore, we can consider that driver DR has correctly taken the HMI for obstacle OB2 into account, and the associated HMI can be deactivated if the required attention level is reached. Conversely, the attention level for obstacle OBI is much lower than the predicted level. Therefore, we can consider that driver DR has become less vigilant with respect to obstacle OBI.

[0073] Comparing the predicted safe travel field PFoST in [Fig. 10] with the safe travel field FoST in [Fig. 11] allows us to determine a difference parameter. This parameter can be used, for example, to deactivate the HMI designed to alert the driver to obstacle OB2 and activate a new HMI to warn of the hazard from obstacle OBI. It also allows us to analyze the relevance of the activated HMIs to the driver's attention level DR. This information can be used to modify the lists of HMIs intended to increase the driver's attention towards at least one obstacle OB or a particular direction, and / or the learning algorithms used to select the HMIs.

[0074] The invention thus makes it possible to evaluate the effectiveness of the HMI in modifying the driver's awareness of the situation, with the aim of selecting and / or shaping / adjusting the HMIs designed to make the driver aware of hazards on the road. It allows for the selection of the best possible HMI in order to minimize the driver's reaction time.

[0075] It also offers the advantage of only activating the HMIs when necessary, thus limiting the driver's workload. Finally, it allows the activated HMIs to be customized to the driver's profile, thereby increasing their acceptability.

[0076] The invention also relates to a method of activating and adjusting one or more HMIs HMI1, HMI2 of an EV vehicle according to an environment of the VR vehicle and the attention of a DR driver of the EV vehicle.

[0077] The activation process, shown in [Fig.2], comprises the following steps implemented iteratively (in a first iterative loop): - an acquisition step El, implemented by acquisition unit 2, to acquire at least some representation of the environment and eye movements of driver DR; - a first determination step E2, implemented by the PR processor, to determine an attentional level matrix M of the DR driver for the environment at least from the representation of the environment and the eye movements of the driver DR; - a listing step E3, implemented by the PR processor, to establish a list of OB obstacles in the environment that the VE vehicle may encounter, based on the representation of the environment; - a second determination step E4, implemented by the PR processor, to determine a safe movement field FoST observed by the driver DR from the attentional level matrix M and the obstacle list OB, the safe movement field FoST comprising a grid G ​​containing the listed obstacles OB and their associated attentional level; - a first activation step E5, implemented by the PR processor, to activate a first HMI IHM1 if at least one listed obstacle OB has an associated attention level less than or equal to the predetermined attention level threshold; - a second activation step E6, implemented by the PR processor, to activate a second HMI IHM2 if a difference parameter between, on the one hand, a safe displacement field predicted PFoST by the PR processor after activation of the first HMI IHM1 and, on the other hand, a new safe displacement field FoST determined by the PR processor after activation of the first HMI IHM1 is greater than or equal to a predetermined difference threshold.

[0078] The acquisition step implemented by the acquisition unit 2 may also include the acquisition of driver action parameters DR on the VE vehicle.

[0079] The first determination step E2, implemented by the PR processor, to determine the attentional level matrix M of the DR driver for the environment can be further determined from the DR driver's action parameters on the VE vehicle.

[0080] The first step E5 of activating the first HMI IHM1 may include the following sub-steps: - a sub-step E51 of determining the first HMI IHM1 in a list of HMIs intended to increase the driver's attention DR towards at least one obstacle OB for which the associated attention level is less than or equal to the predetermined attention level threshold; - a sub-step E52 of activation of the first determined HMI HMI1.

[0081] Advantageously, the second activation step E6 can further include the following substeps implemented iteratively by the PR processor (in a second iterative loop) if a first GUI IHM1 has been activated: - a substep E61 for predicting a safe displacement field predicted PFoST based on the first HMI IHM1 activated in the first activation step E5, the safe displacement field predicted PFoST corresponding to a displacement field sure that the DR driver is supposed to observe after the first HMI IHM1 has been activated; - a sub-step E62 of acquisition, implemented by the acquisition unit 2, to acquire at least one representation of the environment and the eye movements of the driver DR; - a first sub-step E63 of determination, implemented by the PR processor, to determine an attentional level matrix M of the driver DR for the environment at least from the representation of the environment and the eye movements of the driver DR; - a sub-step E64 of listing, implemented by the PR processor, to establish the list of OB obstacles in the environment that the VE vehicle may encounter from the representation of the environment; - a second sub-step E65 of determining the new safe displacement field FoST at the time corresponding to the prediction of the prediction sub-step E61; - a substep E66 comparing the predicted safe displacement field PFoST and the new safe displacement field FoST to determine the difference parameter between the predicted safe displacement field PFoST and the new safe displacement field FoST; - a sub-step E67a of activation of a second HMI HMI2 if the difference parameter is greater than or equal to a predetermined difference threshold; - a sub-step E67b of deactivation of the first HMI IHM1 if the difference parameter is strictly less than the predetermined difference threshold.

[0082] The predicted safe displacement field PFoST can be predicted in the prediction substep E61 further based on displacement parameters of the OB obstacle(s) in the environment. The OB obstacle list includes displacement parameters of the OB obstacles from the OB obstacle list.

[0083] The second E67a activation step may include the following sub-steps: - a sub-step E91a of determining the second HMI IHM2 in a list of HMIs intended to increase the attention of the driver DR for at least one obstacle OB; - a sub-step E92a of activation of the second determined HMI HMI2.

Claims

Demands

1. A method for activating and adjusting one or more HMIs (HMI1, HMI2) of a vehicle (VE) based on the vehicle's environment (VE) and the driver's attention (DR) of the vehicle (VE), characterized in that it comprises the following steps implemented iteratively: - an acquisition step (El), implemented by the acquisition unit (2), to acquire a representation of the environment and eye movements of the driver (DR); - a first determination step (E2), implemented by the processor (PR), to determine an attentional level matrix (M) of the driver (DR) for the environment at least from the representation of the environment and the eye movements of the driver (DR); - a listing step (E3), implemented by the processor (PR), to establish a list of obstacles (OB) in the environment that the vehicle (VE) may encounter, based on the representation of the environment; - a second determination step (E4), implemented by the processor (PR), to determine a safe movement field (FoST) observed by the driver (DR) from the attentional level matrix (M) and the list of obstacles (OB), the safe movement field (FoST) comprising a grid (G) containing the listed obstacles (OB) and their associated attentional level; - a first activation step (E5), implemented by the processor (PR), to activate a first HMI (HMI1) if at least one obstacle (OB) in the safe movement field has an associated attention level less than or equal to a predetermined attention level threshold; - a second activation step (E6), implemented by the processor (PR), to activate a second HMI (HMI2) if a difference parameter between, on the one hand, a predicted safe displacement field (PFoST) by the processor (PR) after activation of the first HMI (HMI1) and, on the other hand, a new safe displacement field (FoST) determined by the processor (PR) after activation of the first HMI (HMI1) is greater than or equal to a predetermined difference threshold.

2. A method according to claim 1, characterized in that the first step (E5) of activating the first HMI (HMI1) comprises the following substeps: - a substep (E51) of determining the first HMI (HMI1) in a list of HMIs intended to increase driver attention (DR) towards at least one obstacle (OB) for which the associated attention level is less than or equal to the predetermined attention level threshold; - a sub-step (E52) of activation of the first determined HMI (HMI1).

3. Method according to claim 2, characterized in that the list of HMIs intended to increase driver attention (DR) is associated with the driver (DR) of the vehicle (VE).

4. A method according to any one of claims 1 to 3, characterized in that the acquisition step (E1) is implemented by the acquisition unit (2) to further acquire at least some driver action parameters (DR), and in that the first determination step (E2) is implemented by the processor (PR) to further determine the attentional level matrix (M) from the driver action parameters (DR).

5. A method according to any one of claims 1 to 4, characterized in that the second activation step (E6) further comprises the following substeps implemented by the processor (PR) iteratively if a first HMI (HMI1) has been activated: - a substep (E61) of predicting a predicted safe displacement field (PFoST) as a function of the first HMI (HMI1) activated in the first activation step (E5), the predicted safe displacement field (PFoST) corresponding to a safe displacement field that the driver (DR) is expected to observe after the first HMI (HMI1) has been activated; - a sub-step (E62) of acquisition, implemented by the acquisition unit (2) after activation of the first HMI (HMI1), to acquire at least one representation of the environment and the eye movements of the driver (DR); - a first sub-step (E63) of determination, implemented by the processor (PR), to determine an attentional level matrix (M) of the driver (DR) for the environment at least from the representation of the environment and the eye movements of the driver (DR); - a sub-step (E64) of listing, implemented by the processor (PR), to establish the list of obstacles (OB) in the environment that the vehicle (VE) may encounter from the representation of the environment; - a second sub-step (E65) of determining the new safe displacement field (FoST) at the time corresponding to the prediction of the prediction sub-step (E61); - a substep (E66) of comparing the predicted safe displacement field (PFoST) and the new safe displacement field (FoST) to determine the difference parameter between the predicted safe displacement field (PFoST) and the new safe displacement field (FoST); - a sub-step (E67a) of activating a second HMI (HMI2) if the difference parameter is greater than or equal to a predetermined difference threshold; - a substep (E67b) of deactivating the first HMI (HMI1) if the difference parameter is strictly less than the predetermined difference threshold.

6. A method according to any one of claims 1 to 4, characterized in that the predicted safe displacement field (PFoST) is further predicted as a function of displacement parameters of the obstacle(s) (OB) in the environment provided by an environment modeling (WM) system.

7. Method according to claim 5, characterized in that the activation substep (E67a) comprises the following substeps: - a sub-step (E91a) of determining the second HMI (HMI2) in the list of HMIs intended to increase driver attention (DR) for at least one obstacle (OB); - a substep (E92a) of activation of the second determined HMI (HMI2).

8. Method according to claim 7, characterized in that the second HMI (HMI2) corresponds to a modulation of the first HMI (HMI1).

9. A system for activating and adjusting one or more HMIs (HMI1, HMI2) of a vehicle (VE) based on the vehicle's environment and the driver's attention (DR) of the vehicle (VE), characterized in that it comprises: an acquisition unit (2) configured to acquire at least some representation of the environment and the driver's eye movements (DR), and a processor (PR) configured to: - determine an attentional level matrix (M) of the driver (DR) for the environment at least from the representation of the environment and the eye movements of the driver (DR); - establish a list of environmental obstacles (OB) that the vehicle (VE) may encounter, based on the representation of the environment; - determine a safe movement field (FoST) observed by the driver (DR) from the attentional level matrix (M) and the list of obstacles (OB), the safe movement field (FoST) comprising a grid (G) containing the listed obstacles (OB) and their associated attentional level; - activate a first HMI (HMI1) if at least one obstacle (OB) in the safe movement field (FoST) has an associated attention level less than or equal to a predetermined attention level threshold, - activate a second HMI (HMI2) if a difference parameter between, on the one hand, a predicted safe displacement field (PFoST) by the processor (PR) after activation of the first HMI (HMI1) and, on the other hand, a new safe displacement field (FoST) determined by the processor (PR) after activation of the first HMI (HMI1) is greater than or equal to the predetermined difference threshold.

10. System according to claim 9, characterized in that, if a first HMI (HMI1) has been activated, in order to activate the second HMI (HMI2), the processor (PR) is further configured to, iteratively: - predict a predicted safe displacement field (PFoST) as a function of the first activated HMI (HMI1), the predicted safe displacement field (PFoST) corresponding to a safe displacement field that the driver (DR) is expected to observe after the first HMI (HMI1) has been activated; - acquire at least one representation of the environment and the driver's eye movements (DR); - determine an attentional level matrix (M) of the driver (DR) for the environment at least from the representation of the environment and the eye movements of the driver (DR); - establish the list of environmental obstacles (OB) that the vehicle (VE) may encounter, based on the representation of the environment; - determine a new safe displacement field (FoST) at the time of predicting the predicted safe displacement field (PFoST); - compare the predicted safe displacement field (PFoST) and the safe displacement field (FoST) to determine a difference parameter between the predicted safe displacement field (PFoST) and the new safe displacement field (FoST); - activate a second GUI (GUI2) if the difference parameter is greater than or equal to a predetermined difference threshold; - deactivate the first HMI (HMI1) if the difference parameter is strictly less than the predetermined difference threshold.

11. Vehicle, characterized in that it includes a system for activating and adjusting one or more HMIs (HMI1, HMI2) of a vehicle (VE) according to a vehicle (VE) environment and driver (DR) attention of the vehicle (VE), as specified according to any one of claims 9 to 10.

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