METHOD FOR DETECTING A STATE OF THE DRIVER OF A VEHICLE IMPLEMENTED IN AN ELECTRONIC SYSTEM, EVALUATION SYSTEM, COMPUTER PROGRAM PRODUCT AND INFORMATION STORAGE MEDIUM

Abstract

The invention relates to a method implemented in an electronic system equipping a vehicle. According to the invention, the method comprises the following steps: E11) detecting, for each detector, the presence of a state in the driver of the vehicle based on the data provided by said detector; E21) determining an overall state of the driver of the vehicle based on the number of states detected in step E11. Figure for abstract: Fig.1.

Description

Title of the invention: Method for detecting a state of the driver of a vehicle implemented in an electronic system, evaluation system, computer program product and information storage medium Technical field of the invention

[0001] The present invention generally relates to a method implemented in an electronic system equipping a vehicle.

[0002] It relates more particularly to a method for determining an overall state of drowsiness of the driver of the vehicle.

[0003] The invention finds a particularly advantageous application in driving a motor vehicle on long and / or difficult and / or changing journeys.

[0004] It also relates to a system for evaluating the overall state of drowsiness of a vehicle driver as well as a computer program product and an information storage medium. State of the art

[0005] Currently produced vehicles, particularly automobiles, have different types of sensors.

[0006] These sensors make it possible to obtain information on the interior environment of the vehicle.

[0007] The sensors include cameras for monitoring the position, posture, behavior of the driver and other occupants of the vehicle and detectors for detecting the presence of life within the vehicle. The sensors also include sensors evaluating the behavior of the vehicle, which behavior can be characterized by the speed and / or acceleration of the vehicle, the steering wheel angle, the activation of turn signals, the brake pressure or the gear engaged in the vehicle's gearbox.

[0008] The processing of the data provided by the various sensors makes it possible to emit warning and / or alert signals to the driver of the vehicle when a danger or risk is detected by one or more sensors fitted to the vehicle.

[0009] In the known state of the art, all of the sensors equipping a vehicle are not or are rarely used to operate in concert, each piece of information captured by a sensor being processed independently. Consequently, the information transmitted by the sensors is not or rarely contextualized. In addition, the recom The mandate given to the driver of the vehicle is basic and consists, for example, of advising them to take a break or to get back behind the wheel.

[0010] Also, and given the reliability of many sensors, there is a significant risk of false positives or false negatives when using these sensors. The alert issued in this case thus delivers false information to the driver of the vehicle.

[0011] Document DE 10 2018 208 060 describes a method of using contextual information, for example, the speed and / or acceleration of the vehicle, the brightness of the environment or a physiological parameter of the driver, for example a body temperature, to determine a state of fatigue of the driver of a vehicle from a multifunction mobile. The method described does not make it possible to determine an overall state of drowsiness based on the aggregation and contextualization of several different measurements of the state of drowsiness of the driver. Finally, this method is implemented from a multifunction mobile and limits the number and precision of the measurements carried out. Presentation of the invention

[0012] The invention aims to propose a solution to these problems and to make it possible to aggregate information from different sensors in order to evaluate a state with a better level of reliability as well as to contextualize the information captured.

[0013] The invention relates more specifically to a method for detecting a state of the driver of a vehicle implemented in an electronic system equipping a vehicle and comprising at least two detectors, the method comprising steps of detecting, for each detector, the presence of the state in the driver of the vehicle based on the data provided by said detector, and of determining an overall state of the driver of the vehicle based on the number of states detected.

[0014] The aggregation method also makes it possible to obtain global “super states” associated with the driver of the vehicle. Other “super states” may be envisaged, such as the state of distraction and / or the state of fatigue of the driver of the vehicle. These “super states” may advantageously be used by a driving management device to determine whether the driver is in a state of sufficient availability for driving the vehicle.

[0015] The information aggregation method may also be considered to be applied to data from different sensors in order to limit the occurrence of false positives and false negatives.

[0016] Other advantageous and non-limiting characteristics of the method according to the invention, taken individually or in all technically possible combinations, are the following: - the system includes at least three detectors, - at least one detector among the at least three detectors analyses the behaviour of the driver of the vehicle, at least one detector among the at least three detectors measures at least one physiological parameter of the driver of the vehicle and at least one detector among the at least three detectors measures at least one parameter of the vehicle, - the method further comprises the steps of: • determination of the number of detectors having detected a state of the vehicle driver at the detection stage, • determination, for each of the other detectors, of the number of detectors having detected a state of the driver of the vehicle over a first time range preceding the detection step, • determination of a first global state corrected according to the number of states detected during the previous steps, - the method further comprises the steps of: • determination of the number of detectors having detected a state, • determination, for each of the other detectors, of the number of detectors having detected a state of the driver over a second time range preceding the determination of the overall state, • determination of a second corrected global state as a function of the number of states detected during the previous steps, the time range used during the determination of the second corrected global state being wider than the time range used during the determination of the first corrected global state, - the first time range includes the five minutes preceding the detection step, - the second time range includes the fifteen minutes preceding the detection step, - the method further comprises a step E28 of determining whether a higher level of the global state is maintained during a third time range following the first time range of the determination step E23 or the second time range of the determination step E26, - the condition of the driver of a vehicle is one of drowsiness, cognitive distraction or total inability to drive.

[0017] The invention also proposes a system for evaluating the overall state of a vehicle driver, comprising: - a behavioral analysis device configured to analyze the behavior of the vehicle driver, - a body detection device for measuring at least one physiological parameter of the vehicle driver, - a vehicle detection device configured to measure at least one vehicle parameter, - a storage unit configured to store the data measured by the devices, - a processing unit configured to determine, for each device, whether a state has been detected in the driver of the vehicle based on the data relating to said device stored on the storage unit and to determine an overall state of the driver of the vehicle based on the number of states of the driver of the vehicle detected.

[0018] The invention also provides a computer program product comprising one or more sequences of instructions which are accessible to a processor and which, when executed by said processor, cause said processor to implement a method according to one of the possible embodiments.

[0019] The invention also provides a non-transitory information storage medium, in which it stores one or more sequences of instructions accessible to a processor and which, when executed by said processor, cause said processor to implement a method according to one of the possible embodiments.

[0020] Of course, the various features, variants and embodiments of the invention may be combined with each other in various combinations to the extent that they are not incompatible or mutually exclusive. Detailed description of the invention

[0021] The description which follows with reference to the appended drawings, given as non-limiting examples, will make it clear what the invention consists of and how it can be implemented.

[0022] In the attached drawings:

[0023] [Fig-1] is a functional diagram of a vehicle including an evaluation system of an overall state of drowsiness of a vehicle driver according to an embodiment in accordance with the invention;

[0024] [Fig.2] is a summary diagram of a method implemented in an electronic system equipping a vehicle according to an embodiment in accordance with the invention. The steps shown in dotted lines are optional. Device

[0025] A system 10 for evaluating an overall sleepiness state of a vehicle driver is shown in [Fig.l] with its peripheral components. The evaluation system 10 is mounted on a vehicle. In addition to the evaluation system 10, the The following elements are mounted on the vehicle: an electronic control unit (or ECU for "Electronic Control Unit" herein referred to as control unit) 90, a storage unit 92, a communication unit 94 and a navigation system 96, a sound device control unit 50 connected to a sound device 52, a visual element generation device control unit 60 connected to a visual element generation device 62, a vibrating device control unit 70 connected to a vibrating device 72, a temperature control device control unit 80 connected to a temperature control device 82,.

[0026] In addition to the various elements described above, numerous other devices can be integrated into the vehicle, such as for example acceleration, braking and obstacle detectors, although these elements are not shown in [Fig.l].

[0027] The control unit 90 makes it possible to control the evaluation system 10 which evaluates an overall state of drowsiness of a driver of a vehicle based on data provided by several detectors of the vehicle.

[0028] The storage unit 92 makes it possible to store information that can be used by the evaluation system 10, such as for example data provided by the detectors of the evaluation system 10. The storage unit 92 also makes it possible to store information that is not used by the evaluation system 10.

[0029] The communication unit 94 allows remote communication with a server located outside the vehicle, with other vehicles, etc. The communication unit 94 can receive information concerning the immediate environment of the vehicle and / or the route taken by the vehicle. The communication unit 94 is connected to the navigation system 96 to which it can communicate the information received.

[0030] The navigation system 96 comprises, for example, means for geolocating the motor vehicle (for example using GPS or GSM signals - according to the commonly used English acronym for "Global System for Mobile communication"). The location is characterized here by a latitude and a longitude.

[0031] The vehicle can also be located by using traffic lane identifiers known as “LinklD”. To explain how, we can first recall that in a navigation map, each portion of road (commonly called “Link”), has a unique identifier called “LinklD”. Each unique LinklD identifier is persistent across map updates and is not reused if the road is modified. We then understand that it is possible to locate the vehicle using not a latitude and a longitude, but rather using a unique LinklD identifier.

[0032] In the embodiment considered, the evaluation system 10 comprises a behavioral analysis device 12 configured to analyze the behavior of the driver of the vehicle. The behavioral analysis device 12 comprises, for example, a driver drowsiness and attention warning device, or an RGB camera. The behavioral analysis device 12 is, for example, configured to measure a state of drowsiness and / or a level of attention of the driver of the vehicle from the analysis of the behavior of the driver of the vehicle. The behavioral analysis device 12 is, for example, configured to analyze the behavior of the driver of the vehicle based on measurements and detections carried out by the latter on the driver of the vehicle.The behavioral analysis device 12 is configured, for example, to detect the posture and position of the driver of the vehicle, the position and orientation of the head of the driver of the vehicle, to detect, for example by means of a capacitive sensor integrated into the steering wheel of the vehicle, the position of the driver's hands relative to the steering wheel of the vehicle, the number of hands of the driver in contact with the steering wheel of the vehicle and the duration of contact of the driver's hands with the steering wheel of the vehicle. The behavioral analysis device 12 also comprises, for example, an eye tracking device configured to detect and track the gaze of the driver of the vehicle. The eye tracking device comprises, for example, a driver vigilance detection camera (for example forming part of a driver monitoring system, or "Driver Monitoring System" according to the commonly used English term).The eye tracking device makes it possible, for example, to measure in real time the orientation of the gaze of the driver of the vehicle. The eye tracking device measures, for example, the orientation of the driver's head and the orientation of the driver's eyes according to a vertical angle and a horizontal angle. The eye tracking device also measures, for example, the time associated with each orientation of the gaze and / or the frequency of the eye movements of the driver of the vehicle. The eye tracking device also measures the frequency of opening and closing of the eyelids of the driver of the vehicle and the duration of closure of the eyelids of the driver of the vehicle. Alternatively, the behavioral analysis device 12 is configured to detect the presence of the driver of the vehicle and / or the presence of a state of drowsiness in the driver of the vehicle.

[0033] The evaluation system 10 also comprises a body detection device 14 configured to measure at least one physiological parameter of the driver of the vehicle. The body detection device comprises, for example, an RGB camera, a connected watch or “Smartwatch” according to the commonly used English term) or a thermographic camera, of the infrared or thermal type. Other types of sensors can also be envisaged, such as, for example, ECG sensors, body temperature sensors or radars. configured to detect the presence of people within the vehicle. The body detection device 14 makes it possible, for example, to measure the temperature and / or the heart rate and / or the blood pressure and / or the respiratory rate of the driver of the vehicle. Alternatively, the body detection device 14 is configured to detect the presence of the driver of the vehicle and / or the presence of passengers and / or the presence of a state of drowsiness in the driver of the vehicle.

[0034] The evaluation system 10 also comprises a vehicle detection device 16 configured to measure at least one parameter of the vehicle. The vehicle detection device 16 comprises, for example, a vehicle speed and / or acceleration detector and / or a device for determining the steering angle of the vehicle and / or a turn signal use detector and / or a brake pressure determination device and / or a detector of the gear engaged in the vehicle's gearbox and / or an ambient light detector and / or a camera connected to a control unit for determining the ambient traffic density and / or a camera for detecting the presence of obstacles on the route traveled and / or one or more radars for monitoring the lateral environments of the vehicle and / or one or more laser sensors for detecting the presence of objects around the vehicle.

[0035] The evaluation system 10 also comprises a storage unit 18 configured to store the data measured by the behavioral analysis device 12, the body detection device 14 and the vehicle detection device 16.

[0036] The evaluation system 10 also comprises a processing unit 20. The processing unit 20 is configured to determine, for each device 12, 14 and 16 taken separately, whether a state of drowsiness has been detected in the driver based on the data relating to said detector and stored on the storage unit 18. The evaluation system 10 according to the embodiment of the invention therefore makes it possible to determine according to three different devices whether a state of drowsiness is detected in the driver of the vehicle. A state of drowsiness in the driver of the vehicle can therefore be detected between zero and three times. By state of drowsiness, it is understood that the evaluation system determines, according to Boolean logic, whether the driver of the vehicle is drowsy or alert.Preferably, each device 12, 14 and 16 is used in its operating range, comprising for example, the minimum speed of the vehicle for which said device can be used or the duration of activation of said device. Preferably, the determination of the overall state of drowsiness is carried out over an operating range common to the devices 12, 14 and 16.

[0037] The processing unit 20 determines a state of drowsiness based on the data provided by the behavioral analysis device 12, for example, based on the posture and position of the driver of the vehicle, the position and orientation of the head of the driver of the vehicle, the position of the driver's hands relative to the steering wheel of the vehicle, the number of hands of the driver in contact with the steering wheel of the vehicle, the duration of contact of the driver's hands with the steering wheel of the vehicle, the orientation of the driver's head or the orientation of the driver's eyes at a vertical angle and a horizontal angle, the time associated with each orientation of the gaze, the frequency of eye movements of the driver of the vehicle, the frequency of opening and closing of the eyelids of the driver of the vehicle and the duration of closure of the eyelids of the driver of the vehicle. Alternatively, the behavioral analysis device 12 determines a state of drowsiness of the driver of the vehicle and transmits it to the processing unit 20.

[0038] The processing unit 20 determines a state of drowsiness based on data provided by the body detection device 14, for example, based on the temperature, heart rate, blood pressure and / or respiratory rate of the driver of the vehicle. Alternatively, the body detection device 14 determines a state of drowsiness of the driver of the vehicle and transmits it to the processing unit 20.

[0039] The processing unit 20 determines a state of drowsiness as a function of the data provided by the vehicle detection device 16, for example, as a function of the speed, the acceleration of the vehicle, the steering angle of the vehicle, the use of the turn signals, the brake pressure, the gear engaged in the vehicle gearbox, the ambient brightness, the density of the ambient traffic, the presence of obstacles on the route traveled. Alternatively, the vehicle detection device 16 determines a state of drowsiness of the driver of the vehicle and transmits it to the processing unit 20.

[0040] The evaluation system 10 is also configured to determine an overall state of drowsiness of the driver of the vehicle as a function of the number of states of drowsiness detected in the driver of the vehicle. According to the embodiment considered, the processing unit 20 is configured to determine an overall state of drowsiness as a function of the data provided by the devices 12, 14 and 16, and stored on the storage unit 18. Alternatively, the processing unit 20 is configured to determine an overall state of drowsiness from the states of drowsiness determined by the devices 12, 14 and 16, and stored on the storage unit 18. Preferably, the overall state of drowsiness takes the form of a level proportional to the number of states of drowsiness detected in the driver of the vehicle.Alternatively, the overall drowsiness state takes the form of a level equal to the number of drowsiness states detected in the driver of the vehicle, each state being weighted by a coefficient assigned to each device 12, 14 and 16 according to the importance. granted to said device in determining the overall state of drowsiness of the driver of the vehicle and / or the level of confidence granted to said device. The weighting coefficient has, for example, a value equal to or greater than 0 and a value less than or equal to 1. For example, if a weighting coefficient of 1 is assigned to the behavioral analysis device 12, a weighting coefficient of 0.5 is assigned to the body detection device 14 and a weighting coefficient of 0.1 is assigned to the vehicle detection device, and the data relating to the three devices 12, 14 and 16 allow, for each of them, the detection by the processing unit 20 of a state of drowsiness in the driver of the vehicle, the overall level of drowsiness of the driver of the vehicle is 1.6. In the embodiment considered, the weighting coefficients all have a value equal to 1.

[0041] Advantageously, the aggregation of several data relating to the state of drowsiness of the driver and the determination of an overall state of drowsiness as a function of these data makes it possible to significantly increase the precision of the determination of the state of drowsiness of the driver of the vehicle and makes it possible to significantly reduce the occurrence of false positives and false negatives.

[0042] In the embodiment considered, the evaluation system 10 is configured to determine an overall state of drowsiness statically and dynamically. By determining an overall state of drowsiness statically, it is understood that the evaluation system 10 is configured to determine an overall state of drowsiness at a time t as a function of the data provided by the devices 12, 14 and 16 at the same time t. Alternatively, by determining an overall state of drowsiness statically, it is understood that the evaluation system 10 is configured to determine an overall state of drowsiness at a time t as a function of the data provided by the devices 12, 14 and 16 at a time t' very close to t, for example less than 1 second away from t.By determining an overall drowsiness state dynamically, it is understood that the evaluation system is configured to determine an overall drowsiness state at a time t based on data provided by the devices 12, 14 and 16 in a time interval preceding and including the time t or in a time interval preceding and including a time t' very close to t, for example less than 1 second away from t. During use of the vehicle, an overall drowsiness state is calculated regularly, for example every second, or continuously, based on the data provided by the devices 12, 14 and 16.When at least one state of drowsiness is detected at a time t, and therefore a non-zero overall state of drowsiness is determined by the processing unit 20, the processing unit 20 is configured to determine the number of detectors, among the devices 12, 14 and 16, whose data sent to the storage unit 18 allowed the detection of a state of drowsiness in . the driver of the vehicle by the processing unit 20 and to determine, for each of the other devices, i.e. the devices whose data sent to the storage unit 18 did not allow the detection of a state of drowsiness in the driver of the vehicle by the processing unit 20 at time t, whether a state of drowsiness was detected over a first time range preceding the detection of the at least one state of drowsiness based on the data sent to the storage unit 18 by the other devices during the first time range. The first time range has, for example, a value equal to or greater than 1 second and a value less than or equal to 30 minutes. In the embodiment considered, the first time range has a value equal to 5 minutes.

[0043] The evaluation system 10 is also configured to determine a first corrected overall sleepiness state based on the number of sleepiness states detected at time t and the number of sleepiness states detected over the first time range.

[0044] In the embodiment considered, the evaluation system 10 is also configured to determine the number of detectors, among the devices 12, 14 and 16, whose data sent to the storage unit 18 allowed the detection of a state of drowsiness in the driver of the vehicle by the processing unit 20 at time t or over the first time range, and to determine, for each of the other devices, i.e. the devices whose data sent to the storage unit 18 did not allow the detection of a state of drowsiness in the driver of the vehicle by the processing unit 20 at time t or during the first time range, whether a state of drowsiness was detected over a second time range preceding the detection of the at least one state of drowsiness and of a duration greater than the first time range as a function of the data sent to the storage unit 18 by the other devices during the second time range.Preferably, the first time range is included in the second time range. The second time range has, for example, a value greater than 1 second and a value less than or equal to 30 minutes. In the embodiment considered, the second time range has a value equal to 15 minutes.

[0045] The evaluation system 10 is also configured to determine a second corrected overall sleepiness state based on the number of sleepiness states detected at time t, the number of sleepiness states detected over the first time range and the number of sleepiness states detected over the second time range.

[0046] Advantageously, the dynamic determination of an overall state of drowsiness makes it possible to significantly increase the accuracy of the determination of the state of drowsiness of the driver of the vehicle and to better contextualize the information captured by the devices 12, 14 and 16 compared to a static determination of the overall state of drowsiness. Advantageously, the determination of a state of drowsiness dynamically global determination significantly reduces the occurrence of false positives and false negatives compared to a static determination of global sleepiness status.

[0047] If the overall sleepiness state or the first corrected overall sleepiness state or the second corrected overall sleepiness state, determined by the evaluation system 10 is greater than a threshold predetermined by the evaluation system 10 (and defining an alert threshold), the control unit 90 selects a countermeasure to be applied in order to reduce the overall sleepiness level of the driver of the vehicle or to increase the safety level of the driver of the vehicle. The countermeasure comprises, for example, the emission of an audible signal and / or a visual signal and / or vibrations, intended for the driver of the vehicle and / or a modification of the temperature within the passenger compartment of the vehicle.The control unit 90 is also configured to control the sound device control unit 50 and / or the visual element generation device control unit 60 and / or the vibration device control unit 70 and / or the temperature control device control unit 80 to respectively, emit an audible signal to the driver with the sound device 52 and / or generate a visual signal to the driver with the visual element generation device 62 and / or generate vibrations perceptible to the driver with the vibration device 72 and / or modify the temperature, globally or locally, within the passenger compartment of the vehicle with the temperature control device 82.

[0048] The sound signal emitted by the sound device 52 may also be a warning signal or a recommendation to the driver of the vehicle. The recommendation includes suggestions such as taking a break of a determined duration depending on the level of drowsiness of the driver of the vehicle. The determination of the duration of the recommended break is carried out by the processing unit 20 depending on the overall state of drowsiness, corrected or not, of the driver of the vehicle and / or the physiological and behavioral data relating to the driver of the vehicle and stored on the storage unit 18.

[0049] Alternatively, the countermeasure selected by the control unit 90 is different if the alert threshold is exceeded by the overall sleepiness state, the first corrected overall sleepiness state or the second corrected overall sleepiness state. For a given alert threshold, the countermeasure selected by the control unit 90 will be, for example, stronger if the alert threshold is exceeded by the overall sleepiness state than by the first corrected overall sleepiness state and the countermeasure selected by the control unit 90 will be, for example, stronger if the alert threshold is exceeded by the first corrected overall sleepiness state than by the second corrected overall sleepiness state. By stronger countermeasure, it is understood that the number of countermeasures measures taken is higher and the intensity of each countermeasure is higher (noise level, vibration intensity, etc.).

[0050] At least one of the devices or units of [Fig.l] may be implemented, at least in part, by means of a processor on which a computer program is executed. Such a computer program product comprises one or more sequences of instructions which are accessible to a processor and which, when executed by said processor, cause said processor to implement a method according to one of the possible embodiments, for example a method as described below with reference to [Fig.2].

[0051] The invention also provides a non-transitory information storage medium, in which it stores one or more sequences of instructions accessible to a processor and which, when executed by said processor, cause said processor to implement a method according to one of the possible embodiments.

[0052] However, some of the devices or units of [Fig.l] may be implemented by a dedicated electronic circuit, for example an application-specific integrated circuit or a hard-wired logic circuit.

[0053] It should be noted that all or part of the operations of the various methods in which the above embodiments can be understood by those skilled in the art can be accomplished by giving instructions to the relevant hardware through the computer program, and the computer program can be stored in the computer-readable storage medium, which can include, but is not limited to: a read-only memory (ROM), a random access memory (RAM), a disk, a CD or a memory unit having a similar function. Process

[0054] The invention also relates to methods implemented in an electronic system equipping a vehicle. The evaluation system 10 can, for example, be advantageously used for implementing such methods.

[0055] The invention, for example, a method implemented in an electronic system equipping a vehicle comprising at least two detectors, represented in [Fig.2] and comprising:

[0056] a detection step Eli for each detector, of the presence of a state of drowsiness in the driver of the vehicle according to the data provided by said detector;

[0057] a step E12 of determining the overall state of drowsiness of the driver of the vehicle as a function of the number of states of drowsiness detected in the driver of the vehicle during step Eli.

[0058] The two detectors are, for example, two detectors among the behavioral analysis device 12, the body detection device 14 and the detection device of vehicle 16 described above.

[0059] During the detection step E1 1, it is determined, for example by the processing unit 20 of the evaluation system 10, from the data of each detector, data for example stored on the storage unit 18, whether a state of drowsiness is detected in the driver of the vehicle. By state of drowsiness, it is understood that it is determined, according to a Boolean logic, whether the driver of the vehicle is drowsy or alert according to the data provided by each detector. A state of drowsiness can therefore be detected zero times or one or more times depending on the number of detectors detecting a state of drowsiness in the driver of the vehicle.

[0060] During the detection step E21, an overall state of drowsiness of the driver of the vehicle is determined, for example by the processing unit 20, as a function of the number of states of drowsiness detected during the step E11. The overall state of drowsiness takes the form of a level consisting of the total number of detectors having detected a state of drowsiness in the driver of the vehicle.

[0061] Preferably, the method is implemented in a system comprising at least three detectors. The three detectors are, for example, the behavioral analysis device 12, the body detection device 14 and the vehicle detection device 16 described above.

[0062] Preferably, at least one detector, for example the behavioral analysis device 12, analyzes the behavior of the driver of the vehicle, at least one detector, for example the body detection device 14, measures at least one physiological parameter of the driver of the vehicle and at least one detector, for example the vehicle detection device 16, measures at least one parameter of the vehicle.

[0063] Advantageously, the aggregation of data from several different types of detectors to determine an overall state of drowsiness makes it possible to significantly increase the accuracy of determining the state of drowsiness of the driver of the vehicle and to better contextualize the information captured by the different detectors.

[0064] In another embodiment, the method further comprises the following steps:

[0065] a step E22 of determining the number of detectors having detected a state of drowsiness of the vehicle driver at detection step El 1;

[0066] a step E23 of determining, for each of the other detectors, the number of detectors having detected a state of drowsiness of the driver of the vehicle over a first time range preceding the detection step El 1;

[0067] a step E24 of determining a first overall state of drowsiness corrected as a function of the number of states of drowsiness detected in the detection step El 1 and of the number of drowsiness states detected at determination step E23.

[0068] During the determination step E22, the number of detectors having detected a state of drowsiness in the driver of the vehicle in the detection step Eli and, consequently, the number of detectors not having detected a state of drowsiness in the driver of the vehicle in the detection step Eli is determined, for example by the processing unit 20.

[0069] During the determination step E23, it is determined, for example by the processing unit 20, whether, for each detector not having detected a state of drowsiness in the driver of the vehicle in step E1 1, the data provided by said detector during a first time range preceding the detection step E11 indicate a state of drowsiness in the driver of the vehicle during the first time range.

[0070] During the step of determining a first corrected overall state of drowsiness E24, a first corrected overall state of drowsiness as a function of the number of drowsiness states detected in the detection step E11 and the number of drowsiness states detected in the determination step E23 is determined, for example by the processing unit 20.

[0071] In another embodiment, the method further comprises the following steps:

[0072] a step E25 of determining the number of detectors having detected a state of drowsiness of the vehicle driver at detection step E1 1 or at detection step E23;

[0073] a determination step E26, for each of the other detectors, of the number of detectors having detected a state of drowsiness of the driver of the vehicle over a second time range preceding the determination of the state of the overall drowsiness state of the determination step E21;

[0074] a step E27 of determining a first overall state of drowsiness corrected as a function of the number of states of drowsiness detected in the detection step E1 1 and the number of states of drowsiness detected in the determination step E23.

[0075] In the embodiment considered, the time range of the determination step E26 is wider than the time range of the determination step E23 and includes the time during which the detection step Eli was carried out.

[0076] During the determination step E25, the number of detectors having detected a state of drowsiness in the driver of the vehicle in the detection step E1 1 or during the detection step E23 and, consequently, the number of detectors not having detected a state of drowsiness in the driver of the vehicle in the detection step E1 1 or in the detection step E23 is also determined, for example, by the processing unit 20.

[0077] During the determination step E26, it is determined, for example by the unit of processing 20, if, for each detector not having detected a state of drowsiness in the driver of the vehicle during the detection step El 1 and the detection step E23, the data provided by said detector during a second time range preceding the detection step El 1 indicate a state of drowsiness in the driver of the vehicle during the second time range.

[0078] During the step of determining a second corrected overall sleepiness state E27, a second corrected overall sleepiness state is determined, for example by the processing unit 20, as a function of the number of sleepiness states detected in the detection step E11, the number of sleepiness states detected in the determination step E23 and the number of sleepiness states detected in the determination step E26.

[0079] Preferably, the first time range and the second time range comprise the time during which the detection step Eli was carried out.

[0080] The first time range extends, for example, over a duration equal to or greater than 1 second and a duration less than or equal to 30 minutes preceding the detection step Eli. In the embodiment considered, the first range comprises the 5 minutes preceding the detection step Eli.

[0081] The second time range extends, for example, over a duration equal to or greater than 1 second and a duration less than or equal to 30 minutes preceding the detection step Eli. In the embodiment considered, the second range comprises the 15 minutes preceding the detection step Eli.

[0082] If the overall sleepiness state or the first corrected overall sleepiness state or the second corrected overall sleepiness state, determined respectively during steps E21, E24 and E26 is greater than a predetermined threshold (and defining an alert threshold), for example by the evaluation system 10, the method further comprises a selection step E29 during which a countermeasure is selected to reduce the overall sleepiness level of the driver of the vehicle and / or a recommendation to the driver of the vehicle, for example, by controlling the sound device control unit 50 and / or the visual element generation device control unit 60 and / or the vibrating device control unit 70 and / or the temperature control device control unit 80 for respectively,emitting an audible signal to the driver with the audible device 52 and / or generating a visual signal to the driver with the visual element generation device 62 and / or generating vibrations perceptible to the driver with the vibrating device 72 and / or modifying the temperature, globally or locally, within the passenger compartment of the vehicle with the temperature control device 82.,

[0083] Of course, the various features, variants and embodiments of the invention can be combined with each other in various combinations. to the extent that they are not incompatible or mutually exclusive. Variants

[0084] The present invention is in no way limited to the embodiment described and shown, but those skilled in the art will be able to provide any variant in accordance with the invention.

[0085] In another variant of the invention, the evaluation system 10 is configured to determine whether an overall state of drowsiness determined during the first time range and / or the second time range is maintained at a higher level during a third time range following the first time range or the second time range. By maintained at a higher level, it is understood that the evaluation system 10 determines, when an oscillation of the overall drowsiness level between two different levels is detected by the evaluation system during the third time range, what is the highest level of drowsiness detected. In the embodiment considered, the third time range extends over the 5 minutes following the end of the first time range and / or the second time range.

[0086] Advantageously, determining whether to maintain a higher level of an overall sleepiness state makes it possible to avoid signal flickering during determination of the overall sleepiness state.

[0087] In another variant of the invention, the evaluation system 10 is configured to measure a state of drowsiness, as a function of the data provided by each detection and / or analysis device, for example, the behavioral analysis device 12, the body detection device 14 and the vehicle detection device 16. According to this variant of the invention, the evaluation system 10 is also configured to determine an overall state of drowsiness as a function of the states of drowsiness measured by each detection and / or analysis device. By measuring the state of drowsiness, it is understood that the state of drowsiness of the driver of the vehicle is characterized as a function of the data provided by the detection and / or analysis device, for example, by a level between 0 (totally alert) and 1 (drowsy).

[0088] In another variant of the invention, the vehicle comprises at least four detectors.

[0089] In another variant of the invention, at least one detector measures the activities peripheral to the driving of the driver of the vehicle.

[0090] In another variant of the invention, the method further comprises a step E28 of determining whether a higher level of the overall state of drowsiness is maintained during a third time range following the first time range of the determination step E23 or the second time range of the determination step E26.

[0091] In another variant of the invention, the state of the driver of a vehicle determined by the evaluation system 10 and during the method of detecting a state of the driver of a vehicle is a state other than drowsiness, for example, cognitive distraction or total inability to drive.

Claims

Claims

1. Method for detecting a state of the driver of a vehicle implemented in an electronic system equipping a vehicle and comprising at least two detectors, the method comprising the following steps: E11) detection, for each detector, of the presence of the state in the driver of the vehicle based on the data provided by said detector; E12) determination of an overall state of the driver of the vehicle based on the number of states detected in step E11.

2. Method for detecting a state of the driver of a vehicle implemented in an electronic system equipping a vehicle according to claim 1, in which the system comprises at least three detectors.

3. Method for detecting a state of the driver of a vehicle implemented in an electronic system equipping a vehicle according to claim 2, in which at least one detector among the at least three detectors analyzes the behavior of the driver of the vehicle, at least one detector among the at least three detectors measures at least one physiological parameter of the driver of the vehicle and at least one detector among the at least three detectors measures at least one parameter of the vehicle.

4. Method for detecting a state of the driver of a vehicle implemented in an electronic system equipping a vehicle according to one of claims 1 to 3, the method further comprising the following steps: E22) determining the number of detectors having detected a state of the driver of the vehicle in the detection step El 1; E23) determining, for each of the other detectors, the number of detectors having detected a state of the driver of the vehicle over a first time range preceding the detection step El 1; E24) determining a first corrected global state as a function of the number of states detected in the detection step Eli and the number of states detected in the determination step E23.

5. Method for detecting a state of the driver of a vehicle implemented in an electronic system equipping a vehicle according to claim 4, the method further comprising the following steps: E25) determining the number of detectors having detected a state in step E1 1 or in step E23; E26) determining, for each of the other detectors, the number of detectors having detected a state of the driver over a second time range preceding the determination of the overall state of step E21; E27) determining a second corrected overall state as a function of the number of states detected in step E21, the number of states detected in determination step E23 and the number of states detected in determination step E26. in which the time range of determination step E26 is wider than the time range of determination step E23.

6. Method for detecting a state of the driver of a vehicle implemented in an electronic system equipping a vehicle according to claim 4 or 5, the first time range comprising the five minutes preceding the detection step Eli.

7. Method for detecting a state of the driver of a vehicle implemented in an electronic system equipping a vehicle according to claim 5 or 6, the second time range comprising the last fifteen minutes preceding the detection step Eli.

8. Method for detecting a state of the driver of a vehicle implemented in an electronic system equipping a vehicle according to one of claims 1 to 7, further comprising a step E28 of determining the maintenance of a higher level of the overall state during a third time range following the first time range of the determination step E23 or the second time range of the determination step E26.

9. A method for detecting a state of the driver of a vehicle implemented in an electronic system equipping a vehicle according to one of claims 1 to 8, in which the state of the driver of a vehicle is one of drowsiness, cognitive distraction or total inability to drive.

10. System (10) for evaluating an overall state of a vehicle driver, comprising: - a behavioral analysis device (12) configured to analyze the behavior of the driver of the vehicle, - a body detection device (14) for measuring at least one physiological parameter of the driver of the vehicle, - a vehicle detection device (16) configured to measure at least one parameter of the vehicle, - a storage unit (18) configured to store the data measured by the devices (12), (14) and (16), - a processing unit (20) configured to determine, for each device, whether a state has been detected in the driver of the vehicle based on the data relating to said device stored on the storage unit (18) and to determine an overall state of the driver of the vehicle based on the number of states of the driver of the vehicle detected.

11. A computer program product comprising one or more sequences of instructions which are accessible to a processor and which, when executed by said processor, cause said processor to implement a method according to one of claims 1 to 9.

12. A non-transitory information storage medium, wherein it stores one or more sequences of instructions accessible to a processor and which, when executed by said processor, cause said processor to implement a method according to one of claims 1 to 9.

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