PROCESSING UNIT, SYSTEM, AND COMPUTER-IMPLEMENTED METHOD FOR A VEHICLE INTERIOR FOR DETECTING AND REACTING TO ODORS OF A VEHICLE OCCUPANT

Abstract

The invention relates to a processing unit, a system, and a computer-implemented method for a vehicle interior, for detecting and reacting to odors of a vehicle occupant.

Claims

1. A processing unit for a vehicle interior for detecting and reaction to odors of a vehicle occupant, comprising: a first interface to a sensor that is configured to detect odor molecules in the exhalations and/or body odor of the vehicle occupant and convert the odor molecules to a first signal to obtain the first signal, wherein the first signal results from light interactions or comprises frequencies and/or amplitudes of oscillations; a second interface to a second sensor that is configured to identify at least one vehicle occupant in order to obtain at least one identity of the at least one vehicle occupant; wherein the processing unit carries out commands with which the processing unit: assigns odors indicating drugs and/or illnesses to the at least one identity of the at least one vehicle occupant on a basis of a position of the at least one vehicle occupant in the vehicle interior, and generates a second signal in response to a positive assignment, wherein the commands comprise a first machine learning algorithm that is trained to identify at least one of alcohol, cocaine, amphetamines, cigarette smoke, cannabis, tetrahydrocannabinol, morphine, methadone, ammonia, acetone, or a combination of these substances in the odors of the at least one vehicle occupant on a basis of the first signal, and a third interface to at least one vehicle unit configured to provide the second signal to the at least one vehicle occupant and/or a vehicle control system, wherein the first machine learning algorithm is trained in semantic image segmentation to identify the at least one vehicle occupant, or the commands comprise a second machine learning algorithm that is trained in semantic image segmentation to identify the at least one vehicle occupant.

2. The processing unit according to claim 1, wherein the first machine learning algorithm simulates a mammalian olfactory system and/or the processing unit forms a neuromorphic circuit.

3. The processing unit according to claim 1, wherein the processing unit is integrated in a vehicle or a vehicle electrical system.

4. A system comprising: at least one first sensor configured to detect odor molecules in the exhalations and/or body odor of the at least one vehicle occupants, and convert the odor molecules into first signals; at least one second sensor configured to identify the at least one vehicle occupants; and the processing unit according to claim 1, which is connected for signal transfer to the at least one first sensor and the at least one second sensor via the first interface and the second interface, respectively, wherein the system is configured to send a second signal from the processing unit to an optical, acoustic, and/or tactile information unit or vehicle control unit via the third interface.

5. The system according to claim 4, wherein the first sensor is a vehicle lidar sensor configured to detect odor molecules on a basis of diffused light returning from the vehicle interior.

6. The system according to claim 5, wherein the vehicle lidar sensor is configured to emit numerous light pulses of different wavelengths, and detect the odor molecules form the returning light for each of the wavelengths.

7. The system according to claim 4, wherein the vehicle lidar sensor comprises Q-switching.

8. The system according to claim 4, wherein the second sensor is a 2D or 3D camera sensor, radar sensor, or lidar sensor, and the system is configured to identify the at least one vehicle occupant through facial recognition.

9. The system according to claim 4, comprising a particular sensor that unifies functionalities of the at least one first sensor and the at least one second sensor, wherein the particular sensor is a time-of-flight sensor, in which the first signals are a result of light returning to the particular sensor form the vehicle interior, and the at least one vehicle occupant is identified on a basis of the time-of-flight for light pulses from the particular sensor to a body surface on the vehicle occupant.

10. The system according to claim 8, wherein the at least one second sensor detects individual appendages, and the system is configured to identify the at least one vehicle occupant on a basis of the detected appendages.

11. The system according to claim 4, wherein the at least one first sensor is located on a vehicle steering wheel or in the dashboard, and the at least one second sensor is located on the vehicle steering wheel, in the dashboard, in the windshield, or in the roof of the vehicle, when used in the vehicle interior.

12. The system according to claim 4, wherein the at least one first sensor is a vehicle lidar sensor configured to detect odor molecules on a basis of light returning from the vehicle interior, and the at lest one second sensor is a CCD or CMOS sensor for a spectroscopic analysis of the returning light.

13. The system according to claim 4, wherein the second signal is a control signal for an immobilizer in the vehicle, and the third interface provides the second signal to the immobilizer, or wherein the second signal is a control signal, and triggers a fail-safe or fail-operational state for the vehicle.

14. The system according to claim 4, comprising a memory and/or communication means for storing identified odors from drugs and/or illnesses and/or sending information regarding the identified odors to a business to which the vehicle belongs, or to a government agency.

15. A computer-implemented method for detecting and reacting to odors of at least one vehicle occupant, comprising: obtaining, by a processing unit, first signals that describe odor molecules; obtaining, by the processing unit, at least one identity identities of the at least one vehicle occupant; identifying, by the processing unit, odors indicating drugs and/or illnesses on a basis of the first signals, using a first machine learning algorithm that is trained to identify odors comprising the odors of at least one of alcohol, cocaine, amphetamines, cigarette smoke, cannabis, tetrahydrocannabinol, morphine, methadone, ammonia, acetone, or combinations of these substances on the basis of the first signals; assigning, by the processing unit, the odors to the at least one identity of the at least one vehicle occupant on a basis of a position of the at least one vehicle occupant in the vehicle interior; generating, by the processing unit, a second signal in in response to a positive assignment; and providing, by the processing unit, the second signal to at least one vehicle unit.

16. The system according to claim 9, wherein the at least one first sensor is located on a vehicle steering wheel or in the dashboard, and the particular sensor is located on the vehicle steering wheel, in the dashboard, in the windshield, or in the roof of the vehicle, when used in the vehicle interior.

Description

[0061] The invention shall be explained below in reference to exemplary embodiments shown in the drawings. Therein:

[0062] FIG. 1 shows an alcohol tester from the prior art;

[0063] FIG. 2 shows an exemplary embodiment of a system according to the invention in a vehicle interior;

[0064] FIG. 3 shows an exemplary embodiment of a processing unit according to the invention;

[0065] FIG. 4 shows a schematic illustration of a system according to the invention;

[0066] FIG. 5 shows a schematic illustration of another system according to the invention; and

[0067] FIG. 6 shows a schematic illustration of an exemplary embodiment of a method according to the invention.

[0068] The same reference symbols are used in the figures for the same or functionally similar elements. For purposes of clarity, only the relevant elements are indicated in the individual drawings.

[0069] FIG. 1 shows a vehicle driver as a vehicle occupant F, exhaling into a handheld device. The handheld device measures the alcohol concentration in the exhalation. If the value exceeds a threshold value, e.g. a legal limit, the vehicle starter motor will be locked. The vehicle will not be able to be started. Use of the handheld device is relatively uncomfortable. Moreover, the vehicle driver must make additional hand movements and/or manipulations in order to operate the handheld device before driving the vehicle.

[0070] The system 20 according to the invention is integrated in a vehicle interior in FIG. 2. FIG. 4 shows a schematic illustration of the system 20. The system 20 comprises a first sensor 21, by way of example. The first sensor 21 is integrated in the vehicle steering wheel and designed to detect odor molecules in the exhalations and/or body odor of the vehicle occupant F. The system 20 also comprises second sensors 22, which identify a vehicle driver's face using software for facial recognition. One of the second sensors 22 is located in the rear-view mirror in the vehicle interior and is a time-of-flight camera, for example. The other second sensor 22 is integrated in the dashboard and comprises, e.g., a camera, lidar, or radar sensor. The system 20 comprises a processing unit 10, as shown in FIG. 3.

[0071] The processing unit 10 receives signals from the first sensor 21 via a first interface 11. The processing unit 10 receives signals from the second sensor 22 via a second interface 12. Based on the signals, the processing unit detects odors in the exhalations and/or body odors of the vehicle occupants breathing toward the steering wheel, which indicate alcohol consumption, for example. The odors or the substances that cause the odors are identified using a machine learning method. The processing unit also links the odors to the identities of the vehicle occupants in order to prevent deception or misuse of the system 20. If it is determined, for example, that the alcohol concentration in the exhalations of the vehicle driver exceed a legal limit, the processing unit 10 generates a second signal. The second signal is sent to a vehicle control system ECU via a third interface 13 in the processing unit 10. The second signal causes the vehicle control system to prevent operation of the vehicle engine and/or drive train. The vehicle control system ECU is formed by an electronic control unit, for example.

[0072] FIG. 5 shows the system in an embodiment with just one sensor, e.g. a time-of-flight sensor or lidar sensor. In this case, the one sensor assumes the roles of both the first sensor 21 and the second sensor 22.

[0073] The method according to the invention is shown in FIG. 6. A first signal, describing odor molecules, is obtained in step V1. The vehicle occupants are identified in step V2. Odors indicating drugs and/or illnesses are identified in step V3 on the basis of the first signal using a first machine learning algorithm that is trained to identify odors on the basis of the first signal that comprise the odors from alcohol, cocaine, amphetamines, cigarette smoke, cannabis, tetrahydrocannabinol, morphine, methadone, ammonia, acetone, or a combination of these substances. The odors are assigned to the identity of a vehicle occupant in step V4 on the basis of the position of the vehicle occupant F in the vehicle interior. A second signal is generated in the case of a positive assignment in step V5. The second signal is sent to at least one vehicle unit in step V6.

[0074] The method is carried out by the processing unit 10 or the system 20.

REFERENCE SYMBOLS

[0075] F vehicle occupant

[0076] 10 processing unit

[0077] 11 first interface

[0078] 12 second interface

[0079] 13 third interface

[0080] 20 system

[0081] 21 first sensor

[0082] 22 second sensor

[0083] ECU vehicle control system

[0084] V1-V6 steps of the method