Method for determining a trajectory for a motor vehicle

Abstract

The invention relates to a method for determining a trajectory (15) for a motor vehicle. The method comprises the steps - Recording a physiological state value (12) of a person who is in a moving motor vehicle, - Determining a motion sickness dosage value (14) based on the recorded physiological state value (12) and - Determining a trajectory (15) for the motor vehicle based on the determined kinetosis dosage value (14).

Description

[0001] The invention relates to a method for determining a trajectory for a motor vehicle.

[0002] Kinetosis (also called motion sickness) is caused by conflicting visual and vestibular sensory impressions and is considered a major hurdle to the acceptance and usability of autonomous vehicles. This requires the development of appropriate avoidance strategies during driving. A well-known approach in this context is the use of optimization-based trajectory planning and control methods, which minimize the so-called motion sickness dose value (MSDV) over a certain planning or control horizon. This allows an optimal trajectory to be determined for the average occupant with regard to kinetosis.

[0003] One object of the present invention can be seen in enabling individual adaptation of trajectory planning and control with regard to the current susceptibility to motion sickness. This object is achieved by the subject matter of the independent patent claim. Advantageous embodiments are the subject matter of the subclaims, the following description, and the figures.

[0004] According to the present invention, adaptive planning of a comfort-optimized trajectory is proposed, taking into account physiological state values ​​or signals (biosignals). In this case, the current physiological state of the occupant(s) is incorporated into a particularly optimization-based method for trajectory planning and trajectory control. In other words, the planning of a future driving trajectory for a motor vehicle is adapted, taking into account physiological signals from one or more occupants of the motor vehicle. This allows motion sickness or kinetosis to be actively reduced or avoided.

[0005] In this sense, the present invention provides a method for determining a trajectory for a motor vehicle. The method comprises, in particular, the following steps: - Recording a physiological state value of a person who is in a motor vehicle that is moving, - Determining a kinetosis dosage value based on the recorded physiological state value and - Determine a trajectory for the motor vehicle based on the determined kinetosis dosage value.

[0006] The trajectory can, for example, be a distance trajectory that assigns a time value to several route points. The distance trajectory thus determines when the vehicle should reach a specified position in the future. Furthermore, the trajectory can, for example, be a speed trajectory or an acceleration trajectory that assigns a speed or acceleration to several route points. The speed trajectory / acceleration trajectory thus determines the speed or acceleration at which the vehicle should move at specified positions.

[0007] According to one embodiment, the motor vehicle, in particular its drive train, is controlled based on the determined trajectory. For example, a motor (electric motor or internal combustion engine) and / or a braking system and / or a steering system can be controlled such that the motor vehicle moves according to the determined trajectory.

[0008] The physiological state value can be determined using various independent physiological measurement methods in the motor vehicle. For example, the effects on pulse, skin conductivity, facial temperature, or respiratory rate can be determined. The pulse and facial temperature can be estimated, for example, using a camera or a so-called driver monitoring system, with the pulse in particular being estimated using an infrared camera. The skin conductivity value can be determined, for example, using electrodes in the steering wheel. The respiratory rate can also be recorded using the aforementioned camera or a sensor built into the seat or belt. Furthermore, conclusions about the physiological state can be drawn by analyzing the exhaled air of the vehicle occupants, e.g. using laser spectroscopy. For example, DE 10 2021 201 498 A1 discloses how exhaled air can be analyzed to determine a physiological state value.In this sense, according to a further embodiment, the physiological state value is a pulse value. Alternatively, it can be a skin conductivity value or a facial temperature value. Furthermore, it can be a respiratory rate or a breath analysis value. The aforementioned physiological state values ​​can also be combined with one another.

[0009] Furthermore, based on the physiological state value, a kinetosis index value can be determined, and based thereon, the kinetosis dosage value can be determined. The kinetosis index value (in English: Motion Sickness Index) can be understood as a versatilely definable indicator value. Based on the physiological state value or the biosignal, the kinetosis index value provides information about whether the risk of kinetosis is increased or not. For example, the kinetosis index value can be a probability value, as described in DE 10 2020 205 622 A1. In this sense, according to a further embodiment, the method further comprises the step of determining a kinetosis index value based on the determined physiological state value, wherein the kinetosis dosage value is determined based on the recorded kinetosis index value (in English: Motion Sickness Index MSI).

[0010] According to a further embodiment, an adaptive adjustment of weighting factors of the kinetosis dosage value is proposed based on the currently measured biosignals or based on the current kinetosis index value of the occupant(s). The feature "adaptive" can be understood in particular to mean that the weighting factors are adjusted at each planning and control time depending on the measured biosignals and / or the determined current kinetosis index value. For example, the probability value described above or the physiological state value can be used to scale the weighting factors. In this case, nominal weighting factors can be multiplied by the kinetosis probability to obtain the adaptive or adapted weighting factors.In this sense, according to a further embodiment, the method further comprises the step of determining at least one adaptive weighting factor based on the determined physiological state value or the kinetosis index value, wherein the determination of the kinetosis dosage value is carried out based on the determined adaptive weighting factor.

[0011] A formula for calculating the kinetosis dosage value can contain three summands. Each of these three summands can be assigned to a spatial direction. Relative to a Cartesian coordinate system, a first summand can be assigned to the x-direction, a second summand to the y-direction, and a third summand to the z-direction. The three summands can each be multiplied by an adaptive weighting factor for the respective spatial direction. In this sense, according to a further embodiment, three adaptive weighting factors are determined, each of which is assigned to one of three spatial directions.

[0012] The three summands can each contain terms with an acceleration variable that describes an acceleration in one of the three spatial directions. For example, the first summand, which is assigned to the x-direction, can contain a first term with a first acceleration variable that describes a location-dependent acceleration of the motor vehicle in the x-direction. The second summand, which is assigned to the y-direction, can contain a second term with a second acceleration variable that describes a location-dependent acceleration of the motor vehicle in the y-direction. The third summand, which is assigned to the z-direction, can contain a third term with a third acceleration variable that describes a location-dependent acceleration of the motor vehicle in the z-direction.In this sense, according to a further embodiment, it is provided that the three adaptive weighting factors are each multiplied by a term which contains a location-dependent acceleration variable.

[0013] Alternatively or additionally, the three summands can each contain terms with a jerk variable, which describes a jerk as the time derivative of the acceleration in one of the three spatial directions. In this sense, according to a further embodiment, the three adaptive weighting factors are each multiplied by a term that contains a location-dependent jerk variable.

[0014] The three terms can each contain the respective location-dependent acceleration variable being squared and integrated over time over the length of a planning or control horizon. The resulting integral value can be taken as a square root and multiplied by the respective weighting factor:

[0015] Expressed in a formula, the kinetosis dosage value is thus: MSDVadaptive=kx(t)(∫tt+T(ax(s))2ds)12+ky(t)(∫tt+T(ay(s))2ds)12+kz(t)(∫tt+T(az(s))2ds)12 This includes: a x y,z Acceleration in all three spatial directions x, y and z k x,y,z Adaptive weighting factors (≥ 0) in all three spatial directions x, y and z depending on the measured physiological signals and / or the determined current Motion Sickness Index t Planning and control time T Length of planning / control horizon

[0016] At each planning and control time t, the weighting factors k can be adjusted depending on the measured biosignals and / or the determined current kinetosis index value.

[0017] The trajectory planning and control attempts to realize the trajectory in such a way that the above expression for the kinetosis dosage value is reduced or minimized. In this sense, according to a further embodiment, the trajectory is determined in such a way that the kinetosis dosage value is minimized or at least reduced.

[0018] If biosignals and / or a current motion sickness index indicate a currently increased susceptibility to kinetosis of the occupant(s), the weighting factors are increased accordingly; otherwise, the weighting factors are maintained or reduced. In this sense, according to a further embodiment, it is provided that the at least one weighting factor - is increased if the physiological status value indicates a currently increased susceptibility to kinetosis of the person, - is reduced if the physiological status value indicates a currently reduced susceptibility to motion sickness in the person, and - is not changed if the physiological status value indicates that the person is currently at a constant susceptibility to kinetosis.

[0019] The functional relationship between biosignals or the current motion sickness index and the weighting factors can be described in a variety of ways, in particular by suitable characteristic maps or neural networks. In this sense, according to a further embodiment, the determination of the motion sickness dosage value is carried out using a characteristic map or a neural network.

[0020] The adjustment of the weighting factors can be supplemented by other suitable inputs, e.g. “inmate reads yes / no” etc.

[0021] In the following, embodiments of the invention are explained in more detail with reference to the schematic drawing, wherein identical or similar elements are provided with the same reference numerals. Fig. 1 a person in a motor vehicle moving along a roadway, wherein a trajectory of the motor vehicle is determined based on physiological state values ​​of the person, and Fig. 2 a flow chart of an embodiment of a method according to the invention, by means of which the trajectory of the motor vehicle according to Fig. 1 can be determined.

[0022] Fig. 1 shows a motor vehicle 1. The motor vehicle 1 comprises four wheels, each with a tire 2. In Fig.1 shows a front tire and a rear tire. The motor vehicle 1 moves along a roadway 3 by means of the tires 2. The motor vehicle 1 comprises a driver assistance system 4 for controlling the motor vehicle 1. To control the motor vehicle 1 and the necessary method steps described in connection with the drawing, the driver assistance system 4 can have a processor unit 8 and a memory unit 9. The driver assistance system 4 can access sensor data 11 generated by at least one interior sensor 5 of the motor vehicle 1. The interior sensor 5 is arranged within an interior 6 of the motor vehicle 1. Also located in the interior 6 is a person 7, in particular a driver, who sits on a front seat 10 and can control the motor vehicle 1.

[0023] The sensor 6 can, for example, be a digital camera which visually records the person 7 and generates corresponding sensor data 11. In particular, the sensor 6 records a physiological state value 12 (e.g. pulse or facial temperature) of the person 7 who is located in the moving motor vehicle 1. The physiological state value 12 is contained in the sensor data 11 or can be derived therefrom. For example, the pulse and facial temperature of the person 7 can be estimated by the camera 6. The driver assistance system 4 can access the sensor data 11 in a first method step 100 and store the physiological state value 12, for example, in the memory unit 9. In a second method step 200, a kinetosis index value 13 can be determined based on the physiological state value 12.Based on the physiological state value 12, the kinetosis index value 13 provides information about whether the risk of kinetosis is increased for person 7 or not. For example, the kinetosis index value 13 can be a probability value.

[0024] In a third method step 300, the driver assistance system 4 determines a kinetosis dosage value 14 based on the detected physiological state value 12 or based on the kinetosis index value 13. In doing so, the driver assistance system 4 adjusts values ​​of adaptive weighting factors k x , k y , k z to determine the kinetosis dosage value 14, based on a currently measured physiological state value 12 or a currently measured kinetosis index value 13 of person 7.

[0025] In a fourth method step 400, the driver assistance system 4 determines a trajectory 15 for the motor vehicle 1, specifically based on the determined kinetosis dosage value 14. In a fifth method step 500, the driver assistance system 4 controls the motor vehicle 1 based on the determined trajectory 15. The trajectory planning and control attempts to realize the trajectory 15 in such a way that, for example, the following expression for the kinetosis dosage value 14 (in the formula: MSDV adaptive ) is reduced or minimized: MSDVadaptive=kx(t)(∫tt+T(ax(s))2ds)12+ky(t)(∫tt+T(ay(s))2ds)12+kz(t)(∫tt+T(az(s))2ds)12 a x y,z Acceleration in all three spatial directions x, y and z k x,y,z Adaptive weighting factors (≥ 0) in all three spatial directions x, y and z depending on the measured physiological signals and / or the determined current Motion Sickness Index t Planning and control time T Length of planning / control horizon

[0026] At each planning and control time t, the adaptive weighting factors k are adjusted depending on the measured physiological state values ​​12 and / or the determined current kinetosis index value 13.

[0027] If current physiological status values ​​12 and / or a current kinetosis index value 13 indicate a currently increased susceptibility to kinetosis of the person 7, the weighting factors k x , k y , k z increased accordingly, otherwise the weighting factors k x , k y , k z maintained or reduced. The functional relationship between the physiological state values ​​12 or the current kinetosis index value 13 and the weighting factors k x , k y , k zcan be described in different ways, e.g. by characteristic maps, suitable neural networks, Bayesian networks, logistic regression or decision trees. Reference symbol 1 vehicle 2 tires 3 lane 4 Driver assistance system 5 Interior sensor 6 Interior 7 drivers 8 Processor unit 9 Storage unit 10 front seat 11 Sensor data 12 physiological state value 13 Kinetosis index value 14 Kinetosis dosage value 15 Trajectory 100 first procedural step 200 second process step 300 third process step 400 fourth process step 500 fifth process step QUOTES CONTAINED IN THE DESCRIPTION

[0000] This list of documents submitted by the applicant was generated automatically and is included solely for the convenience of the reader. This list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions. Cited patent literature

[0000] DE 10 2021 201 498 A1

[0008] DE 10 2020 205 622 A1

[0009]

Claims

[1] Method for determining a trajectory (15) for a motor vehicle (1), the method comprising the steps - detecting a physiological state value (12) of a person (7) who is in a motor vehicle (1) that is moving, - determining a kinetosis dosage value (14) based on the detected physiological state value (12) and - Determining a trajectory (15) for the motor vehicle (1) based on the determined kinetosis dosage value (14). [2] Method according to claim 1, wherein the motor vehicle (1) is controlled based on the determined trajectory (15). [3] Method according to claim 1 or 2, wherein the physiological state value (12) is - a pulse value or - a skin conductivity value or - a facial temperature value or - a respiratory rate or - a breath analysis value. [4] Method according to one of the preceding claims, the method further comprising the step of determining a kinetosis index value (13) based on the determined physiological state value (12), wherein the determination of the kinetosis dosage value (14) is carried out based on the detected kinetosis index value (13). [5] Method according to one of the preceding claims, the method further comprising the step of determining at least one adaptive weighting factor (k x , k y , k z ) based on the determined physiological state value (12) or the kinetosis index value (13), wherein the determination of the kinetosis dosage value (14) is based on the determined adaptive weighting factor (k x , k y , k z ) takes place. [6] Method according to claim 5, wherein three adaptive weighting factors (k x , k y , k z), each of which is assigned to one of three spatial directions. [7] Method according to claim 6, wherein the three adaptive weighting factors (k x , k y , k z ) are each multiplied by a term containing a location-dependent acceleration variable. [8] Method according to claim 6 or 7, wherein the three adaptive weighting factors (k x , k y , k z ) are each multiplied by a term which contains a location-dependent jerk variable. [9] Method according to one of the preceding claims, wherein the trajectory (15) is determined such that the kinetosis dosage value (14) is minimized or at least reduced. [10] Method according to one of claims 5 to 9, wherein the at least one weighting factor (k x , k y , k z ) - is increased if the physiological status value (12) indicates a currently increased susceptibility to kinetosis of the person (7), - is reduced if the physiological state value (12) indicates a currently reduced susceptibility to kinetosis of the person (7), and - is not changed if the physiological state value (12) indicates a currently constant susceptibility to kinetosis of the person (7). [11] Method according to one of the preceding claims, wherein the determination of the kinetosis dosage value (14) is carried out using a characteristic map or a neural network.

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