Method for operating a vehicle dynamics system device of a motor vehicle during driving, control device and motor vehicle

Abstract

The invention relates to a method for operating a driving dynamics system device (22) of a motor vehicle (10). A control device (12) provides driving style data during driving and uses it to determine a driver type of the driver (S2). The control device (12) determines a road category of the driving surface (S4). Depending on the driver type and the road category, the control device (12) determines a current driving situation (S5) and preselects at least one driving level (S8). Depending on further driver monitoring data, the control device (12) determines a current mood of the driver (S9, S10) and selects a driving level from the preselected driving levels on the basis thereof (S11). The control device (12) generates a switching signal for switching to the driving level to be activated (S12) and configures at least two motor vehicle systems accordingly (S13). Depending on further driver monitoring data, which illustrate the reaction of the driver to the activated driving level, the driving level can be adjusted.

Description

Technical Field

[0001] This invention relates to a method for operating a vehicle's motion dynamics system device during vehicle operation. Background Technology

[0002] The driving dynamics system equipment is understood as a device, device component, or device group configured to set, i.e., activate different driving levels. Here, each driving level describes a driving level-specific setting, i.e., a driving level-specific configuration, for a set of at least two vehicle systems. In each driving level, at least two vehicle systems, preferably all vehicle systems, are centrally set by the driving dynamics system equipment. Vehicle systems include: a steering system in which steering torque can be variably set; a dynamic steering unit in which the steering ratio can be variably set; an accelerator pedal and / or powertrain system in which variable characteristic curves can be preset; a headlight system in which, for example, variable oscillation characteristics of turn signals can be set; and / or an automatic transmission in which a switching program can be set specifically for the driving level. Other feasible vehicle systems include systems for setting a sports differential with variable lateral distribution, damping systems with variable damper characteristics, music output systems for controlling interior lighting and / or setting the interior atmosphere, and variable triggering programs.

[0003] Motor vehicles offer various driving configurations (such as "Comfort," "Off-road," and "Efficiency"), each placing the system in attributes tailored to that mode, resulting in corresponding overall vehicle characteristics. These different configurations are manually activated by the driver, for example, via buttons or touch controls on the central display screen.

[0004] To activate the preferred driving configuration, the driver must manually switch, which increases mental workload, as the driver must, for example, locate the buttons on the touchscreen to set the driving configuration. Furthermore, a systematic understanding of the driving configuration characteristics is required to select the appropriate configuration based on vehicle-driver-environment conditions, further increasing mental workload.

[0005] DE 10 2019 200 597 A1 discloses a method for adapting the driving mode of a vehicle to the driver's emotional state.

[0006] DE 10 2018 001 342 A1 discloses a vehicle driving assistance system comprising: one or more processors configured to implement a general driver model learning program and an individual driver model learning program, the general driver model learning program being configured to build a general driving model applicable to multiple vehicle drivers based on driving data from multiple drivers, the individual driver model learning program being configured to build an individual driver model based on driving data specific to an individual driver, which is unique to the individual vehicle driver, and providing an onboard controller in a vehicle operated by the individual driver.

[0007] DE 10 2016 204 901 A1 discloses a scenario adaptation method for driver parameters in a driving profile for a motor vehicle. Summary of the Invention

[0008] One of the objectives of this invention is to configure motor vehicles more precisely according to the driver's individual needs.

[0009] The proposed objective is achieved by the method and apparatus according to the invention as described in the independent claims, which are presented side by side. The dependent claims provide advantageous improvements.

[0010] The idea behind this invention is to perform situational analysis during driving, determining the road category of the vehicle's current driving surface and analyzing driving behavior, combined with driver emotion analysis, to select a driving level from multiple driving levels for a specific situation and a specific driver, and switch to the selected driving level. Factors are weighted, taking into account not only the environment but also the characteristics specific to the driver, such as their driving style and current emotion. Then, at least two vehicle systems are configured based on the driving level selected by the analysis. Thus, for example, a dynamic program can be selected and activated as a driving configuration or driving level for a sporty driver type, provided that the sporty dynamic program is suitable for the specific situation, i.e., the vehicle is currently driving on a road suitable for sporty driving. Unlike determining the driving level based on road conditions, the driving level is selected based on road category and driver emotion. Therefore, for example, if the driver is "sporty," the dynamic driving program is particularly meaningful on highways. For example, when exiting a highway, the dynamic program can be adapted to the conditions and possibilities of "national roads" or "rural roads."

[0011] The switching between contextual and sentiment analysis forms the basis for continuous reassessment, allowing driving configurations to change during driving and always adapt as best as possible to the situation and the driver. This principle is combined with a learning algorithm that examines the driver's reaction to newly set driving levels and adapts the analysis and selection methods as needed.

[0012] In other words, it automatically activates the configuration that provides the optimal experience for the individual driver through comprehensive analysis. This reduces the driver's workload, namely the effort required to switch driving configurations and familiarize themselves with the technology, and continuously optimizes the driving configuration experience across all vehicle-driver-environment situations. This learning algorithm not only achieves automatic configuration switching based on the driver's preferences and mood, but also enables individual configuration activation based on the driver's current mood. Therefore, this learning algorithm ensures that the analysis and selection method becomes increasingly accurate in selecting the driving level over time.

[0013] The advantageous result is that automatic and intelligent switching enables the optimal driving configuration for the best experience. Experiencing the optimal driving configuration allows for a full appreciation of all vehicle characteristics without requiring the driver to be familiar with the system. Therefore, manual operation by the driver is rendered obsolete, and in this way, it significantly contributes to reducing distractions and thus mental workload.

[0014] The method according to the invention for operating a driving dynamics system device for a motor vehicle is executed by a control device while the motor vehicle is in motion. The control device should be understood as a device, device component, or group of devices configured to receive and evaluate signals and generate control signals. The control device may, for example, be designed as a control device for a motor vehicle, a computer program, or a combination of multiple control devices interconnected for data fusion.

[0015] The control device provides driving style data, which describes the driving style of the motor vehicle driver. The driving style data can describe the driver's current and / or long-term driving behavior. For example, the driving style data can describe the driver's steering behavior, i.e., the steering movements they make while driving. Alternatively or additionally, the driving style data can describe the driver's acceleration and braking behavior, i.e., the corresponding longitudinal control set by the driver. Furthermore, optionally, the state of various vehicle functions and systems described by the driving style data can be how the driver adjusts them in manual operation. Therefore, the driving style data can, for example, describe how the driver holds the steering wheel, how they accelerate and / or brake, whether they brake suddenly or gently, and which assistance systems they use. Based on the provided driving style data, the control device determines the driver's driving type. For example, the driver could be a sporty driver, a comfort driver, or a family person.

[0016] The control unit determines the road category on which the vehicle is currently traveling. In other words, the control unit determines what type of road the vehicle is on—whether it is, for example, a rural road, a highway entrance, or a city road. Therefore, it considers not road conditions, but road category, which, for example, determines what is feasible and what is not on that road in terms of speed or lane width. For example, a driving mode is more meaningful on a highway than on a road not classified as a main road (such as a road within a construction zone).

[0017] The control device may receive driving style data, for example, from vehicle sensor devices, and information about road categories, for example, from navigation devices. Accordingly, the vehicle may preferably include sensor devices, i.e., devices, groups of devices, or device components configured and designed to detect driving style data by means of at least one sensor. For detecting driving style data, the sensor devices include commonly used sensor devices for detecting, for example, braking and steering behaviors.

[0018] The control unit determines the current driving situation based on the determined driver type and road category. For example, the combination of a sporty driver and a highway as the road surface can represent the driving situation "sporty or dynamic long-distance travel". For example, a more comfortable driver type currently driving in the city can form the driving situation "comfortable short-distance driving".

[0019] When pre-selecting from multiple predetermined driving levels, such as from available driving levels Comfort, Dynamic, and Off-road, the control device selects at least one driving level, preferably at least two, corresponding to a defined driving scenario. For example, the driving scenario "Sporty Long-Distance Tour" may be associated with the driving levels "Dynamic" and "Auto". For example, the driving scenario "Cautious City Driving" may be associated with the driving levels "Comfort" and "Efficiency" (i.e., the fuel-efficient driving level).

[0020] Each driving level corresponds to a set of settings for at least two vehicle systems used in the motor vehicle, tailored to that specific driving level. Thus, for example, a driving level "Dynamic" can be associated with a transmission setting that results in very quick acceleration and late gear shifts. Therefore, the driving level "Dynamic" could be a Sport mode, while "Automatic" could be a Balanced mode, where, for example, experience suggests that most drivers prefer this system setting. For example, a "Comfort" mode could be associated with dim interior lighting, optional calm music, and the lowest possible background noise settings to create a comfortable cabin atmosphere, as well as a safety-focused transmission setting. On roads that cannot be associated with any type of main road or urban road, for example, a driving level could be associated with a sporty driver, in which damping is specifically adapted to potentially uneven surfaces.

[0021] The control device provides driver monitoring data that describes the driver's current state. The control device uses the provided driver monitoring data to determine the driver's current mood. This data can be received, for example, by capacitive and / or pressure sensors in the steering wheel, such as a sweat sensor in the steering wheel. Alternatively or additionally, camera images viewed by the driver can be evaluated to determine the driver's facial expressions and / or body movements and / or physical posture and / or eye movements. The driver monitoring data may optionally describe the characteristics of the driver's voice; for this purpose, a microphone in the sensor device may record the driver's speech. Additionally or alternatively, the driver monitoring data may describe the driver's vital signs, such as data on heart rate and / or skin conductivity and / or other physiological parameters, which can be detected by the vehicle's sensor devices or received, for example, from a mobile terminal device, such as a wearable device or smartphone.

[0022] Ideally, for pre-selection, one or more driving classes can be selected first based on driver type, and then the selection can be further refined based on the determined road category.

[0023] Based on the determined emotion, the control device selects one of the pre-selected driving levels as the driving level to be activated, where the driving level to be activated corresponds to the determined emotion. For example, if the "Comfort" and "Dynamic" driving levels are selected in the pre-selection, but the control device concludes that there is a "stressed" emotion based on factors such as busy eye movements and high sweating rate, the driving level to be activated could be "Comfort," for example. If the determined emotion is, for example, "good mood" or "fun," the control device can alternatively select the "Dynamic" driving level as the driving level to be activated.

[0024] The control device generates a switching signal indicating a transition from the current driving level to a driving level to be activated, which has corresponding association settings for at least two motor vehicle systems, and transmits the generated switching signal to the vehicle's dynamics system equipment, which then configures the at least two motor vehicle systems accordingly.

[0025] This leads to the advantages mentioned above. The preceding pre-selection implements weight control, giving driver type and road category a higher weight than driver sentiment when finally selecting the driving class to be activated. For example, if the pre-selection includes two driving classes, where the first selection is based on driver type and then on road category, the weighting is still more related to the already determined driver type.

[0026] After configuring at least two vehicle systems, the control unit provides additional driver monitoring data and uses this additional data to determine whether the described driving behavior meets a preset acceptance criterion. This acceptance criterion specifies that the determined emotion or the driver's reaction described by the additional driving monitoring data is a preset positive emotion or reaction. If the driving behavior does not meet the preset acceptance criterion, the control unit associates a different driving level with the emotion determined using the first driver monitoring data.

[0027] Therefore, for example, if the control unit determines, after setting a driving level, that the driver is smiling and relaxed, and, for example, determines through microphone and speech analysis that the driver is positively discussing the driving experience in the set driving level, this can be considered a positive emotion for evaluation. On the other hand, if the control unit determines, for example, that after setting the driving situation to be activated, the driver becomes agitated, has tense eye movements, even though he is driving on a desolate country road, and his heart rate increases, for example, according to this embodiment, the control unit can determine, for example, that the driver is stressed, and in this example, "stress" cannot be labeled as a positive emotion.

[0028] Therefore, for example, if a driver feels uncomfortable with the "Dynamic" driving level setting on a desolate rural road, the control unit, which does not meet the preset acceptance criteria, can change the driving level to, for example, "Comfort." A new evaluation can then preferably be performed again, and the control unit can, for example, determine that the driver is now more satisfied. Thus, the control unit can "learn" how the driver reacts to its selection and adjust as necessary. This is especially true in the case of a newly purchased vehicle, where the control unit is not yet "familiar" with the driver, or if the driver may fall between two typical driving types, allowing for fine-tuning of the driving level selection. Therefore, the driving level selection becomes increasingly precise and driver-specific. For example, if the driver purchases a new vehicle, or if the driver sells their vehicle, the "intelligence" of the control unit—the dynamics of driving level switching—can grow with the driver.

[0029] In a preferred embodiment of the method according to the invention, the control device may additionally provide driving situation data describing the current driving situation, wherein the driving situation data describes events that affect the driving behavior of the motor vehicle and / or the driver independently of the motor vehicle.

[0030] Such events, independent of the impact of motor vehicles, can preferably be: an incoming phone call; an impending traffic situation where a motor vehicle is about to enter a road lane on a ramp; a proactive downshift; a downshift to a lower gear performed by the driver, i.e., manually intervened by the driver; when the remaining available driving fuel reserves drop below a predetermined value, i.e., the current state of charge drops below a threshold or the fuel tank level drops below a threshold; or driving on a low-grade road (i.e., a road that is not paved or asphalt); or a driver-initiated overtaking maneuver.

[0031] In this preferred embodiment, the control device may check whether the current driving situation meets a preset priority criterion, which specifies the preset requirements for activating the priority driving level associated with the event. The control device may then generate a second switching signal and transmit it to the driving dynamics system equipment, indicating a change in the priority driving level.

[0032] Therefore, checking the preset priority criteria involves checking for situations where the determined driving level takes precedence over contextual and emotional analysis. For example, if the fuel tank is nearly empty, an "efficiency" mode can be activated without considering driving style and environmental data, allowing the vehicle to travel as economically as possible and thus increasing the probability that the driver will still reach a gas station. Preferably, the transition to the priority driving level only lasts for the necessary time, i.e., only for the time the fuel tank is empty. Preferably, continuous reassessment is possible, i.e., periodic checks can be performed to determine whether this priority still exists, for example, when the road category changes. Priority factors such as fuel tank level, example phone call, or one of other preset priority conditions have priority.

[0033] Alternatively or additionally, driving condition data may also be attributes and / or events in the vehicle's current environment, such as weather data, data on traffic flow and / or data on traffic congestion, and / or, for example, the current road route. In one of these variations, driving condition data may also be referred to as environmental data. To detect such environmental data, sensor devices may include communication modules for receiving traffic information and / or common sensor devices, preferably sensors for radio-assisted ranging and / or optical ranging, i.e., radar and / or lidar. Other suitable sensors are, for example, cameras.

[0034] Other optional environmental data could be environmental data describing the current traffic volume in the vehicle environment. Alternatively, the environmental data could also determine, for example, the number of vehicles in a preset environment surrounding the vehicle. Therefore, the control device confirms the current traffic volume in the environment based on the provided environmental data, and additionally selects the driving class to be activated from a pre-selected driving class based on the determined traffic volume. Here, the driving class selection is also more precise and more situation-specific.

[0035] For example, if the sensor device malfunctions and cannot detect secondary factors, such as traffic volume, the assessment is based solely on primary factors, namely driver type, road type, and mood. Special cases under optional prioritization still exist.

[0036] The first vehicle system in at least two vehicle systems is preferably a system for driving control of the vehicle, and the other vehicle system is preferably a system for controlling steering, interior lighting, or systems related to the interior atmosphere of the vehicle. The corresponding driving class preferably specifies settings for at least three vehicle systems.

[0037] The present invention also includes a control device for a motor vehicle. The control device may have a data processing device or a processor device configured to perform embodiments of the method according to the invention. For this purpose, the processor device may have at least one microprocessor and / or at least one microcontroller and / or at least one FPGA (Field Programmable Gate Array) and / or at least one DSP (Digital Signal Processor). Furthermore, the processor device may have program code configured to perform embodiments of the method according to the invention when implemented by the processor device. The program code may be stored in the data memory of the processor device.

[0038] The motor vehicle according to the invention is preferably designed as an automobile, particularly as a passenger car or commercial vehicle, or as a bus or motorcycle. The motor vehicle according to the invention includes embodiments of the control device according to the invention.

[0039] The present invention also includes improvements to the motor vehicle and control device according to the invention, which have features already described in conjunction with improvements to the method according to the invention. For this reason, corresponding improvements to the motor vehicle and control device according to the invention will not be described here.

[0040] The invention also includes combinations of features from the illustrated embodiments. The invention further includes implementations having combinations of features from multiple embodiments of the illustrated embodiments, unless such features are described as mutually exclusive. Attached Figure Description

[0041] Embodiments of the present invention are described below. Wherein:

[0042] Figure 1 A schematic diagram of a first embodiment of the method and apparatus according to the invention is shown;

[0043] Figure 2 A schematic diagram of another embodiment of the method according to the present invention is shown. Detailed Implementation

[0044] The embodiments described below are preferred embodiments of the invention. In the embodiments, the described components of the embodiments are correspondingly individual features of the invention, which should be considered independently of each other and also independently improve the invention accordingly. Therefore, this disclosure is also intended to cover combinations of features of the embodiments other than those shown. Furthermore, the described embodiments may be supplemented by other features among the already described features of the invention.

[0045] In the figure, the same reference numerals indicate elements that have the same function.

[0046] Figure 1 The principles of the apparatus and method according to the invention are shown. Therefore, Figure 1 Motor vehicle 10, such as a passenger car, is shown.

[0047] The control device 12 may be designed as a controller or, for example, a control chip. Figure 1 The example control device 12 may preferably have a data memory 14 and a processor device 16, i.e., one or more microchips or one or more microprocessors. Data communication between the control device 12 and the sensor device 18 may be performed, for example, via a wireless or wired data communication link 20.

[0048] Figure 1Sensor device 18 is schematically shown, which preferably includes multiple sensors for detecting driving style data and environmental data. Furthermore, sensor device 18 includes at least one sensor for detecting driver monitoring data. Optional driving condition data may be provided, for example, by an onboard computer and includes sensors or practical devices known to those skilled in the art in the prior art, such as those used to determine incoming calls, fuel tank levels, or battery state of charge. Environmental data, optionally indicative of road conditions, may be acquired, for example, via image analysis from a camera on the vehicle, or by invoking current warning information relating to poor road conditions or, for example, lane wetness due to rain. Environmental data used to determine traffic volume may be, for example, data from a server outside the vehicle, illustrating, for example, traffic congestion, or data collected from other vehicles via near-field communication. Alternatively, sensors based on radio ranging and / or optical ranging, such as radar and / or lidar, may be considered for determining traffic volume.

[0049] For clarity, Figure 1 The individual sensors are not shown. The sensor system may include, for example, capacitive or pressure sensors arranged in the steering wheel to monitor steering driving behavior. A driver observation camera inside the vehicle's cabin may focus on, for example, the face and / or body to record facial expressions or postures. Optionally, sensor device 18 may have one or more microphones through which speech can be recorded, and speech and / or sound analysis software, for example, can then analyze the speech and / or sound.

[0050] In method step S1, control device 12 provides driving style data describing the driver's driving style. For example, based on steering behavior, control device 12 can determine (S2) that the driver is sporty.

[0051] In step S3, to provide environmental data, the control device 12 may receive relevant data from corresponding sensors, such as camera data capturing road conditions or map data indicating road categories. Therefore, in S4, the control device may, for example, determine that the vehicle is on a highway. For example, in S5, the scenario "dynamic long-distance travel" may be designated as the driving scenario.

[0052] The following input data can be used individually or in any combination preferably for scenario analysis: current and / or long-term driving behavior; whether there are other occupants in the motor vehicle 10 and what other occupants are present; one or more maneuvers performed inside the vehicle, such as setting interior lights and music; the status of various vehicle functions and systems (e.g., state of charge, fuel tank level, activated driver assistance systems, system malfunctions, component functionality); hazardous situations (rural roads, highway entrances, cities, construction sites); traffic volume (open roads, traffic congestion, slow-moving traffic); and / or upcoming route data (road conditions, coefficient of friction). For the optional determination of current traffic volume, in S7, the control device can also optionally receive and evaluate traffic broadcasts.

[0053] In the pre-selection S8, for example, you can select the "Dynamic" and "Auto" driving levels for dynamic highway driving.

[0054] After pre-selection, driver emotions are influenced by driver monitoring data. The driver monitoring data provided in S9 allows for the analysis of the driver's current emotion, for example, by considering "enthusiastic" in the evaluation S10. Driver monitoring data may include, for example, heart rate, skin conductivity, facial expressions, eye movements, or vocal characteristics. Suitable sensors are known to those skilled in the art from the prior art. If the control device 12 determines, for example, "discomfort" rather than "enthusiastic," the driving level "automatic" instead of "dynamic" can be selected in S11.

[0055] Depending on the mood, control device 12 generates a switching signal in S12, which in this example is described as "dynamic driving level" or "autonomous driving level" (S12), and transmits the generated switching signal to driving dynamics system device 22 in S13. Figure 1 In the example, it is a component of controller 12. Alternatively, the driving dynamics system device 22 may be a structurally separate component from the control device 12 and may communicate with the control device 12 via data communication link 20.

[0056] For each driving class, the driving dynamics system device 22 may store corresponding settings for at least two, preferably more than two, vehicle systems 24, and the driving dynamics system device 22 may control the vehicle systems 24, such as the transmission mechanism and interior lighting devices, according to the switching signal of the control device 12 (S14).

[0057] For example, the learning process of the control device 12, used to "understand" the driver, is particularly advantageous when the driver has purchased a new vehicle or when the driver's type classification is not yet clear. For instance, after switching to the "Dynamic" driving level on a highway, it can be determined in S15 that the driver is clearly dissatisfied with the driving level selection, i.e., it does not meet the preset acceptance criteria. In this example, instead of the "Dynamic" driving level, the "Auto" driving level can be activated at this time, and in S15, it can be checked again whether the driver now appears happier. If so, the driving level can be "Auto" associated with the driver's mood before switching to "Dynamic" (S16). Optionally, the learning algorithm can be configured to consider the driver's manual selection of another driving mode in specific situations, preferably depending on whether the manual selection is frequently repeated in the same location. This can be determined, for example, by geofencing.

[0058] For optional pre-checks for priority driving situations, when providing driving situation data (S17), it can be determined, for example, whether the fuel tank level is below a predetermined threshold. For example, preset priority criteria can be stored in data memory 14, and check S18 can indicate that the preset priority criteria have been met. Control device 12 can generate a second switching signal (S12) and transmit it to driving dynamics system device 22 (S13), which can, for example, indicate a change to "efficiency" priority driving level. The vehicle 10 then drives in an energy-efficient manner, preferably until, for example, the vehicle enters an acceleration lane on a highway, or until the fuel tank is refilled.

[0059] Figure 2 A logical example of initial data transformation according to another embodiment of the method of the present invention is shown.

[0060] The optional check S18 regarding whether the preset priority criteria (column S18) are met can be further subdivided into the possibility of no priority condition (26) or the possibility of meeting the preset priority criteria (28, 30, 32). For example, the first priority condition 28 could be that the fuel tank is empty, the second priority condition is the "off-road" condition 30, or an alternative priority condition 32, in which, for example, a phone call can be answered while driving. Each of these priority conditions 28, 30, 32 can be selected to activate a different driving level 34, such as an energy-saving driving level, an "all-terrain driving level" 36, or an alternative driving level 38 (column 40 as a result column of driving configuration).

[0061] If there is no priority condition, i.e., if the preset priority criterion (26) is not met, or if the optional check process S18 is not performed, then preferably the driver's type can be determined first (list S2). Possible driver types are, for example, sporty (40), "undefined" (44) - i.e., a type that cannot be associated with any general category if the control device 12 does not yet know the driver; or "efficient" (46), i.e., a driver who prefers to drive in an energy-saving manner.

[0062] Driving class can preferably be directly associated with types 42, 44, and 46 without determining road category (list S4) or optional evaluation of secondary factor 48. For example, "Comfort" driving class 50 can be associated with "Comfort" type 42, "Auto" driving class (52) can be associated with "Undefined" type, and "Efficiency" driving class (34) can be associated with "Efficiency" type.

[0063] Then, further choices are made based on the identified emotion. Examples of this have already been mentioned above.

[0064] The assessment of secondary factors may preferably include the determination of traffic volume (S7). Prior to secondary factor 48 is primary factor 54, and the determination of driver type S2 and road category S4 are primary factors 54.

[0065] When determining road category S4, for example, the category of highway (56), rural road (58) or city (60) can be determined.

[0066] For example, the driver's current mood can be determined through the vehicle's sensor system (S10). Here, different moods 62, 64, 66, 68, 70, 76, and 82 can affect the driving level selection differently. For example, depending on whether the mood is "happy" (62) or "normal" (64), the driving level can be selected as either "dynamic" (84) or "automatic" (52), or only the driving level "automatic" (52) can be selected.

[0067] Optionally, road conditions (S4) and road conditions (S6) may be further determined. Possible optional road conditions may be "good" or "bad", "good (straight)" or "good (curved)" or "bad".

[0068] Possible traffic volume options could be "Smooth" (72) or "Congested" (74); or, for the road category "City" (60) and the optional road condition "Good," the traffic volume could be "Smooth" (78) or "Stalled / Congested" (80). For optional adverse road conditions in the city—or only for the city—it could be directly associated with the driving level "Auto" (52). The driving level "Auto" (52) could be associated with different combinations of primary and secondary factors, such as... Figure 2 As shown in the example. However, for example, if the driver type is sporty, and optionally if the road conditions are good, the driving level "Dynamic" (84) can be associated with unobstructed highways. "Dynamic" can also be associated as driving level 84, for example, with winding country roads for sporty driver types, optionally only if the road conditions are good or the roads in the city are unobstructed.

[0069] Ideally, in Figure 2 In the example, there is a post-learning function with steps S9, S15, and S16. Here, if the driver is dissatisfied with the suggestion "Dynamic," for example, they can switch from "Dynamic" to "Comfort," which can be derived, for example, from the driver's uneasy gestures or typical facial expressions of dissatisfaction.

[0070] Overall, these examples demonstrate how automated driving configuration switching can be provided based on empathy and optional learning and prediction algorithms.

[0071] In another embodiment, to reduce workload and consistently optimize the driving configuration experience across all vehicle-driver-environment-situations, the optimal configuration for the individual driver's experience can be automatically activated through comprehensive analysis. The learning algorithm regarding driver preferences and emotions preferably enables configuration activation based on the driver's current mood, in addition to automatic configuration switching.

[0072] In another exemplary technical implementation, to determine the optimal driving configuration, the driver's driving style can first be categorized and associated with one or more suitable driving configurations (e.g., driving selection) (S2, S8). Since the driving mode must always be adjusted according to the corresponding environment and driving conditions, various data regarding road type (e.g., rural road / highway / urban), traffic volume, and available road conditions are included (S4, S8). For this purpose, measurement parameters and backend data from the vehicle 10 can be accessed.

[0073] The preferred input data for analysis includes:

[0074] - Current and long-term driving behavior, and / or

[0075] - Other occupants in the vehicle, and / or

[0076] - Operations performed inside the vehicle's interior, and / or

[0077] - The driver's mood, and / or

[0078] - The status of each vehicle function and system (e.g., state of charge, fuel tank level, activated driver assistance systems, malfunctions of systems, functions, and components), and / or

[0079] - Driving conditions (rural roads, highway entrances, cities, construction sites), and / or

[0080] - Traffic volume (unobstructed roads, traffic congestion, slow traffic), and / or

[0081] - Forward route data (road conditions, friction coefficient).

[0082] The ideal driving pattern determined by this data can also preferably be rejected by so-called priority factors. These priority factors can include various events:

[0083] – Incoming calls, and / or

[0084] -Merging into fast-moving traffic (e.g., highway entrances), and / or

[0085] –Active downshifting, and / or

[0086] - Manual downshift, and / or

[0087] –Drive source material reserves, and / or

[0088] - dirt road, and / or

[0089] -Overtaking maneuvers,

[0090] Accordingly, the mode with the most suitable configuration can be selected (S18).

[0091] To further cater to users' individual preferences, driver overdrive can be processed within a learning algorithm. For example, if a driver repeatedly selects a mode different from the function under certain circumstances, the algorithm can directly select the user's request in similar situations and / or at the same location (e.g., via geofencing) in the future.

[0092] In other steps, users’ emotional reactions to changes in driving configuration can be categorized and used to make the algorithm more accurately match the driver’s personal tastes.

[0093] The driver's emotions can be detected by analyzing physiological parameters. For this purpose, the following physiological parameters can preferably be analyzed:

[0094] - Heart rate, and / or

[0095] -Skin conductivity, and / or

[0096] - Facial expressions, and / or

[0097] - Eye movements, and / or

[0098] -sound.

[0099] Driver-level switching is based on contextual analysis (driving behavior and environmental data) and emotion analysis (e.g., facial expressions and / or language).

[0100] Advantageously, the automatic and intelligent switching to the optimal driving configuration allows for a full experience of all vehicle features without requiring the driver to be familiar with the system. Therefore, manual driver intervention is rendered obsolete, and this significantly contributes to reducing visual distraction, thus also helping to reduce mental workload.

Claims

1. A method for operating a motion dynamics system device (22) of a motor vehicle (10) during driving, wherein, Control device (12) during operation: - Provide driving style data (S1) that describes the driving style of the driver of the motor vehicle (10), and determine the driver type (S2) based on the provided driving style data. - Determine the road category (S4) of the road surface on which the motor vehicle (10) travels. - Determine the current driving situation based on the determined driver type and the determined road category (S5). - Select from a plurality of predetermined driving classes (S8) that are associated with the determined driving scenario, wherein each of the plurality of driving classes describes a set of driving class-specific settings for at least two motor vehicle systems (24) of the motor vehicle (10). - Provide driver monitoring data describing the driver's current state (S9), and determine the driver's current mood based on the provided driver monitoring data (S10). - Select a driving class from the pre-selected driving classes as the driving class to be activated based on the determined emotion, wherein the driving class to be activated is associated with the determined emotion (S11). - Generate a switching signal (S12) that describes the transition from the current driving level to the driving level to be activated, along with the corresponding association settings for at least two vehicle systems (24), and transmit the generated switching signal to the driving dynamics system device (22) to configure the at least two vehicle systems (24) (S13). - Additional driver monitoring data (S9) is provided after the at least two motor vehicle systems (24) are configured. - Determine whether the driver behavior described based on additional driver monitoring data provided meets a preset acceptance criterion (S15), which specifies that the determined emotion or driver reaction described by the additional driver monitoring data provided is a preset positive emotion or reaction, said driver reaction being the operation of the motor vehicle (10). - In cases where driving behavior does not meet the preset acceptance criteria: associate other driving levels with the emotions determined based on the first driver's monitoring data (S16).

2. The method according to claim 1, characterized in that, The control device (12): - Provide driving situation data that describes the current driving situation, wherein the driving situation data describes events (S17) that affect the driving behavior of the motor vehicle (10) and / or affect the driver, independent of the motor vehicle. - Check whether the current driving conditions meet the preset priority criteria, which describe the preset requirements for activating the priority driving level associated with the event (S18). - A second switching signal is generated (S12) and transmitted to the driving dynamics system device (22) (S13), the second switching signal describing the transition to the priority driving level.

3. The method according to claim 2, characterized in that, Events that are independent of the motor vehicle and affect the driving behavior of the motor vehicle (10) and / or the driver include: incoming calls; impending traffic conditions in which the motor vehicle (10) will enter the road lane on a ramp; active downshifting; manual downshifting performed by the user; the availability of driving raw materials being lower than a preset value; driving on a low-grade road; or overtaking maneuvers.

4. The method according to any one of claims 2 or 3, characterized in that, The control device (12): - Determine the current traffic volume (S7) of the environment of the motor vehicle (10) based on the provided driving data. - Additionally, select the driving class to be activated from the pre-selected driving classes based on the determined traffic volume (S11).

5. The method according to any one of claims 1-3, characterized in that, The first of the at least two motor vehicle systems (24) is the drive control unit of the motor vehicle (10), and the other motor vehicle system (24) is a system for controlling steering, interior lighting, or a system for controlling systems related to the atmosphere inside the motor vehicle (10).

6. The method according to any one of claims 1-3, characterized in that, The corresponding driving class requires the setting of at least three motor vehicle systems (24).

7. A control device (12) configured to perform the method according to any one of claims 1-6.

8. A motor vehicle (10) having a control device (12) according to claim 7.

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