Control device and method for automatically providing adapted vehicle functions / driving parameters

Abstract

The disclosure relates to a control device and a method for automatically providing adapted vehicle functions / driving parameters.The control device (10) is designed to detect the situation-related driving behavior and / or operating parameters of the vehicle (1) during operation of the vehicle (1); to compare the situation-related driving behavior and / or operating parameters of the vehicle (1) with data in an artificial intelligence (AI) unit (20) trained model, wherein the model is trained with provided training datasets of situation-related driving behavior and / or operating parameters of the vehicle (1); and further designed to, during operation of the vehicle (1), if a deviation has occurred during the comparison, to perform an adjustment of the vehicle functions / driving parameters based on the detected situation-related driving behavior and / or operating parameters of the vehicle (1) and to provide the adjusted vehicle functions / driving parameters to the vehicle (1).

Description

[0001] The present disclosure relates to a control device and a method for automatically providing adapted vehicle functions / driving parameters. Furthermore, the disclosure relates to a computer program and a vehicle. Additionally, a computer-readable medium is provided which includes instructions that, when executed by a computer, cause it to execute at least part of the disclosed method.

[0002] Modern vehicles, especially automobiles, increasingly incorporate driver assistance systems. Advanced Driver Assistance Systems (ADAS) are electronic, particularly mechatronic, devices in vehicles designed to support the user in specific driving situations. The primary focus is often on safety aspects, but also on increasing driving comfort by providing a wide range of vehicle functions.

[0003] Currently, there is only one application software version for vehicle release, which the user operates with. This software application can be provided subsequently, for example, via an over-the-air update from the OEM; however, these software updates are always the same for the entire customer base.

[0004] Once application software has been defined and released by the OEM, it cannot be adapted to specific customer needs (the same for all users of all vehicles), even though customer perception may be subjective.

[0005] Document DE 10 2017 219 365 A1 discloses a device for adapting a vehicle control system to the condition of a person in the interior of a vehicle.

[0006] Document DE 10 2021 131 737 A1 discloses a method for operating a vehicle dynamics system device of a motor vehicle during a journey with the motor vehicle.

[0007] Against the background of this prior art, the purpose of the present disclosure is to specify a control device and / or a method, each of which is suitable to enrich the prior art.

[0008] The problem is solved by the features of the independent claims. The dependent and subordinate claims each contain optional further developments of the disclosure.

[0009] The task is then solved by a control device for automatically providing adapted vehicle functions / driving parameters to the vehicle's situational driving behavior.

[0010] The control unit is designed to monitor the vehicle's driving behavior and / or operating parameters during operation. This enables precise and continuous monitoring of current vehicle conditions. This monitoring allows for real-time adjustments and modifications to enhance vehicle efficiency and safety. Accurate monitoring of operating parameters can help identify and resolve potential problems early on, thereby improving the vehicle's overall performance and reliability.

[0011] Dynamic vehicle adaptation is based on a base version of the vehicle function that the vehicle user received from the manufacturer (OEM). The base version is the version of the vehicle function that all purchasers of the vehicle receive.

[0012] For the purposes of this disclosure, situational driving behavior refers to the dynamic adaptation of the vehicle to the current traffic and environmental conditions while driving. This includes aspects such as acceleration, braking behavior, cornering behavior, and the reaction to unexpected obstacles or weather conditions. Capturing situational driving behavior enables precise control and adjustment of vehicle parameters in real time. This increases the vehicle's safety and efficiency by allowing it to react optimally to changing conditions. It also contributes to improved driving comfort and reduced wear on vehicle components. Situational driving behavior can involve an adaptation of the driving style of a user or the vehicle itself to the current road and traffic conditions, as well as the environment.It can include the ability to react appropriately to changing situations to ensure the safety, efficiency, and comfort of the vehicle and its occupants. This may involve taking into account traffic density, weather conditions, road conditions, traffic signs and signals, environmental factors, emergency situations, hazardous situations, and / or evasive maneuvers.

[0013] For the purposes of this disclosure, an operating parameter refers to the multitude of measured quantities and states that describe the current technical condition and operation of a vehicle. These include, among others, engine power, speed, temperature, fuel consumption, battery state, tire pressure, and brake temperature. Furthermore, operating parameters may include parameters acquired from the vehicle's interior or its immediate external environment. Operating parameters serve to monitor and control vehicle performance and safety using real-time data.

[0014] Furthermore, the control device is designed to compare the vehicle's situational driving behavior and / or operating parameters with data (output data, regression results) from an artificial intelligence (AI) unit containing a trained model. This model is trained using provided training datasets of the vehicle's situational driving behavior and / or operating parameters. This allows the vehicle's situational driving behavior and / or operating parameters to be compared with a model trained in the AI ​​unit. This enables precise and context-dependent adjustment of the vehicle control in real time, based on extensive training datasets. As a result, the vehicle's responsiveness to changing conditions can be significantly improved. Moreover, the vehicle's safety and efficiency are increased, as the AI ​​unit continuously provides optimized control suggestions.This leads to a longer service life for the vehicle components and improved overall vehicle performance.

[0015] Furthermore, the control device is designed to provide options for adjusting the vehicle functions / driving parameters during vehicle operation if a deviation has occurred during the adjustment, based on the detected situation-related driving behavior and / or the vehicle's operating parameters.

[0016] Alternatively or additionally, the control device is designed to adjust the vehicle functions / driving parameters and provide the adjusted vehicle functions / driving parameters to the vehicle during operation of the vehicle if a deviation has occurred during the adjustment.

[0017] This allows deviations in the vehicle's situational driving behavior and / or operating parameters to be detected during operation, enabling immediate adjustments to vehicle functions or driving parameters. This provides continuous optimization and adaptation of the vehicle to current operating conditions. As a result, the vehicle's operational efficiency and safety can be increased by ensuring optimal responses to changing situations. Furthermore, the vehicle's overall performance can be improved, leading to greater driver satisfaction.

[0018] The control device or control unit can be part of the driver assistance system or constitute the system itself. The control device can, for example, be an electronic control unit (ECU). The electronic control unit can be an intelligent, processor-controlled unit that can communicate with other modules via a central gateway (CGW) and may, if necessary, form the vehicle's electrical network via fieldbuses such as CAN bus, LIN bus, MOST bus, FlexRay, and / or Automotive Ethernet, for example, together with telematics control units and / or environmental sensors.

[0019] The control device includes a communication interface for communicating with a storage unit. The storage unit can be configured as an internal storage unit, thus forming an integral part of the control device. Alternatively, the storage unit can be configured as an external storage unit connected to the control device. Communication can take place via known communication protocols. The storage unit can include a hard disk drive, a flash drive, and / or a USB drive for storing and / or retrieving data. The storage unit is configured to store at least one database, which in turn is configured to store parameters relating to the control device, the vehicle, and / or parameters relevant to the operation of the vehicle. The database can contain systems known from the prior art.The control unit has an interface for communication with a higher-level system. This interface can be configured for mobile communication. The artificial intelligence (AI) unit can be located in the higher-level system, such as a server or computer system, and data between the vehicle, the control unit, and the higher-level system is exchanged via mobile communication.

[0020] In the context of the disclosure, the artificial intelligence (AI) unit is a component of the control device responsible for processing and analyzing data captured by the vehicle's cameras and sensors and / or retrieved from a database. This unit is a core component of the control device, serving to provide automatically adapted vehicle functions / driving parameters. The AI ​​unit may comprise a system of algorithms, models, and data processing techniques designed to identify patterns in the provided data and provide corresponding optimizations. The optimizations are provided as data (e.g., calculation results). It uses machine learning and potentially known neural networks to learn from the provided training datasets.The AI ​​unit can be implemented in an executable program using known programming languages ​​and processed on a processing unit.

[0021] The implementation of the AI ​​unit can include data collection and data processing. Data processing can include gathering training data based on situational driving behavior and / or vehicle operating parameters.

[0022] The implementation of the AI ​​unit can include model development and training. Model development can involve selecting a suitable machine learning model (e.g., neural network, random forest, etc.) which is trained using the provided training datasets. During a training phase, the AI ​​unit can learn to recognize specific and / or relevant and / or predefined vehicle functions / driving parameters and their optimization and behavior.

[0023] The implementation of the AI ​​unit can include integration and configuration to receive and process real-time data from cameras and sensors and / or retrieved data from the database. Once implemented, the AI ​​unit can be designed to evaluate situational driving behavior and / or operating parameters and provide correspondingly optimized vehicle functions / driving parameters.

[0024] It is conceivable that the control unit manages functions relevant to the vehicle's driving behavior, such as steering, engine control, power transmission, and / or the braking system. Furthermore, driver assistance systems, such as a parking assistant, adaptive cruise control (ACC), lane keeping assist, lane change assist, traffic sign recognition, light signal recognition, hill start assist, night vision assist, and / or intersection assist, can be controlled by the control unit.

[0025] The control system described above offers a number of advantages. Among other things, by utilizing swarm data and AI-induced optimization of application and vehicle data, vehicle manufacturers can individually tailor the control system and vehicle performance to the needs of each user. This allows for consideration of specific user preferences and requirements, leading to greater customer satisfaction. Furthermore, a universal "world application" that must be equally suitable for all users worldwide is unnecessary. Instead, artificial intelligence can optimize the vehicle's delivery state for the respective user in the specific target market. This results in customized vehicle control that optimally meets individual requirements and environmental conditions.

[0026] Possible further developments of the device described above are explained in detail below.

[0027] The control device may also be designed to adapt the vehicle functions / driving parameters and to make these adapted functions / driving parameters available to the vehicle and / or user. Thus, an adaptation based on the data can be performed.

[0028] It may be intended that the alignment process involves incremental optimization of the model's training datasets within system boundaries. For the purposes of this disclosure, incremental optimization involves a step-by-step and continuous process of improving and adjusting training datasets or parameters. Small, controlled changes can be made to the model or the training datasets to achieve a gradual approximation of optimal system behavior. Each optimization iteration builds upon the results of the previous one, allowing for targeted and continuous refinement of the adjustments. This approach makes it possible to achieve safe and effective improvements within defined system boundaries. Incremental optimization thus ensures that the adjustments are stable and sustainable, without sudden or drastic changes that could lead to instabilities.Furthermore, the model's training datasets can be incrementally optimized within predefined system limits. This enables a step-by-step and precise adjustment of vehicle parameters, resulting in continuous improvement of vehicle performance. Adherence to the system limits ensures that optimizations always occur within safe and permissible parameters, thus increasing operational reliability. Moreover, the incremental approach allows for faster and more efficient adaptation to changing conditions. This leads to improved overall performance and increased durability of vehicle components.

[0029] The artificial intelligence (AI) unit can be configured to provide and / or adapt data based on driving time, route, and / or vehicle environment. Alternatively, vehicle functions can be provided and / or adapted based on the vehicle, route, and / or environment. The AI ​​unit's capabilities allow for the provision and / or adaptation of data and / or vehicle functions based on driving time, route, and / or environment. Adapting and / or providing data and / or vehicle functions based on driving time enables optimized performance and energy efficiency at different times of day, for example, by treating nighttime and peak-hour driving differently. Considering the route allows for predictive adjustment of driving parameters, leading to improved driving dynamics and safety, for example, by...Curves and inclines can be mastered optimally. Adapting to the vehicle's environment allows for consideration of external influences such as weather conditions or road surfaces, thus increasing safety and comfort for the user.

[0030] It may be possible to implement the ability to adjust vehicle functions / driving parameters by induced changes in the driving state, and these induced changes can be made available to the user via an output unit. Induced changes in the driving state can be achieved by adjusting vehicle functions or driving parameters and then made available to the user via an output unit. An induced change in the driving state represents a change in the vehicle's driving behavior brought about by targeted adjustments to vehicle functions or driving parameters. These changes can affect various aspects such as acceleration, braking behavior, cornering stability, or damping. The induced change in the driving state results from the vehicle's reaction to the optimizations calculated and implemented by the artificial intelligence (AI) unit.

[0031] These changes can be implemented in real time to adapt the driving behavior to current conditions and requirements, resulting in improved vehicle dynamics and safety. By providing the induced driving state change, the user receives immediate feedback on the adjustments made and their impact on driving behavior. This real-time information on driving state changes contributes to increased safety by enabling the user to make better-informed decisions. Furthermore, it fosters a better understanding and trust in the vehicle technology, as the changes are presented transparently and comprehensibly.

[0032] The ability to adjust vehicle functions may include an evaluation and / or classification of the vehicle's driving state changes induced by these adjusted functions. This allows for a precise analysis of the effects of each adjustment, thereby continuously improving the efficiency and effectiveness of optimizations. The evaluation and classification support data-driven decisions, leading to better fine-tuning of vehicle functions. Furthermore, this contributes to increased safety by enabling the early detection and correction of potential negative impacts.

[0033] The artificial intelligence (AI) unit model can be trained on fleet data and / or individual data, with the ability to adapt vehicle functions further enhanced by fleet data and / or recorded situational driving behavior and / or vehicle operating parameters. Using an AI model trained on fleet data and / or individual data enables highly precise and adaptive optimization of vehicle functions. A wide variety of datasets can be used for this purpose. This leads to a tailored adjustment of driving parameters based on both comprehensive data analysis and specific individual driving behavior. By incorporating fleet data, the AI ​​can benefit from a broad data base, making the optimizations more robust and effective.In addition, considering the recorded situational driving behavior and operating parameters enables real-time adaptation to current conditions, thus increasing the vehicle's safety and efficiency. Adjusting vehicle functions based on these operating parameters allows for highly precise and situation-specific optimization of vehicle performance. This leads to improved efficiency and safety, as the adjustments are tailored to the vehicle's current technical condition and the specific situation and / or environment in which it is located. Continuous monitoring and analysis of operating parameters allows for the early detection and resolution of potential problems, extending the service life of vehicle components. Furthermore, this approach enables dynamic adaptation to changing operating conditions, which can improve driving comfort and the vehicle's overall performance.

[0034] The artificial intelligence (AI) unit can be configured to continuously receive new data while the vehicle is in motion and to adapt and / or optimize its training datasets in real time. This continuous data reception and adaptation capability allows the AI ​​unit to optimize vehicle functions in real time. This ensures that the vehicle can always react to current conditions and changes in driving behavior, thus increasing vehicle safety and efficiency. By adapting the training datasets in real time, the AI ​​can react more quickly and precisely to new information, continuously improving vehicle performance. Furthermore, adaptability to individual driving styles and environmental conditions is maximized, enhancing driving comfort and user satisfaction.

[0035] The artificial intelligence (AI) unit's model can be adapted and / or optimized based on user feedback. This adaptability and / or optimization allows for targeted improvements to vehicle functions based on user feedback. Individual user preferences and needs can be directly incorporated into the optimization processes, leading to increased user satisfaction. The feedback can be used to fine-tune driving parameters to ensure a personalized and comfortable driving experience. Furthermore, the continuous incorporation of user feedback can help identify and correct potential problems early on, improving the vehicle's overall performance and reliability.This results in flexible and adaptive vehicle control that can optimally adjust to the changing requirements and wishes of the users.

[0036] It may be intended that the artificial intelligence (AI) unit's model is trained using simulation and / or test drives under varying conditions and / or environments to cover a wide range of driving scenarios. Using simulation and / or test drives to train the AI ​​unit's model under diverse conditions and environments enables comprehensive coverage of driving scenarios. This ensures that the AI ​​unit is capable of making precise and reliable adjustments and optimizations to vehicle functions in a variety of real-world driving situations. This increases the system's robustness and flexibility by training it to a broad spectrum of possible traffic and environmental conditions.The diverse training scenarios can help maximize the safety and efficiency of the vehicle, as the AI ​​unit learns from a comprehensive database.

[0037] The control device may include at least one interface for communicating with a sensor unit comprising at least one sensor for determining the vehicle's operating parameters. Integrating such an interface into the control device enables precise and continuous monitoring of the vehicle's condition. This allows for real-time data acquisition and analysis, enabling rapid and efficient adjustments to vehicle functions. Accurate determination of operating parameters helps optimize the vehicle's performance and efficiency by allowing the control system to respond to current conditions and needs.Furthermore, this interface enables seamless integration and expansion of the system, allowing future sensors and sensing units to be added easily. This leads to improved adaptability and flexibility of the vehicle control system, which increases the overall reliability and safety of the vehicle. The interface can support a variety of state-of-the-art communication standards to connect a multitude of vehicle sensors and / or other control devices and / or an OEM backend.

[0038] Various sensors can be used to determine the vehicle's operating parameters, including engine sensors that record parameters such as speed, temperature, oil level, and oil pressure to monitor the engine's condition and performance. Speed ​​sensors measure the revolutions per minute (RPM) of the drive shaft or wheels to determine the vehicle's speed and acceleration. Temperature sensors monitor the temperature of various vehicle components, including the engine, transmission, and exhaust system, to prevent overheating and maximize efficiency. Pressure sensors measure the pressure in various vehicle systems, such as tire pressure, brake fluid pressure, and fuel pressure, to ensure safety and performance. Battery sensors monitor the state of charge, voltage, and temperature of the vehicle battery to optimize power supply and battery lifespan.

[0039] Fuel level sensors measure the fuel level in the tank and fuel consumption to inform the driver about remaining fuel and optimize consumption. Mass airflow (MAF) sensors measure the amount of air flowing into the engine to calculate the air-fuel ratio for optimal combustion. Oxygen sensors (O2 sensors) monitor the oxygen content in the exhaust gas to optimize combustion efficiency and exhaust aftertreatment. Acceleration sensors record the vehicle's acceleration along various axes to monitor driving dynamics and stability. GPS sensors determine the vehicle's position and speed to support navigation and vehicle-specific optimizations. Gyroscopic sensors measure the vehicle's rotation rate and orientation to improve stability control and driving dynamics.LiDAR / RADAR sensors scan the vehicle's surroundings to detect obstacles and support driver assistance systems. Humidity sensors measure the humidity inside the vehicle and its various components to prevent corrosion and condensation. The combination of these sensors allows for the acquisition of comprehensive operating parameters, enabling continuous monitoring and optimization of vehicle performance, safety, and efficiency.

[0040] The control device may include at least one interface for communicating with a sensor unit comprising at least one sensor for determining the vehicle's interior conditions. Integrating such an interface into the control device enables precise monitoring and adjustment of the vehicle interior. This results in optimized climate control, ventilation, and overall comfort management, thereby enhancing the driver and passenger experience. Continuous monitoring of interior conditions such as temperature, humidity, and air quality allows for real-time adjustments to ensure optimal conditions at all times. Furthermore, this precise monitoring contributes to energy efficiency by activating the air conditioning and other systems only when necessary.The interface enables seamless integration and expandability of the system, facilitating future adjustments and expansions through the replacement and / or addition of sensors. Sensors for determining the vehicle's interior conditions encompass a variety of technologies that monitor and control specific parameters. Temperature sensors measure the interior temperature to optimize the control of the air conditioning and heating systems and ensure passenger comfort. Humidity sensors monitor the humidity level in the vehicle to prevent condensation and maintain a comfortable interior climate. Air quality sensors detect pollutants and particles in the air to adjust ventilation and ensure healthy breathing air. CO2 sensors measure the carbon dioxide level in the interior to regulate the fresh air supply and support passenger concentration.Furthermore, light intensity sensors can adjust the interior brightness to prevent glare and optimize visibility. Noise level sensors monitor the noise level inside the vehicle to control active noise cancellation systems and create a quiet environment. Seat occupancy sensors detect whether seats are occupied to adjust the climate control and safety systems, such as airbags, accordingly. These sensors work together to enable comprehensive monitoring and control of interior conditions, thereby improving comfort, safety, and efficiency within the vehicle.

[0041] The control device may include at least one interface for communicating with a sensor unit comprising at least one sensor for determining the vehicle's environmental conditions. Integrating such an interface into the control device for communicating with a sensor unit enables precise adaptation of vehicle functions to current external influences. These sensors record parameters such as outside temperature, humidity, light conditions, and road conditions, allowing for optimized control of vehicle systems like air conditioning, lighting, and suspension. Continuous monitoring of environmental conditions allows the vehicle to react dynamically to changes, thereby increasing safety and comfort for the occupants.Sensors for determining the vehicle's environmental conditions encompass various technologies that monitor specific external parameters. These include outside temperature sensors, which measure the ambient temperature and adjust the air conditioning and heating accordingly. Humidity sensors detect the ambient humidity to optimize the control of the windshield heating and air conditioning and prevent condensation. Light sensors measure the ambient light levels to enable automatic adjustment of the vehicle's lighting and improve visibility. Rain sensors detect precipitation and automatically activate the windshield wipers to ensure clear visibility. Furthermore, road surface sensors monitor the condition of the road surface to adjust the suspension and traction control accordingly.These sensors can work together to ensure comprehensive monitoring of environmental conditions and optimally adapt the vehicle to external influences, which can lead to improved safety, efficiency and comfort.

[0042] The control device may include at least one interface for communicating with a sensor unit comprising at least one set of sensors for determining the vehicle user's state. Integrating an interface into the control device for communicating with a sensor unit and its sensors enables personalized and adaptive vehicle control. Sensors such as heart rate monitors can monitor the driver's health and issue warnings or initiate emergency measures as needed. Fatigue sensors detect signs of driver fatigue and can suggest appropriate warnings or driving breaks to enhance safety. Facial recognition sensors can verify the driver's identity and automatically adjust individual preferences such as seat position and climate control.

[0043] The artificial intelligence (AI) unit can be configured to automatically provide updates and adjustment options to ensure continuous adaptation of vehicle functions to changes in the vehicle's situational driving behavior and / or operating parameters. This automatic provision of updates and adjustments by the AI ​​unit can guarantee continuous optimization of vehicle functions, resulting in a consistently up-to-date and precise adaptation to the vehicle's situational driving behavior and operating parameters. This increases the vehicle's efficiency and safety, as it can continuously respond to new conditions and requirements.

[0044] The artificial intelligence (AI) unit can be configured to compare the vehicle's driving parameters and operating states with the driving behavior of surrounding road users and environmental conditions. By comparing these parameters and states, the AI ​​unit can make precise and adaptive control decisions, increasing the vehicle's safety and efficiency. These real-time adjustments enable optimal responses to changing traffic and environmental conditions, thereby reducing the risk of accidents. Furthermore, driving comfort is improved, as the vehicle integrates harmoniously into traffic and reacts flexibly to external influences.

[0045] It may be envisaged that the artificial intelligence (AI) unit optimizes driving parameters and vehicle states depending on comfort requirements, including acceleration, damping, air conditioning, insulation, acoustics and cornering.

[0046] The artificial intelligence (AI) unit can be designed to optimize driving parameters and vehicle states based on the lifespan of components, including dampers, engine / transmission components, axle components, bodywork, and electronic components (fans). By optimizing these parameters and states according to comfort requirements, a tailored and enjoyable driving experience is ensured. This leads to increased driver and passenger satisfaction, as aspects such as acceleration, damping, climate control, sound insulation, acoustics, and cornering are individually adjusted. Furthermore, this precise adjustment contributes to improved vehicle safety and stability, as the vehicle always responds optimally to current comfort demands.

[0047] The artificial intelligence (AI) unit can be configured to optimize driving parameters and vehicle states based on driving time, route, and / or environment, particularly for rural and urban driving. This optimization allows for precise adaptation to specific driving situations, thereby increasing vehicle efficiency and safety. These adjustments take into account the different requirements of rural and / or urban driving, ensuring optimal driving behavior tailored to the respective environment. This results in improved overall performance and greater driving comfort, as the vehicle dynamically responds to changing conditions.

[0048] The artificial intelligence (AI) unit can be configured to optimize driving parameters and vehicle states in accordance with legal regulations and societal conformity requirements, including exhaust noise. This optimization ensures compliance with all relevant standards and guidelines. It also helps reduce legal risks by ensuring the vehicle is always operated within the legally prescribed framework. Furthermore, it increases public acceptance, as, for example, exhaust noise is controlled, thus minimizing noise pollution.

[0049] The artificial intelligence (AI) unit can be designed to take environmental conditions such as potholes, temperature, snowfall, and ice into account. This consideration of environmental conditions allows the AI ​​unit to precisely adapt the vehicle parameters to current road conditions. This significantly increases driving safety, as the vehicle can react to hazardous conditions in real time. Furthermore, driving comfort is improved by minimizing jerky movements and ensuring a stable ride even under challenging conditions.

[0050] The artificial intelligence (AI) unit can be designed to optimize multidimensional physical relationships through repeated incremental changes to variables and measurements. By optimizing these relationships, the AI ​​unit can make more precise and efficient control decisions. This leads to a continuous improvement in vehicle performance, as the adjustments are always based on the latest measurement data and are finely tuned.

[0051] Furthermore, this iterative approach increases the reliability and adaptability of the vehicle by enabling it to respond flexibly to varying conditions and requirements.

[0052] The artificial intelligence (AI) unit can be designed to consider sustainability, minimal fuel consumption, and maximum lifespan of all components as overarching objectives. By considering these overarching objectives, the AI ​​unit optimizes resource utilization and increases vehicle efficiency. This not only reduces operating costs but also contributes to the vehicle's environmental friendliness by minimizing emissions and waste.

[0053] The artificial intelligence (AI) unit can continuously monitor the vehicle's operating conditions and the driver's driving style, making adjustments to enhance safety. By continuously monitoring these conditions, the AI ​​unit can make real-time adjustments to identify and minimize potential hazards. This significantly improves vehicle safety, as the vehicle can proactively respond to critical situations before accidents occur. Furthermore, the driving experience can be enhanced, as the vehicle is always optimally adapted to the current conditions and the driver's behavior.

[0054] The artificial intelligence (AI) unit may be tested and optimized under various weather conditions, such as rain, snow, and extreme heat, to ensure optimal driving parameters. Testing and optimizing the AI ​​unit under these conditions guarantees that the driving parameters are optimally adjusted even under extreme conditions. This leads to increased vehicle reliability and safety, as it is able to dynamically adapt to a wide range of environmental conditions. Furthermore, driving comfort is improved because the AI ​​unit optimizes relevant vehicle functions, ensuring the vehicle always responds optimally to the prevailing weather conditions.

[0055] The artificial intelligence (AI) unit can be configured to monitor the performance of vehicle components and make adjustments to maximize their lifespan. By monitoring component performance and making appropriate adjustments, the AI ​​unit can ensure that each vehicle component is always operating at its optimal level. This maximizes the lifespan of vehicle components by detecting and preventing excessive wear and potential damage early on. Furthermore, this preventative maintenance strategy leads to increased vehicle reliability and reduces maintenance and repair costs in the long term.

[0056] The artificial intelligence (AI) unit may be specifically designed to optimize the vehicle's energy efficiency by adjusting driving parameters. By selectively optimizing these parameters to increase energy efficiency, the AI ​​unit can significantly reduce the vehicle's fuel consumption and emissions. This results in a longer range and lower operating costs, thus improving the vehicle's overall cost-effectiveness. Furthermore, the improved energy efficiency contributes to environmental protection by minimizing the vehicle's ecological footprint.

[0057] The above can be summarized in other words and in a possible more concrete elaboration of the revelation as described below, whereby the following description is to be interpreted as not being restrictive for the revelation.

[0058] The disclosure covers the AI-supported optimization of control units for a customer-specific vehicle, which is optimized for the needs of the user, the driving environment / external influences, etc. The user's needs can include: - Comfort requirements (acceleration, damping, air conditioning, insulation, acoustics, cornering, etc.) - Component lifespan of, for example, dampers, engine / transmission components, axle components, bodywork, electronic components (fans) - Travel time / route / surroundings (countryside / city) - Compliance with laws, social conformity (exhaust system noise level) - Under “customer detail location” the adaptation of all driving parameters and conditions to the individual wishes / needs of the user and the vehicle in the respective driving environment can be understood.

[0059] In the case of multidimensional physical relationships (e.g., 10 variables → e.g., NOx concentration at the exhaust system outlet; or: max. permissible discharge power of the HV battery at high ambient temperature or high thermal stress on a racetrack), the mathematical / physical dependencies can be optimized by repeatedly incrementally changing individual variables, followed by measuring all relevant resulting parameters, in such a way that the overall property of the entire system is optimized with regard to overarching target variables (e.g., sustainability; lowest possible consumption; longest possible service life of all components, etc.).

[0060] Furthermore, a vehicle equipped with the control unit or control device described above will be provided.

[0061] The vehicle in question can be a passenger car, in particular an automobile, or a commercial vehicle, such as a truck. The vehicle can be automated. The vehicle can be designed to take over longitudinal and / or lateral control, at least partially and / or temporarily, by means of the control device during automated driving. Automated driving can be implemented in such a way that the vehicle's movement is (largely) autonomous. Automated driving can be controlled, at least partially and / or temporarily, by the control device. It is conceivable that the vehicle actively intervenes in the vehicle's lateral control through a driver assistance system, e.g., by adjusting the current steering wheel position, and optionally passively, e.g., by displaying a turn instruction.

[0062] The vehicle can be a Level 0 autonomous vehicle, meaning the driver remains fully responsible for driving, even if support systems (e.g., ABS or ESP) are present. The vehicle can be a Level 1 autonomous vehicle, meaning it has certain driver assistance systems that support the driver in operating the vehicle, such as adaptive cruise control (ACC). The vehicle can be a Level 2 autonomous vehicle, meaning it is partially automated to the extent that functions such as automatic parking, lane keeping / lateral control, general longitudinal control, acceleration, and / or braking are handled by driver assistance systems. The vehicle can be a Level 3 autonomous vehicle, meaning it is conditionally automated to the extent that the driver does not need to continuously monitor the vehicle system. The vehicle independently performs functions such as activating the turn signals, changing lanes, and / or maintaining lane position.The driver can engage in other activities but will be prompted by the system to take over driving within a specified warning period if necessary. The vehicle can be a Level 4 autonomous vehicle, meaning it is so highly automated that the vehicle's system permanently takes over driving. If the system can no longer handle the driving tasks, the driver may be prompted to take over. The vehicle can be a Level 5 autonomous vehicle, meaning it is so fully automated that the driver is not required to perform the driving task. No human intervention is required except for setting the destination and starting the system. The vehicle can operate without a steering wheel and pedals.

[0063] The above description with reference to the control device also applies analogously to the motor vehicle and vice versa.

[0064] The disclosure also includes further developments of the process that exhibit features already described in connection with the further developments of the disclosed control device and motor vehicle. For this reason, the corresponding further developments of the disclosed process are not described again here.

[0065] A method is proposed for automatically providing adapted vehicle functions / driving parameters based on the vehicle's situational driving behavior. The method comprises several steps: - Recording situation-dependent driving behavior and / or operating parameters of the vehicle during operation of the vehicle; - Matching the situation-dependent driving behavior and / or the operating parameters of the vehicle with data in an artificial intelligence (AI) unit comprising a trained model, wherein the model is trained with provided training datasets of situation-dependent driving behavior and / or operating parameters of the vehicle, - Providing a way to customize the

[0066] To provide vehicle functions / driving parameters based on the recorded situational driving behavior and / or the vehicle's operating parameters, and to provide the adapted vehicle functions / driving parameters to the vehicle if a deviation has occurred during the adjustment.

[0067] Alternatively or additionally, customization options can be provided.

[0068] Furthermore, the procedure includes, in a further configuration: - Adjusting the vehicle functions / driving parameters and providing the adjusted vehicle functions / driving parameters to the vehicle (1) and / or user.

[0069] The procedure can be a computer-implemented procedure, meaning that one, several, or all steps of the procedure can be at least partially executed by a computer or a data processing device, optionally the control device. The statements above regarding the control device and the vehicle apply analogously to the procedure and vice versa.

[0070] Furthermore, a computer program is provided, comprising instructions that, when executed by a computer, cause it to at least partially execute the above-described procedure. The program code of the computer program can be in any form, in particular code suitable for motor vehicle control systems. The above descriptions relating to the control device, the motor vehicle, and the procedure apply analogously to the computer program and vice versa.

[0071] Furthermore, a computer-readable medium, in particular a computer-readable storage medium, is provided. The computer-readable medium comprises instructions which, when executed by a computer, cause it to at least partially execute the procedures described above. That is, a computer-readable medium can be provided that contains a computer program as defined above. The computer-readable medium can be any digital data storage device, such as a USB flash drive, a hard drive, a CD-ROM, an SD card, or an SSD card (or SSD drive / SSD hard drive).

[0072] The computer program does not necessarily have to be stored on such a computer-readable storage medium to be made available to the motor vehicle; it can also be obtained via the internet or other external sources. The above descriptions regarding the procedure, the control device, the computer program, and the motor vehicle also apply analogously to the computer-readable medium and vice versa.

[0073] The disclosure also includes combinations of features of the described embodiments. The disclosure therefore also includes realizations that each exhibit a combination of features from several of the described embodiments, provided that the embodiments have not been described as mutually exclusive.

[0074] The following are examples of the disclosure's implementation. This is illustrated by: Fig. 1 schematically a vehicle 1 with the control device 10 as disclosed for automatically providing adapted vehicle functions / driving parameters; and Fig. 2 schematically a flowchart of an embodiment of the disclosed method for automatically providing adapted vehicle functions / driving parameters of a vehicle 1.

[0075] The exemplary embodiments described below are preferred embodiments of the disclosure. In these exemplary embodiments, the described components each represent individual features of the disclosure, which are to be considered independently of one another and further develop the embodiments independently. Therefore, the disclosure is intended to include combinations of features of the embodiments other than those shown. Furthermore, the described embodiments can also be supplemented by further features of the disclosure already described.

[0076] In the figures, identical reference symbols denote functionally equivalent elements.

[0077] The in Fig. 1. Vehicle 1, shown only schematically, includes a control device 10 as disclosed. The control device 10 may include a storage unit (not shown). Alternatively, the storage unit may be located in a cloud and communicate with the control device 10.

[0078] The vehicle 1 can be configured as a motor vehicle. The vehicle 1 can have at least one detection unit 12 comprising a sensor unit 12-1, 12-2, 12-3, 12-4. In particular, the vehicle can have a plurality of sensor units 12-1, 12-2, 12-3, 12-4. The sensor units 12-1, 12-2, 12-3, 12-4 can be configured redundantly. Various vehicle data, in particular the situation-dependent driving behavior and / or operating parameters of the vehicle 1, can be detected via the at least one sensor unit 12-1, 12-2, 12-3, 12-4. The sensor unit 12-1, 12-2, 12-3, 12-4 can be configured to detect data / information from the vehicle 1, from the user, from the interior and / or the environment of the vehicle 1 and to make it available for further processing and / or use. Vehicle 1 has an interface 60 to a mobile communication connection 50 for providing vehicle data to a higher-level instance 40.Data / information can be exchanged between vehicle 1 and the higher-level instance 40 via the mobile communication connection 50. The higher-level instance 40 can be configured as a service center, database, and / or server system. An agent for providing services can be located within the service center. Alternatively, the artificial intelligence (AI) unit 20 can be a trained model implemented within the higher-level instance 40. Additionally, the artificial intelligence (AI) unit 20 can be implemented in the control device 10 and the higher-level instance 40. Calculations and optimizations can be performed in a distributed system.

[0079] The control device 10 is designed to perform the following, also with reference to the Fig. 2 detailed procedures for automatically providing options for adapting vehicle functions / driving parameters of a vehicle 1 to the situation-dependent driving behavior of the vehicle 1

[0080] Alternatively or additionally, the control device 10 is designed to execute a method for automatically providing adapted vehicle functions / driving parameters of a vehicle 1 to a situation-dependent driving behavior of the vehicle 1.

[0081] Fig. Figure 2 shows the disclosed method 100 for automatically providing adapted vehicle functions / driving parameters of a vehicle 1 to a situation-dependent driving behavior of the vehicle 1. The method 100 comprises the following steps: - Recording 110 of the situation-dependent driving behavior and / or operating parameters of vehicle 1 during operation of vehicle 1; - Matching 120 of the situational driving behavior and / or the operating parameters of the vehicle 1 with data from an artificial intelligence (AI) unit 20 comprising a trained model, wherein the model is trained with provided training datasets of situational driving behavior and / or operating parameters of the vehicle 1, - Providing a means of adjusting the vehicle functions / driving parameters based on the recorded situational driving behavior and / or the operating parameters of vehicle 1, and making the adjusted vehicle functions / driving parameters available to vehicle 1 if a deviation has occurred during the adjustment. Furthermore, the procedure includes adjusting the vehicle functions / driving parameters and making the adjusted vehicle functions / driving parameters available to vehicle 1 and / or users.

[0082] Fig. Figure 2 shows the method that can be implemented by the control device 10, which automatically provides options for adapting vehicle functions and driving parameters based on the situational driving behavior, or alternatively or additionally provides adapted vehicle functions and driving parameters based on the situational driving behavior. Alternatively, the method is executed in the higher-level instance 40 and automatically provides options for adaptation, or alternatively, adapted vehicle functions and driving parameters based on the situational driving behavior. The control device 10 detects and processes the situational driving behavior and operating parameters during the operation of the vehicle 1. The control device 10 is connected to various detection units 12, in particular sensors 12-1, 12-2, 12-3, and 12-4.These include sensors 12-1 for determining operating parameters, sensors 12-2 for indoor conditions, sensors 12-3 for environmental conditions, and sensors 12-4 for monitoring the user's condition. These sensors collect comprehensive data required by the control device 10 to make precise adjustments.

[0083] The control unit 10 is connected to an artificial intelligence (AI) unit 20, which contains a model trained on extensive data about situational driving behavior and operating parameters. This model is continuously updated with new data acquired by the acquisition units 12. During vehicle operation, the control unit 10 compares the current driving behavior and operating parameters with data from the trained model. If discrepancies are detected, the control unit 10 suggests ways to adjust vehicle functions and parameters accordingly, thereby optimizing the vehicle's performance (1) in real time. Alternatively or additionally, if discrepancies are detected, the control unit 10 adjusts the vehicle functions and parameters accordingly, thus optimizing the vehicle's performance in real time.

[0084] AI Unit 20 is capable of incremental optimizations, meaning it continuously refines the model within the system boundaries and ensures that Vehicle 1 adapts seamlessly to changing conditions. This unit also adjusts vehicle functions based on factors such as driving time, route, and environmental conditions, thus improving the vehicle's adaptability and performance in various driving scenarios.

[0085] An output unit 70 is included to provide the user with feedback on induced changes in the driving state, keeping the user informed and enabling them to react accordingly. Furthermore, the output unit 70 can provide options for adjusting vehicle functions / driving parameters. The vehicle 1 is also equipped with a communication interface 60, which establishes a connection to a mobile network 50 and enables data exchange with a higher-level instance 40. This higher-level instance 40 can function as a service center, database, or server system and is crucial for providing additional data and support for vehicle operation. The higher-level instance 40 can host part of the trained model of the AI ​​unit, enabling distributed computations and optimizations, which increases the overall performance and accuracy of the vehicle 1.

[0086] The control unit 10 and the AI ​​unit 20 work together to ensure that vehicle functions are continuously adapted to the latest situational data. This includes real-time adjustments based on sensor feedback, model updates with new data, and optimization of vehicle performance parameters. The AI ​​unit also considers user feedback and further refines vehicle functions to better suit individual preferences and improve user satisfaction.

[0087] Overall, Fig. 1 and Fig.Figure 2 presents a detailed representation of a highly advanced control system in a vehicle 1, capable of adapting and optimizing vehicle functions in real time based on a comprehensive variety of data inputs from various acquisition units 12. Supported by advanced AI and communication technologies, this system significantly enhances safety, efficiency, and the user experience by ensuring that the vehicle 1 can dynamically respond to constantly changing driving conditions.

[0088] In one possible configuration, the climate control system can be optimized using standard data and artificial intelligence (AI) provided by the OEM based on its development experience. The AI ​​learns each user's individual climate control preferences, taking into account factors such as season, outside temperature, and sunlight. For example, in summer, a user might prefer the airflow directed straight at their upper body or head, especially when the sun is shining directly on their face. The AI ​​recognizes these patterns and adjusts the climate control accordingly or asks the user if they want a similar setting to the last time. The AI ​​can also access camera data to determine whether the customer is wearing a jacket or sitting in the car in just a T-shirt.Additionally, the AI ​​can use a smartwatch to measure body temperature at specific points or detect perspiration via the camera, as well as taking into account the customer's height, weight, and gender. Similar functionality applies to seat heating or ventilation in winter.

[0089] In another possible configuration, vehicle functions can be linked via prioritized properties. A user might want maximum power output for sporty driving at a specific point on their commute. The artificial intelligence (AI) learns this pattern and can proactively respond to the user's desire for sporty driving. At this point, the AI ​​might, for example, switch off all electrical consumers such as the heating, air conditioning, seat heating, and auxiliary displays to concentrate energy on the powertrain. The AI's insights are then used to adapt and optimize the overall vehicle characteristics by automatically adjusting the optimal parameter settings.

[0090] In another possible configuration, the start-stop function is designed so that artificial intelligence (AI) registers that the customer does not want the start-stop system to activate at a roundabout entrance. The AI ​​learns this pattern because the customer might unexpectedly want to accelerate. By recording and analyzing the customer's driving behavior, the AI ​​can react accordingly and deactivate the start-stop function at these specific locations. This leads to optimized vehicle safety and an improved driving experience, as the vehicle is always ready to accelerate in critical situations.

[0091] In another possible implementation, various sensors and devices such as cameras and smartwatches are used to continuously monitor the user's vital signs and characteristics to detect their mood. These include body temperature, pulse, blood pressure, tone of voice, and facial expression. If the AI ​​registers a specific mood, such as sadness, it can, for example, play cheerful music to lift the user's spirits. If the AI ​​detects signs of aggression, it can intervene to de-escalate the situation by actively addressing the user or steering the conversation toward a pleasant topic, such as asking, "Where are you going on your next vacation, Armin?" These AI-driven adjustments contribute to an improved driving experience by responding to the user's emotional state and taking appropriate action.

[0092] Overall, the examples demonstrate how AI-supported optimization of control units can be provided for customer-specific vehicle functions / characteristics. QUOTES INCLUDED IN THE DESCRIPTION

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

[0000] DE 10 2017 219 365 A1

[0005] DE 10 2021 131 737 A1

[0006]

Claims

[1] Control device (10) for automatically providing adapted vehicle functions / driving parameters of a vehicle (1) to a situation-dependent driving behavior of the vehicle (1), wherein the control device (10) is designed to: - to record the situation-dependent driving behavior and / or operating parameters of the vehicle (1) during operation of the vehicle (1); - to compare the situational driving behavior and / or the operating parameters of the vehicle (1) with data from an artificial intelligence (AI) unit (20) comprising a trained model, wherein the model is trained with provided training datasets of situational driving behavior and / or operating parameters of the vehicle (1), characterized by , that - the control device (10) is further designed during the operation of the vehicle (1) to provide possibilities for adjusting the vehicle functions / driving parameters if a deviation has occurred during the adjustment, based on the detected situation-related driving behavior and / or the operating parameters of the vehicle (1). [2] Control device (10) according to the immediately preceding claim, wherein the control device (10) is further configured to perform the adaptation of the vehicle functions / driving parameters and to provide the adapted vehicle functions / driving parameters to the vehicle (1) and / or user. [3] Control device (10) according to one of the preceding claims, wherein the matching involves incremental optimization of the training data sets of the model within system boundaries. [4] Control device (10) according to one of the preceding claims, wherein the artificial intelligence (AI) unit provides and / or adapts vehicle functions depending on driving time, driving route and / or vehicle environment. [5] Control device (10) according to one of the preceding claims, wherein the possibilities for adapting the vehicle function / driving parameters include an induced driving state change and the induced driving state change can be made available to the user via an output unit (70). [6] Control device (10) according to one of the preceding claims, wherein the possibilities for adapting the vehicle functions include an evaluation and / or classification of the driving state changes of the vehicle (1) induced by the adapted vehicle functions. [7] Control device (10) according to one of the preceding claims, wherein the model of the artificial intelligence (AI) unit is trained on fleet data and / or individual data, and wherein the possibilities for adapting the vehicle functions are additionally based on fleet data and / or recorded situation-related driving behavior and / or operating parameters of the vehicle (1). [8] Control device (10) according to the immediately preceding claim, wherein the model of the artificial intelligence (AI) unit (20) continuously receives new data during the journey of the vehicle (1) and adapts and / or optimizes learned training data sets in real time. [9] Control device (10) according to one of the preceding claims, wherein the model of the artificial intelligence (AI) unit (20) is adaptable and / or optimizable based on received user feedback. [10] Control device (10) according to any one of the preceding claims 5 to 7, wherein the model of the artificial intelligence (AI) unit (20) is trained by means of simulation and / or test driving with different conditions and / or different environments in order to cover a high degree of coverage of driving scenarios. [11] Control device (10) according to one of the preceding claims, wherein the control device (10) comprises at least one interface (11) for communicatively connecting a detection unit (12) comprising at least: - Sensors (12-1) for determining operating parameters of the vehicle (1); - Sensors (12-2) for determining interior conditions of the vehicle (1); - Sensors (12-3) for determining the vehicle's environmental conditions (1); and / or - Sensors (12-4) for determining the condition of the user of the vehicle (1) are included. [12] Control device (10) according to one of the preceding claims, wherein the artificial intelligence (AI) unit automatically provides updates and adaptation options to provide continuous adaptation of the vehicle functions to changes in the situational driving behavior of the vehicle (1) and / or operating parameters of the vehicle (1). [13] Vehicle (1), characterized by that the vehicle includes the control device (2) according to one of the preceding claims. [14] Method (100) for automatically providing adapted vehicle functions / driving parameters of a vehicle (1) to a situation-dependent driving behavior of the vehicle (1), wherein the method comprises: - Recording (110) the situation-dependent driving behavior and / or operating parameters of the vehicle (1) during operation of the vehicle (1); - Matching (120) the situational driving behavior and / or operating parameters of the vehicle (1) with data from an artificial intelligence (AI) unit (20) comprising a trained model, wherein the model is trained with provided training datasets of situational driving behavior and / or operating parameters of the vehicle (1), - To provide (130) a means of adapting the vehicle functions / driving parameters based on the recorded situational driving behavior and / or the operating parameters of the vehicle (1), and to provide the adapted vehicle functions / driving parameters to the vehicle (1) (140) if a deviation has occurred during the adjustment. [15] A method according to the immediately preceding claim, the method further comprising: - Adjusting the vehicle functions / driving parameters and providing the adjusted vehicle functions / driving parameters to the vehicle (1) and / or user. [16] Computer program, characterized by that the computer program includes instructions which, when the program is executed by a computer, cause it to execute the method according to the method claim. [17] Computer-readable medium, characterized by that the computer-readable medium comprises instructions which, when executed by a computer, cause it to execute the method according to the method claim.

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