RU2685998C2 - Situational vehicle interface - Google Patents

Abstract

FIELD: vehicles.

SUBSTANCE: invention relates to a vehicle interface system, particularly to prediction of use of a situational interface of a vehicle. Such result is achieved due to that the vehicle interface system includes an interface configured to display icons indicating the selected functions of the vehicle, as well as a controller programmed to generate an estimated value for each of the functions based on the situational variable including the location of the vehicle and/or the speed of the vehicle, and/or information on previous use of function, and/or predicted final position of vehicle, as well as display one icon and hide other icons based on generated estimated values.

EFFECT: technical result is providing a flexible system for displaying vehicle functions to a user to prevent driver distraction when driving a vehicle for unnecessary options.

9 cl, 14 dwg

Description

The technical field to which the invention relates.

The present invention relates to a vehicle interface system, in particular, to predicting the use of a vehicle situational interface.

The level of technology

A standard vehicle includes a variety of systems that allow the user to interact with the vehicle. In particular, standard vehicles have various devices and capabilities for controlling and controlling various subsystems and vehicle functions. As technology develops, more and more opportunities appear to control the various subsystems of the vehicle. Some of these functions can be presented to the user through the user interface. However, these functions may be displayed to the user in a predetermined manner. Thus, there is a need for an improved flexible system for displaying vehicle functions to a user.

DISCLOSURE OF INVENTION

The vehicle interface system may include an interface configured to display icons indicating selectable vehicle functions; a controller configured to generate an estimated value of each function based on the situational variable, including the position and / or speed of the vehicle, and / or the predicted final location of the vehicle, and display some icons and hide other icons based on the generated estimated values.

A vehicle controller may include at least one situational module, configured to generate at least one situational variable characterizing the current driving situation, including vehicle position or vehicle speed, and a processor programmed to generate an estimated value of a specific function on the basis of the location of the vehicle and (or) the speed of the vehicle, determined with the help of her situational least one variable, and the estimated value of the function is a probability that the traffic situation on the basis of the function of the vehicle is selected, and display one icon and other icons to hide under evaluation function values.

The method may include receiving at least one situational variable from the situational module, generating an estimated function value based on at least one situational variable, and displaying an icon indicating a specific vehicle function on the interface based on the estimated value, wherein the icon is the ability to interact with the system associated with a specific function in the vehicle.

Brief Description of the Drawings

FIG. 1 shows an example of a user interface system component;

in fig. 2 is a diagram of the components of the user interface system of FIG. one;

in fig. 3 is a block diagram of an exemplary method that can be used by a user interface system;

in fig. 4 is a diagram of an embodiment of the user interface system of FIG. one;

in fig. 5 is a block diagram of an embodiment of a method that can be used by the user interface system of FIG. four;

in fig. 6 is a block diagram of an alternative embodiment of a method that can be used by the user interface system of FIG. four;

in fig. 7 shows an example of a location database that can be used by the user interface system of FIG. one;

in fig. 8 is a graph of estimated values characterizing the probability that the components of the user interface system of FIG. one;

in fig. 9 is a graph of estimated values characterizing the probability that the components of the user interface system of FIG. one;

in fig. 10 shows an example of a scheme for generating an estimate value of a function;

in fig. 11–13 are examples of data graphs that show the situational variables used to generate the estimated value of a function;

in fig. 14 shows an example flowchart of a method for generating an estimate value of a function.

The implementation of the invention

In accordance with the requirements herein, embodiments of the present invention are described in detail; however, it should be understood that the disclosed embodiments of the invention should be considered solely as examples of the invention and that they can be implemented in various alternative forms. In the drawings, the scale is not necessarily respected, some distinctive features can be enlarged or reduced for more detailed representation of certain details. Thus, the description of specific structural and functional details should be interpreted not as limitations, but as illustrative examples to familiarize specialists in the art with the embodiments of the concepts disclosed in the document.

Vehicle interface systems can control various options that allow the user to access and interact with vehicle systems. These systems include climate control systems, navigation systems, parking systems, etc. Each system can provide various functions (capabilities) of the vehicle, such as cruise control, driving direction, parking assistance, etc. Given the current driving conditions, when operating a vehicle at certain times, some functions may be more relevant than others. For example, when driving a vehicle at a high speed, the likelihood of the driver activating the cruise control function will be relatively high, and the probability that the driver activating the parking function will be relatively low. In accordance with another example, when a vehicle is driving at a speed below 20 miles per hour, switching on the cruise control function may not be possible. Since the use of this function will be impossible, then in this case it may not be displayed to the driver at all. Based on the driving situation, the vehicle interface system may use the predicted probability to increase the priority display of certain functions on the user interface of the vehicle. In other words, certain icons denoting the respective functions of the vehicle may or may not be displayed based on the likelihood that they will be used by the user. This approach allows the user to easily view and select the appropriate functions. Functions that are not allowed or which most likely will not need to be used may not be displayed so that the driver is not distracted while driving to unnecessary options. In accordance with the example, when using the parking function (for example, an automatic assistance system, rear view cameras), certain variables can be used to determine the estimated value of the function. For example, the distance between the current location and the final location can be used to determine the likelihood of a driver using the parking function. As an addition to determining the estimated value of the function and increasing the priority of displaying the parking function on the user interface, the number of cycles of its choice by the driver at a certain final location, as well as the current vehicle speed can also be used. Moreover, the current status of the function can be monitored. If the function is already in use, there is no need to increase its display priority.

The vehicle system may include a controller configured to receive input signals from sensors. The controller can generate an estimated function value, at least in part, based on the input from the sensors and location data from the database. The controller can match the estimated value of the function and the selected option. The controller can issue commands for the user interface to display the selected option depending on the estimated value of the function, with the result that the user is displayed options of interest based on certain attributes, such as input from sensors or location data. In accordance with one example, selectable options may include an automatic parking option and / or a parking mode option. When choosing the option of automatic parking, it helps the driver to automatically park his vehicle. In other words, the vehicle can independently perform taxiing in parallel or perpendicular parking in a parking space with little or no help from the driver. In accordance with another example, the parking mode option may be available. The valet mode can be included next to certain organizations that provide valet services, for example, near hotels, restaurants, bars, etc. Thus, the system can detect the approach of the vehicle to a place where the user may want to use the automatic parking option or the parking attendance option. These options can be assigned a higher priority than other functions, such as cruise control, and they can be displayed to the user on the user interface. In the parking mode, the screen can be dimmed in a vehicle so that the person driving the vehicle cannot access personal information and the preferred settings of the vehicle owner. The parking mode function is usually installed in a system that includes navigation systems and infotainment systems. system. Information such as the home address of the vehicle owner will not be available to unauthorized drivers.

FIG. Figure 1 shows an example of a user interface system. The system can take various forms and include additional and / or alternative components and distinctive features. Although the example presents an example of a system, these components should not be considered as limitations. Moreover, additional or alternative components and / or applications may be used.

FIG. 1 shows an example of a user interface system 100. Although in accordance with the description, this embodiment is used in a vehicle, user interface system 100 may also be implemented in any other vehicle, including, but not limited to, motorcycles, boats, airplanes, helicopters and all-terrain vehicles, trucks, etc.

FIG. 1 and 2, the system 100 includes a user interface 105. The user interface 105 may include one interface, for example, one touch screen, or several interfaces. The user interface system 100 may also have an interface of the same type or interfaces of various types (eg, audio and video devices) configured to provide interaction between man and machine. The interface 105 may include a display, such as a touch screen. A display controlled by various hardware controls may also be included. The interface 105 may also include a display on the windshield (HUD), in which images are projected onto the windshield of the vehicle. The user interface 105 may be configured to receive user signals from the passengers of the vehicle. In accordance with the example, the user interface may include control buttons and / or control buttons displayed on the touch screen (i.e. hardware buttons and / or virtual buttons) that allow the user to enter commands and information for use by the system 100 user interface. To control various vehicle functions, the controller 110 can receive input signals for the user interface 105. For example, the input signals for the user interface 105 can be used by the controller 110 to control the climate in the vehicle, interact with the navigation system, control the playback in the multimedia system, automatic parking systems, etc. The user interface 105 may also include a microphone, allowing the user to input commands or other information using voice.

The controller 110 is connected to the user interface 105. The controller 110 may include any computing device configured to execute computer readable instructions that control the operation of the user interface 105 as described in this document. For example, controller 110 may include a processor 115, a situational module 120, and external data storage 130. External data storage 130 may include flash memory, RAM, EPROM, EEPROM, a hard disk, and / or any other type of storage device. Alternatively, the situational module 120 and external data storage 130 may be embedded in the processor. Another embodiment may involve several controls connected to each other, each of which may have a processor 115, a situational module 120 and external data storage 130. The controller 110 may be embedded in the user interface 105 or may be installed separately.

In general, computing systems and / or devices such as controller 110 and user interface 105 can use any of a number of operating systems, including, but not limited to versions and / or flavors, of the Microsoft Windows® OS; Unix (for example, Solaris® OS from Oracle Corporation, California); AIX UNIX by International Business Machines, Armonk, New York; Linux OS; Mac OS X and iOS from Apple Inc., Cupertino, California; BlackBerry OS OS by Research In Motion, Waterloo, Canada; as well as the Android OS of the Open Handset Alliance. After reading this description, it will be understood by those skilled in the art that the specific hardware or software of the user interface 105 and controller 110 can be any combination that allows it to perform the functions of the presented embodiment.

The controller 110 may be configured to control the display of the function on the user interface 105 using the processor 115. The processor 115 may be configured to detect a signal from the user indicating that the user wishes to activate the vehicle system or subsystem based on the detection of the option selected on the user interface 105. A selectable option is created for each function available in the vehicle (for example, for temperature control, heating Deny, automatic parking system, cruise control system, etc.). Each selectable option can control the vehicle system or subsystem. For example, the selectable option for the cruise control system controls the vehicle system that controls the constant speed of the vehicle (cruise control). Also, each selectable option can control multiple vehicle systems. For example, a user may select a selectable option corresponding to a driving assistance system. This selection can control the auto parking function as well as the availability of certain rear view cameras. The selected option can be an icon displayed on the interface. It may also include a textual description of the vehicle function, which is controlled by the corresponding option, as well as other visual information.

With the help of the processor 115, the controller 110 can be configured to determine the function that will be used by the driver or passenger with the highest probability, as well as the removal of the function, the probability of using which is minimal or equal to zero, based on the specific driving situation. To determine the function that is most relevant at the moment, the controller 110 can receive an input signal from the situational module 120, sending situational variables, and from the standard sensor 135 via an interface (not shown). Interfaces may include an input / output system configured to transmit and receive data from the respective components. The interface can be unidirectional, that is, data can be transferred only in one direction. In addition, the interface can be bidirectional, i.e. receive and transfer data between components.

The controller may include a plurality of situational modules 120, each of which is configured to issue situational information or a situational variable. In accordance with the example, the single situational module 120 may be configured to determine the distance to a known location. Another situational module 120 may be configured to compare the speed of the vehicle with the current speed limit. Another situational module can be made with the possibility of determining whether a vehicle has entered a region with other traffic rules (for example, a zone in which you need to use a hands-free headset to talk on the phone). In accordance with another example, a situational module may be configured to provide access to data storage 130 to determine how often a particular vehicle function is used at a particular location. In accordance with another example, each output signal may be received by each of a plurality of selectable options, and may also be used once or repeatedly used by selectable options when generating an estimated function value. In other words, each of the plurality of situational modules 120 always performs the same operation. For example, when comparing driving speed with a current speed limit, the situational module 120 will always produce the same situational condition, although this condition can be obtained by other selectable . A situational variable can also use information about the vehicle and vehicle module to provide a situational estimate value. For example, the automatic parking function may remain inoperative / inactive until the vehicle speed drops below 10 miles per hour. In this case, the output situational estimated value also characterizes the design of the vehicle subsystem and (or) the limiting values of the physical characteristics under which the driver / passenger can work and possess.

A situational variable may be a specific driving condition, for example, the speed of a vehicle or the previous place in which the driver activated a particular function. The values of situational variables can be obtained from situational module 120 or standard sensor 135. Controller 110 can be configured to select a function that is likely to be used by the user, based on the input signal received from situational module 120 and standard sensors 135. For example, under certain circumstances or driving situations, the controller 110 may indicate that the cruise control function may be particularly relevant. In accordance with one approach, each function available on user interface 105 is displayed by a certain selectable option. For example, a garage door opener can always match or be associated with a selectable option for a garage door opener.

Situational variables can be a numerical value, depending on the situation of movement. In accordance with one possible application, situational variables can take values in the range from 0 to 1, with “1” corresponding to the largest value. Alternatively or additionally, situational variables may characterize a particular situation, such as ambient temperature, precipitation, or distance to a particular place or final location. For example, a situational variable issued may indicate that the vehicle is approaching the place where valet parking services are provided. The output signal may indicate the approach of the vehicle to the car park, parking space in the parking lot or to the parking space on the street. There are two types of situational variables: simple situational variables and intellectual situational variables. Simple situational variables can be obtained from the standard sensor 135. The standard sensor 135 can be any sensor or sensor system installed in a vehicle. For example, standard sensor 135 may include audio sensors, light sensors, accelerometers, motion speed sensors, temperature sensors, navigation sensors (for example, a GPS sensor), etc. Intelligent situational variables may be issued by situational module 120 and may be other situational variables combined into values that cannot be immediately obtained using vehicle equipment. In other words, these vehicle systems or subsystems cannot generate intelligent situational variables by themselves. For example, to obtain intelligent situational variables, situational module 120 may receive input data based on simple situational variables received from standard sensors 135 or other intelligent situational variables received from situational modules 120, after which situational module 120 may combine this output values (for example, in groups of several values). There are various ways in which a situational module can generate these values. For example, these methods can include simple or complicated algebraic calculation methods, fuzzy logic, neural networks, a statistical approach, a frequency approach, etc.

The controller 110 may include location data stored in a database, for example, on external data storage 130. External data storage 130 may be embedded in controller 110 or may be a separate component. Location data may include data on stopping points, for example, previous stopping places of a vehicle, or data on a selectable option, which may include, for example, the number of cycles to use a selectable option at a previous stopping point (for example, using a function based on location). Publicly available information for a parking space may contain information about whether it is paid or free, and (or) about the cost of parking (if applicable). Location data may also include information about a place of interest, for example, places of interest where valet services are provided (for example, restaurants, hotels, conference rooms, etc.). Data about a place of interest can also include user preferences for different situations, for example, preferences regarding visits to places where many or few people gather. For example, a user may prefer to visit restaurants that provide valet services, which may affect the estimated value of a function attributed to each option selected. Although external data storage 110 can be part of controller 110, it can also be installed separately from controller 110 and can be connected to it via a network, for example, using a cloud computing environment or an application programming interface (API) over the Internet.

The processor 115 may be configured to exchange data with the external data storage 130 if necessary to use the stored information when generating a selectable option. To generate an intelligent situational variable, external data storage 130 can exchange data with situation module 125. Similarly, external data storage 130 can exchange data directly with the processor 115. External data storage 130 may contain general information, such as a navigation database, which can be traffic rules in particular streets and districts, or user information, such as the preferred temperature in the passenger compartment deleterious agents. Alternatively or additionally, external data storage 130 may track activation of vehicle functions at specific locations or under certain driving conditions. For example, an external data repository may store data on the number of activations of the cruise control system on a particular highway. This, in turn, may affect the estimated value of the cruise control function when a vehicle is traveling on a given highway. Also, external data storage 130 may update information, for example, using telematic systems or any other suitable technique. A telematics system located in a vehicle can be configured to receive updates from a server or other source (for example, from a dealership). Similarly, information on external data storage 130 can be manually updated using a signal from a vehicle user transmitted to user interface 105. Moreover, controller 110 can be configured to use user interface system 100 to communicate with a mobile device over a wireless network . Such a network may include a cordless phone, a Bluetooth® device, a tablet computer, as well as 3G and 4G devices, etc.

In the present example, the user interface 105 may allow the user to specify his preferences for a particular location. As their preferences, the user can specify the places in which there is a valet service or offers a secluded dining environment. These preferences can be stored in the external data storage 130 (for example, as points of interest) and can be used by the situational module 120, 125 for issuing situational variables. For example, the estimated value of the functions for the parking mode in a certain place can be defined above (in particular, it can have a larger estimated value of the function) if the user has set a preference to turn on the parking mode, regardless of whether it stopped there earlier or not. Appropriate setting your own preferences will avoid the need to stop at a certain place to get a high estimated value for it.

The processor 115 may be configured to detect input data, such as situational variables, transmitted by the situational module 120. The processor 115 may store each selectable option corresponding to a specific function that the user can access via the user interface 105. Each selectable option accepts input data in the form of several situational variables generated by the standard sensor 135 and situational module 120. The processor 115 combines the obtained variables for the generator Ania estimated value function associated with the selected options, which indicates the possibility of using a specific user function. Thus, for each selectable option, a certain estimated value of the function is set. However, depending on the traffic conditions and the situation, the estimated values of the function corresponding to the options selected may vary. A variety of methods can be used to combine situational variables, including, but not limited to, multiplication, summation, averaging, or the use of non-linear algorithms, such as fuzzy logic. In accordance with one embodiment, processor 115 may set an estimated value for the selectable option from 0 to 1, with “0” corresponding to a function with a low probability of use at a given moment, and “1” corresponding to a function with a high probability of use. Thus, the function used (for example, the system currently in use or the vehicle subsystem) will have a low estimated value in the decimal system, since the probability of activating this function in the near future is small. However, this preference may be changed by the driver or the manufacturer so that an estimated value of “1” indicates that the user is currently using the function. The decimal estimate is presented as an example, if necessary, you can use different ranges of values.

After the processor 115 generates the estimated value of the function, it can raise the priority of displaying it on the user interface 105. Based on the preferences of the driver or the manufacturer, the processor 115 can select the option with the highest estimated value and display it on the user interface 105. The highest estimated value can match the preferred selectable option or selected function. In other words, the selectable option with the highest estimated value for the function may be the preferred function. In an alternative embodiment of the invention, the processor 115 may rank the selectable options based on their estimated function values and select several functions with the highest estimated value for the function to display on the user interface 105. The selectable options corresponding to the smallest estimated values can be hidden or deleted from the user interface 105. The icons displayed on the user interface 105 may change continuously with each change in the estimated values for the functions.

In accordance with one example, a vehicle may provide an automatic parking function, such as an active automatic parking system for parallel parking, or a standard parking function using rear view cameras for perpendicular parking. The probability of using different parking functions may be higher in certain places, in certain geographical areas (for example, in a city, suburb, popular places, etc.), at certain times of day, etc. Also, the parking function can be used more likely when the vehicle is moving at a low speed. In accordance with this illustrative example, data on the current location of the vehicle (for example, using a GPS system) can be provided by a standard sensor (for example, a standard sensor 135). Another standard sensor (eg, standard sensor 140) may provide vehicle speed data. Both output values may be simple situational variables. Simple situational variables characterizing the speed of movement and location may be adopted by the situational module 120. Situational module 120 may use the current location to obtain additional intelligent situational variables. In accordance with one example, the current location may be used to determine possible end locations (e.g., a preferred end location). These end locations can be entered by the user using the navigation system. They can also be saved or predicted locations. Predicted end locations can be compared with the current location. The selection and analysis of the final location closest to the current location may be performed. Situational module 120, 125 may use the end location to determine the type of functions selected by the user at that end location previously. In other words, it can be determined if the user used the parking function at a specific destination. In addition, these situational variables and other variables may be fed to the situational module 120, 125. In accordance with one example, the situational module 120, 125 may receive publicly available parking data containing information about possible parking options near the current location. These variables can be transferred to the processor 115, which can set the estimated value of the function for each selectable option, taking into account the specific situation of movement. In accordance with one example, if the vehicle is close to a location where the parking function is normally used in a vehicle, but it is moving at high speed, a low estimated value (eg, 0.3) can be assigned to the driving situation. In accordance with another example, if the vehicle is traveling at a relatively low speed, a higher estimated value (eg, 0.8) may be assigned to the driving situation. The processor 115 may select the option (s) with the highest estimated value and display them on the user interface 105. The selectable option may replace the current options if the estimated value of a certain function corresponding to the selected option exceeds the estimated value of the function corresponding to the currently displayed option.

In accordance with the previous example, to determine the estimated value of the parking function, the system 100 can use the current vehicle location, the final location, as well as the vehicle speed. The final location may be the desired destination specified by the user. The final location can be determined using the situational module 120, 125. It can also be determined by another component (for example, a GPS system) in response to a signal from the user. As mentioned above, the final location may also be a predicted location or destination. The predicted destination can be determined using the dynamic learning and forecasting module. The module may be able to train and transcode the various habits of the driver when stopping and moving off, as well as frequently visited locations that are recognized without entering the appropriate signal from the user. The prediction module can take into account several factors, such as time of day, day of the week, etc. Thus, when the vehicle starts moving along the recognized route, the module can determine that the final location is one of several likely locations using historical data about the user and / or vehicle. Also, the predicted location may be the location where the user used the parking function last time. The data about the previous parking places can be determined by the user and stored in the data storage 130 in accordance with the description provided.

The final location can also be used to determine a possible parking space that can be detected based on external data. A parking space detectable on the basis of external data may differ from the final location in that the parking space may be a car parking or a car parking space near the end location. Parking spaces detected by external data can be obtained from data storage 130 or another source, such as a mobile device, transmitted over a wireless communication channel or ad hoc channel. For example, a mapping application in a mobile device may provide information about the nearest car parks to the processor 115 and / or situational module 120, 125. The area map can also be used to provide data on the location of various car parks. The data storage 130 may also include a map database of available car parks. Thus, car parks detected on the basis of external data can be determined using information from data storage 130, another component of interface system 100, or an individual component. In some cases, car parks detected on the basis of external data can be determined using a public source, as well as a private database.

FIG. 2 is a diagram of the interaction of the components of the system 100 user interface. First, the controller receives input from standard sensors 135 and 140, which collect information from sensors and sensor systems installed in the vehicle, and issue simple situational variables. For example, a standard sensor may be an ambient temperature sensor, a speed sensor, or a GPS vehicle position sensor. To generate intelligent situational variables, situational modules 120 and 125 can receive simple situational variables, other intelligent situational variables, and / or location data from external data storage 130. Location data from external data storage 130 may include parking location data obtained from a public source as well as from a private database. To determine the values of intelligent situational variables and simple situational variables for a variety of selectable options, these variables can be sent to the processor 115. Each selectable option is associated with an estimated value for the function that was generated based on the values of the adopted situational variables. Each selectable option continuously receives input from standard sensors and situational modules. However, depending on the traffic situation, the estimated values of the function associated with the options selected may be different. For example, if situational variables indicate that a vehicle is driving on a highway at a speed close to the speed limit value, the option selected for the cruise control function will receive a high estimated value, and the function of seat heating or garage door opening will receive a low estimated value.

Processor 115 may rank selectable options according to their estimated function value. The processor 115 may select the option with the highest estimated value. Depending on the configuration of the user interface system 100, the processor 115 may increase the display priority of the selected option with the highest estimated value or may increase the display priority of several selectable options on the user interface 105. At the same time, the processor 115 may stop displaying the function (s) on the user interface 105, the probability use of which has decreased. Standard sensors 135, 140 and situational modules 120, 125 are always active and continuously generate an evaluation value of the function for each selectable option. The processor 105 uses these estimated values to provide the most current information about the traffic situation on the interface 105, whereby the selectable option with the highest estimated value will always be displayed on the user interface 105.

FIG. 3 shows a flow chart of a method 200, which may be performed using a user interface system 100. The operation of the user interface system 100 may start (step 205) automatically when the vehicle ignition is turned on. At this moment, the vehicle can perform an internal check of the system, in which the state of readiness of one or several systems and (or) vehicle subsystems will be determined, which will make sure that the vehicle is ready for operation. When performing an internal check at step 210, system 100 may also classify selectable options available in the vehicle. The system 100 may further subdivide the available functions (and the corresponding selectable options) of the user interface system 100 into two groups: a departure group and an arrival group. The departure group may include functions that are often used when leaving a particular place, such as opening a garage door or climate control. The arrival group may include features that are often used when driving on a route or approaching a destination, such as cruise control or automatic parking. The classification process can be performed by the controller 110. The division of functions into classes can be configured by the vehicle manufacturer or dealer, and the vehicle owner can also set up groups of departure and arrival functions based on their own preferences. The division of functions into two or more groups will reduce the processing time at subsequent stages by reducing the number of functions available for selection.

At step 215, system 100 can monitor situational variables generated by standard sensors 135 and situational modules 120. As mentioned above, situational variables can be simple situational variables derived directly from vehicle sensors, or intelligent situational variables obtained by combining other situational variables variables (simple or intelligent) to obtain values that cannot be immediately obtained by the vehicle. At step 220, system 100 may also verify the need to receive external data from external data storage 130. This situation may occur when situational variables use stored information, such as speed limits, location data, or preferred cabin temperature. If there is a need for additional external data, this information can be transferred to situational modules 120, which will allow them to generate an intelligent situational variable. If additional external data is not needed or has already been received, method 200 may proceed to step 225.

At step 225, the situational variables may be transmitted to the processor 115, which will generate the estimated value of the function. To obtain an estimated value, the processor 115 may combine the received input data (for example, situational variables) and compare the obtained values with each selectable option. Estimated values of the function can be generated by combining situational variables by multiplying them, averaging, determining the maximum value and / or determining the minimum value, or any combination thereof, as well as using other non-linear algorithms, such as fuzzy logic. The estimated value of the function may be directly proportional to the level of relevance (relevance) of combining situational variables transmitted to processor 115. For example, when situational variables indicate that the vehicle is traveling along a highway at a speed close to the limit value, but at the same time the vehicle speed becomes lower or higher than the limit value (which is observed, for example, during heavy traffic), the estimated value of the function for the cruise control option to be selected will be relative o low value compared with the situation when the vehicle is moving at a constant speed, close to the limit value, over a long period of time. In addition, the same variables that correspond, for example, to the selectable automatic parking option, may have a very low estimated value, since the probability of parking while driving at high speed is extremely small.

At step 230, the processor 115 may determine the priority of selectable options based on their respective estimated function values. In the general case, the selectable options with the highest estimated value may have the highest priority, while the remaining available selectable options will be evaluated accordingly for this value. Depending on the user's preferences, at step 235, the function with the highest estimated value or several functions (for example, the three functions with the highest estimated values) may receive a higher priority for display on the interface 105. Similarly, if the displayed functions decrease on the user interface 105, situations of motion can be hidden (or deleted). Alternatively or additionally, the processor 115 or the controller 110 may order the selectable options according to the estimated values for the functions corresponding to each selectable option. Then, the controller 110 can determine the order of selectable options, the estimated values of which exceed a predetermined threshold value. For example, controller 110 may select only options with an estimated value equal to or greater than 0.7. Then, the controller 110 can set the available selectable options with the highest estimated value to the first place, and other selectable options to the relatively lower estimated value to the second place, etc.

At steps 215-225, this cycle is performed continuously as long as the vehicle continues to run. Standard sensors 135 and situational modules 120 are always active and continuously transmit information to a processor that continuously generates new estimated values for the functions. Thus, at step 230, the processor 115 updates the priorities so that at step 235, the most relevant functions are always displayed on the user interface 105.

In accordance with one embodiment, user interface system 100 may determine a selectable option based on received input data from sensors and location data. Location data may include previous stopping points and the number of cycles of using location-based functions. The selectable option can usually be activated based on the location of the vehicle relative to other known or previously detected locations. For example, this description presents a system and method for generating selectable options for automatic parking and valet mode that are activated when approaching certain places (for example, parking, an office building, or a restaurant). An available automatic parking feature that activates the vehicle parking system in automatic mode. In other words, the vehicle can independently perform taxiing in parallel or perpendicular parking in a parking space with little or no help from the driver. The valet mode or option is a similar function that is activated near certain places, for example, near hotels, restaurants, bars, etc., on the territory of which valet services are provided. Activating the vehicle system for the parking mode option can block vehicle components (for example, user interface, glovebox, trunk) so that the parking attendant cannot access personal information that can be stored in the vehicle. The valet option may begin to be used by the controller 110 when approaching the place where valet services are provided. This information can be obtained on the basis of data on a specific location stored in the external data store 335.

Options based on location can take into account the normalized frequency of using a certain function to determine the number of activation cycles of the selected option at a specific location. The normalized frequency of use can be determined by the controller 110. The value of the normalized frequency (F _AF (i, j)) of use can be obtained using a two-level method. Initially, when the number of visits or measurements is limited, the actual value of the normalized frequency is generated using the first level. In other words, before reaching a predetermined minimum number (N _min ) of visits to a certain place, the total number of cycles of using a certain function in a certain place is divided by the total number of visits to a given place and get the actual number of cycles of activation of a certain function in a certain place. The minimum threshold value can be used in order to increase the sample for the number of activation cycles of a certain function in a certain place and to obtain a more accurate value in percent. The minimum number of visits can be a value recorded on external data storage 335, and it can be set by the vehicle manufacturer, dealer, or even the driver.

The mode for determining the actual value (percentage value) of the number of cycles of using a certain function in a certain place can be applied when calculating the actual value of the activation cycles of a certain function in a certain place. The value N (i, j) _a characterizes the number of activation cycles of a certain function in a certain place, for example, the number of cycles when the automatic parking function was used in a certain place, for example, in a supermarket. For example, let i correspond to a specific place, aj be functions. N (i) _all is the total number of visits to location i. The actual value can be calculated using the following formula: F _AF (i, j) -N (i, j) _a / N (i) _all .

If the total number of visits to a particular location is equal to or greater than the specified minimum value, then the method proceeds to the second level. At the second level of the method, a recursive formula is used, which can be used to estimate the normalized frequency (F _AF (i, j)) of real-time use without the need to obtain specific data, for example, the number of activation cycles of a certain function in a certain place. At the second level, the learning rate is used, which can depend on the memory depth of the external data storage 335, and the amplification signal, the value of which can gradually increase with the number of activation cycles of a certain function in a certain place. The normalized frequency of use can be calculated in real time using the following formula: F _AF (i, j) = (1-α) * F _AF (i, j-1) + (α) * Sig _reinforce (i, j), where α is the learning rate (for example, in the range from 0 to 1, while “1” corresponds to the highest speed), F _AF (i, j) is the normalized frequency of using function j in place i, as described above, a Sig _reinforce (i, j) is the amplification signal, which is a function of j, activated at location i (for example, in the range from 0 to 1, with “1” corresponding to the strongest signal).

Switching to a second, recursive formula helps solve two problems. First, the formula allows to reduce the amount of used memory, since the second formula does not use the value N (i) _all or N (i, j) _a to determine the normalized frequency of use. This not only frees the memory, but also increases the speed. Similarly, real-time mode provides more reliable output, as the minimum threshold level of activations in a certain place will be passed, indicating the driver’s preference to use a certain function more often in a certain place. Also, the second formula takes into account the most current data on the use of the function by the driver when his preferences change. The value of speed (a) of training can vary in accordance with the most relevant actions of the driver when using a certain function in different places.

FIG. 7 shows location-based options (for example, automatic parking, valet mode, garage door control, etc.) that can be activated when a vehicle approaches or leaves a certain place. In the general case, in the external data store 335, a separate entry may be provided for each location corresponding to that location. On the external data storage 335, the longitude and latitude of each specific location (eg, home, office, restaurant located near the office, etc.) can be recorded. Each record corresponding to a particular place may also include a field characterizing the normalized frequency of using certain functions in a given place. Alternatively or additionally, each entry can be saved to one or both of the arrival and departure groups, with the result that two entries can be created that are associated with a specific place. Thus, the functions used at the beginning of the driving cycle and at the end of the driving cycle may be different, which will allow for more accurate and timely forecasting of the usefulness of each function for the driver.

Each element in the field represents the normalized frequency of using a certain function (for example, cruise control, garage door control, home alarm activation, automatic parking, parking mode, cabin temperature settings, etc.). For example, in the record of the arrival group home, the field may contain the normalized frequency of using cruise control, automatic parking, cabin temperature settings, etc. If a function (or a selectable option) has never been activated in a particular place, then the normalized frequency of use may be low or may not exist at all in the field. For example, the normalized frequency of use of a selectable cruise control option near the house may be equal to 0.00. On the other hand, the field for a selectable garage door control option may be a high value of the normalized frequency of use depending on the number of activation cycles of the selectable option or the learning rate for the selectable option. The normalized frequency of use for each function can be set once or can be updated when a change in driver or passenger preferences is detected.

FIG. 4 shows an embodiment of the system 300 generating an estimated function value for a selectable option. The system may include a user interface 305, a controller 310 having a processor 315, situational modules 320, 325, and 330, as well as several sensors 340 and 345 transmitting input signals for the controller 310. Standard sensors 340, 345 and situational modules 320, 325 and 330 collect data on variable values and transmit it to the processor, which generates the estimated value of the function for each selectable option. The estimated value of the function can be used to determine the most current selectable option, taking into account the current traffic situation. The system 300 may also include location data that is stored in the external data store 335 and may include, for example, previous stopping places for the vehicle, the number of activation cycles of the automatic parking function and valet mode for each previous stopping place, as well as user location (POI). Location data stored on an external storage device can be updated after a certain period of time has passed. For example, external data storage 335 may store data on previous stopping places only for the last 30, 60, or 90 days. This can be useful when tracking the most current driver preferences, and can also reduce the amount of memory used to store data about important places.

In accordance with one embodiment, system 300 may generate a selectable option for automatic parking. As mentioned above, the position sensor 340 and the speed sensor 345 can communicate with the controller using an interface. The vehicle speed sensor 345 may include a speedometer, a gear / shift lever position sensor or a wheel / axle sensor that detects the rotation of the wheel / axle. The vehicle position sensor 340 may be a global positioning system sensor (GPS sensor) capable of locating the vehicle, as well as a radio frequency identification device (RFTD) using radio frequency electromagnetic fields, a GPS device of a cellular phone or a pocket personal computer (PDA). ), which transmits signals, for example, via a Bluetooth® connection.

Each situational module 320, 325 and 330 in the controller 310 may perform a specific function. Although the specific functions described are given only as an example, all or some of these functions can be performed using a single module. The third situational module 330 may be configured to receive vehicle position data from vehicle position sensor 340 and data from previous stopping points from external data store 335. Based on these inputs from the sensors, the third module 330 can determine where to stop (for example, any organization) located near the current location of the vehicle.

The first situational module 320 may be configured to receive data on the stopping point from the third situational module 330. It can also determine the number of cycles to use a certain function in a certain place. For example, the first module 320 may determine the number of activation cycles of the automatic parking function next to a specific organization. As mentioned above, this information can be stored as a record of a certain location on external data storage 335 and can be used to determine the normalized frequency of use of a function in a certain place (using the formula for determining the actual value or using the formula for determining the value in real time). For example, the number of activation cycles of the automatic parking function at a certain place can be represented as an input signal N (i, j) _a , and the number of visits to the nearest place of the previous stop can be represented as an input signal N (i) _all in the formula for determining the actual values. On the other hand, as input for the first situational module 320, when determining the value in real time, only the previous stop point may be needed, on the basis of which the value of the normalized frequency of use will be obtained for the available selectable options. The first situational module 320 may be configured to provide a normalized frequency of use as input for processor 315 to generate an estimated function value for the selected option and output the normalized frequency of use to external data storage 335 to update the record for a particular location.

To determine the distance to the nearest point of interest, the second situation module 325 may be configured to receive vehicle position data from the position sensor 340 and receive data on the vehicle’s closest stopping point from the third situation module 330. According to one approach, the speed sensor 345 can exchange data directly with the processor 315. Output data of the first and second situational modules 320 and 325 and vehicle speed data speed sensor 345 can then be transmitted to processor 315, which will assign the appropriate values for the selectable parking option. The processor 315 may then generate an estimated value of the function corresponding to the selectable parking option based on the obtained variable values and display the selectable parking option to the user using the user interface 305.

Alternatively or additionally, system 300 may create a selectable option / valet mode. The operation of the system 300 is in many respects similar to the use of a selectable option of automatic parking, except for the presence of points of interest (POI) for the valet mode. Places of interest for valet mode contain information on the availability of valet services at a specified location. Points of interest for the parking mode can be specified in the on-board map database, saved as location data in external data storage 335 or as a network service (for example, using cloud computing). Places of interest for the parking mode can be determined using data obtained directly from external data storage 335 (for example, external data storage 335 storing information about the places in which parking services are provided), or by analyzing the name of a place stored in external storage 335 data. For example, keywords such as “conference room”, “hotel” or “restaurant” may indicate that parking services are most likely provided in these places. If places of interest for valet mode have not yet been stored in external data storage 335 or the place name does not indicate the presence of valet services, then activating the selectable mode option can update data in external data store 335 to indicate the presence of valet services in this place. Places of interest for the parking mode can change the estimated value of the function for the parking mode option so that if there is no parking service in some place, the corresponding function will lose relevance (and will receive a low estimated value of the functions).

FIG. 5 illustrates a method 400 for generating an estimated function value associated with a selectable option. The following information will be discussed on the example of the automatic parking option. First, at step 405, the current location of the vehicle can be determined. For this, a vehicle position sensor 340 may be used. At step 410, information obtained by the vehicle position sensor 340 can be transmitted directly to the third situational module 330. To determine the nearest stopping point where the vehicle has previously stopped, the third situational module 330 compares the current location with the previous stopping places stored in data store 335 For example, to determine the nearest stopping point (for example, based on the distance between the current location and the stopping place, which is stored in the data store 335), the third situational module 330 may combine the current vehicle position data transmitted by the vehicle position sensor 340, and data on previous stopping points transmitted by external storage 335 data.

At step 415, the third situational module 330 may transmit data about the nearest stopping point to the first situational module 320. The first situational module may read from the data store 335 information about the closest point of the previous stop. This information may include a counter value indicating the number of activations of a particular function in a particular location, such as an automatic parking function. In turn, this value can be used by the first situational module 320 to calculate the normalized frequency of use, as described above. For example, the first situational module 320 may also receive information from the external data storage 335 on the number of activation cycles of the selected option (or function) in a specific location. External data store 335 may contain information that the selectable automatic parking option was activated seven times at a supermarket located near the driver’s house. If the total number of visits to the nearest stop does not exceed a predetermined minimum value of visits (for example, N (i) _all ≤N _min ), then the situational variable indicating the actual frequency of use of the automatic parking function at that location will be generated in the mode of determining the actual value (at step 425). On the other hand, after reaching the minimum number of visits (for example, N (i) _all > N _min ), an intelligent situational variable characterizing the normalized frequency of using the function in a given place will be generated in real time. Depending on the value obtained with regard to signal amplification (Sig _reinforce (i, j)) and learning speed (α), the situational variable generated by the first situational module 320 may have a higher value (for example, close to 1) or a lower value. .

To calculate the distance between the current position and the previous stopping point, at step 435, the second situational module 325 can receive input data from the vehicle position sensor 340 and data about the closest stopping point from the third situational module 330. the greater the value of the intellectual situational variable. Then, at step 440, the vehicle speed sensor 345 detects the current vehicle speed. The simple situational variable provided by the speed sensor 345 is inversely proportional to the speed of the vehicle. For example, if the speed of a vehicle is 40 mph, the probability of stopping the vehicle (and hence the probability of using the automatic parking option) is small.

At step 445, the situational variables provided by the first situational module 320, the second situational module 325, and the vehicle speed sensor 345 can be transmitted to the processor 315. At 450, the processor 315 assigns the values to selectable options. As mentioned above, if the selectable options are divided into a group of arrival functions and a group of departure functions, then situational variables can be used as input only for selectable options for a group of arrival functions. They can be defined as functions used after some time and moving some distance after the driver activates the ignition in the vehicle. To obtain the estimated value of the function (step 455), the variables can be combined. The heuristic algorithm applied when combining values can be implemented in various ways, including, but not limited to, multiplication, averaging, determining the minimum value or determining the maximum value. To obtain an estimated function value for the selected options, at step 455, the processor 315 can multiply the output variable values of the first situational module 320, the second situational module 325, and the vehicle speed sensor 345.

At step 460, the processor 315 may select an automatic parking option if the estimated value of the function exceeds the values for other available selectable options. At step 465, the processor 315 may increase the priority of the function mapping on the user interface 305. At the same time, the processor may stop displaying on the user interface 305 a function that is no longer relevant under these conditions.

FIG. 6 shows a method 500 of generating a selectable option for the parking mode and increasing the priority of displaying this option on the user interface 305. At step 505, the vehicle position sensor 340 may determine the current position of the vehicle. To determine the relative position based on the current location of the vehicle, at step 510, information about previous stopping points and points of interest for the valet mode can be obtained from external data storage 335. The external data store 335 may transmit location data to the third situational module 330. To determine the nearest stopping point where valet services are provided, at step 515 the third situational module 330 may combine the position data received by the external data store 335 with the location vehicle from vehicle position sensor 340. As mentioned above, places of interest for the valet mode can be obtained directly from external data storage 335 or can be determined based on the analysis of place names (for example, a restaurant, cinema, conference room).

At step 520, data on the nearest stopping point may be transmitted to the first situational module 320 to determine the normalized frequency of use of the parking mode in a particular place. For example, if the nearest stopping place is a restaurant located next to the driver’s office, this place will be used in the formula for the normalized frequency of use as an input value (i), and valet mode will be used as an input value (j). If the minimum number of visits before switching to real time did not exceed the total number of visits (for example, N (i) _all ≤N _min ), then at step 530 the actual frequency of use will be calculated. On the other hand, if the number of visits to location (i) has reached a predetermined minimum value, then at step 535 the frequency of use can be calculated using a recursive formula in real time. Regardless of the formula used, the first situational module 320 will produce an intelligent situational variable for the normalized number of activation cycles of the parking mode function. If the normalized number of cycles for using the selectable option for the parking mode is high, then the probability of activating the function will also be high, respectively, a high value will be assigned to an intelligent situational variable.

To determine the distance to the nearest place of the previous stop, at step 545, the second situational module 325 can receive data about the vehicle’s location from the vehicle position sensor 340 and data about the nearest place of the previous stop from the third situational module 330. If the distance to the nearest place of the previous stop is valet service is small, the probability of selecting the function of the valet mode will be high (as well as the value of intellectual situational variable). In addition, at step 545, the vehicle speed sensor 345 detects the vehicle speed. With a low speed of the vehicle, the probability of stopping the vehicle in the near future will be high.

At step 550, the processor 315 receives the values of the vehicle speed, the normalized frequency of use, and the distance to the nearest place. At step 555, the processor 315 may assign the appropriate values to the available selectable options. Processor 315 may then generate an estimated function value for each selectable option based on the combination of the values received in step 555. The processor 315 may additionally assign priorities to selectable options whose values exceed the minimum threshold value. The selectable option with the highest estimated value can be assigned the highest priority, and the selectable option with the second largest estimated value can be assigned the second largest priority, etc. If the estimated value for the parking mode option is the highest, then it will receive the highest priority, after which the processor 315 can select the parking mode option (at step 565) and display it on the user interface 305 (at step 570). In the alternative, the processor 315 may select multiple selectable options that have first, second priority, etc. and display them on the user interface 305. The processor 315 can also remove a selectable option with a low estimated value under the current driving situation to ensure that the option with the highest estimated value can be displayed on the user interface 315.

FIG. 8 and 9, the estimated value of the function corresponding to the selectable options for different stopping places (for example, automatic parking or valet mode) can be based on at least three “if, then” rules. If the value of the normalized frequency of using the automatic parking option or valet mode issued by the first situational module 320 is high, then the probability (as well as the value of the output situational variable) of using the corresponding option can also be high. FIG. 8 shows the dependence of the estimated values for functions on the distance between the current location of the vehicle and a specific place. FIG. 8 shows that at a short distance (for example, less than 500 meters) to a certain place (represented as the output value of the second situational module 325), the probability of stopping the vehicle will be high. FIG. 9 shows the dependence of the estimated values of the function on the vehicle speed. FIG. 9 shows that at low vehicle speeds (represented as the output value of the vehicle speed sensor 345) the probability of stopping the vehicle will be high. To determine the estimated value of the function, the processor 315 performs a combination of these values. Thus, a high estimated value depends on all three specified values.

In accordance with one example, if the distance to the nearest place of the previous stop is small, and the normalized frequency of using the function is high, but the vehicle speed is 45 mph, then the probability of stopping the vehicle will be very small. Consequently, the estimated value of the function will be low, for example, for the automatic parking function or the parking mode, as a result of which the user interface will not display these options. Similarly, if the distance from the vehicle to the previous stop is small and the driving speed is low, but the specific function has never been activated in this place, then the normalized frequency of use will be low, as is the probability of activation of this function (for example, the estimated value functions).

FIG. 10 shows an example of a scheme for generating an estimated value of a parking function. The diagram is exemplary and is intended to illustrate how end location 810, previous stop places 815 and parking spot 820, determined based on external data, can be used when analyzing the use of the parking function in interface system 100. The entered locations 810 can be entered by the user using the navigation system.

The previous stop location 815 may be the location in which this parking function is normally used. For example, when visiting a bank, a driver can usually choose to perform parallel parking using an automatic parking system. Each time a function is used at a specific location, the value of the usage cycle counter for that location can be increased and stored as data on the final location in the data store 130. In addition, if a certain function is not selected in a specific place, the value of the usage cycle counter may decrease. A usage cycle counter can be mapped to a specific end location, for example, an address. However, it can be mapped to any geographic location (for example, with certain geographic coordinates). In other words, the previous stop location 815 may be mapped to an end location address (for example, a bank address) and / or the previous stop location may be a geographical parking location (for example, the geographical coordinates of a parking space in front of the bank). To increase / decrease the value of the cycle usage counter, a low-pass filter can be used. For example, the frequency vector may be a list of places frequented by the driver. When a driver sees a certain place, the value in the frequency vector associated with that place will be increased by a low-pass filter by the amplifying signal (equal to one), while the remaining values in the vector will be reduced by the corresponding values of the amplification signals (equal to zero). In accordance with this example, because the amplification signals can be 1 or 0, the content of the frequency vector will vary between 0 and 1, indicating the preferred destinations for the driver. In addition, the value of the usage cycle counter may be stored outside the data storage 130. Thus, the end location may be a predicted location based on previous user / vehicle behavior.

As mentioned above, a parking space 820, determined on the basis of external data, may be a parking space (for example, an organized parking lot or a parking space) located near a certain place (for example, a stadium, a restaurant, etc.). This information may be obtained from data storage 130 or from external sources such as a map or public database. In addition, the situational module 120, 125 can identify and identify several entered places 810, places 815 of previous stops and parking places 820 determined based on external data. Before storing a certain place, the driver may be asked to confirm the saving of data about this place. In other words, before the place becomes the preferred or memorized place, the driver will have to enter the appropriate confirmation. Similarly, a driver can delete a location and data about it. Thus, the driver can delete locations that are no longer interesting to him.

When a vehicle is traveling along a route, a current location (i.e., a situational variable), determined, for example, by a situational module 120, 125 using a GPS system, may be periodically or as required compared with one or all of the predicted end locations. end locations and the current location can be determined using situational module 120. After calculating the distance, the nearest location can be selected as the final location from the predicted end locations (for example, from the entered location 210, the previous parking location 815 and the parking location 820 determined based on external data). In some configurations, the entered default location may be the final location, and the situational module 120, 125 may not calculate the distance between the current location and the final location. However, in some configurations, when the end location is separately entered by the user into the navigation system, a parking space or site may be a more suitable end location and, therefore, the distance can be calculated to determine the final location. In accordance with one example, when a vehicle approaches a restaurant whose address could have been previously entered by the user, the vehicle can drive to the parking space at the restaurant. In this case, a parking space can be used as the final location, not the address of the restaurant.

As mentioned above, if there are several predicted end locations, the location data can be combined and compared with each other, which will determine which of them is the closest to the current location. After selecting the final location, the situational module 120, 125 may receive a simple situational variable from standard sensors 135, 140, for example, the vehicle speed. The processor 115 may assign an estimated value for the current driving situation based on the vehicle speed, the distance between the current location and the selected location, and then may increase the value of the usage cycle counter corresponding to the selected location. For example, if the vehicle is traveling at a low speed near the location where the vehicle is usually parked, a high estimated value may be assigned to the parking function, after which it will appear on the interface 105 as an option. On the other hand, if the vehicle is moving at a low speed, but there is no final location or previous parking spot, then the estimated value of the function may be low.

FIG. Figures 11–13 present examples of data graphs that show the situational variables used by the interface system when generating estimated function values. FIG. 11 shows an example of a plot of location data. The plot of the location data may contain the values of latitude and longitude, the route of the vehicle, indicated by a solid line. In addition, different end locations may be indicated by circles. FIG. 12 the graph shows the dependence of the speed of the vehicle on time. Knowing the distance between the current location of the vehicle and the specified final location and the given vehicle speed, the controller 110 can determine the estimated value of the function corresponding to the current driving situation. FIG. 12 shows an example of estimated function values. At a time corresponding to approximately 50 seconds, the estimated value of the function is approximately 0.9. At a time of approximately 450 seconds, the estimated value of the function is approximately 0.85. These high estimated values correspond to the small distance between the current location of the vehicle and the known final location, as well as a very low vehicle speed. On the other hand, between time points corresponding to 50 seconds and 450 seconds, the estimated value of the function may be low, because, regardless of the vehicle speed, it does not come close to or be near the final locations. Moreover, between time points corresponding to approximately 550 seconds and 675 seconds, the estimated value of the function may increase to a level of 0.35. In this case, the speed of the vehicle may decrease, but the distance from the current location of the vehicle to any known final location will be large enough.

FIG. 14 is a block diagram of a method 400 used by an interface system. Method 1000 can begin with step 1005, in which the operation of user interface system 100 can be activated automatically no later than the vehicle ignition is turned on. At this moment, the vehicle can perform an internal check of the system, in which the state of readiness of one or several systems and (or) vehicle subsystems is determined, which will make sure that the vehicle is ready for operation. After passing through an internal system check, system 100 may also determine the current location of the vehicle. After activating the system, the method may return to step 1010.

At step 1010, the situational module 120, 125 may receive position information (i.e., a simple situational variable) from one of the situational modules 120, 125. As mentioned above, the position information may include one or more predicted end locations. These end locations may be determined based on user input (for example, an address entered into the navigation system) or predicted based on previous user / vehicle behavior. After predicting the end locations, the received location information may include a list of predicted end locations. For example, an end location may include several previously used parking spaces that situational module 120, 125 may add to location information based on the route a vehicle is traveling. After obtaining the location information, method 400 may return to step 1015.

At step 1015, the situational module 120, 125 may determine an end location (i.e., an intelligent situational variable) based on the predicted end locations. Depending on the configuration, the processor 115 may determine the end location based on a predetermined hierarchy, for example, always select the location entered by the user rather than the predicted location, and may also combine the predicted end locations and select a possible location located at a minimum distance from the current location facilities. In the latter configuration, the processor 115 must obtain information about the current location of the vehicle from the standard sensor 135, 140. One of the situational modules 120, 125 in the processor 115 may determine the distance between the current location and each predicted final location. Based on the distance data, the location that is closest to the current location can be selected as the final location. As mentioned above, this analysis may not be necessary when the user enters the final location using the navigation system on the interface 105. After determining the final location, method 1000 proceeds to step 1020.

At step 1020, the situational module 120, 125 may receive data on the final location, including a usage cycle counter (i.e., an intelligent situational variable) for the final location. This data can be read from data storage 130 or other external source. The usage cycle counter may contain information on the number of cycles to use a certain function at a specific target location. Method 1000 proceeds to step 1025.

At step 1025, the situational module 120, 125 may receive data about the current vehicle speed (i.e., a simple situational variable) from the standard sensor 135, 140. The situational modules 120, 125 may receive the value of the speed of movement and output it to the processor 115. Method 1000 may proceed to step 1030.

At step 1030, situational variables, including the final position and speed of the vehicle, can be transferred to the processor 115, which will generate an estimate of the function. The processor 115 may combine the received situational variables and compare these values with a specific function (s). Estimated values of the function can be generated by combining situational variables by multiplying them, averaging, determining the maximum value and / or determining the minimum value, or any combination of them, as well as using other non-linear algorithms, such as fuzzy logic or neural networks. The estimated value of the functions may be directly proportional to the relevance of combining the situational variables passed to the processor 115. For example, if the vehicle is near the final location where the automatic parking system is usually used, then the estimated value of the function for the selectable option corresponding to the automatic parking function will be greater than if the vehicle was far from the final location and was moving at high speed. Method 1000 proceeds to step 1045.

At step 1045, the processor 115 may determine the priority of the selectable options based on their estimated function values. In the general case, the selectable options with the highest estimated value may have the highest priority, while the remaining available selectable options will be evaluated accordingly for this value. Depending on the user's preferences, at step 1040, the function with the highest estimated value or several functions (for example, the three functions with the highest estimated values) may receive a higher priority for display on the interface 105. Similarly, if the displayed functions decrease on the user interface 105, driving conditions, they can be hidden (or deleted). Alternatively or additionally, the processor 115 or the controller 110 may order the selectable options according to the estimated values for the functions corresponding to each selectable option. Then, the controller 110 can determine the order of selectable options, the estimated values of which are above a predetermined threshold value. For example, controller 110 may select only options with an estimated value equal to or greater than 0.7. Then, the controller 110 can set the available selectable options with the highest estimated value to the first place, and other selectable options to the relatively lower estimated value to the second place, etc.

In accordance with one example, when a high probability that the user is about to park a vehicle is detected, the display priority of the parking function can be increased and it can be displayed on the interface 105. This solution can be partially based on the approach to the final location, the frequency with which the function was used in the final location earlier, and the current vehicle speed. As mentioned above, the parking function may include an automatic parking function that can be used for parallel parking of a vehicle. The parking function may also include a conventional parking system / function, in which the image from the rear view cameras will be transmitted to the interface 105 or another screen that the user is looking at, which makes parking the vehicle easier. The automatic parking function and the normal parking function can be analyzed and can be estimated independently of each other. As a result, one selectable option corresponding to one of the parking functions will be displayed on the interface 105, and the other will not. However, under certain driving conditions, both selectable options may be displayed.

At steps 1010-1030, this cycle may be performed continuously as long as the vehicle continues to operate. The standard sensors 135, 140 and situational modules 120, 125 continuously operate by transmitting information to the processor 115, which continuously generates new estimated values of a function corresponding to the available selectable options (for example, values corresponding to parking functions) so that the corresponding functions are available. and displayed on the interface 105.

Accordingly, this document describes the interface system, which allows to determine the probability that the vehicle function will be selected by the driver, and display this function on the interface. Analysis of selected functions in terms of current conditions allows the interface to take into account the individual characteristics of the user, as well as to increase the frequency of use of various functions by displaying the selected functions at the right time. In addition, the system allows you to increase the level of driving safety and less distracting the driver.

Computing devices include computer-readable instructions, and these instructions can be executed by one or more computing devices, for example, the computing devices listed above. Machine-readable instructions can be compiled or translated from computer programs created using various languages and / or programming technologies, including, but not limited to, Java, C, C ++, Visual Basic, Java Script, Perl, etc. . or combinations thereof. In the general case, a processor (for example, a microprocessor) receives instructions, for example, from a storage device or computer-readable media, etc., and executes these instructions, thereby implementing one or more processes, which include one or more processes from the present description . Such instructions and other data may be stored and transmitted using various computer-readable media.

Machine-readable media (this also includes media readable by the processor) can be any non-volatile media (for example, physical media) that provides data (for example, instructions) that can be processed by a computer (for example, a computer processor). Such a medium can take many forms, including, but not limited to, permanent and operational storage devices. Permanent storage devices can be, for example, optical or magnetic disks, as well as other types of non-volatile media. Random access memory devices can be, for example, dynamic random access memory (DRAM), which are usually part of the main storage device. Such instructions may be transmitted using one or more data transmission means, for example, using coaxial cables, copper cables and fiber optic cables, including wires that are part of the system bus connected to the computer's processor. The standard forms of computer-readable media are floppy disk, hard disk, magnetic tape, any other kind of magnetic media, CD-ROM, DVD, any other optical media, punched tape, paper tape, any other physical media with holes, RAM, PROM, EPROM, FLASH-EEPROM, other chips or memory cards, as well as any other media your computer can work with.

Databases, archives, or other data warehouses described may include various mechanisms for storing, accessing, and reading various data, such as hierarchical databases, file system file sets, application databases in the appropriate format, relational database management systems (RDBMS ) etc. Each such data storage is usually embedded in a computing device with an operating system, for example, in one of the above systems, and is accessed via the network using one or more of any of the existing methods. Access to the file system can be made from the operating system, and such a system can support various file formats. RDBMS typically uses a structured query language (SQL) along with a language for creating, storing, editing, and executing stored procedures, such as PL / SQL.

In some embodiments of the invention, elements of the system may be computer-readable instructions (for example, software) on one or more computer devices (for example, servers, personal computers, etc.) and may be stored on appropriate computer-readable media (for example, disks that store devices, etc.). A computer program may consist of such instructions stored on a machine-readable medium for performing the described functions.

As regards the processes, systems, methods, heuristic algorithms, etc. described in this document, it should be understood that, despite the designated sequence of steps, such processes can be performed using a different sequence of these steps. You should also understand that some steps can be performed simultaneously, and some steps can be added or excluded. In other words, process descriptions are presented only as an example of embodiments of the invention and cannot be considered as limiting the claims.

Thus, it should be understood that the description given above is for clarity and not limitation. Many embodiments and methods of use other than the above examples will become apparent after reading the above description. The scope of the invention should not be determined on the basis of the above description, but on the basis of the appended claims, along with all equivalents specified in this claims. We can assume and expect the future development of the technologies mentioned in this description of the invention, as well as the fact that the disclosed systems and methods will be included in such future embodiments of the invention. Thus, it should be understood that the application of the invention can be changed and adjusted.

All terms used in the claims should be understood in their broadest reasonable interpretations and their usual meanings, as understood by those skilled in the art referred to in this specification, unless explicitly stated otherwise herein. In particular, the words "first", "second", etc. can be interchangeable.

Claims (15)

1. A vehicle interface system that includes: an interface adapted to display icons representing selectable vehicle functions, and a controller programmed to generate an estimate value for each of the functions based on a situational variable including the vehicle position and / or vehicle speed and / or the predicted final vehicle position, and display some of the icons representing the vehicle functions, the probability of using which is greatest, and hiding other icons denoting the functions of the vehicle, the probability of using which is minimal if zero, generated on the basis of the estimated values, moreover, at least one situational variable includes data on the final location, including a usage cycle counter indicating the number of previous uses of the vehicle function, and wherein the controller is additionally programmed to generate an estimated

function value based on the value of the icon cycle usage counter. 2. The system of claim 1, wherein the controller is further programmed to generate an estimated value based on the distance between the vehicle location and the predicted end position. H. The system of claim 2, wherein the estimated value increases as the distance decreases. 4. The system of claim 1, wherein the estimated value increases as the vehicle speed decreases. 5. The system of claim 1, in which the predicted end position is set by the user, is determined based on the previous driving style, or is determined based on the parking position data. 6. Vehicle controller, which includes: at least one situational module, configured to generate at least one situational variable characterizing a driving situation, including the position or speed of the vehicle, and a processor programmed to generate an estimate of a function based on the vehicle’s location and / or vehicle speed determined using at least one situational variable, the estimated value of a function characterizing the likelihood that this vehicle function will be selected using icons corresponding to the function the vehicle, based on the driving situation, and display some of the icons representing the vehicle’s functions, probably the use of which is greatest, and hide other icons indicating the functions of the vehicle, the probability of using which is minimal or equal to zero, based on the estimated values of the function, moreover, at least one situational variable includes data on the final location, including a usage cycle counter indicating the number of previous uses of the vehicle function, the processor being additionally programmed to generate an estimated

function value based on the value of the icon cycle usage counter. 7. The controller according to claim 6, wherein the at least one situational variable includes an end location, wherein the processor is configured to generate an estimate value of the function based, at least in part, on the distance between the vehicle location and the end position. 8. The controller according to claim 7, in which the final location is specified by the user, is determined based on the previous driving manner or is determined based on the parking location data. 9. The controller according to claim 6, wherein the at least one situational variable includes the vehicle speed value, the processor is further programmed to generate an estimated function value based on the vehicle speed value.

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