Method, computer readable medium, system and vehicle for providing an active recommendation message for a driver of a vehicle digital

Abstract

The invention relates to a method for providing an active recommendation message of a vehicle digital assistant to a vehicle driver, the method includes: receiving, by a server external to a vehicle, an operational interaction of a vehicle driver with a vehicle software application, an identifier of the vehicle driver, and a plurality of context information of the vehicle at a moment when a vehicle user interacts with the operational interaction of the vehicle software application; determining, by a server external to the vehicle, an operation frequency at which the driver operates the vehicle software application using the received operation interaction of the vehicle driver with the vehicle software application; determining a vehicle usage scenario from a predetermined set of usage scenarios through a server outside the vehicle according to the operation frequency of the vehicle user operating the software application and the various situation information of the vehicle; and providing an active recommendation message of the digital assistant to the vehicle driver by means of the vehicle digital assistant according to the vehicle usage scenario determined by the server external to the vehicle.

Description

Technical Field

[0001] The present invention relates to a method for providing proactive recommendation messages of a vehicle digital assistant to a vehicle driver. The present invention also relates to a computer-readable medium for providing proactive recommendation messages of a vehicle digital assistant to a vehicle driver, a system for providing proactive recommendation messages of a vehicle digital assistant to a vehicle driver, and a vehicle including a system for providing proactive recommendation messages of a vehicle digital assistant to a vehicle driver. Background Art

[0002] Digital assistants capable of executing the instructions of vehicle users are known in vehicles. For this purpose, the vehicle user can activate the digital assistant and then issue an instruction for executing a function or ask a question to the digital assistant. The digital assistant can execute the corresponding function and provide a reply to the vehicle user. Generally, there is no setting and it is not possible to actively provide messages through the vehicle digital assistant so as not to distract the vehicle driver from the driving task and / or unnecessarily disturb or interrupt the vehicle user. Summary of the Invention

[0003] Therefore, the task of the present invention is to effectively provide proactive recommendation messages of the vehicle digital assistant to the vehicle user. In particular, the task of the present invention is to accurately provide proactive recommendation messages of the digital assistant to the vehicle driver without distracting the vehicle driver.

[0004] This task is solved by the features of the independent claims. Advantageous designs and further developments of the present invention are derived from the dependent claims.

[0005] According to a first aspect, the present invention is characterized by a method for providing proactive recommendation messages of a vehicle digital assistant to a vehicle driver. The method can be a computer-implemented method and / or a controller-implemented method. The proactive recommendation message can be a proactive conversation message of the vehicle digital assistant, and the proactive conversation message can include a recommendation to the vehicle driver that matches the vehicle usage scenario. The vehicle digital assistant can be a cloud-based digital assistant. The digital assistant can be controlled via different operation modes, such as voice-based, touch-based, and / or gesture-based control. The vehicle can be a motor vehicle or a motorcycle.

[0006] The method includes: receiving, by a server external to the vehicle, an operation interaction between a vehicle driver and a vehicle software application, an identifier of the vehicle driver, and a plurality of context information of the vehicle at the moment of the operation interaction between the vehicle user and the vehicle software application. The method further includes: determining, by the server external to the vehicle, an operation frequency of the driver operating the vehicle software application in the case of using the received operation interaction between the vehicle driver and the vehicle software application, and determining, by the server external to the vehicle, a vehicle usage scenario from a predetermined set of usage scenarios based on the operation frequency of the vehicle user operating the software application and the plurality of context information of the vehicle. The method further includes: providing, by means of a vehicle digital assistant, a proactive recommendation message of the digital assistant to the vehicle driver according to the vehicle usage scenario determined by the server external to the vehicle.

[0007] Advantageously, the method can effectively and automatically provide a proactive recommendation message matching the determined usage scenario. Therefore, the vehicle digital assistant can provide a more accurate recommendation according to the situation for the driver based on the vehicle usage scenario. The vehicle driver is less distracted from the driving task by this method. In addition, the vehicle matches the following usage scenario, in which a matching proactive recommendation message is provided by the digital assistant. Therefore, the manual configuration and / or explicit invocation of the software application of the vehicle and / or the functions of the software application can be reduced. In addition, the driver can learn unknown functions and unknown software applications of the vehicle in the corresponding usage scenario, and thus correctly learn the operation of the functions and / or software applications of the vehicle according to the situation.

[0008] According to an advantageous design, the method may further include: determining, by a server external to the vehicle, lifecycle information based on the identifier of the vehicle driver and the identifier of the vehicle, the lifecycle information preferably representing the frequency and / or duration of the vehicle used by the vehicle driver, and determining, by the server external to the vehicle, a vehicle usage scenario from a predetermined set of usage scenarios based on the operation frequency of the vehicle user operating the software application, the plurality of context information of the vehicle, and the lifecycle information. For example, the lifecycle information may include the number of times the vehicle driver travels using the vehicle. For example, the lifecycle information may include time information, which represents the duration that the vehicle driver owns and / or drives the vehicle as the vehicle owner. In other words, the lifecycle information may represent a macro situation describing the relationship between the driver and the vehicle. Thus, the usage scenario can be effectively determined according to the lifecycle information between the driver and the vehicle in a personalized manner.

[0009] According to another advantageous design, one of the multiple pieces of context information may represent a situation in the interior space of the vehicle, and the context information representing the situation in the interior space of the vehicle may preferably include the occupancy of the vehicle seats, information about the emotional state of the vehicle driver, and / or time information and / or distance information to the driving destination. Thereby, the vehicle usage scenario can be determined more effectively and thus the proactive recommendation message of the vehicle digital assistant can be determined.

[0010] According to another advantageous design, one of the multiple pieces of context information may represent the vehicle state, and the context information representing the vehicle state may preferably include the state of charge of the vehicle, the fuel tank state, the driving state, and / or the parking state. Thereby, the vehicle usage scenario can be determined more effectively and thus the proactive recommendation message of the vehicle digital assistant can be determined.

[0011] According to another advantageous design, one of the multiple pieces of context information may represent weather information in the vehicle's immediate surroundings. Thereby, the vehicle usage scenario can be determined more effectively and thus the proactive recommendation message of the vehicle digital assistant can be determined.

[0012] According to another advantageous design, one of the predetermined multiple usage scenarios may include one or more recommendations for one or more vehicle software applications. Thereby, multiple recommendations for the usage scenario can be provided to the vehicle driver more effectively and accurately.

[0013] According to another advantageous design, the recommendation for the vehicle software application in one of the predetermined multiple usage scenarios may represent the operation frequency of the software application by the users of the vehicle manufacturer's vehicle fleet, especially the drivers. Thereby, the recommendation for the usage scenario can be determined effectively.

[0014] According to another advantageous design, the determined vehicle usage scenario may be associated with a confidence interval that indicates how reliably the usage scenario is determined based on the operation frequency of the vehicle user operating the software application and the multiple pieces of context information of the vehicle, and the proactive recommendation message of the digital assistant may be provided to the vehicle driver only when the lower limit of the confidence interval of the determined usage scenario exceeds a minimum confidence threshold. Thereby, the proactive recommendation message is provided to the vehicle driver with a higher accuracy.

[0015] According to another advantageous design, the proactive recommendation message may include one or more recommendations for one or more software applications for the determined usage scenario, and / or the proactive recommendation message may include the determined usage scenario and the confidence interval of the determined usage scenario. Thus, an explanation for why the recommendation is proactively provided to the vehicle driver can be effectively provided to the user. Therefore, the driver can more easily understand the reason for the recommendation message. The distraction of the driver from the driving task can be effectively reduced.

[0016] According to another aspect, the present invention features a computer-readable medium for providing a proactive recommendation message of a vehicle digital assistant to a vehicle driver, wherein the computer-readable medium includes instructions that, when executed on a computer, perform the above-described method.

[0017] According to another aspect, the present invention features a system for providing a proactive recommendation message of a vehicle digital assistant to a vehicle driver, wherein the system is configured to perform the above-described method.

[0018] According to a first aspect, the present invention features a vehicle including the above-described system for providing a proactive recommendation message of a vehicle digital assistant to a vehicle driver.

[0019] Further features of the present invention result from the claims, the drawings, and the description of the drawings. All the features and combinations of features mentioned above in the description and the features and combinations of features mentioned below in the description of the drawings and / or shown individually in the drawings can be used not only in the combinations given respectively, but also in other combinations or can be used individually. Description of the Drawings

[0020] Preferred embodiments of the present invention are described below with the aid of the drawings. Further details, preferred designs, and further expansions of the present invention result therefrom.

[0021] Figure 1 An exemplary method for providing a proactive recommendation message of a vehicle digital assistant to a vehicle driver is schematically shown in detail. Detailed Description of the Preferred Embodiments

[0022] Figure 1 An exemplary method 100 for providing a proactive recommendation message of a vehicle digital assistant to a vehicle driver is shown in detail. The proactive recommendation message may be a recommendation message proactively provided to the vehicle driver or other users of the vehicle by the vehicle digital assistant. The proactive recommendation message may include one or more recommendations. Preferably, the proactive recommendation message is a message visually provided on the display device of the vehicle by the vehicle digital assistant. Additionally or alternatively, the proactive recommendation message may be a voice message from the vehicle digital assistant to the driver or other users of the vehicle.

[0023] A vehicle digital assistant can be a cloud-based digital assistant of the vehicle. The cloud-based digital assistant can include a dialogue control application executed on a cloud-based server. In addition, the cloud-based digital assistant can use one or more output devices of the vehicle, such as one or more display devices and / or one or more speakers, to provide proactive recommendation messages preferably generated by the dialogue control application of the digital assistant to the vehicle driver.

[0024] The method can receive, via a server external to the vehicle, 102 the operation interaction between the vehicle driver and the vehicle software application, the identifier of the vehicle driver, and / or various context information of the vehicle at the moment of the operation interaction between the vehicle user and the vehicle software application. In addition, the method can receive the identifier of the vehicle, such as the vehicle identification number. The vehicle software application can be a vehicle APP. For example, the software application can be a navigation APP, an audio streaming APP, a phone APP, an instant messaging APP, or other APPs that can be executed on the vehicle's infotainment system. The various context information can represent the driving situation, the surrounding environment situation, and / or the vehicle state in which the vehicle is at the moment of the operation interaction. For example, one piece of context information among the various context information can represent the state of charge of the vehicle, the fuel tank state, the driving state, and / or the parking state. For example, the driving state can indicate that the driver is on his daily commute to work, on the way to regular leisure activities, on a hiking trip, or on a vacation trip. For example, one piece of context information among the various context information can represent the situation in the interior space of the vehicle. The context information representing the situation in the vehicle interior can include the occupancy of the vehicle seats, information about the emotional state of the vehicle driver, and / or the time information and / or distance information to the driving destination. In addition, one piece of context information among the various context information can represent the weather information in the immediate surrounding environment of the vehicle.

[0025] Method 100 can also determine 104, via a server external to the vehicle, the operation frequency of the driver operating the vehicle software application in the case of using the received operation interaction between the vehicle driver and the vehicle software application. The method can determine the operation frequency for each vehicle software application and for each vehicle driver. The vehicle driver can be identified, for example, using the received identifier of the vehicle driver.

[0026] Method 100 can determine 106 a vehicle usage scenario from a predetermined set of usage scenarios by a server external to the vehicle based on the operation frequency of the vehicle user's software applications and the multiple context information of the vehicle. The predetermined set of usage scenarios can include typical and known vehicle usage scenarios. Examples of usage scenarios in the predetermined set of usage scenarios of the vehicle can be: driving on a commute, driving on vacation, driving to a leisure activity, driving to shopping, driving for business, driving for personal affairs, charging, charging in sunny conditions, charging in rainy conditions, parking, parking in a public parking lot, and / or parking in a private parking lot. The predetermined set of usage scenarios can include a predetermined maximum number of the most common vehicle usage scenarios. For example, the predetermined set of usage scenarios can include the most common 10, 20, 30, 40, 50, 60... vehicle usage scenarios. Each usage scenario in the predetermined set of usage scenarios can include a set of vehicle software applications, in particular a set of vehicle APPs, which are most commonly used in that usage scenario. The set of software applications for a usage scenario can be determined based on the operation frequencies of the software applications of all or some of the drivers using the vehicle fleet. Preferably, the set of software applications for a usage scenario is determined based on the operation frequencies of the software applications of all the drivers of the fleet. The order of the software applications for a usage scenario can be determined based on the operation frequencies of the software applications of all or some of the drivers of the vehicle fleet. For example, the software application with the highest operation frequency can be in the first position in the set of software applications for that usage scenario, and the software application with the second highest operation frequency can be in the second position in the set of software applications for that usage scenario. The set of software applications can include the n software applications with the highest operation frequencies. For example, the set of software applications can include the three software applications with the highest operation frequencies respectively in that usage scenario.

[0027] If it is a software application in the set of software applications for a usage scenario, the vehicle digital assistant can add a recommendation for that software application to the proactive recommendation message. For example, the recommendation can include a dialogue for using that software application in that usage scenario. The digital assistant can add recommendations for all or some of the software applications in the set of software applications for that usage scenario to the proactive recommendation message. For example, the digital assistant can add a recommendation for a software application in the set of software applications for that usage scenario to the proactive recommendation message according to context information (such as weather information).

[0028] The method can determine lifecycle information by a server external to the vehicle based on the identifier of the vehicle driver and the identifier of the vehicle. The lifecycle information can represent the relationship between the driver and the vehicle. For example, the lifecycle information can represent the frequency and / or duration of vehicle use by the vehicle driver. If the vehicle driver uses the vehicle for the first time or drives the vehicle for the first time (e.g., the first 10 drives of the vehicle), this information can be used to determine the usage scenario. Specifically, the vehicle usage scenario can be determined from the predetermined set of usage scenarios by a server external to the vehicle based on the operation frequency of the vehicle user operation software application, the various context information of the vehicle, and the lifecycle information.

[0029] Method 100 can provide proactive recommendation messages of the digital assistant 108 to the vehicle driver by means of the vehicle digital assistant according to the vehicle usage scenario determined by a server external to the vehicle. The proactive recommendation messages can include the usage scenario and one or more recommendations for the usage scenario. If it is determined that the usage scenario includes estimating the usage scenario based on the context information, the proactive recommendation messages can additionally include the probability of determining the usage scenario.

[0030] Advantageously, the method can effectively estimate the vehicle situation through the context information of the vehicle. Therefore, the digital assistant can provide proactive recommendation messages that match the vehicle situation to the vehicle driver. Thereby, it is possible to effectively reduce and / or avoid the driver being distracted during the driving process. According to the usage scenario, the vehicle driver can obtain matching proactive recommendations for the vehicle software application. The server external to the vehicle only obtains the context information for the current situation of the vehicle. The data of the sensors does not need to be transmitted to the server external to the vehicle to determine the vehicle usage scenario and the recommendations for the usage scenario. Therefore, the recommendations for the software application regarding the usage scenario can be provided to the vehicle driver more accurately by the vehicle digital assistant.

[0031] List of reference numerals

[0032] Method 100

[0033] 102 Receive operation interaction

[0034] 104 Determine operation frequency

[0035] 106 Determine usage scenario

[0036] 108 Provide proactive recommendation messages

Claims

1. A method for providing proactive recommendation messages of a vehicle digital assistant to a vehicle driver, the method comprising: Receiving, by a server external to the vehicle, an operation interaction between the vehicle driver and a vehicle software application, an identifier of the vehicle driver, and a plurality of context information of the vehicle at the moment of the operation interaction between the vehicle user and the vehicle software application; Determining, by a server external to the vehicle, an operation frequency of the driver for the vehicle software application in the case of using the received operation interaction between the vehicle driver and the vehicle software application; Determining, by a server external to the vehicle, a vehicle usage scenario from a predetermined set of usage scenarios according to the operation frequency of the vehicle user for the software application and the plurality of context information of the vehicle; and Providing, by means of the vehicle digital assistant, a proactive recommendation message of the digital assistant to the vehicle driver according to the vehicle usage scenario determined by the server external to the vehicle.

2. The method according to claim 1, the method further comprising: Determining, by a server external to the vehicle, life cycle information according to the identifier of the vehicle driver and the identifier of the vehicle, the life cycle information preferably representing the frequency and / or duration of the vehicle being used by the vehicle driver, and wherein, the server external to the vehicle determines the vehicle usage scenario from a predetermined set of usage scenarios according to the operation frequency of the vehicle user for the software application, the plurality of context information of the vehicle, and the life cycle information.

3. The method according to any one of the preceding claims, wherein, One piece of context information among the plurality of context information represents a situation in the interior space of the vehicle; and wherein, the context information representing a situation in the interior space of the vehicle preferably includes the occupancy of the vehicle seat, information about the emotional state of the vehicle driver, and / or time information and / or distance information to the driving destination.

4. The method according to any one of the preceding claims, wherein, One piece of context information among the plurality of context information represents the vehicle state; and wherein, the context information representing the vehicle state preferably includes the state of charge of the vehicle, the fuel tank state, the driving state, and / or the parking state.

5. The method according to any one of the preceding claims, wherein, One piece of context information among the plurality of context information represents weather information in the vicinity of the vehicle.

6. The method according to any one of the preceding claims, wherein, One of the predetermined plurality of usage scenarios includes one or more recommendations for one or more vehicle software applications.

7. The method according to any one of the preceding claims, wherein, The recommendation for the vehicle software application in one of the predetermined plurality of usage scenarios represents the operation frequency of the users, especially the drivers, of the vehicle fleet of the vehicle manufacturer for the software application.

8. The method according to any one of the preceding claims, wherein, The determined vehicle usage scenario is associated with a confidence interval, wherein the confidence interval indicates how reliably the usage scenario is determined according to the operation frequency of the vehicle user for the software application and the plurality of context information of the vehicle; and wherein, the proactive recommendation message of the digital assistant is provided to the vehicle driver only when the lower limit of the confidence interval of the determined usage scenario exceeds a minimum confidence threshold.

9. The method according to any one of the preceding claims, wherein, The proactive recommendation message includes one or more recommendations for one or more software applications of the determined usage scenario, and / or wherein, the proactive recommendation message includes the determined usage scenario and the confidence interval of the determined usage scenario.

10. A computer-readable medium for providing proactive recommendation messages of a vehicle digital assistant to a vehicle driver, wherein, The computer-readable medium includes instructions that, when executed on a computer, perform the method according to any one of claims 1 to 10.

11. A system for providing proactive recommendation messages of a vehicle digital assistant to a vehicle driver, wherein, The system is configured to perform the method according to any one of claims 1 to 10.

12. A vehicle, comprising the system according to claim 11 for providing proactive recommendation messages of a vehicle digital assistant to a vehicle driver.

Images