WO2023036403A1

WO2023036403A1 - A method for providing an automatic logbook for a driver of a vehicle, a system, a vehicle, an electronic control device and a computer program product

Info

Publication number: WO2023036403A1
Application number: PCT/EP2021/074602
Authority: WO
Inventors: Markus-Julian CHUR; Sebastian Gehrling; Jan Pingel; Prathvirani TOLETY; Jan WELZBACHER; Adnan YURBAS
Original assignee: Volkswagen Aktiengesellschaft
Priority date: 2021-09-07
Filing date: 2021-09-07
Publication date: 2023-03-16
Also published as: EP4377922A1

Abstract

The invention relates to a method for providing an automatic logbook for a driver (D) of a vehicle (10), the method comprising: - identify the driver (D) of the vehicle (10), - determine at least one navigation information (I1, I2) for a driver trip (T) with the vehicle (10), - assign a characteristic (C1, C2) to the driver trip (T) for an identified driver identity (ID) according to the at least one navigation information (I1, I2) automatically by a machine learning system (MLS), wherein especially the at least one navigation information (I1, I2) is used as training data and/or input data for the machine learning system (MLS), - output the assigned characteristic (C1, C2) of the driver trip (T) by the machine learning system (MLS) to the driver (D) by a human machine interface (HMI), - obtain a verification (True, False) of the assigned characteristic (C1, C2) from the driver (D), especially in a non-contact way, preferably by a voice command, - especially use the verification (True, False) from the driver (D) for training and/or for adaptation of the machine learning system (MLS).

Description

A method for providing an automatic logbook for a driver of a vehicle, a system, a vehicle, an electronic control device and a computer program product

The invention is related to a method for providing an automatic logbook for a driver of a vehicle according to the independent method claim. Further, the invention is related to a corresponding system for a vehicle for providing an automatic logbook for a driver of a vehicle in the vehicle according to the independent system claim. Furthermore, the invention is related to a vehicle comprising a corresponding system according to the independent device claim. Moreover, the invention is related to an electronic control device according to the further independent device claim as well as to a computer program product according to the independent product claim.

Logbooks are basically known, especially for business uses. When drivers are required (e.g. by law and/or employer) to maintain a logbook for a vehicle, they nowadays have to manually provide information, whether a trip with this vehicle is related to a private or a business reason. The manual provision of travel information causes effort for the vehicle driver. Digital logbooks already exist.

The user may usually decide between three solutions:

• Manual logbook: write the logbook in the car by pen and official paper blog.

• Mobile phone app: track is recorded, the driver has to decide in the app if the trip is business or private, needs to export the report and hand it in to the tax authorities.

• n-car device: third party device has to be installed in the car, a user receives the logbook in digital format and needs to manually separate business and private trips and forward it to the tax office.

According to all available solutions, the user has to manually decide after the trip was done whether a business or private trip was done. For this activity, manual effort is still required (e.g. writing the record, calculating number of kilometers driven, checking the mobile phone app, separating private tracks from business trips, storing information in a fleet management system, send data to a tax consultant, the tax consultant checking the data, send the data to a tax authority, etc.).

The aim of the present invention is to provide a method for providing an automatic logbook for a driver of a vehicle, with preferable features, trustful results, especially acknowledged by authorized authorities, and convenient use, preferably in an easy, simple and intuitive way, with reduced effort for the vehicle driver. Also, the aim of the invention is to provide an improved system for a vehicle for providing an automatic logbook for a driver of a vehicle in the vehicle. Besides, the aim of the invention is to provide a vehicle comprising a corresponding system. Further, the aim of the invention is to provide an electronic control device and a computer program product for a corresponding method.

According to the first aspect, embodiments of the invention provide a method for providing an automatic logbook for a driver of a vehicle with the features of the independent method claim. According to the second aspect, embodiments of the invention provide a system for an automatic logbook for a driver of a vehicle in the vehicle with the features of the independent system claim. According to the third aspect, embodiments of the invention provide a vehicle comprising a corresponding system with the features of the independent device claim.

According to the fourth aspect, embodiments of the invention provide a corresponding electronic control device for a corresponding method with the features of the second independent device claim. According to the fifth aspect, embodiments of the invention provide a computer program product for a corresponding method with the features of the independent product claim. Details and features disclosed on individual aspects of the invention also apply to the other aspects of the invention and vice versa.

According to the first aspect, embodiments of the invention provide a method for an automatic logbook for a driver of a vehicle, the method comprising: identify the driver of the vehicle, in particular by an identification device, preferably installed in the vehicle, such as a device for face recognition, voice recognition, key recognition, code recognition and/or driving profile recognition, determine at least one navigation information for a driver trip with the vehicle, in particular by a navigation device, preferably installed in the vehicle, for example by starting a navigation to a destination point, wherein at least one navigation information may comprise a starting point, a destination point, navigation data, such as gps-data, of the trip, map data of the trip, and so on, assign a characteristic (for example a private trip or business trip) to the driver trip for an identified driver identity according to the at least one navigation information automatically by a machine learning system, especially comprising an artificial neural network, wherein especially the at least one navigation information is used (initially) as training data and/or (further) input data for the machine learning system, wherein in particular the machine learning system (and that is an artificial neural network) may be installed in a computing device of an electronic control device of the vehicle and/or in an external server contacted by the vehicle to provide computational services, output the assigned characteristic of the driver trip by the machine learning system to the driver by a human machine interface, preferably installed in the vehicle, such as a display device, for example head device of the vehicle, obtain a verification (True, False) of the assigned characteristic from the driver, in particular through an input device, preferably an audio device, like a microphone, of the vehicle, being for example a part of the human machine interface, especially in a non-contact way, preferably by a voice command, preferably use the verification (True, False) from the driver for training and/or for adaptation of the machine learning system.

The idea is to provide a (to be certified and/or approved and/or officially recognized) method and a system for a vehicle for detection of and separation between different trip types (e.g. business vs. private) of a particular user of the vehicle for the use of automatically provided logbooks for official purposes, for example tax declarations, without further efforts. Preferably, publicly available information (e.g. map data) and vehicle information (e.g. track records) may be used to distinguish the driver trips between business and private trips. The driver trips will be separated into “business” and “private”. The user only has to confirm via human machine interface if the “guess” of the machine learning system (that is of the artificial neural network) was right. The confirmed information may be provided to employers and/or tax authority automatically, for example every year, without any additional actions and/or calculations and/or registration actions required from the user.

Preferably, the method may use the track record of the vehicle and pair it with other information such as day time, trip duration, navigation details, driver identity, etc. and publicly available data such as map data. Advantageously, the method may use a self-optimizing machine learning clustering algorithm to decide if the driver trip was a business or private trip. Comfortably, the method may let the driver confirm or correct the “guess” of the learning algorithm to confirm or correct the data but also improve the learning algorithm. Preferably, the method may provide an entry to the logbook in accordance to the assigned characteristic of the driver trip.

Preferably, the method may provide several advantages for the driver, such as:

Only very little effort to maintain the logbook, No need to install a third party device, Not providing data to another third parties, Automatic transfer of data to employers and/or authorized and/or governmental authorities, such as tax authorities. Preferably, the method may provide several advantages for employers and/or authorized and/or governmental authorities, such as tax authorities:

T ransparent overview about the driver’s trips,

Reliable approach to separate between private and business trips, which is preferably safer than non-automated solutions due to susceptibility to error and potential driver’s negligence.

In some embodiments, a driver of a vehicle will be identified at least by one of the following technics: face recognition, voice recognition, user mobile device, especially smartphone, recognition, key recognition, code recognition, and/or driving profile.

Thus, variable technics may be provided for identifying the driver of the vehicle. Therefore, the method may be executed on different vehicles of various manufacturers having different equipment.

In some embodiments, the at least one navigation information for the driver trip contain at least one of the following data: a trip starting point, a trip destination point, available facilities at the destination point, a trip record, a trip starting time, a trip destination time, a trip duration, navigation details, and/or map data.

Thus, different parameters may be provided within the navigation information to provide improved and/or extended input data and/or learning data for the machine learning system. Therefore, the quality of the machine learning system may be enhanced. With the help of the improved learning network, reliable results may be provided by the detection of and separation between different trip types (e.g. business vs. private). In some embodiments, the at least one navigation information is used as training data and/or input data for the machine learning system, and thus for the artificial neural network of the machine learning system. Thus, a self-learning network may be provided, preferably learning by the use of the vehicle.

Preferably, the machine learning system may be configured as an adaptive and/or permanently learning system. Thus, reliable, correct and trustworthy logbooks may be provided by the method.

Preferably, the assigned characteristic of the driver trip may comprise: a business trip or a private trip.

However, further characteristics may be added if needed to expand the use cases of the method. For example, vacation use, service use and so on.

In some embodiments, the verification of the assigned characteristic will be executed in a noncontact way, preferably by a voice command. Thus, no manual actions need to be done by the driver. Thus, the convenience of the use of the method may be increased. Also, manual errors may be voided. Therefore, trustful logbooks may be provided. The verification of the assigned characteristic may be recorded by an input device of the vehicle, especially by the human machine interface, preferably an audio device of the human machine interface.

In some embodiments, the method comprises at least one of the following: recording of the driver trip, the assigned characteristic of the driver trip and/or the at least one navigation information as a logbook entry, especially in an non-transitory and/or non-volatile memory device of the vehicle and/or of an external server.

Thus, detailed logbooks may be provided in the vehicle and/or in the external server.

In some embodiments, the method comprises at least one of the following: transmitting the driver identity and corresponding logbook entries to an official authority and/or a trip detection system for official purposes.

Thus, additional official advantages may be provided to the driver.

In some embodiments, the method comprises at least one of the following: transmitting logbook entries to a trip detection system for commercial purposes.

Thus, additional commercial advantages, like personalized promotions and/or discounts, may be provided to the driver. In some embodiments, the method will be executed by an electronic control device of the vehicle, wherein especially some actions and/or calculations will be at least partly transferred to an external server for execution. Thus, the method may be executed in the vehicle without external devices of third parties.

According to the second aspect, embodiments of the invention provide a system for providing an automatic logbook for a driver of a vehicle, comprising: identification device for identifying the driver of the vehicle, navigation device for determining at least one navigation information for a driver trip with the vehicle, a computing device comprising a machine learning system (and that is an artificial neural network) for automatically assigning a characteristic to the driver trip according to an identified driver identity and the at least one navigation information, wherein especially the at least one navigation information is used as training data and/or input data for the machine learning system (and that is for the artificial neural network), a human machine interface, preferably installed in the vehicle, for outputting the assigned characteristic of the driver trip by the machine learning system to the driver, an input device, preferably an audio device, for obtaining a verification of the assigned characteristic from the driver, especially in a non-contact way, preferably by a voice command, wherein especially the computing device is configured to use the verification (True, False) from the driver for training and/or for adaptation of the machine learning system.

With such a system, the same advantages may be achieved as with the method described above. Full reference is made to these advantages in the present case.

Preferably, an non-transitory and/or non-volatile memory device may be provided for the storage of the driver trip, the assigned characteristic of the driver trip and/or the at least one navigation information as a logbook entry.

Embodiments of the invention provide, according to the third aspect, a vehicle comprising a corresponding system. With such a vehicle, the same advantages may be achieved as with the system described above. Full reference is made to these advantages in the present case.

According to the fourth aspect, embodiments of the invention provide an electronic control device comprising: a memory device, in which a program code is stored, and a computing device, wherein when carrying out the program code by the computing device, a method is performed as described above. With embodiments of such an inventive electronic control device, the same advantages may be achieved as with corresponding embodiments of the method described above. Full reference is made to these advantages in the present case.

According to the fourth aspect, the invention provides a computer program product comprising a program code for carrying out a method as described above. In other words, the computer program product comprises instructions which, when the program is executed by a computer, cause the computer to carry out embodiments of the method described above. With embodiments of such a computer program product, the same advantages may be achieved as with corresponding embodiments of the method described above. Full reference is made to these advantages in the present case.

Embodiments of the invention and its further developments as well as its advantages will be explained in more detail below using figures. The figures show schematically:

Fig. 1 a schematic design of possible use cases of a system within the meaning of the invention,

Fig. 2 a schematic design of a possible machine learning system within the meaning of the invention, and

Fig. 3 a schematic design of a system within the meaning of the invention.

Fig. 1 and Fig. 2 serve as an explanation of a method and a system 100 for providing an automatic logbook for a driver D of a vehicle 10.

As Fig. 1 and Fig. 2 show, the method comprises: 201 identify the driver D of the vehicle 10.

Action 201 may be executed by an identification device 101 , preferably installed in the vehicle 10. As a technic for driver recognition may be used: ID1 : face recognition, ID2: voice recognition,

ID3: key/code/device recognition, and/or

ID4: driving profile recognition, etc.

For this aim, vehicle devices may be used, such as cameras, microphones, ID-devices, evaluation systems, preferably using machine learning technics for the recognition.

As Fig. 1 and Fig. 2 show, the method comprises: 202 determine at least one navigation information 11 , I2 for a driver trip T with the vehicle 10.

Action 202 may be executed by a navigation device 102, preferably installed in the vehicle 10, for example by starting a navigation to a destination point. This action may be executed with the help of an external map data provider 21 . An external map data provider 21 may for example supply mad data MAP to the navigation device 102 of the vehicle 10, directly or over the external server 20.

As Fig. 2 shows, the at least one navigation information 11 , I2 may comprise: a trip starting point A, a trip destination point B, available facilities F at the destination point B, a trip record REC, for example in the form of the function of GPS coordinates depending on the time t, a trip starting time t1 , a trip destination time t2, a trip duration dt, navigation details NAVI, map data MAP, and so on.

As Fig. 2 shows, the method comprises:

203 assign a characteristic C1 , C2 (for example a private trip C2 or business trip C1 ) to the driver trip T for an identified driver identity ID according to the at least one navigation information 11 , I2 automatically by a machine learning system MLS, especially comprising an artificial neural network ANN.

Initially, the at least one navigation information 11 , I2 may be used as training data for the artificial neural network ANN of the machine learning system MLS. Furthermore, the at least one navigation information 11 , I2 may be used as input data for the artificial neural network ANN.

The machine learning system MLS, especially comprising the artificial neural network ANN, may be installed in a computing device cu of an electronic control device of the vehicle 10 and/or in an external server 20 which may be contacted by the vehicle 10 to provide computational services.

As Fig. 2 shows, the method comprises the following:

204 output the assigned characteristic C1 , C2 of the driver trip T by the machine learning system MLS to the driver D by a human machine interface HML The human machine interface HMI may be installed in the vehicle 10. The human machine interface HMI may be designed in the form of a display device, for example in a head device of the vehicle 10.

As Fig. 2 shows, the method comprises the following:

205 obtain a verification True, False of the assigned characteristic C1 , C2 from the driver D.

As Fig. 2 schematically shows, the verification True, False of the assigned characteristic C1 , C2 may be obtained through an input device of the vehicle 10, especially through the human machine interface HMI, preferably an audio device au of the human machine interface HMI.

For improved user convenience, action 205 may be executed especially in a non-contact way, preferably by a voice command.

As Fig. 2 shows, the method may comprise the following:

206 use the verification True, False from the driver D for training and/or for adaptation of the machine learning system MLS.

Thus, the invention provides a reliable method (which may be certified and/or officially authorized by governmental authorities) and a system 100 for a vehicle 10 for detection of and separation between different types of trips of a particular user of the vehicle 10 for the use of automatically provided logbooks, especially for official purposes, for example tax declarations, without any further efforts. An artificial neural network ANN is used to distinguish the driver trips T between business trips C1 and private trips C2. Thus, the driver trips T may be automatically separated into “business” and “private”. The driver D only has to confirm via a human machine interface if the “guess” of the artificial neural network ANN was right. The confirmed information is used to provide a logbook entry which may be provided to employers and/or a tax authority automatically, for example every year, without any additional actions and/or calculations and/or registration actions required from the user.

Further, the method may comprise at least one of the following:

207 recording of the driver trip T, the assigned characteristic C1 , C2 of the driver trip T and/or the at least one navigation information 11 , I2 as a logbook entry, especially in a non- transitory and/or non-volatile memory device mu.

Furthermore, the method may comprise at least one of the following: 208 transmitting the driver identity ID and corresponding logbook entries to an official authority T 1 and/or a trip detection system T2 for official purposes, preferably over a secure connection.

Moreover, the method may comprise at least one of the following:

209 transmitting logbook entries to a trip detection system T3 for commercial purposes, preferably anonymously.

In an optional action 210, additional commercial advantages, like personalized promotions and/or discounts, may be provided to the driver D by the trip detection system T3 for commercial purposes.

As Fig. 3 indicates, the method may be executed by an electronic control device ECU of the vehicle 10.

However, some actions and/or calculations may be at least partly transferred to an external server 20 for execution. For example, the machine learning system MLS, especially comprising the artificial neural network ANN, may be installed in the external server 20.

A corresponding system 100 for providing an automatic logbook for a driver D of a vehicle 10 within the meaning of the invention is schematically shown in Fig. 3, comprising: identification device 101 for identifying the driver D of the vehicle 10, navigation device 102 for determining at least one navigation information 11 , I2 for a driver trip T with the vehicle 10, a computing device cu comprising a machine learning system MLS (and that is an artificial neural network ANN) for automatically assigning a characteristic C1 , C2 to the driver trip T according to an identified driver identity ID and the at least one navigation information 11 , I2, wherein especially the at least one navigation information 11 , I2 is used as training data and/or input data for the machine learning system MLS (and that is for artificial neural network ANN), a human machine interface HMI, preferably installed in the vehicle 10, for outputting the assigned characteristic C1 , C2 of the driver trip T by the machine learning system MLS to the driver D, an input device, preferably an audio device au, for obtaining a verification True, False of the assigned characteristic C1 , C2 from the driver D, especially in a non-contact way, preferably by a voice command, wherein especially the computing device cu is configured to use the verification True, False from the driver for training and/or for adaptation of the machine learning system MLS (and that is of the artificial neural network ANN).

Furthermore, a non-transitory and/or non-volatile memory device mu may be provided within the system 100 for the storage of the driver trip T, the assigned characteristic C1 , C2 of the driver trip T and/or the at least one navigation information 11 , I2 as a logbook entry.

As Fig. 3 indicates, the elements of the system 100 may be preferably installed in the vehicle 10.

However, parts of the computing device cu, like a machine learning system MLS comprising an artificial neural network ANN, may be provided in the external server 20.

The vehicle 10 comprising a corresponding system 100 provides the third aspect of the invention.

An electronic control device ECU comprising a memory device mu, in which a program code is stored, and a computing device cu, wherein when carrying out the program code by the computing device cu, a method is performed as described above, provides the fourth aspect of the invention. In other words, the electronic control device ECU is configured in such a way to execute embodiments of the method as described above.

Also, a computer program product comprising a program code for carrying out a method as described above provides an aspect of the invention.

The above description of the figures describes the present invention only in the context of examples. Of course, individual features of the embodiments may be combined with each other, provided it is technically reasonable, without leaving the scope of the invention. Reference signs

10 vehicle 0 external server 1 map data provider

100 system

101 identification device

102 navigation device

201 action

202 action

203 action

204 action

205 action

206 action

207 action

208 action

209 action

210 action

C1 characteristic

C2 characteristic

D driver

ID driver identity

ID1 face recognition

ID2 voice recognition

ID3 key/code/device recognition

ID4 driving profile recognition

11 navigation information

I2 navigation information T driver trip

A trip starting point

B trip destination point

F available facilities t time t1 trip starting time t2 trip destination time dt trip duration

NAVI navigation details

MAP map data REC rip record

T 1 official authority

T2 trip detection system

T3 trip detection system

ANN artificial neural network

MLS machine learning system

True positive verification False negative verification

ECU electronic control device cu computing device mu memory device

HMI human machine interface au audio device

Claims

Claims A method for providing an automatic logbook for a driver (D) of a vehicle (10), the method comprising: identify the driver (D) of the vehicle (10), determine at least one navigation information (11 , I2) for a driver trip (T) with the vehicle (10), assign a characteristic (C1 , C2) to the driver trip (T) for an identified driver identity (ID) according to the at least one navigation information (11 , I2) automatically by a machine learning system (MLS), wherein especially the at least one navigation information (11 , I2) is used as training data and/or input data for the machine learning system (MLS), output the assigned characteristic (C1 , C2) of the driver trip (T) by the machine learning system (MLS) to the driver (D) by a human machine interface (HMI), obtain a verification (True, False) of the assigned characteristic (C1 , C2) from the driver (D), especially in a non-contact way, preferably by a voice command, wherein especially the verification (True, False) from the driver (D) is used for training and/or for adaptation of the machine learning system (MLS). The method according to claim 1 , wherein a driver (D) of a vehicle (10) will be identified at least by one of the following technics: face recognition, voice recognition, user mobile device, especially smartphone, recognition, key recognition, code recognition, and/or driving profile recognition. The method according to any one of the preceding claims 1 or 2, wherein the at least one navigation information (11 , I2) for the driver trip (T) contain at least one of the following data: a trip starting point (A), a trip destination point (B), available facilities (F) at the destination point (B), a trip record (REC), a trip starting time (t1 ), a trip destination time (t2), a trip duration (dt), navigation details (NAVI), and/or map data (MAP). The method according to any one of the preceding claims, wherein the at least one navigation information (11 , I2) is used as training data and/or input data for the machine learning system (MLS), and/or the machine learning system (MLS) is configured as an adaptive and/or permanently learning system. The method according to any one of the preceding claims, wherein the assigned characteristic (C1 , C2) of the driver trip (T) comprise: a business trip (C1 ) or a private trip (C2). The method according to any one of the preceding claims, wherein the verification of the assigned characteristic (C1 , C2) will be executed in a non-contact way, preferably by a voice command, and/or the verification of the assigned characteristic (C1 , C2) will be recorded by an input device of the vehicle (10), especially by the human machine interface (HMI), preferably an audio device (au) of the human machine interface (HMI). The method according to any one of the preceding claims, wherein the method comprises at least one of the following: recording of the driver trip (T), the assigned characteristic (C1 , C2) of the driver trip (T) and/or the at least one navigation information (11 , I2) as a logbook entry, especially in an non-transitory and/or non-volatile memory device (mu).

- 16 - The method according to any one of the preceding claims, wherein the method comprises at least one of the following: transmitting the driver identity (ID) and corresponding logbook entries to an official authority (T1) and/or a trip detection system (T2) for official purposes. The method according to any one of the preceding claims, wherein the method comprises at least one of the following: transmitting logbook entries to a trip detection system (T3) for commercial purposes. The method according to any one of the preceding claims, wherein the method will be executed by an electronic control device (ECU) of the vehicle (10), wherein especially some actions and/or calculations will be at least partly transferred to an external server (20) for execution. A System (100) for providing an automatic logbook for a driver (D) of a vehicle (10), comprising: an identification device (101 ) for identifying the driver (D) of the vehicle (10), a navigation device (102) for determining at least one navigation information (11 , I2) for a driver trip (T) with the vehicle (10), a computing device (cu) comprising a machine learning system (MLS) for automatically assigning a characteristic (C1 , C2) to the driver trip (T) according to an identified driver identity (ID) and the at least one navigation information (11 , I2), wherein especially the at least one navigation information (11 , I2) is used as training data and/or input data for the machine learning system (MLS), a human machine interface (HMI), preferably installed in the vehicle (10), for outputting the assigned characteristic (C1 , C2) of the driver trip (T) by the machine learning system (MLS) to the driver (D), an input device, preferably an audio device (au), for obtaining a verification (True, False) of the assigned characteristic (C1 , C2) from the driver (D), especially in a non-contact way, preferably by a voice command, wherein especially the computing device (cu) is configured to use the verification (True, False) from the driver (D) for training and/or for adaptation of the machine learning system (MLS). The System (100) according to claim 11 , wherein - 17 - an non-transitory and/or non-volatile memory device (mu) is provided for storage the driver trip (T), the assigned characteristic (C1 , C2) of the driver trip (T) and/or the at least one navigation information (11 , I2) as a logbook entry. A vehicle (10) comprising a system (100) according to any one of the preceding claims

11 or 12. An electronic control device (ECU) comprising: a memory device (mu), in which a program code is stored, and a computing device (cu), wherein when carrying out the program code by the computing device (cu), a method according to any one of the proceeding claims 1 to 10 is performed. A computer program product comprising instructions which, when the program is executed by a computer, cause the computer to carry out a method according to any one of claims 1 to 10.