Method and system for monitoring a use of a mobile device in a vehicle

Abstract

In a method and system for monitoring a use of a mobile device in a vehicle, the vehicle and the mobile device each measure its acceleration and provide corresponding acceleration data. The method includes transmitting the acceleration data of the vehicle and the acceleration data of the mobile device to an evaluation device; comparing, in the evaluation device, the acceleration data of the vehicle to the acceleration data of the mobile device; and generating a message if the acceleration data differ from each other to a predetermined extent.

Description

METHOD AND SYSTEM FOR MONITORING A USE OF A MOBILE DEVICE IN A VEHICLEBACKGROUND1. Technical Field

[0001] The disclosure relates to a system and method (generally referred to as a “system”) for monitoring a use of a mobile device in a vehicle.2. Related Art

[0002] Driving behavior monitoring systems are increasingly being used to monitor and assess the driving behavior of vehicles and their drivers. The data collected in this way is used for various purposes. One use such purpose is to calculate or adjust a vehicle insurance premium dependent on the vehicle use. Others include providing feedback to the drivers on how safely they are driving, or triggering automatic vehicle actions such as generating alerts and emergency braking or steering.

[0003] Driver distraction is a major issue in road safety and is often due to the use of a mobile device, such as a smartphone, while driving. Most of the existing driver distraction detection systems are based on image processing in connection with one or more cameras installed in the vehicle, which requires an expensive and complex hardware setup in the vehicle. It is therefore desirable to provide systems and methods for monitoring the use of a mobile device in a vehicle that are less complex and less costly.SUMMARY

[0004] In a method for monitoring a use of a mobile device in a vehicle, the vehicle and the mobile device each measure their respective acceleration and provide corresponding acceleration data. The method includes transmitting the acceleration data of the vehicle and the acceleration data of the mobile device to an evaluation device; comparing, with the evaluation device, the acceleration data of the vehicle to theacceleration data of the mobile device; and generating a message if the acceleration data differ from each other to a predetermined extent.

[0005] In a system for monitoring a use of a mobile device in a vehicle, the vehicle comprises an acceleration sensor configured to measure accelerations of the vehicle and to provide acceleration data of the vehicle, and the mobile device comprises an acceleration sensor configured to measure accelerations of the mobile device and to provide acceleration data of the mobile device. The system comprises an evaluation device operatively coupled to the acceleration sensor of the vehicle and the acceleration sensor of the mobile device, the evaluation device being configured to compare the acceleration data of the vehicle to the acceleration data of the mobile device, and to generate a message if the acceleration data differ from each other to a predetermined extent.

[0006] Other systems, methods, features and advantages will be, or will become, apparent to one with skill in the art upon examination of the following detailed description and appended figures. It is intended that all such additional systems, methods, features and advantages be included within this description, be within the scope of the invention, and be protected by the following claims.BRIEF DESCRIPTION OF THE DRAWINGS

[0007] The system may be better understood with reference to the following drawings and description. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the invention. Moreover, in the figures, like referenced numerals designate corresponding parts throughout the different views.FIG. 1 is a block diagram illustrating the components of an example system for monitoring the use of a mobile device in a vehicle.FIG. 2 is a block diagram illustrating the data streams in the system shown in FIG. 1.FIG. 3 is a flow chart illustrating an example implementation and application of a method for monitoring use of a mobile device in a vehicle.FIG. 4 is an acceleration-time diagram showing one example output of a three-axis acceleration sensor of a vehicle and three example outputs of a three-axis acceleration sensor of a mobile device.FIG. 5 is a general flow chart of a method for monitoring use of a mobile device in a vehicle.FIG. 6 is a flow chart of a process for comparing acceleration data of the vehicle and the mobile device with each other using maximum detection within a first time window.FIG. 7 is a flow chart of a process for comparing acceleration data of the vehicle and the mobile device with each other using a correlation factor within a second time window.DETAILED DESCRIPTION

[0008] FIG. 1 illustrates the components and their interconnections involved in an example driving behavior monitoring system that specifically monitors the distraction of a driver (not shown) of a vehicle 101 caused by the use of a mobile device such as a smartphone 102 (herein also referred to as phone, mobile or mobile phone) while driving. A plug-in dongle (shown), an on-board vehicle interface (not shown) or any other suitable portable or permanently installed interface, herein generally referred to as a diagnosis device 103, is connected, e.g., by hard-wire, through plug-in or wirelessly, to an On-Board Diagnosis (OBD) port or an In-Vehicle Infotainment (IVI) system of the vehicle 101. The diagnosis device 103 is capable of reading the state of the vehicle and sensor data of the vehicle, particularly acceleration sensor data. On-board diagnostics (OBD) is a term referring to a vehicle's self-diagnostic and reporting capability. A primary benefit of OBD systems is that they give the user or repair technician access to the status of the various vehicle sub-systems. IVI is a collection of hardware and software components in automobiles that provides audio or video entertainment. Besides entertainment functions, IVI systems may include automotive navigation, Universal Serial Bus (USB) connectivity, Bluetooth connectivity, carputers, in-car internet, and wireless network (WiFi). Modem IVI systems are able to access more and more functions of the vehicle such as sensors, e.g. through a suitable bus. A cloud service 104 located distant from the vehicle 101, the phone 102 and the diagnosisdevice 103 receives data from these and stores the received data for further processing with an evaluation device which, for example, may be a remote data processing unit 105

[0009] A (e.g., bidirectional) data transfer path 106 between the phone 102 and the cloud service 104, as well as a (e.g., bidirectional) data transfer path 107 between the diagnosis device 103 and the cloud service 104, may be wireless, far distance connections which fulfill the applicable technology standards, such as the Global System for Mobile Communications (GSM), Long Term Evolution (LTE), the fifthgeneration technology standard for cellular networks (5G) or any other mobile communication channels. A wireless, near distance connection using, for example, Bluetooth or WiFi may provide an alternative or additional (e.g., bidirectional) data transfer path 108, which allows transfer of data from the phone 102 to the diagnosis device 103 for processing the data from the phone 102 or passing on the data to the cloud 104 via data transfer path 106, or both. Any suitable, wireless or wired connection may form a (e.g., bidirectional) data transfer path 109 for transferring stored data from the cloud service 104 to the data processing unit 105 and possibly for sending back processed data.

[0010] FIG. 2 illustrates an example data flow of the system shown in FIG. 1 in detail. Acceleration data, e.g., three-axis acceleration data, of the vehicle 101 measured by an acceleration sensor 201 are supplied to the diagnosis device 103 via a plug-in connection 203 and are processed (process 204) by a dedicated software application, herein referred to as device application 205, installed in the diagnosis device 103. The acceleration sensor 201 and the plug-in connection 203 may pre-exist in the vehicle 101 and the diagnosis device 103 with installed application 205 may be added thereto. Acceleration data, e.g., three-axis acceleration data, of the phone 102 measured by an acceleration sensor 202 are processed 206 by a software application, herein referred to as mobile application 207, installed in the phone 102. The acceleration sensor 202 may pre-exist in the phone 102 and the mobile application 207 may be additionally installed. The device application 205 communicates with the cloud service 104 via data path 107, e.g., using a Hypertext Transfer Protocol (HTTP) or Message Queuing Telemetry Transport (MQTT) protocol and may not only send data to, but may also, if needed, receive data from, the cloud service 104. The mobile application 207 communicateswith the cloud service 104 via data path 106, e.g., using HTTP, and can also send data to and receive data from the cloud service 104. Furthermore, the device application 205 and the mobile application 207 may communicate with each other using Bluetooth or on-board WiFi in order to exchange data and control signals depending on the desired overall or temporary data flow structure.

[0011] The mobile application 207 may not only monitor the acceleration of the phone, e.g., by means of a gyroscope or accelerometer or both, but also other aspects of the phone status such as the call status, media status, power consumption, active applications and other suitable parameters of the phone. The device application 205 may assess, in addition to acceleration values, e.g., values derived from at least one of a gyroscope, accelerometer and speedometer, as well as other vehicle parameters like ignition status, motor revolutions-per-minute (rpm), and accelerator pedal position. The mobile application 207 can share the data with the cloud service 104 when a data connection to the cloud service 104 can be established and maintained for a sufficient time. Similarly, the device application 205 also shares the collected data with the cloud service. At the cloud service 104, the data from the vehicle 101 and the phone 102 are interpreted to detect deviations over time in the acceleration signal progressions, herein referred to as acceleration profiles, of the vehicle 101 and the phone 102. If the mobile device is in motion and deviations of a certain kind and / or extent are detected, a notification or alert will be sent to mobile application 207 from the cloud service 104. Additionally or alternatively, the notification or alert may be sent to device application 205 for notification to the IVI or to an instrument cluster. If there is a connection between the phone 102 and the vehicle 101 (diagnosis device 103), the processing of data can be carried out locally, in the vehicle 101 (e.g., in the diagnosis device 103) or phone 102 and alerts are also generated locally, for example as an alternative if the cloud service 104 is not available or as a backup system in the event of a loss of data.

[0012] FIG. 3 illustrates an example process flow involving a device application 301, a user / driver 302, a mobile application 303 and a cloud service 304 (including data processing for the sake of simplicity). It is assumed that the driver has the required mobile application installed in his / her phone and all required permissions given, and the device is ready (dongle connected to vehicle or IVI capable of receiving vehicle data)and is connected to the cloud service and / or phone. The user / driver 302 starts the vehicle (process 305), which starts the device application (process 306). The mobile application 303 starts (process 307). At this point, a connection to the cloud service 304 is established (process 308). The device application 301 starts to collect diagnosis device and acceleration sensor data (process 309) and the mobile application 303 starts to collect phone and acceleration sensor data (process 310). These data from the device application 301 and the mobile application 303 are sent to the cloud service 304, where they are stored (process 311) and may be processed (process 312), specifically, analyzed for distractions of the user / driver 302.

[0013] After driving a while, the user / driver 302 starts using his / her phone (process 313). The newest (updated) phone and sensor data are sent to the cloud service 304 (process 314), where they are stored (process 311) and processed (process 312). If a distraction is detected (process 315) by the cloud service 304 resulting from the use of the phone 302, alerts (processes 316, 317) are generated in at least one of the device application 301 and the mobile application 303. Optionally, after checking and confirming the connection to the device application 301 (process 318), the newest phone and sensor data may be sent (process 319) from the phone 302 to the device application 301 where they are received (process 320), provided the connection between the mobile application 303 and the device application 301 has been established. The device application 301 processes the data received from the mobile application 303 (process 321), specifically, interprets the data for distraction of the user / driver 302. If a distraction is detected (process 322) during use of the phone 302, alerts (processes 316, 317) are generated in at least one of the device application 301 and the mobile application 303.

[0014] The application installed on the phone may be capable of reading the phone state (in call, media playing etc.), and is also able to read the sensor values (gyroscope and accelerometer). When the custom built application reads all these values, it can detect whether the mobile device is in the user’s hands or in a moving vehicle. Similarly, an application in the dongle or IVI can also read the sensor values and possibly the vehicle state (via CAN messages) to interpret whether the vehicle is in motion. Collected gyroscope and accelerometer values can be used to calculate the motion of theobject. When these values are interpreted (either locally or at the cloud service) to mean that the phone is in use and the vehicle is in motion, an alert is generated. This data can be further used to monitor the driver behavior and to report on it to the owner of the vehicle or any other entitled entities. Based on the capabilities of the vehicle, if reckless behavior is detected, control methods such as restricting speed, presenting alert beeps etc. can be applied via instructions given by the cloud service to the diagnosis device / IVI or taken locally.

[0015] The acceleration sensors in the vehicles and phones described above may include at least one of an accelerometer, a triple axis (AXL) acceleration sensor, a gyroscope or any other suitable means. An accelerometer is a device that measures the proper acceleration of an object which is per definition the acceleration (the rate of change of velocity) of the object relative to an observer who is in free fall (that is, relative to an inertial window of reference). Proper acceleration is different from coordinate acceleration, which is acceleration with respect to a given coordinate system which may or may not be accelerating. AXL accelerometers are sensors that measure accelerations in three perpendicular directions (along three perpendicular axes). Gyroscopes are devices used for measuring or maintaining orientation and angular velocity. A gyroscope may be a spinning wheel or disc in which the axis of rotation (spin axis) is free to assume any orientation on its own. When rotating, the orientation of this axis is unaffected by tilting or rotation of the mounting, being conserved by angular momentum. Gyroscopes based on other operating principles also exist, such as the microchip-packaged MEMS gyroscopes found in electronic devices, solid-state ring lasers, and fiber optic gyroscopes. The sensors in the vehicles and phones may be, for example, a combination of an AXL sensor and a gyroscope in order to allow for an exact determination of the acceleration direction.

[0016] Referring again to FIG. 2, deviations between the acceleration profiles (e.g., graphs over time per direction) of the vehicle 101 and the phone 102 can be detected in a variety of ways. In a simple case, the maximum values of both profiles are compared, as is the case with one-axis motion profiles of motion sensors that only measure in one direction, for example. The temporal correlation between the maximum acceleration events in the vehicle 101 and the phone 102 can also be evaluated to increase accuracy.More complex evaluations include the calculation of horizontal and vertical 360° motion profiles in the vehicle 101 and in the phone 102, for example when using three- axes motion sensors. The motion profiles created in this way are analyzed with regard to their spatial and temporal correlation.

[0017] For example, the vehicle 101 drives at a constant speed and straight ahead. Accordingly, the acceleration sensor 201 of the vehicle 101, which is assumed to be a three-axis sensor, detects no acceleration. If the phone 102 is not moved relative to the vehicle, e.g., because it rests in the center storage compartment of the car, its acceleration sensor 202 detects no acceleration as the phone 102 is moved in the same way as the vehicle 101. However, when the user puts the phone to his / her ear to make a call, it is moved relative to the vehicle, which can be detected through the differing acceleration profiles of the vehicle 101 and the phone 102. The movements of vehicles in general are relatively monotonous over a long distance, i.e. they do not exhibit strong accelerations and, if they do, these are very typical and of limited time, making them easy to recognize in the movement profile of the phone. Accelerations of the phone that deviate from the vehicle’s acceleration profile are therefore also easily recognizable and allow the evaluation device, e.g., the data processing unit 105, to determine the use of the phone. Additional information about the vehicle’s status and the phone’s status as outlined above may provide further assistance in determining whether the phone is in use or not.

[0018] FIG. 4 shows a graph 401 depicting an acceleration a into one direction (e.g., the forward direction of a vehicle) over time t as measured by a three-axes acceleration sensor disposed in the vehicle. Although only one axis (direction) output by the acceleration sensor of the vehicle is shown here, the following also applies in the same or a similar way to its other two axes. FIG. 4 further shows three graphs 402, 403 and 404 depicting the measured accelerations a over time t of an acceleration sensor in the mobile device for the three axes (directions) X, Y and Z. The graph 401 has a first relative positive maximum (peak) in a first time window between a first point in time ti and second point in time t2. In a second time window between the first point in time t2 and a third point in time t3, no significant accelerations are detected by the vehicle’s acceleration sensor. The graph 401 has a second relative negative maximum in a thirdtime window between the third point in time t3 and fourth point in time t4. A relative positive maximum also appears in the first time window and a negative maximum appears in the third time window also in graphs 402, 403 and 404, whereas one of the graphs may be sufficient to detect the use of the phone, but detection may be difficult depending on the unknown position of the phone, it can indicate that the vehicle and the mobile device are being accelerated by the same force, the source of which is most likely the vehicle engine. However, in the second time window the graphs 402, 403 and 404 exhibit various maxima. As the vehicle experiences no considerable acceleration (see graph 401) in the second time window, the mobile device is being moved relative to the vehicle, which suggests that the mobile device is in use.

[0019] FIG. 5 illustrates a basic method for monitoring the use of a mobile device in a vehicle. The vehicle and the mobile device each measure, e.g., continuously, sampled or in certain time intervals, their respective acceleration and provide corresponding acceleration data (process 501). Subsequently, the acceleration data of the vehicle and the acceleration data of the mobile device are transmitted to an evaluation device (process 502), which may be a processor or computer with suitable software located in the vehicle, in the mobile device or distant from both. In the evaluation device, the acceleration data of the vehicle and the acceleration data of the mobile device are compared to each other (process 503). As outlined above, deviations (differences) between the acceleration profiles (e.g., graphs over time per direction) of the vehicle and the phone can be detected in a variety of ways, some of which are described herein in detail. A message (alert, warning, notification etc.) is generated if the acceleration data differ from each other to a predetermined extent (process 504).

[0020] As shown in FIG. 6, comparing the acceleration data of the vehicle and the mobile device (process 503) may include determining a maximum value of the acceleration data of the vehicle within a predetermined (sufficiently small) first time window (sub-process 601) and determining a maximum value of the acceleration data of the mobile device within the predetermined first time window (sub-process 602). The determined maximum value of the acceleration data of the vehicle and the determined maximum value of the acceleration data of the mobile device are then compared with each other (sub-process 603). If the maximum value of the acceleration data of themobile device exceeds the maximum value of the acceleration data of the vehicle by a first predetermined amount (sub-process 604), an alert is generated (sub-process 605). This process 503 is repeated continuously, i.e., starts again with sub-process 601.

[0021] Alternatively, comparing the acceleration data of the vehicle and the mobile device (process 503) may include calculating a correlation factor representing a (cross) correlation between the acceleration data of the vehicle and the mobile device within a predetermined (sufficiently large) second time window (sub-process 701), as shown in FIG. 7. The calculated correlation factor, which can assume values between and including zero and one, is compared to a value of one (sub-process 702) and an alert is generated if the correlation factor is smaller than one by a second predetermined amount (sub-process 703).

[0022] Other ways of comparison, such as comparing the graphs’ integrals or the sum of (the integrals of) all axes of each acceleration sensor within a suitable time window, may also be used. Thus, if an acceleration with a certain minimum strength is detected in both the vehicle and the mobile device within a specific time window, both devices can be considered to be in motion. The values on both devices may slightly change. It is assumed that both devices are being accelerated by the vehicle engine. If only the mobile device reports an acceleration within a time window, this is interpreted to mean that the mobile device is in use. If only the vehicle reports an acceleration within a time window, this is interpreted to mean that an error in the mobile device occurred. The information provided by the acceleration sensors can be processed by a remote cloud service, in the vehicle or in the mobile device, and a warning can be generated in one, some or all of them. Even if the connection to the cloud service is interrupted, the connection between the mobile device and the vehicle (e.g., its infotainment system) via Bluetooth or any other possible connectivity, can be used to process data locally to generate messages, warnings or alerts to safeguard the driver as well as others inside and outside the vehicle. This information can be further used to generate or amend a driver score.

[0023] The method described above may be implemented by software and / or firmware stored on or in a computer-readable medium, machine-readable medium, propagated-signal medium, and / or signal-bearing medium. The media may compriseany device that contains, stores, communicates, propagates, or transports executable instructions for use by or in connection with an instruction executable system, apparatus, or device. The machine-readable medium may selectively be, but is not limited to, an electronic, magnetic, optical, electromagnetic, or infrared signal or a semiconductor system, apparatus, device, or propagation medium. A non-exhaustive list of examples of a machine-readable medium includes: a magnetic or optical disk, a volatile memory such as a Random Access Memory “RAM,” a Read-Only Memory “ROM,” an Erasable Programmable Read-Only Memory (i.e., EPROM) or Flash memory, or an optical fiber. A machine-readable medium may also include a tangible medium upon which executable instructions are printed, as the logic may be electronically stored as an image or in another format (e.g., through an optical scan), then compiled, and / or interpreted or otherwise processed. The processed medium may then be stored in a computer and / or machine memory.

[0024] The method may be encoded as instructions for execution by a processor. Alternatively or additionally, any type of logic may be utilized and may be implemented as analog or digital logic using hardware, such as one or more integrated circuits (including amplifiers, adders, delays, and filters), or one or more processors executing amplification, adding, delaying, and filtering instructions; or in software in an application programming interface (API) or in a Dynamic Link Library (DLL), functions available in a shared memory or defined as local or remote procedure calls; or as a combination of hardware and software.

[0025] The systems may include additional or different logic and may be implemented in many different ways. A controller may be implemented as a microprocessor, microcontroller, application specific integrated circuit (ASIC), discrete logic, or a combination of other types of circuits or logic. Similarly, memories may be DRAM, SRAM, Flash, or other types of memory. Parameters (e.g., conditions and thresholds) and other data structures may be separately stored and managed, may be incorporated into a single memory or database, or may be logically and physically organized in many different ways. Programs and instruction sets may be parts of a single program, separate programs, or distributed across several memories and processors.

[0026] The description of embodiments has been presented for purposes of illustration and description. Suitable modifications and variations to the embodiments may be performed in light of the above description or may be acquired from practicing the methods. For example, unless otherwise noted, one or more of the described methods may be performed by a suitable device and / or combination of devices. The described methods and associated actions may also be performed in various orders in addition to the order described in this application, in parallel, and / or simultaneously. The described systems are exemplary in nature, and may include additional elements and / or omit elements.

[0027] As used in this application, an element or step recited in the singular and proceeded with the word “a” or “an” should be understood as not excluding plural of said elements or steps, unless such exclusion is stated. Furthermore, references to “one embodiment” or “one example” of the present disclosure are not intended to be interpreted as excluding the existence of additional embodiments that also incorporate the recited features. The terms “first,” “second,” and “third,” etc. are used merely as labels, and are not intended to impose numerical requirements or a particular positional order on their objects.

[0028] While various embodiments of the invention have been described, it will be apparent to those of ordinary skilled in the art that many more embodiments and implementations are possible within the scope of the invention. In particular, the skilled person will recognize the interchangeability of various features from different embodiments. Although these techniques and systems have been disclosed in the context of certain embodiments and examples, it will be understood that these techniques and systems may be extended beyond the specifically disclosed embodiments to other embodiments and / or uses and obvious modifications thereof.

Claims

CLAIMS:

1. A method for monitoring a use of a mobile device in a vehicle, the vehicle and the mobile device each measuring their respective acceleration and providing corresponding acceleration data, the method comprising: transferring the acceleration data of the vehicle and the acceleration data of the mobile device to an evaluation device; comparing, in the evaluation device, the acceleration data of the vehicle to the acceleration data of the mobile device; and generating a message if the acceleration data differ from each other to a predetermined extent.

2. The method of claim 1, wherein: comparing the acceleration data of the vehicle to the mobile device comprises determining a maximum value of the acceleration data of the vehicle and a maximum value of the acceleration data of the mobile device within a predetermined first time window; comparing the determined maximum value of the acceleration data of the vehicle to the determined maximum value of the acceleration data of the mobile device; and generating an alert if the maximum value of the acceleration data of the mobile device exceeds the maximum value of the acceleration data of the vehicle by a first predetermined amount.

3. The method of claim 1 or 2, wherein: comparing the acceleration data of the vehicle to the mobile device comprises calculating a correlation factor representing a correlation between the acceleration data of the vehicle and the mobile device within a predetermined second time window; comparing the calculated correlation factor to a value of one; and generating an alert if the correlation factor is smaller than one by a second predetermined amount.

4. The method of any of claims 1-3, wherein the vehicle and the mobile device each measure its accelerations along two or three axes, the axes being perpendicular with respect to each other.

5. The method of claim 4, further comprising a two or three axis acceleration profiles of the vehicle and the mobile device, and comparing each profile of the vehicle and each profile of the mobile device with each other.

6. The method of any of claims 1-5, wherein the evaluation device is disposed in a location distant from the vehicle and the mobile device, and the acceleration data are wirelessly and directly transmitted from the vehicle and the mobile device to the evaluation device.

7. The method of claim 6, wherein the acceleration data from the mobile device are transferred to the vehicle and passed on by the vehicle to the evaluation device.

8. The method of any of claims 1-7, further comprising storing the acceleration data of the vehicle and the acceleration data of the mobile device in a cloud memory, and the evaluation device accesses the data stored in the cloud memory.

9. The method of any of claims 1-8, further comprising assessing additional data on use of the mobile device using a first software application installed on the mobile device and sending the additional data on use of the mobile device to the evaluation device.

10. The method of any of claims 1-9, further comprising assessing additional data on use of the vehicle using a second software application installed in the vehicle and sending the additional data on use of the vehicle to the evaluation device.

11. A system for monitoring a use of a mobile device in a vehicle, wherein the vehicle comprises an acceleration sensor configured to measure accelerations of the vehicle and to provide acceleration data of the vehicle;the mobile device comprises an acceleration sensor configured to measure accelerations of the mobile device and to provide acceleration data of the mobile device; and the system comprises an evaluation device operatively coupled to the acceleration sensor of the vehicle and the acceleration sensor of the mobile device, the evaluation device being configured to compare the acceleration data of the vehicle to the acceleration data of the mobile device, and to generate a message if the acceleration data differ from each other in a predetermined manner.

12. The system of claim 11, further comprising transfer paths configured to transfer acceleration data from the vehicle and the mobile device to a cloud memory disposed at a distant location from the vehicle and the mobile device, the cloud memory being operatively connected to the evaluation device.

13. The system of claim 11 or 12, further comprising a first processor controlled by a first software application and configured to assess additional data on the use of the mobile device and to send the additional data on the use of the mobile device to the evaluation device.

14. The system of any of claims 11-13, further comprising a second processor controlled by a second software application and configured to assess additional data on the use of the vehicle and to send the additional data on the use of the vehicle to the evaluation device.

15. The system of any of claims 11-14, wherein the acceleration sensors in the vehicle and the mobile device are each configured to measure accelerations along two or three axes, the axes being perpendicular with respect to each other.

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