Privacy-friendly relative location of a vehicle

Abstract

The examples described here provide a method for supplying an approximate location of a vehicle to a user device. The method includes receiving a handshake request in a processing system of the vehicle, the handshake request being initiated by the user device associated with an operator of the vehicle. The method further includes the vehicle's processing system determining an exact location of the user device. The method further includes the vehicle's processing system generating the approximate location of the vehicle. The method further includes transmitting the approximate location of the vehicle from the processing system to the user device. The method further includes activating a function of a virtual key of the user device based at least partially on the exact location of the user device and the approximate location of the vehicle.

Description

BACKGROUND

[0001] The present invention relates to a computer-implemented method for providing an approximate location of a vehicle to a user device. The present disclosure relates to vehicles and, in particular, to the provision of a privacy-friendly relative location of a vehicle.

[0002] For example, US Patent 2023 / 0188930A1 describes a method for accessing vehicle functionality via a mobile device. German Patent DE 102020211072A1 describes a method encompassing booking a vehicle using an application installed on an electronic device and establishing a wireless data connection when the electronic device is within a certain range of the vehicle after booking.

[0003] Modern vehicles (e.g., cars, motorcycles, boats, or other motor vehicles) can be equipped with one or more communication systems to communicate with other vehicles and / or other devices. For example, a vehicle may be equipped with a communication system that enables vehicle-to-vehicle (V2V) communication with another vehicle. Alternatively, a vehicle may be equipped with a communication system for communicating with a user device, such as a smartphone, laptop, tablet computer, wearable computer (e.g., a smartwatch), and / or similar device, including combinations and / or multiple devices thereof. SUMMARY

[0004] In one embodiment, a method is provided for making an approximate location of a vehicle available to a user device. The method includes receiving a handshake request in a processing system of the vehicle, wherein the handshake request is initiated by the user device assigned to an operator of the vehicle. The method further includes the vehicle's processing system determining an exact location of the user device. The method further includes the vehicle's processing system generating the approximate location of the vehicle. The method further includes transmitting the approximate location of the vehicle from the processing system to the user device. The method further includes activating a function of a virtual key of the user device based at least partially on the exact location of the user device and the approximate location of the vehicle.

[0005] In addition to one or more of the features described here, or as an alternative, further embodiments of the method may include the application of a noise factor in determining the inaccurate position of the vehicle.

[0006] In addition to one or more of the features described here, or as an alternative, further embodiments of the method may include generating the inaccurate position of the vehicle by determining a value T. reply1 , of a value T round1 , of a value T round2 and a value T reply2 , Applying the noise factor to the value T reply1 and the value T round2 , and calculating the imprecise location of the vehicle at least partially based on the noise factor applied to each of the values ​​T reply1 and T round2 is applied.

[0007] In addition to one or more of the features described here, or as an alternative, further embodiments of the method may include applying the noise factor to each of the values ​​T. reply1 and T round2 subtracting the noise factor from the value T reply1 and adding the noise factor to the value T round2 contains.

[0008] In addition to one or more of the features described here, or as an alternative, further embodiments of the method may include the application of the noise factor to the value T to generate the inaccurate position of the vehicle. reply1 and the transmission of a resulting noisy value T reply1 to the user device, where the user device contains the noisy value T reply1 is used to calculate an approximate distance to the vehicle.

[0009] In addition to one or more of the features described herein, or as an alternative, further embodiments of the method may include generating the inaccurate location of the vehicle at least partially based on a time-of-arrival difference (TDoA) or a phase-of-arrival difference (PDoA) relative to a plurality of antennas of the vehicle and on noise added to the results of TDoA and / or PDoA.

[0010] In addition to one or more of the features described here, or as an alternative, further embodiments of the method may include generating the inaccurate position of the vehicle by generating noisy information about the geometric arrangement of a plurality of antennas of the vehicle.

[0011] In addition to one or more of the features described herein, or as an alternative, further embodiments of the method may include the fact that the inaccurate location of the vehicle is based at least partially on responses from a subset of a plurality of antennas of the vehicle, including a time period required to decide which of the plurality of antennas comprises the subset.

[0012] In addition to one or more of the features described herein, or as an alternative, further embodiments of the method may include generating the inaccurate position of the vehicle by generating a random delay for each of a plurality of antennas of the vehicle.

[0013] In addition to one or more of the features described here, or as an alternative, further embodiments of the method may include the fact that the exact location of the vehicle is more precise than the imprecise location of the user device.

[0014] In another embodiment, a vehicle is provided. The vehicle has a plurality of antennas for wirelessly transmitting data to and receiving data from a user device. The vehicle further comprises a processing system with a memory containing computer-readable instructions and a processing device for executing the computer-readable instructions. The computer-readable instructions control the processing device to perform operations for providing an approximate location of the vehicle to the user device. The operations include receiving a handshake request in the vehicle's processing system, the handshake request being initiated by the user device assigned to an operator of the vehicle. The operations further include the vehicle's processing system determining an exact location of the user device.The operations further include generating the vehicle's approximate location using the vehicle's processing system. The operations further include transmitting the vehicle's approximate location from the processing system to the user device via at least one of the plurality of antennas. The operations further include activating a function of a virtual key of the user device based at least partially on the user device's precise location and the vehicle's approximate location.

[0015] In addition to one or more of the features described here, or as an alternative, further embodiments of the vehicle may include the application of a noise factor in determining the inaccurate position of the vehicle.

[0016] In addition to one or more of the features described here, or as an alternative, further embodiments of the vehicle may include the following features for generating the vehicle's inaccurate position: Determining a value T reply1 , of a value T round1 , of a value T round2 and a value T reply2 , Applying the noise factor to the value T reply1 and the value T round2 , and calculating the imprecise location of the vehicle at least partially based on the noise factor applied to each of the values ​​T reply1 and T round2 is applied.

[0017] In addition to one or more of the features described here, or as an alternative, further embodiments of the vehicle may include the application of the noise factor to each of the values ​​T. reply1 and T round2 subtracting the noise factor from the value T reply1 and adding the noise factor to the value T round2contains.

[0018] In addition to one or more of the features described here, or as an alternative, further embodiments of the vehicle may include the fact that generating the inaccurate position of the vehicle involves applying the noise factor to the value T. reply1 and the transmission of a resulting noisy value T reply1 to the user device, where the user device contains the noisy value T reply1 is used to calculate an approximate distance to the vehicle.

[0019] In addition to one or more of the features described herein, or as an alternative, further embodiments of the vehicle may include the generation of the inaccurate position of the vehicle being based at least partially on a time difference at arrival (TDoA) or a phase difference at arrival (PDoA) relative to the multitude of antennas of the vehicle and on noise added to the results of the TDoA and / or PDoA.

[0020] In addition to one or more of the features described here, or as an alternative, further embodiments of the vehicle may include generating noisy information about the geometric arrangement of the vehicle's multiple antennas to determine the vehicle's inaccurate position.

[0021] In addition to one or more of the features described herein, or as an alternative, further embodiments of the vehicle may include the fact that the inaccurate location of the vehicle is based at least partially on responses from a subset of the multitude of antennas of the vehicle, including a period of time spent deciding which of the multitude of antennas comprises the subset.

[0022] In addition to one or more of the features described herein, or as an alternative, further embodiments of the vehicle may include generating the inaccurate position of the vehicle by generating a random delay for each of the plurality of antennas of the vehicle.

[0023] In another embodiment, a computer program product is provided. The computer program product comprises a computer-readable storage medium containing program instructions, wherein the program instructions can be executed by at least one processor to cause the at least one processor to perform operations. The operations include receiving a handshake request at a vehicle, wherein the handshake request is initiated by a user device associated with an operator of the vehicle. The operations further include determining the precise location of the user device within the vehicle. The operations further include generating the precise location of the vehicle at the vehicle. The operations further include transmitting the precise location of the vehicle to the user device.The operations further include masking the vehicle's precise location on the user device to generate an inaccurate location, sharing this inaccurate location with third-party applications running on the user device without sharing the vehicle's precise location with those applications. The operations also include activating a function of a virtual key on the user device based, at least in part, on the user device's precise location and the vehicle's inaccurate location.

[0024] The above properties and advantages, as well as further properties and advantages of the disclosure, are readily apparent from the following detailed description in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Further features, advantages and details are listed only as examples in the following detailed description, which refers to the drawings in which the following applies: Fig. 1 is a representation of a vehicle with a processing system for providing a privacy-friendly relative position of the vehicle to a user device according to one or more embodiments; Fig. 2 is a block diagram of the processing system of Fig. 1. To provide a privacy-friendly relative position of the vehicle from Fig. 1 for the user device of Fig. 1 according to one or more embodiments; Fig. 3A is a sequence diagram of a one-sided distance measurement method; Fig. 3B is a sequence diagram of a double-sided distance measurement method; Fig. Figure 4 is a flowchart of a procedure for providing a privacy-friendly relative position of the vehicle from Fig. 1 according to one or more embodiments; and Fig. Figure 5 is a block diagram of a processing system for the implementation of one or more embodiments described here. DETAILED DESCRIPTION

[0026] The following description is for illustrative purposes only. It should be understood that in the drawings, corresponding reference numerals denote identical or equivalent parts and features. As used here, the term "module" refers to processing circuits that may include an application-specific integrated circuit (ASIC), an electronic circuit, a processor (common, dedicated, or as a group), memory executing one or more software or firmware programs, a combinational logic circuit, and / or other suitable components that provide the described functionality.

[0027] One or more of the embodiments described here relate to the provision of a privacy-friendly relative position of a vehicle.

[0028] Vehicles may contain one or more communication systems for communicating with other devices, other vehicles, and / or similar entities, including combinations and / or multiple systems. For example, a vehicle may include a system for communicating with a user device, such as a smartphone, laptop, tablet computer, wearable computer (e.g., a smartwatch), and / or similar device, including combinations and / or multiple systems. In such cases, the user device may provide information to the vehicle's communication system for use by the vehicle and its systems. Similarly, the vehicle may provide information to the user device for use by the user device. One type of information exchanged between the user device and the vehicle's communication system is location information (e.g., the location of the user device and / or the location of the vehicle).In one scenario, the user device (e.g., a smartphone) can serve as a "virtual key," replacing a traditional key. A virtual key can be used to lock / unlock the vehicle, start the vehicle (locally or remotely), and operate vehicle systems (e.g., lowering windows, activating / deactivating a security alarm, controlling an infotainment system, navigating / driving the vehicle, and / or similar functions, including combinations and / or multiple functions). In such cases, the location information of the vehicle and the user device is used to verify the virtual key and / or to activate some or all of its functions. For example, the virtual key can be prevented from starting the vehicle if it moves further than a certain distance away.Accordingly, virtual keys use location information about the vehicle and / or the user device.

[0029] Location information can be determined, for example, through one-way or two-way localization. In one-way localization, one device (e.g., the vehicle's communication system) precisely locates the other device (e.g., the user device). In two-way localization, both devices (e.g., the vehicle's communication system and the user device) precisely locate each other. While these approaches are suitable for the intended purpose, they do not allow for the approximate determination of the location of one device while simultaneously precisely locating the other.

[0030] One or more of the embodiments described here address these and other shortcomings by providing a privacy-friendly localization approach that accurately locates one device while simultaneously approximating the location of the other device. Such an approach can be useful in the case of virtual keys when it is desirable for the vehicle to precisely locate the user device, while the user device only needs to know the approximate location of the vehicle (e.g., the vehicle's communication system) without knowing its exact location. Approximating the location of a vehicle (e.g., the vehicle's communication system) involves determining a relative location of the vehicle, which does not precisely define the vehicle's location.

[0031] The embodiments described here offer several techniques for determining the privacy-friendly relative location of a vehicle. One or more embodiments use a combination of techniques, such as adding noise to distance measurement data, geometric configuration information transmitted from one device to another, inserting delays in the transmission of distance measurement information, and / or similar techniques, including combinations and / or multiples thereof. These techniques are described in detail here.

[0032] The functionality of a vehicle employing one or more of the embodiments described herein is improved. For example, specifying an imprecise location of the vehicle enhances its security by preventing a user device from disclosing the vehicle's exact location to third parties (e.g., via a malicious third-party application running on the user device). This reduces or eliminates potential cybersecurity threats and / or malicious attacks on the vehicle, as the vehicle's precise location is obscured. Further benefits and advantages are apparent to experts.

[0033] Fig. Figure 1 is a representation of a vehicle 100 with a processing system 102 for providing a privacy-friendly relative position of the vehicle to a user device 104 according to one or more embodiments.

[0034] Vehicle 100 can be a car, truck, van, bus, motorcycle, boat, or other vehicle. According to one embodiment, Vehicle 100 includes an internal combustion engine powered by gasoline, diesel, or a similar fuel. According to another embodiment, Vehicle 100 is a hybrid electric vehicle powered partially or entirely by electricity. According to yet another embodiment, Vehicle 100 is an electric vehicle powered by electricity. According to one or more embodiments, Vehicle 100 is an autonomous or semi-autonomous vehicle. An autonomous vehicle is a vehicle capable of driving itself. A semi-autonomous vehicle is a vehicle that has certain autonomous functions (e.g., self-parking, lane keeping, etc.) but does not have full autonomous control.

[0035] According to one or more embodiments, the vehicle 100 comprises the processing system 102. The processing system 102 is an example of a "communication system" as described herein and can communicate directly or indirectly with the user device 104. The processing system 102 can use any suitable technology for communication with the user device 104, such as Bluetooth, WiFi, infrared, radio frequency (RF), and / or similar technologies, including combinations and / or multiple technologies thereof.

[0036] The user device 104 can be any suitable device for communicating with the processing system 102. For example, the user device 104 can be a smartphone, a laptop, a tablet computer, a portable computing device (e.g., a smartwatch), and / or similar devices, including combinations and / or multiple devices thereof. According to one or more embodiments, the user device 104 can execute a software application that provides virtual key functions for the vehicle.

[0037] Further features of the processing system 102 will now be described with reference to Fig. 2 described

[0038] Fig. Figure 2 is a block diagram of the processing system 102. Fig. 1. To provide a privacy-friendly relative position of the vehicle from Fig. 1 for the user device of Fig. 1 according to one or more embodiments. The processing system 102 comprises a processing device 202, a memory 204, a communication engine 210, and a localization engine 212. It should be noted that the processing system 102 can be any device capable of communicating with the user device 104 and / or performing one or more of the localization techniques described herein. For example, the processing system 102 can be a device installed in or otherwise connected to the vehicle 100. As another example, the processing system 102 can be a smartphone, a tablet computer, a laptop computer, a desktop computer, a portable computing device, and / or the like, including combinations and / or multiples thereof.

[0039] The processing device 202 is any suitable processing circuit for processing data (e.g., location data and / or communication data) and / or instructions. The processing device 202 is an example of one or more of the processing devices 521 from Fig. 5, which are described in more detail here.

[0040] Memory 204 is any suitable device for storing data and / or instructions. Memory 204 is an example of system memory 522, random access memory 523, and / or read-only memory 524. Fig. 5, as described in more detail herein.

[0041] The communication engine 210 enables communication between the processing system 102 (and / or other devices / systems of the vehicle) and the user device 104. For example, the communication engine 210 uses one or more antennas 220a, 220b, 220c (collectively, "antennas 220") to wirelessly transmit data to and from the user device 104. The localization engine 212 enables the precise location of the user device 104 to be determined and generates an approximate location of the vehicle 100, which can be transmitted to the user device 104 or otherwise provided. The features and functions of the communication engine 210 and the localization engine 212 are now described with reference to the Fig. 3A - 4 described in more detail.

[0042] In the Fig. 3A and Fig. Section 3B describes further details of the Communication Engine 210 and the Localization Engine 212. The Localization Engine 212 can perform localization (or "ranging" or "distance measurement") techniques to determine the distance between the vehicle 100 and the user device 104. For example, the Localization Engine 212 can perform one-sided or two-sided distance measurement. One-sided and two-sided distance measurement are distance measurement techniques commonly used in navigation, surveying, and communication systems. Fig. 3A is a sequence diagram 300 of a one-sided distance measurement method. In one-sided distance measurement, the distance between two points (e.g., one of the vehicle's antennas 220 and the user device 104) is measured by sending a signal from one point (transmitter) to another point (receiver) and then calculating the distance between these points based on the time the signal takes to transmit. Fig. Figure 3B is a sequence diagram 310 of a two-sided distance measurement method. Two-sided distance measurement (or two-way distance measurement) improves accuracy by measuring the time a signal takes to travel from the transmitter to the receiver and back. One-sided and two-sided distance measurement are now described in more detail.

[0043] An initiator (e.g., user device 104) (in Fig. 3A and Fig. 3B (designated as "Device A") has at least one antenna (also referred to as "distance anchor" or "anchor"). A responder (e.g., the processing system 102 of vehicle 100) has multiple antennas / distance anchors (e.g., antennas 220). Fig. 3A and Fig. Figure 3B shows an exchange between device A and an anchor of device B. Device A (e.g., user device 104) sends (Tx) an initial query message P1 to device B (e.g., processing system 102). Each anchor (e.g., antennas 220) on device B (e.g., processing system 102) receives (Rx) and processes the initial query message P1 and responds (e.g., sends (Tx)) with a reply M2. Device A may process the replies from the multiple anchors of device B and send (e.g., sends (Tx)) a reply message M3 back to device B. For each exchange between device A and device B, the following values ​​exist: a value T reply2 (at device A), a value T round1(at device A), a value T round2 (for device B) and a value T reply1 (in device B). According to one or more embodiments, the localization engine 212 calculates the value T. round2 and the value T reply1 Device A sends its distance information to device B, allowing device B to determine the distance of device A relative to the anchors (e.g., antennas 220) of device B. The localization engine 212 performs trilateration to determine the location of device A relative to device B.

[0044] In one-sided or two-sided distance measurement, the localization engine 212 calculates a travel time that is used to determine the distance between device A (e.g., the user device 104) and one or more antennas 220 of device B (e.g., the processing system 102).

[0045] For one-sided distance measurement, the transit time is determined using the following equation: Tprop=(Tround−Treply) / 2.

[0046] For two-sided distance measurement, the transit time is determined using the following equation: Tprop=Tround1×Tround2−Treply1×Treply2Tround1×Tround2+Treply1×Treply2.

[0047] Once the localization engine 212 has calculated the runtime, the localization engine 212 can use the runtime to determine the distance between device A (e.g., the user device 104) and one or more of the antennas 220 of device B (e.g., the processing system 102).

[0048] The various components, modules, engines, etc., that are in Fig. The engines described in Section 2 (e.g., the communication engine 210 and / or the localization engine 212) can be implemented as instructions stored on a computer-readable storage medium, as hardware modules, as specialized hardware (e.g., application-specific hardware, application-specific integrated circuits (ASICs), application-specific specialized processors (ASSPs), field-programmable gate arrays (FPGAs), as embedded controllers, hard-wired circuits, etc.), or as a combination or combinations thereof. The engine(s) described here can consist of a combination of hardware and programming. The programming can consist of processor-executable instructions stored in physical memory, and the hardware can include the processing device 202 for executing these instructions. Thus, a system memory (e.g.,The memory (204) stores program instructions which, when executed by the processing device (202), implement the engines described here. Other engines can also be used to incorporate other features and functions, which are described in other examples here.

[0049] Further aspects and features of the Communication Engine 210 and the Localization Engine 212 are discussed here with reference to the Fig. 3A - 4 described.

[0050] Fig. Figure 4 is a flowchart of a method 400 for providing a privacy-friendly relative location of the vehicle 100 according to one or more embodiments. The method 400 can be performed with any suitable system or device. For example, the method 400 can be performed with the processing system 102 of Fig. 1 and Fig. 2, with the processing system 500 from Fig. 5 and / or similar, including combinations and / or several thereof. Procedure 400 is now carried out with reference to Fig. 1 and Fig. 2 described, but is not limited to that.

[0051] In block 402, the processing system 102 of vehicle 100 receives a handshake request from user device 104. That is, the handshake request is initiated by user device 104, for example by an operator of vehicle 100 who initializes an application for a virtual key on user device 104.

[0052] In block 404, the processing system 102 of the vehicle 100 (e.g., using the localization engine 212) determines an exact location of the user device 104. The exact position of the user device 104 is determined, for example, using the one-sided or two-sided distance measurement described here.

[0053] In block 406, the processing system 102 of vehicle 100 (e.g., using the localization engine 212) generates the imprecise position of vehicle 100. The precise position of vehicle 100 is more accurate than the imprecise position. Several techniques for determining the imprecise position of vehicle 100 are described here.

[0054] According to one or more embodiments, generating the inaccurate position of vehicle 100 involves applying noise to make the position of vehicle 100 inaccurate. The application of noise can be carried out, for example, as follows: First, a value T is applied. reply1 , a value T round1 , a value T round2 and a value T reply2 determined. Then the value T is used. reply1 and the value T round2 A noise factor is applied in each case. According to one or more embodiments, the application of the noise factor to the value T involves reply1 and the value Tround2 the subtraction of the noise factor from the value T reply1 and the addition of the noise factor to the value T round2 as follows: TReply 1*=TReply 1−δ, TRound 2*=TRound 2+δ, where δ is the noise factor. Finally, the inaccurate position of vehicle 100 is calculated at least partially based on the noise factor applied to each of the values ​​T. reply1 and T round2 was applied.

[0055] According to one or more embodiments, noise can be added by setting the noise factor to the value T. reply1 applied and then the value T reply1 is transmitted to user device 104. User device 104 verifies the received value (e.g., a value T). reply1 with added noise) and then uses it to calculate an approximate (or inaccurate) distance to vehicle 100.

[0056] According to one or more embodiments, the generation of the vehicle's inaccurate position is based at least partially on a time difference of arrival (TDoA) or a phase difference of arrival (PDoA) relative to a plurality of antennas (e.g., the antennas 220) of the vehicle 100. TDoA and PDoA can be used for localization to determine the position of the antennas 220 relative to the user device 104 based on measurements of differences in signal characteristics at multiple receivers (e.g., several of the antennas 220). TDoA determines the position of a signal source by measuring the difference in the signal's arrival times at several of the antennas 220 (e.g., antenna 220a and antenna 220b), which are spatially separated from one another. To perform TDoA-based localization, the user device 104 transmits a signal that is received by several antennas 220 (e.g.The signal is received by antenna 220a and antenna 220b. Due to their spatial separation, the multiple antennas 220 receive the signal at slightly different times. The difference in the arrival times of the signal at the multiple antennas 220 is measured, and using the known positions of the antennas 220 and the measured time differences, the position of the source signal can be calculated (e.g., by solving hyperbolic equations derived from the time differences). PDoA determines the position of a signal source by measuring the phase difference of the signal at multiple receivers (e.g., multiple antennas 220). To perform PDoA, the user device 104 transmits a signal that is received by multiple antennas 220 (e.g., antenna 220a and antenna 220b). The phase difference between the signals received by the multiple antennas 220 is measured.Based on the known positions of the multiple antennas 220 and the measured phase differences, the position of the source signal can be calculated (e.g., by solving equations that relate the phase differences to the geometry of the multiple antennas 220). To generate the exact position, noise can be added to the processes for either TDoA or PDoA, so that the resulting position is imprecise.

[0057] According to one or more embodiments, generating the inaccurate position of the vehicle 100 involves generating noisy information about the geometric arrangement of a plurality of the vehicle's antennas. That is, noise is added to the geometric information (e.g., position) of the antennas 220. According to one or more embodiments, this noisy information about the geometric configuration of the antennas 220 is sent to the user device 104 instead of changing the information over time.

[0058] According to one or more embodiments, the inaccurate location of the vehicle 100 is based at least partially on the responses of a subset of the antennas 220, including the time spent deciding which of the plurality of antennas should be included in the subset. For example, all antennas 220 remain switched on for reception to avoid deteriorating the localization on the vehicle side. However, only a subset of the antennas 220 is used to respond to the user device 104. For example, two or three antennas (of the antennas 220) with the least favorable geometric configuration respond to the user device 104.To locate vehicle 100, the user device 104 must find a way to place the vertices of a predefined triangle (segment), corresponding to the responding antennas 220, on several concentric circles, which can result in multiple positions, thus preventing the user device 104 from determining the exact position of vehicle 100. The antennas 220 used to respond include in their message of final data to the user device 104 a time interval that was consumed in deciding which antenna 220 should respond, and which corresponds to the value T. reply1 is added. In some embodiments, an additional noise factor can be added at time (e.g., to the value T). reply1 ) will be added to make the position of vehicle 100 even less accurate.

[0059] According to one or more embodiments, generating the inaccurate position of the vehicle 100 involves generating a random delay for each of the antennas 220 of the vehicle 100. In this case, each of the antennas 220 remains active, but each can add a random delay (e.g., by skipping its time slots by a certain time interval) and send a correction factor in a message about the final data to the user device. In some embodiments, noise can be added to the correction factors described herein for one or more of the antennas 220.

[0060] In block 408, the processing system 102 of the vehicle 100 (e.g. using the localization engine 212) transmits the inaccurate location of the vehicle 100 from the processing system 102 to the user device 104.

[0061] In block 410, a function of a virtual key on user device 104 is activated, at least partially, based on the precise location of user device 104 and the imprecise location of vehicle 100. User device 104 can then interact with vehicle 100 using the virtual key function without knowing the vehicle's precise location. This improves the security of vehicle 100 by preventing user device 104 from disclosing the vehicle's precise location to third parties (e.g., via a malicious third-party application running on user device 104).

[0062] According to one or more embodiments, instead of the user device 104 generating the inaccurate position of the vehicle 100 based on noisy information sent by the vehicle 100, the vehicle 100 can generate its own inaccurate position and send it to the user device 104. In another embodiment, the user device 104 can mask the exact position of the vehicle 100 to generate an inaccurate position. The inaccurate location of the vehicle 100 is then shared with third-party applications running on the user device 104, without sharing the vehicle 100's exact location with these third-party applications. This also improves the security of the vehicle 100 by preventing the user device 104 from disclosing the vehicle 100's exact location to third parties (e.g., via a malicious third-party application running on the user device 104).

[0063] Additional processes can also be included, and it should be understood that the in Fig. The processes shown in section 4 are illustrations, and it should be understood that other processes can be added, or existing processes can be removed, modified, or rearranged without departing from the scope of this disclosure. It should also be understood that the processes shown in Fig. The processes shown in section 4 can be implemented as programmatic instructions stored on a non-transitory, computer-readable storage medium, which, when read by a processor (e.g., the processing device 202 of Fig. 2, the processor(s) 521 of Fig. 5 and / or similar, including combinations and / or several thereof) of a computer system (e.g., the processing system 102 of Fig. 1 and Fig. 2, the processing system 500 of Fig. 5 and / or similar, including combinations and / or several thereof) are executed, causing the processor to perform the processes described herein.

[0064] It is understood that one or more of the embodiments described here can be implemented in conjunction with any other type of computer environment known today or developed later. Fig.Figure 5, for example, shows a block diagram of a processing system 500 for implementing the techniques described herein. According to one or more embodiments described herein, the processing system 500 is an example of a cloud computing node in a cloud computing environment. In examples, the processing system 500 has one or more central processing units (also referred to as "processors" or "processing resources" or "processing devices") 521a, 521b, 521c, etc. (collectively or generally referred to as processor(s) 521 and / or processing device(s)). In aspects of this disclosure, each processor 521 may contain a RISC (Reduced Instruction Set Computer) microprocessor. The processors 521 are connected via a system bus 533 to a system memory 522 and / or various other components.The system memory 522 can contain one or more temporary and / or permanent memory modules, such as a random-access memory (RAM) 523, a read-only memory (ROM) 524, and / or similar devices, including combinations and / or multiples thereof. The system bus 533 can contain a basic input / output system (BIOS) that controls certain basic functions of the processing system 500.

[0065] Also shown are an input / output (I / O) adapter 527 and a network adapter 526, which are connected to the system bus 533. The I / O adapter 527 can be a SCSI (Small Computer System Interface) adapter that communicates with a hard disk 535 and / or a storage device 536 or another similar component. The I / O adapter 527, the hard disk 535, and the storage device 536 are collectively referred to here as mass storage 534. The operating system 540 for execution on the processing system 500 can be stored in the mass storage 534. The network adapter 526 connects the system bus 533 to an external network 538 and enables the processing system 500 to communicate with other such systems.

[0066] A display (e.g., a screen) 539 is connected to the system bus 533 via a display adapter 532, which may include a graphics adapter to improve the performance of graphics-intensive applications and a video controller. In one aspect of this disclosure, the adapters 526, 527, and / or 532 may be connected to one or more I / O buses that are connected to the system bus 533 via an intermediate bus bridge (not shown). Suitable I / O buses for connecting peripheral devices such as hard disk controllers, network adapters, and graphics adapters typically include common protocols such as Peripheral Component Interconnect (PCI). Additional input / output devices are connected to the system bus 533 via a user interface adapter 528 and the display adapter 532. A keyboard 529, a mouse 530 and a speaker 531 can be connected to the system bus 533 via a user interface adapter 528, which e.g.It may include a super I / O chip that integrates multiple device adapters into a single integrated circuit.

[0067] In some aspects of the present disclosure, the processing system 500 includes a graphics processing unit (GPU) 537. The graphics processing unit 537 is a special electronic circuit used to manipulate and modify memory in order to accelerate the creation of images in a frame buffer intended for output to a display. In general, the graphics processing unit 537 is very efficient in computer graphics and image processing and has a highly parallel structure, which makes it more effective than general-purpose CPUs for algorithms in which the processing of large blocks of data is carried out in parallel.

[0068] Thus, as configured here, the processing system 500 comprises processing capacities in the form of processors 521, storage capacities including system memory 522 and mass storage 534, input means such as keyboard 529 and mouse 530, and output means including speakers 531 and display 539. In some aspects of the present disclosure, a portion of the system memory 522 and the mass storage 534 jointly store the operating system 540 in order to coordinate the functions of the various components represented in the processing system 500.

[0069] The terms "a" and "an" do not imply a limitation of quantity, but rather denote the presence of at least one of the mentioned items. The term "or" means "and / or," unless the context clearly indicates otherwise. When the entire description refers to "an aspect," this means that a specific element (e.g., a feature, a structure, a step, or a property) described in connection with that aspect is contained in at least one of the aspects described here and may or may not be present in other aspects. It goes without saying that the described elements can be combined in any suitable way across the various aspects.

[0070] When an element such as a layer, film, foil, area, or substrate is described as lying "on" another element, it can lie directly on top of the other element, or there can be intermediate elements. Conversely, when an element is described as lying "directly on" another element, there are no intermediate elements.

[0071] Unless otherwise stated herein, all testing standards are the latest standard in force on the filing date of this application or, if priority is claimed, on the filing date of the earliest priority application in which the testing standard appears.

[0072] Unless otherwise defined, the technical and scientific terms used herein have the same meaning as generally understood by experts in the field of the present disclosure.

[0073] While the above disclosure has been described with reference to exemplary embodiments, those skilled in the art understand that various modifications can be made and their elements replaced by equivalents without deviating from the scope of application. Furthermore, many modifications can be made to adapt a particular situation or material to the teachings of the disclosure.

Claims

[1] Computer-implemented method (400) for providing an inaccurate location of a vehicle (100) to a user device (104), wherein the method (400) comprises: Receiving (402) a handshake request in a processing system (102) of the vehicle (100), wherein the handshake request is initiated by the user device (104) assigned to an operator of the vehicle; Determining (404) an exact location of the user device (104) by the processing system (102) of the vehicle (100); Generating (406) the inaccurate location of the vehicle (100) by the processing system (102) of the vehicle (100); Transmitting (408) the inaccurate location of the vehicle (100) from the processing system (102) to the user device (104); and Activating (410) a function of a virtual key of the user device (104) based at least partially on the exact location of the user device (104) and the imprecise location of the vehicle (100). [2] Computer-implemented method (400) according to claim 1, wherein generating (406) the inaccurate location of the vehicle (100) comprises the application of a noise factor. [3] Computer-implemented method (400) according to claim 2, comprising generating (406) the inaccurate location of the vehicle (100): Determining a value T reply1 , of a value T round1 , of a value T round2 and a value T reply2 , Applying the noise factor to the value T reply1 and the value T round2 , and Calculating the imprecise location of the vehicle (100) at least partially based on each of the values ​​T reply1 and T round2 applied noise factor. [4] Computer-implemented method (400) according to claim 3, wherein the application of the noise factor to each of the values ​​T reply1 and T round2 subtracting the noise factor from the value T reply1 and adding the noise factor to the value T round2 includes. [5] Computer-implemented method (400) according to claim 2, wherein generating (406) the inaccurate location of the vehicle (100) involves applying the noise factor to the value T reply1 and the transmission of a resulting noisy value T reply1 to the user device (104), wherein the user device (104) provides the noisy value T reply1 applied to calculate an approximate distance to the vehicle (100). [6] Computer-implemented method (400) according to claim 1, wherein the generation (406) of the inaccurate location of the vehicle (100) is based at least partially on a time-of-arrival difference (TDoA) or a phase-of-arrival difference (PDoA) relative to a plurality of antennas (220) of the vehicle (100) and on noise added to the results of TDoA and / or PDoA. [7] Computer-implemented method (400) according to claim 1, wherein generating (406) the inaccurate location of the vehicle (100) comprises generating noisy information about the geometric arrangement of a plurality of antennas (220) of the vehicle (100). [8] Computer-implemented method (400) according to claim 1, wherein the inaccurate location of the vehicle (100) is based at least partially on responses from a subset of a plurality of antennas (220) of the vehicle (100), including a time period consumed to decide which of the plurality of antennas (220) constitute the subset. [9] Computer-implemented method (400) according to claim 1, wherein generating (406) the inaccurate location of the vehicle (100) comprises generating a random delay for each of a plurality of antennas (220) of the vehicle (100). [10] Computer-implemented method (400) according to claim 1, wherein the exact location of the vehicle (100) is more precise than the imprecise location of the user device (104).

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