Adaptive Quick Response Code Generation and Display Method

Abstract

A method for dynamically generating a customized quick-response code (QR code) for scanning by a moving vehicle during a vehicle-dealer transaction involves capturing parameters from the vehicle-mounted camera via a sensor suite at an infrastructure node, communicating with a dealer back office, as the vehicle approaches the infrastructure node. These parameters include the camera's distance and approach angle relative to the infrastructure node. The method also involves dynamically reshaping a base QR code in response to these parameters using a processor at the infrastructure node, thereby generating a customized QR code with a modified shape, size, and / or data capacity relative to the base QR code.The customized QR code is then displayed on the screen as the moving vehicle approaches the infrastructure node, allowing the camera to scan the customized QR code during the transaction.

Description

Introduction

[0001] The present disclosure relates to automated systems and methods for supporting quick-response code scanning (QR code scanning) in a vehicle using one or more onboard cameras. As a person skilled in the art understands, QR codes are two-dimensional barcodes that store information, such as a website address, plain text, contact information, and the like. The information is converted into binary data and then encoded into a pixelated black-and-white pattern. In a typical QR code, three large squares are arranged in the corners of the QR code to enable the QR code to be identified and aligned by a QR code scanner, such as a smartphone camera. Smaller squares of the QR code are used to help correct distortion.A QR code also contains version information corresponding to the data capacity of the QR code, and data and error correction keys that form encoded information and associated error correction codes.

[0002] To scan a QR code using a smartphone or other dedicated QR code reader, the reader's camera sees an image of the displayed QR code. The reader's image processing software then locates the QR code within the camera's field of view and aligns it before extracting the binary data mentioned above from the displayed pattern of squares. If necessary, error correction is applied before the reader's onboard processor decodes the information. Depending on the type of encoded data, the reader can respond to the decoded information by opening a website, displaying text, adding contact information, or performing a variety of other possible actions. Description

[0003] This document discloses systems and methods for enabling a camera mounted on a moving vehicle to read a Quick Response (QR) code from a display screen. In a representative scenario, the display screen may be connected to or located alongside a stationary infrastructure node, such as a kiosk, shop, toll booth, roadside stand, or other drive-through or drive-by building or structure. Traditionally, a camera is positioned correctly, facing the QR code, so that the camera can scan and read a displayed QR code. However, in a usage scenario where the vehicle and its mounted camera are moving relative to the display screen, adjusting the camera's position for this purpose is challenging.However, using the present teachings, the adapted QR code generation and presentation of it on the display screen is optimized based on the dynamically changing location of the vehicle / camera, so that the vehicle-mounted camera is able to read the QR code much earlier and more accurately than would otherwise be possible in the absence of the present teachings.

[0004] In particular, this document discloses a method for dynamically generating a customized QR code for scanning by a vehicle-mounted camera on a moving vehicle. The method involves capturing camera parameters via a sensor suite of an infrastructure node as the moving vehicle approaches the infrastructure node. The parameters include at least the vehicle's distance and approach angle relative to the infrastructure node. The method also involves dynamically reshaping a base QR code, such as a typical square, forward-facing QR code, in response to the parameters. This action, performed by a processor on the infrastructure node, generates the customized QR code, i.e., one with a modified shape, size, and data capacity relative to the base QR code.Additionally, the procedure involves transmitting a display control signal to a display screen at the infrastructure node to cause the display screen to present the adapted QR code as the moving vehicle approaches the infrastructure node.

[0005] One aspect of the disclosure involves a method for dynamically generating a customized QR code for scanning by a moving vehicle during a vehicle-dealer transaction. The method may involve capturing parameters from the vehicle-mounted camera via a sensor suite on an infrastructure node, with the node communicating with a dealer back office. This occurs as the moving vehicle approaches the infrastructure node. The parameters include the distance and approach angle of the vehicle-mounted camera relative to the infrastructure node. The method involves dynamically reshaping a base QR code in response to these parameters via a processor on the infrastructure node to generate a customized QR code with a modified shape, size, and / or data capacity relative to the base QR code.Additionally, the procedure may involve transmitting a display control signal to a display screen of the infrastructure node and displaying the adapted QR code on the display screen in response to the display control signal as the moving vehicle approaches the infrastructure node, to allow the vehicle-mounted camera to scan the adapted QR code during the vehicle-dealer transaction.

[0006] Displaying the adapted QR code on the display screen may involve generating a pixelated image that is distorted in a two-dimensional (2D) frame of reference of the display screen.

[0007] The acquisition of the parameters may involve the use of one or more infrastructure cameras mounted on or arranged with the infrastructure node, and wherein the sensor suite includes the one or more infrastructure cameras, possibly using a lidar sensor or radar sensor of the infrastructure node.

[0008] Acquiring the parameters in one or more embodiments involves using an ultra-wideband sensor (UWB sensor) of the infrastructure node.

[0009] The dynamic transformation of the square base QR code can involve performing a three-dimensional projection (3D projection) to a 2D projection via the infrastructure node's processor to ensure that a 2D plane of the adapted QR code, when displayed on the screen, is perpendicular to a focal axis of the vehicle-mounted camera.

[0010] The process can involve establishing a secure network connection between the infrastructure node and the dealer's back office, and then completing the vehicle-dealer transaction in response to a successful scan of the customized QR code by the vehicle-mounted camera. Implementations of the process also include establishing another secure network connection between the dealer's back office and a cloud-based payment service. In this case, completing the vehicle-dealer transaction involves transmitting payment information to the cloud-based payment service via the dealer's back office.

[0011] Dynamic transformation of the base QR code can involve calculating the required data capacity and resolution of the adapted QR code based on the relative position of the moving vehicle and the infrastructure node.

[0012] The method, in one or more implementations, may involve collecting historical transit data for a large number of vehicles encountered in the past and the infrastructure nodes. This includes recording the time and position of each vehicle encountered and training a support vector module (SVM) to identify successfully decoded and unsuccessfully decoded scans using the historical transit data. The method may also involve using the trained SVM to generate a predicted ideal size and data capacity for the customized QR code during the vehicle-dealer transaction, along with dynamically reshaping the base QR code, at least partially, using the predicted ideal size and data capacity.

[0013] This also discloses an infrastructure node capable of conducting a vehicle-dealer transaction with a moving vehicle. The infrastructure node may include a stationary structure, a sensor suite mounted on or associated with the stationary structure, a display screen, and a server communicating with a dealer back office. The server may include a processor and non-volatile, machine-readable storage medium ("memory") on which instructions are recorded. The execution of the instructions by the processor causes the server to dynamically generate a customized QR code for scanning by the moving vehicle with a vehicle-mounted camera and to acquire parameters of the vehicle-mounted camera via the sensor suite as the moving vehicle approaches the stationary structure.The parameters include a distance and an approach angle of the vehicle-mounted camera relative to the stationary structure.

[0014] The execution of the instructions in this embodiment also causes the processor to dynamically reshape a base QR code in response to the parameters passed through the processor, thereby generating a customized QR code with a modified shape, size, and / or data capacity relative to the base QR code. The processor then transmits a display control signal to the display screen to cause the display screen to show the customized QR code as the moving vehicle approaches the stationary structure, thus enabling the vehicle-mounted camera to scan the customized QR code during the vehicle-dealer transaction.

[0015] Another embodiment of the above-summarized method for dynamically generating a customized QR code involves capturing parameters from a vehicle-mounted camera via a sensor suite on an infrastructure node, communicating with a dealer back office, as the moving vehicle approaches the infrastructure node. The sensor suite comprises an infrastructure camera and one or more radar, lidar, or UWB sensors mounted on the infrastructure node. The parameters include the distance and approach angle of the vehicle-mounted camera relative to the infrastructure node. The method involves dynamically reshaping a base QR code in response to these parameters via a processor on the infrastructure node to generate a customized QR code with a modified shape, size, and / or data capacity relative to the base QR code.This action in turn involves performing a 3D projection to a 2D projection, via the processor of the infrastructure node, to ensure that a 2D plane of the adapted QR code, when displayed on the screen, is perpendicular to a focal axis of the vehicle-mounted camera.

[0016] The process also includes calculating the required data capacity and resolution of the adapted QR code based on the relative position of the moving vehicle and the infrastructure node, transmitting a display control signal to a display screen of the infrastructure node, and displaying the adapted QR code on the display screen in response to the display control signal as the moving vehicle approaches the infrastructure node to allow the vehicle-mounted camera to scan the adapted QR code during the vehicle-dealer transaction.

[0017] The aforementioned and other features and advantages of this disclosure will be readily apparent from the following detailed description of the illustrative examples and modes of implementation of the present disclosure in conjunction with the accompanying drawings and claims. Furthermore, this disclosure expressly includes combinations and subcombinations of the elements and features described above and below. Brief description of the drawings Fig. Figure 1 illustrates an exemplary operating scenario in which a moving vehicle reads a displayed customized Quick Response (QR) code from an infrastructure node, with properties of the customized QR code being calculated and applied by a server of the infrastructure node. Fig. Figure 2 illustrates the adaptation and display of QR codes according to one aspect of the revelation. Fig. Figure 3 is a flowchart that describes a procedure to enable a vehicle-mounted camera of a moving vehicle to scan / read a QR code from a display screen of an infrastructure node. Fig. Figure 4 is an illustration of the reprojection of an adapted QR code according to an aspect of the revelation. Fig. Figure 5 is a flowchart that describes a possible crowdsourcing procedure that can be used as part of the present strategy. Fig. Figure 6 is an illustration of a support vector machine (SVM) that can be used as an optional part of the present strategy. Fig. 7 and Fig. Figure 8 illustrates possible cloud-based payment processes that can be implemented according to disclosure aspects.

[0018] The present disclosure can be modified or implemented in alternative forms, representative embodiments of which are shown in the drawings and described in detail below. Inventive aspects of the present disclosure are not limited to the disclosed embodiments. Rather, the present disclosure is intended to cover alternatives that fall within the scope of the disclosure as defined by the appended claims. Detailed description

[0019] With reference to the drawings, where the same reference symbols in the different views refer to the same features, illustrates Fig. 1 a networked architecture 10 in which a vehicle 12 moves with respect to the infrastructure node 14, e.g., a roadside kiosk, toll booth, shop, or other drive-through / pass-by structure, which acts as a point of sale for a vehicle-dealer transaction. The vehicle 12 includes a vehicle-mounted camera 16, i.e., one or more cameras mounted on a rearview mirror, dashboard, or other forward-facing location on the vehicle body 18 of the vehicle 12. The camera 16 has a three-dimensional (3D) coordinate system or camera reference frame 11, the axes of which are nominally labeled X, Y, and Z.The vehicle 12 may also include a set of road wheels 20 coupled to the vehicle body 18, with an internal combustion engine, an electric traction motor, or another propulsion machine (not shown) providing torque to one or more of the road wheels 20 to drive the vehicle 12 toward the infrastructure node 14. Although the vehicle 12 is shown as a typical passenger car, other mobile platforms within the scope of this disclosure, such as trucks, boats, motorcycles, bicycles, agricultural equipment, etc., may be used without restriction.

[0020] In a possible use case, an operator of vehicle 12 may wish to trade with a potentially remote supplier or dealer via infrastructure node 14, for example, by purchasing goods or services or possibly by gaining access to a road, bridge, or other restricted location. For this purpose, camera 16 can be automatically focused on a display screen 22, which is connected to or located with infrastructure node 14 and displays a customized quick response (QR) code 24. To complete the aforementioned vehicle-dealer transaction, camera 16 is capable of detecting the customized QR code 24 within its field of view, zooming in on the customized QR code 24, and then scanning / reading multiple frames of the customized QR code 24.However, the movement of vehicle 12 relative to infrastructure node 14 can reduce the scanning speed and accuracy. The teachings presented here are therefore aimed at improving these and other aspects of a QR code-based vehicle-dealer transaction.

[0021] Particularly when vehicle 12 is moving relative to infrastructure node 14 and camera 16 attempts to read a displayed QR code located in front of and at an angle to vehicle 12, several factors are considered to optimize the QR code scanning task. For example, the position of camera 16 on vehicle 12 is usually fixed, or at least difficult to adjust in real time. The distance between camera 16 and infrastructure node 14 may be too great and / or at too steep an angle for fast and accurate scanning. The resolution of camera 16 may be too low. While QR codes have embedded special patterns to help reduce distortion and align with the patterns, problems can arise when attempting to view and scan a QR code from an angle.For example, the pixel resolution is significantly reduced at larger distances / angles, which in turn causes QR code reading errors.

[0022] To address these and other potential problems in the scenario of Fig. To address point 1, an infrastructure server 25 of infrastructure node 14 is configured to detect the position of camera 16 and optimize the generation and display of the customer-specific QR code 24 to reflect the detected position. This helps camera 16 to accurately detect and read the customer-specific QR code 24 earlier than would otherwise be possible without these lessons. The solutions presented here therefore provide an improved customer experience, for example in onboard mobile payment application scenarios, examples of which are given below with reference to Fig. 7 and Fig. 8 will be described.

[0023] To implement the solutions presented here, infrastructure node 14 of Fig. 1 is equipped with a sensor suite 26 capable of detecting relative positions between the vehicle 12 and the display screen 22, on which the customized QR code 24 is ultimately displayed. Resident sensors of the sensor suite 26 can include, but are not limited to, infrastructure cameras, lidar sensors, radar sensors, ultra-wideband (UWB) sensors, etc. The server 25 ultimately uses the detected relative positions to generate the customized QR code 24 in a customized form, e.g., size, angle, and / or data content, and displays the customized QR code 24 in its customized form on the display screen 22.

[0024] For this purpose, the vehicle 12 can communicate with the server 25 via a secure network connection 28, e.g., a communication link or channel such as a 5G cellular or WiFi connection. Likewise, a network connection 240 can be established between the server 25 and the sensor suite 26, while another secure network connection 260 can be established between the server 25 and the display screen 22. Since the sensor suite 26 and the display screen 22 can be located together with the infrastructure node 14, the network connections 240 and 260 can be hardwired in some embodiments, for example, via an Ethernet connection, or the network connections 240 and 260 can be implemented wirelessly. Wireless communication can be carried out according to suitable wireless protocols, such as the IEEE 802.11 protocols, Worldwide Interoperability for Microwave Access (WiMAX), and / or BLUETOOTH™.

[0025] Server 25 is in Fig. 1 schematically represented such that it has one or more processors (P) 27 and memory (M) 29, the latter comprising non-volatile memory or tangible non-volatile computer storage media / devices (read-only memory, programmable read-only memory, solid-state memory, random-access memory, optical memory, magnetic memory, etc.). The memory 29, on which computer-readable instructions may be recorded, which the method 100 of Fig. 3 embody, is capable of storing machine-readable instructions in the form of one or more software or firmware programs or routines, combinational logic circuit(s), input / output circuit(s) and devices, signal conditioning and buffer circuits, and other components that can be accessed by one or more processors to provide a described functionality.

[0026] Additionally, with respect to Server 25, the input / output circuitry and devices include analog-to-digital converters and associated devices that monitor inputs from sensors, such inputs being monitored at a preset sampling rate or in response to a trigger event. Software, firmware, programs, instructions, control routines, code, algorithms, and similar terms refer to sets of instructions executable by a controller, including calibrations and lookup tables. Each controller executes control routine(s) to provide desired functionality. Ultimately, Server 25 outputs a display control signal (arrow CC). 22 ) to the display screen 22 to cause the display screen 22 to display the reshaped adapted QR code 24 as set forth herein.

[0027] With brief reference to Fig. Figure 2 shows a basic QR code 24S as it might appear when displayed on the screen 22 in its normal, front-facing, square configuration. When such a basic QR code 24S is scanned by a smartphone 30 or another suitable code scanner, the camera (not shown) of the smartphone 30 is located near and facing the basic QR code 24S, typically with one plane of the smartphone 30 aligned parallel to a plane of the screen 22. The position of the smartphone 30 must therefore be adjusted for the smartphone 30's camera to successfully capture and decode the QR code 24S. The scenario of Fig. However, 1 would see that camera 16 (also for reference in Fig. (2 shown) is located at a considerable distance from the base QR code 24S (and at an approach angle to it). Therefore, the normal square appearance of the base QR code 24S is not read accurately and in a timely manner by camera 16 as it approaches infrastructure node 14.

[0028] As indicated by arrow A, the operation of server 25, as set forth herein, leads to a dynamic transformation of the base QR code 24S based on a detected relative position of camera 16. Using the present teachings and regardless of the approach angle of camera 16 relative to infrastructure node 14 as vehicle 12 approaches, the adapted QR code 24 (from the viewing perspective of camera 16) appears to have the same square shape, despite its distorted, resized and / or otherwise modified properties, as it actually appears on display screen 22.

[0029] With reference to Fig. 3. A procedure 100 can be executed as computer-readable instructions and stored in the memory 29 of server 25. Fig. 1. For illustrative clarity, the procedure 100 is described in the form of code segments or logic blocks, each of which is recorded by processor 27. Fig. 1 are executable to cause the server 25 to perform the described functions. In general, the procedure 100 is configured to dynamically generate the adapted QR code 24 for scanning by the moving vehicle 12 with at least one camera 16 mounted on the vehicle.

[0030] Starting at block B102, procedure 100 involves acquiring parameters from the vehicle-mounted camera 16 via the sensor suite 26 of infrastructure node 14 as the moving vehicle 12 approaches infrastructure node 14. As described below with reference to Fig. 7 and Fig. As noted in section 8, the infrastructure node 14 communicates with a merchant back office (BO) 42. The parameters include a distance and an approach angle (“relative position data 32”) of the camera 16 relative to the infrastructure node 14.

[0031] As part of block B102, the server receives 25 from Fig. 1. The relative position data 32 from the sensor suite 26 via the network connection 260, wherein the relative position data 32 describe a relative position of the vehicle 12 / the camera 16 and the infrastructure node 14, in particular the display screen 22. Using the relative position data 32, the server 25 acquires the position of the vehicle 12 and its connected camera 16. As the person skilled in the art understands, the sensor suite 26 has a position p0 (x0, y0, z0) using nominal x, y, z position coordinates, the vehicle 12 has a position p1 (x1, y1, z1), and the display screen 22 has a position p2 (x2, y2, z2). Thus, block B102 includes determining the 3D coordinates for the vehicle 12, the sensor suite 26, and the display screen 22 as p0, p1, and p2, respectively. The procedure 100 then proceeds to block B104.

[0032] Block B104 includes calculating the data capacity and resolution of the adapted QR code 24 using the relative position of the vehicle 12 / the camera 16. After calculating the data capacity and resolution, the procedure 100 proceeds to block B106.

[0033] In block B106, procedure 100 involves the dynamic transformation of the base QR code 24S in response to parameters via processor 27 of infrastructure node 14, in order to generate the adapted QR code 24. The adapted QR code 24 has a modified shape, size, and / or data capacity relative to the base QR code 24S, as described above.

[0034] In one or more embodiments, block B106 can involve performing a 3D projection to a two-dimensional projection (2D projection), while the processor 27 of the in Fig. The adapted QR code 24 shown on server 25 is projected from a 3D space into a 2D space. In the 3D space, i.e., the 3D position of camera 16 in free space, or in other words, the reference frame 11 of Fig. 1. Server 25 generates a QR code display plane and ensures that the display plane is perpendicular to the focal axis of camera 16. The QR code in this virtual 3D space is then rendered onto a 2D plane for display on the display screen 22. Fig. 1 projected, i.e. onto 2D space.

[0035] With brief reference to Fig. Block B106, number 4, involves generating a virtual QR code in 3D space, which is then plotted on a plane v in 3D space. The plane v is perpendicular to the line (p1, p2). The rectangle formed by the virtual QR code has four vertices (q1, q2, q3, q4). For a 3D-to-2D projection onto the 2D plane, with its vertices (q'1, q'2, q'3, q'4), the plane can be expressed in vector notation as: (p−p0)⋅n=0 where n is a normal vector to the plane v and p0 is a point on the plane v. The line (p1, q1) can also be expressed in vector notation, this time as: p=l0+ld d∈ℝ where l is a unit vector in the direction of the line, l0 is a point on the line, and d is a scalar in the real number space. The intersection point q1 can be calculated as follows: d=(p0−l0)⋅nl⋅n q1=l0+ld q2, q3, q4 can be calculated in a comparable manner. Procedure 100 then proceeds to block B108.

[0036] At block B108 of Fig. 3. Server 25 can receive the display control signal (CC). 22 ) from Fig. 1 is transmitted to the display screen 22 to cause the display screen 22 to display the reshaped adapted QR code 24. Unlike the standard QR code 24S from Fig. 2. The reshaped / reprojected nature of the adapted QR code 24 appears to camera 16 as a square rather than an arbitrary quadrilateral, although the same adapted QR code 24 appears as the latter to a viewer standing directly in front of the display screen 22. This appearance allows the vehicle-mounted camera 16 to scan the adapted QR code 24 during the vehicle-dealer transaction. Procedure 100 proceeds to block B110 after server 25 displays the adapted QR code 24.

[0037] Block B110 involves determining whether the QR code scan / vehicle dealer transaction initiated at Block B102 is complete. If so, procedure 100 transitions to Block B111. Procedure 100 transitions to Block B102 as an alternative.

[0038] Block B111 may involve the execution of a payment processing sequence, e.g., as in Fig. 7 and Fig. 8 shown and discussed below. If, for example, the QR code scanning process of blocks B102-B110 involves a financial transaction, such as the payment of a bridge or road toll, the purchase of goods or services, etc., then block B111 can be used to transfer currency between the owner of vehicle 12 and the owner of infrastructure node 14. Fig. To exchange 1. Procedure 100 is complete after the payment has been successfully processed.

[0039] With reference to Fig. 5. The above teachings can be extended using optional crowdsourcing, which can be used to identify an ideal size of the adapted QR code 24 and the data capacity for the vehicle 12 at a given distance through the infrastructure node 14 of Fig. To facilitate this, infrastructure node 14 can use crowd-sourced "passage" data to generate a supervised learning model. This model can help infrastructure node 14 more accurately predict the ideal QR code size and data capacity when a new / previously unfamiliar vehicle 12 visits the same location as a large number of previous / previously encountered vehicles 12.

[0040] As one possible approach, a procedure 200 to utilize such crowdsourcing advantages begins with block B202 by collecting historical transit data. For example, server 25 of Fig. 1. Record the time and position of each encountered vehicle 12 every time the sensor suite 26 (i) detects a vehicle 12, (ii) initiates a vehicle-dealer transaction in the cloud, and (iii) completes the vehicle-dealer transaction in the cloud. Procedure 200 then proceeds to block B204.

[0041] Block B204 may involve calculating the data capacity and resolution of the adapted QR code 24. This action involves representing the data in a high-dimensional space, where the dimensions in such a space may include vehicle positions, QR code display size, QR code data capacity, decoding success, and / or other dimensions. After calculating the data capacity and resolution of the adapted QR code 24, procedure 200 proceeds to block B206.

[0042] At block B206, server 25 can train a support vector module (SVM) to identify a hyperplane that separates data samples into at most two distinct sets: (i) successful decoding / decoded and (ii) unsuccessful decoding / not decoded. As a person skilled in the art understands, an SVM is an exemplary supervised learning strategy for classifying samples. Once the hyperplane of the SVM is determined, new data points can be classified by determining the side of the hyperplane to which the point falls. Procedure 100 proceeds to block B208 once the SVM has been trained.

[0043] With brief reference to Fig. Figure 6 shows a high-dimensional space in an SVM 30. Data points 32A and 32B are located on either side of the hyperplane 34 mentioned above. In this example, data points 32A correspond to the phrase "unsuccessful decoding / not decoded." Data points 32B correspond to the phrase "successful decoding / decoded." In SVM 30, x represents the position of vehicle 12, y is the QR code size, and z is the data capacity. Additionally, a polynomial kernel (k) can be used in the SVM, i.e.,: k(xi,xj)=(xi⋅xj+1)d where x i , x j Given two data sets, each point can have three dimensions (vehicle position, QR code size, data capacity) and d is the degree of the polynomial.

[0044] With renewed reference to Fig. Block B208 includes performing a real-time classification of new data samples using the trained SVM from Block B206. When vehicle 12 arrives at the same transit location, the SVM model can be used by server 25 to predict the ideal size of the adapted QR code 24 and its data capacity. Together, the predicted values ​​help server 25 to accurately scan and quickly decode the adapted QR code 24 as vehicle 12 approaches infrastructure location 14.

[0045] For each transit event using procedure 200, the infrastructure node can store 14 recorded sensor data, QR code states, and system states in memory 29 ( Fig. 1) for subsequent crowdsourcing processing. Representative sensor data may include the current position of vehicle 12 (distance and angle relative to the infrastructure, etc.) and the speed / acceleration of vehicle 12. The QR code states may include QR code display size and data capacity, as mentioned above. System states may include a binary classification, e.g., "decoded" and "undeciphered," as discussed above in Block B206.

[0046] With reference to Fig. 7 and Fig. Figures 8 and 50 illustrate respective cloud-based payment processes, while figures 40 and 50 show two possible implementations for monetizing the basic vehicle-to-infrastructure transaction. Fig. 1. In the merchant back office (BO) path of Fig. 7. It is assumed that the vehicle 12 and a dealer BO 42 are mutually certified and that a secure element of the vehicle 12 stores payment account or credit card information. Additionally, a submission to a payment cloud, e.g., a payment processor or payment gateway such as PayPal, etc., is made, and a security protocol such as SPAKE2 is used.

[0047] In an exemplary sequence beginning with step (1), the infrastructure node 14 can request a QR code from the dealer BO 42 for a specific good, service, or other service, as specified by the communication link AA, with the dealer BO 42 returning the QR code to the infrastructure node 14 via a communication link BB at step (2). At step (3), the infrastructure node 14 determines the location of the vehicle 12 using the sensor suite 26 ( Fig. 1), as outlined above, via a communication loop CC and then displays the optimized / reshaped adapted QR code 24 on the display screen 22 via the communication link DD at step (4), the link DD being analogous to the link 240 of Fig. 1 is.

[0048] The vehicle 12 then scans and decodes the adapted QR code 24 using its camera 16 at step (5) via a communication loop EE. Step (6) may involve user authorization of the payment, possibly via an in-vehicle touchscreen confirmation or a confirmation code, via the communication loop FF. The user's card information and the merchant server entry point (e.g., a URL) are sent to a vehicle BO 41 at step (7) via the communication link GG, e.g., using SPAKE2 or another suitable security protocol.

[0049] Continuing with the discussion of Fig. 7. The vehicle BO 41 can send the card information to an entry point of the merchant BO 42 via communication link HH at step (8), with the merchant BO 42 transmitting the information to a cloud-based payment service 44 via communication link II at step (9). The service 44 can then confirm the successful payment at steps (10a) and (10b), for example, by transmitting a payment receipt to the infrastructure node 14 via communication link JJ at step (10a) and to the vehicle BO 41 via communication link KK at step (10b). The vehicle BO 41 can then confirm the transaction with the user at step (10c) via communication link LL by transmitting the payment receipt to the vehicle 12. As with communication links 28, 240, and 260 of Fig. 1. The various connections / loops AA-LL can be wireless communication paths that are established and coordinated according to suitable wireless protocols, such as an IEEE-802.11 protocol, Worldwide Interoperability for Microwave Access (WiMAX), BLUETOOTH™, BLUETOOTH LOW ENERGY (BLE), etc.

[0050] Referring to the cloud-based payment process, 50 of Fig. 8, which uses a vehicle back office (BO) path, the above assumptions are made, i.e., the vehicle 12 and a dealer BO 42 are mutually certified, a secure element of the vehicle 12 stores payment account or credit card information, a submission is made to the cloud-based payment service 44, and a suitable security protocol is used. Similarly, payment process 50 uses steps (1)-(7) and connections / loops AA-GG together with payment process 40. Fig. 7, where steps (1) - (7) are described above.

[0051] In step (8) of payment process 50, and in contrast to the sequence of process 40, the vehicle BO 41 can send the card information directly to the payment cloud system 44 via a communication link MM. The cloud-based payment service 44 can confirm the successful payment via a communication link NN at step (9) by transmitting a payment receipt to the vehicle BO 41. The vehicle BO 41 can then initiate communication with the merchant BO 41 via a security protocol (e.g., SPAKE2) at step (10) and confirm the transaction with the merchant BO 41 at step (11) via the secure connection, e.g., a communication link OO. The merchant BO 41 can transmit a similar confirmation to the infrastructure node 14 via a communication link PP at step (11a).

[0052] Among other potential advantages, the present approach enables a faster and more accurate method for generating QR codes for use in vehicle-dealer transactions where the vehicle 12 moves relative to the infrastructure node 14, such as those described in the Fig. 1, Fig. 7 and Fig. The eight exemplary use cases are shown. The solutions described here can be used to optimize QR code generation and display based on the dynamically changing location of the vehicle's camera 16, enabling the camera 16 to accurately read the adapted QR code 24 from a distance. This is achieved by projecting the QR code onto the 2D plane of the display screen 22. Fig. 1 in a way that takes into account the relative position of the vehicle 12 and the infrastructure node 14. Despite the embedding of special patterns in a QR code to help a scanner with distortion and alignment, scanning errors can result from the significantly reduced pixel resolution when attempting to scan a QR code from an approach angle such as in Fig. 1. Therefore, the teachings presented here can be used to improve the overall customer experience during in-vehicle mobile payment situations, such as ride-hailing services or dealerships, toll booths, electric vehicle (EV) charging stations, and the like. These and other potential benefits will be readily apparent to the person skilled in the art, who now has the benefit of the foregoing disclosure.

[0053] The present disclosure is open to embodiments in many different forms. Representative examples of the disclosure are shown in the drawings and are described in detail herein as non-limiting examples of the disclosed principles. For this purpose, elements and limitations described in the abstract, introduction, description, and detailed description, but not explicitly set forth in the claims, should not be considered, individually or collectively, as included in the claims by deduction, inference, or otherwise.

[0054] For the purposes of this description, unless expressly excluded, the use of the singular includes the plural and vice versa; the terms "and" and "or" are to be understood as both subjunctive and disjunctive; "any" and "all" are to mean both "any" and "all"; and the words "including," "containing," "comprehensive," "having," and the like are to mean "including without limitation." Furthermore, words of approximation such as "about," "almost," "essentially," "generally," "approximately," etc., may be used herein to mean "at, close to, or nearly at" or "within 0-5% of" or "within acceptable manufacturing tolerances," or logical combinations thereof.

[0055] The detailed description and the drawings or figures support and describe the present teachings, but the scope of the present teachings is defined exclusively by the claims. While some of the best modes and other embodiments for carrying out the present teachings have been described in detail, there are various alternative designs and embodiments for implementing the present teachings defined in the appended claims. Furthermore, this disclosure expressly includes combinations and subcombinations of the elements and features shown above and below.

Claims

[1] Method for dynamically generating a customized quick response code, QR codes, for scanning by a moving vehicle during a vehicle-dealer transaction, the method comprising: Capturing parameters of the vehicle-mounted camera via a sensor suite of an infrastructure node in communication with a dealer back office while the moving vehicle approaches the infrastructure node, wherein the parameters include a distance and an approach angle of the vehicle-mounted camera relative to the infrastructure node; Dynamically transforming a base QR code in response to parameters via a processor of the infrastructure node to generate a customized QR code with a modified shape, size and / or data capacity relative to the base QR code; Transmitting a display control signal to a display screen of the infrastructure node; and Displaying the customized QR code on the display screen in response to the display control signal as the moving vehicle approaches the infrastructure node, to allow the vehicle-mounted camera to scan the customized QR code during the vehicle-dealer transaction. [2] Method according to claim 1, wherein the dynamic transformation of the square base QR code includes performing a three-dimensional projection, 3D projection, to a two-dimensional projection, 2D projection, via the processor of the infrastructure node to cause a 2D plane of the adapted QR code, when displayed via the display screen, to be perpendicular to a focal axis of the vehicle-mounted camera. [3] Infrastructure nodes capable of carrying out a vehicle-dealer transaction with a moving vehicle, comprising: a stationary structure; a sensor suite that is mounted on or arranged together with the stationary structure; a display screen; and a server in communication with a merchant's back office and with a processor and a non-volatile, computer-readable storage medium, "memory", on which instructions are recorded, wherein the execution of the instructions by the processor causes the server to: to dynamically generate a customized quick response code (QR code) for scanning by the moving vehicle using a vehicle-mounted camera; to capture parameters of the vehicle-mounted camera via the sensor suite as the moving vehicle approaches the stationary structure, wherein the parameters include a distance and an approach angle of the vehicle-mounted camera relative to the stationary structure; to dynamically transform a basic QR code in response to the parameters via the processor in order to generate a customized QR code with a modified shape, size and / or data capacity relative to the basic QR code; to transmit a display control signal to the display screen to cause the display screen to show the adapted QR code as the moving vehicle approaches the stationary structure, thereby enabling the vehicle-mounted camera to scan the adapted QR code during the vehicle-dealer transaction. [4] Infrastructure node according to claim 3, wherein the execution of the instructions by the processor causes the server to display the adapted QR code on the display screen as a pixelated image that is distorted in a two-dimensional reference frame, 2D reference frame, of the display screen. [5] Infrastructure node according to claim 3, wherein the sensor suite includes one or more infrastructure cameras. [6] Infrastructure node according to claim 3, wherein the sensor suite includes a radar sensor, a lidar sensor and / or an ultra-wideband sensor, UWB sensor. [7] Infrastructure node according to claim 3, wherein the execution of the instructions by the processor causes the server to dynamically transform the base QR code into a two-dimensional projection, 2D projection, by performing a three-dimensional projection, 3D projection, in order to cause a 2D plane of the adapted QR code, when displayed via the display screen, to be perpendicular to a focal axis of the camera mounted on the vehicle. [8] Infrastructure node according to claim 3, wherein the execution of the instructions by the processor causes the server to establish a secure network connection with the dealer back office as part of the vehicle-dealer transaction. [9] Infrastructure node according to claim 3, wherein the execution of the instructions by the processor causes the server to dynamically transform the base QR code by calculating a required data capacity and resolution of the adapted QR code based on a relative position of the moving vehicle and the infrastructure node. [10] Infrastructure node according to claim 3, wherein the stationary structure is a store, toll booth, roadside stand or passage or pass-by structure.

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