Two-dimensional code spraying method, system and equipment for tunnel vehicle positioning and medium

Abstract

The invention discloses a two-dimensional code spraying method, system and device for tunnel vehicle positioning and a medium. The two-dimensional code spraying method comprises the steps of obtaining test parameter data required by two-dimensional code spraying of a road in a tunnel; according to the test parameter data, designing a plurality of groups of control experiments and executing tests, and generating test result data corresponding to the two-dimensional code recognition rate; and analyzing test result data to determine optimal spraying parameter data. According to the method, the test parameters required by two-dimensional code spraying are obtained and tested, the optimal parameters corresponding to the vehicle speed, the two-dimensional code size, the color difference, the asphalt grading type and the road surface illumination factor are determined according to the test result, and then the optimal spraying parameter data are determined according to the optimal parameters, so that the recognition success rate of vehicles in the tunnel is increased, the positioning accuracy is ensured, and the efficiency is improved. And identification cost is reduced.

Description

Technical Field

[0001] The present invention relates to the field of tunnel traffic technology, and in particular to a two-dimensional code spraying method, system, equipment and medium for tunnel vehicle positioning. Background Art

[0002] Vehicle identification and positioning technology uses various technical means to determine the position and movement status of a car in space, and plays an important role in the fields of intelligent transportation, autonomous driving, and vehicle monitoring. The GPS signal in the tunnel is weak, and the traditional vehicle navigation system cannot work properly, resulting in the driver being unable to obtain accurate positioning information in the tunnel, thus affecting driving safety.

[0003] At present, the above problems are solved by installing cameras in the tunnel for monitoring or setting navigation signs in the tunnel for indication. However, these solutions have limitations, such as high cost, complex installation and difficult maintenance. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the defects of the prior art of installing cameras or setting navigation signs in tunnels, which are high cost and poor accuracy, and to provide a QR code spraying method, system, equipment and medium for tunnel vehicle positioning.

[0005] The present invention solves the above technical problems through the following technical solutions:

[0006] In a first aspect, the present invention provides a two-dimensional code spraying method for tunnel vehicle positioning, the two-dimensional code spraying method comprising:

[0007] Acquire test parameter data required for spraying the QR code on the road in the tunnel; the test parameter data includes vehicle speed data, QR code size data, color difference data between the QR code and black asphalt, asphalt gradation type data and reflectivity data;

[0008] Design several groups of control experiments according to the test parameter data and perform the tests to generate test result data corresponding to the QR code recognition rate;

[0009] The test result data are analyzed to determine the optimal spraying parameter data.

[0010] Preferably, the step of designing several groups of control experiments according to the test parameter data and performing the tests to generate the test result data corresponding to the two-dimensional code recognition rate includes:

[0011] Taking any one of the parameters of the vehicle speed data, the two-dimensional code size data, the color difference data between the two-dimensional code and black asphalt, the asphalt gradation type data and the reflectivity data as a single variable, designing several target control tests; the target control test includes at least one of the vehicle speed change control test, the two-dimensional code size change control test, the two-dimensional code and black asphalt color difference change control test, the asphalt gradation type change control test and the reflectivity control test;

[0012] The test result data corresponding to the recognition rate of the two-dimensional code of each group of the target control test is collected.

[0013] Preferably, the average road illumination in the reflectivity data is obtained by the following formula:

[0014] E=φNU / KB

[0015] Among them, E represents the average illumination of the road, φ represents the luminous flux of the lamp, N represents the arrangement of street lights, which is 2 for symmetrical arrangement and 1 for unilateral and staggered arrangement, U represents the utilization system, K represents the maintenance factor, which is 2 for asphalt pavement, B represents the width of the pavement, and D represents the distance between poles.

[0016] Preferably, the step of analyzing the test result data to determine the optimal spraying parameters corresponding to each of the test parameter data includes:

[0017] Determine the optimal parameter corresponding to each test parameter data according to the test result data;

[0018] Obtaining the weight ratio corresponding to each test parameter data;

[0019] The optimal spraying parameter data is determined according to the weight ratio corresponding to each of the test parameter data and the optimal parameter corresponding to each of the test parameter data.

[0020] In a second aspect, the present invention provides a two-dimensional code spraying system for tunnel vehicle positioning, the two-dimensional code spraying system comprising:

[0021] An acquisition module is used to acquire test parameter data required for spraying the QR code on the road in the tunnel; the test parameter data includes vehicle speed data, QR code size data, color difference data between the QR code and black asphalt, asphalt gradation type data and reflectivity data;

[0022] An execution module, used to design several groups of control experiments according to the test parameter data and execute the test to generate test result data corresponding to the two-dimensional code recognition rate;

[0023] The analysis module is used to analyze the test result data to determine the optimal spraying parameter data.

[0024] Preferably, the execution module comprises:

[0025] The design unit is used to design a plurality of target control tests by taking any one of the vehicle speed data, the two-dimensional code size data, the color difference data between the two-dimensional code and black asphalt, the asphalt gradation type data and the reflectivity data as a single variable; the target control test includes at least one of a vehicle speed change control test, a two-dimensional code size change control test, a two-dimensional code and black asphalt color difference change control test, an asphalt gradation type change control test and a reflectivity control test;

[0026] The collecting unit is used to collect the test result data corresponding to the two-dimensional code recognition rate of each group of the target control test.

[0027] Preferably, the average road illumination in the reflectivity data is obtained by the following formula:

[0028] E=φNU / KB

[0029] Among them, E represents the average illumination of the road, φ represents the luminous flux of the lamp, N represents the arrangement of street lights, which is 2 for symmetrical arrangement and 1 for unilateral and staggered arrangement, U represents the utilization system, K represents the maintenance factor, which is 2 for asphalt pavement, B represents the width of the pavement, and D represents the distance between poles.

[0030] Preferably, the analysis module comprises:

[0031] A judgment unit, used for judging the optimal parameter corresponding to each test parameter data according to the test result data;

[0032] An acquisition unit, used for acquiring a weight ratio corresponding to each test parameter data;

[0033] A determination unit is used to determine the optimal spraying parameter data according to the weight ratio corresponding to each of the test parameter data and the optimal parameter corresponding to each of the test parameter data.

[0034] In a third aspect, the present invention provides an electronic device comprising a processor, a memory, and a computer program of a computer stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, the two-dimensional code spraying method for tunnel vehicle positioning as described in the first aspect is implemented.

[0035] In a fourth aspect, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the two-dimensional code spraying method for tunnel vehicle positioning as described in the first aspect.

[0036] The positive and progressive effects of the present invention are: obtaining the test parameter data required for the spraying of the two-dimensional code on the road in the tunnel; designing several groups of control experiments and performing tests according to the test parameter data to generate test result data corresponding to the two-dimensional code recognition rate; analyzing the test result data to determine the optimal spray parameter data. The present invention obtains several test parameters required for the spraying of the two-dimensional code and conducts tests, determines the optimal parameters corresponding to the vehicle speed, the two-dimensional code size, the color difference, the asphalt gradation type and the road surface illumination factors according to the test results, and then determines the optimal spray parameter data according to the optimal parameters, so as to improve the success rate of vehicle recognition in the tunnel, ensure the accuracy of positioning, and reduce the recognition cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a schematic flow chart of a two-dimensional code spraying method for tunnel vehicle positioning according to Example 1 of the present invention.

[0038] Figure 2 This is a schematic diagram of the process of a two-dimensional code spraying system for tunnel vehicle positioning according to embodiment 2 of the present invention.

[0039] Figure 3 This is a schematic diagram of the structure of an electronic device for implementing a two-dimensional code spraying method for tunnel vehicle positioning according to embodiment 3 of the present invention. DETAILED DESCRIPTION

[0040] The present invention is further described below by way of examples, but the present invention is not limited to the scope of the examples.

[0041] Example 1

[0042] The two-dimensional code spraying method for tunnel vehicle positioning in this embodiment is as follows: Figure 1 As shown, the two-dimensional code spraying method includes:

[0043] S11, obtaining test parameter data required for spraying the QR code on the road in the tunnel; the test parameter data includes vehicle speed data, QR code size data, color difference data between the QR code and black asphalt, asphalt gradation type data and reflectivity data;

[0044] S12. Design several groups of control experiments according to the test parameter data and perform the tests to generate test result data corresponding to the QR code recognition rate;

[0045] S13. Analyze the test result data to determine the optimal spraying parameter data.

[0046] For the above step S11, in the process of collecting test parameter data, in order to ensure the accuracy of vehicle recognition, multiple groups of data need to be experimented. The vehicle speed data include 50km / h, 80km / h, and 120km / h, and the QR code recognition rate at different vehicle speeds is investigated; the QR code size data include 5cm×5cm, 10cm×10cm, and 30cm×30cm, and the influence of the QR code size on the QR code recognition rate is investigated; the color difference data between the QR code and black asphalt include △E=5, △E=10, and △E=15, and the influence of different color differences on the QR code recognition rate is investigated; the asphalt gradation type data include AC, SMA, and OGFC, and the influence of different asphalt gradation types on the clarity of the QR code is investigated; the reflectivity data of the asphalt pavement irradiated with different light intensities include 5Lx, 10Lx, and 15Lx, and the influence of the reflectivity of different asphalt pavements on the clarity of the QR code is investigated, and the influence of the vehicle speed, QR code size, color difference, asphalt gradation type, and reflectivity on the QR code recognition rate is determined based on the above test parameter data. In this embodiment, AC is ordinary asphalt concrete, which is composed of aggregate, mineral powder and asphalt, and has a closed-chamber suspension structure; SMA is asphalt mastic crushed stone mixture, which is composed of asphalt, fiber stabilizer, fine aggregate and mineral powder to form asphalt mastic, which is filled between the coarse aggregate skeletons of discontinuous grading; OGFC is a skeleton pore structure, with a large proportion of large crushed stone and very little fine aggregate.

[0047] In the process of designing several groups of control experiments and performing the tests according to the test parameter data in step S12, the vehicle is first equipped with a camera with a special recognition function, such as a laser radar camera, to recognize the QR code on the road surface in the tunnel. The camera is installed in a position that does not affect the driver's line of sight and can illuminate the road surface. Then, a section of asphalt road surface is selected in the tunnel, and the QR code is sprayed according to the collected test result data. The size, color, and shape parameters of the QR code are designed according to the vehicle speed and asphalt road surface characteristics.

[0048] In the first group of tests, recognition tests were carried out at vehicle speeds of 50km / h, 80km / h, and 120km / h, and the success rate of QR code recognition was recorded; in the second group of tests, recognition tests were carried out on sizes of 5cm×5cm, 10cm×10cm, and 30cm×30cm, and the success rate of QR code recognition was recorded; in the third group of tests, recognition tests were carried out with different color differences set, and the success rate of QR code recognition was recorded; in the fourth group of tests, recognition tests were carried out on pavements with asphalt grading types of AC, SMA, and OGFC, and the success rate of QR code recognition was recorded; in the fifth group of tests, recognition tests were carried out under pavement illumination of 5Lx, 10Lx, and 15Lx, and the success rate of QR code recognition was recorded.

[0049] For the above step S13, in the process of analyzing the test result data, as the vehicle speed increases, the recognition success rate gradually decreases; when the vehicle speed reaches 120km / h, the QR code recognition success rate decreases significantly. As the size of the QR code increases, the QR code recognition success rate gradually increases, and when the QR code size reaches 30cm×30cm, the QR code recognition success rate is the highest. As the color difference increases, the QR code recognition success rate gradually increases, and when the color difference reaches △E=15, the QR code recognition success rate is the highest. The recognition success rate of SMA asphalt pavement is the highest, followed by AC asphalt pavement, and the QR code recognition success rate of OGFC asphalt pavement is the lowest. As the road illumination increases, the QR code recognition success rate gradually increases; when the road illumination reaches 15Lx, the QR code recognition success rate is the highest. This method calculates the real-time position and driving trajectory of the vehicle through the recognized QR code information, combined with the vehicle speed and time parameters, and outputs the calculated positioning information to the vehicle navigation system to provide accurate navigation information for the driver.

[0050] In an optional implementation, step S12 specifically includes:

[0051] S121. Taking any one parameter among vehicle speed data, QR code size data, color difference data between QR code and black asphalt, asphalt gradation type data and reflectivity data as a single variable, designing several target control tests; the target control test includes at least one of vehicle speed change control test, QR code size change control test, QR code and black asphalt color difference change control test, asphalt gradation type change control test and reflectivity control test;

[0052] S122. Collect test result data corresponding to the QR code recognition rate of each group of target control tests.

[0053] For the above steps S121-S122, in the first group of tests, a QR code with a size of 10cm×10cm and a color difference of △E=10 was sprayed on an asphalt grading type AC road surface, and the road surface illumination was 10Lx. Recognition tests were conducted at vehicle speeds of 50km / h, 80km / h, and 120km / h, and the success rate of QR code recognition was recorded. In the second group of tests, QR codes with sizes of 5cm×5cm, 10cm×10cm, and 30cm×30cm and a color difference of △E=10 were sprayed on an asphalt grading type AC asphalt road surface with a road surface illumination of 10Lx, and the vehicle speed was set to 80km / h. Recognition tests were conducted and the success rate of QR code recognition was recorded. In the third group of tests, two-dimensional codes with a size of 10cm×10cm and a color difference of △E=5, △E=10, and △E=15 were sprayed on asphalt pavement with asphalt grading type AC and road illumination of 10Lx. The vehicle speed was set to 80km / h, and recognition tests were carried out respectively, and the success rate of QR code recognition was recorded. In the fourth group of tests, two-dimensional codes with a size of 10cm×10cm and a color difference of △E=10 were sprayed on asphalt grading types AC, SMA, and OGFC, respectively. The road illumination was set to 10Lx and the vehicle speed was 80km / h. Recognition tests were carried out respectively, and the success rate of QR code recognition was recorded. In the fifth group of tests, two-dimensional codes with a size of 10cm×10cm and a color difference of △E=10 were sprayed on asphalt pavement with asphalt grading type AC. The vehicle speed was set to 80km / h, and recognition tests were carried out under road illumination of 5Lx, 10Lx, and 15Lx, and the success rate of QR code recognition was recorded.

[0054] In an optional implementation, step S13 specifically includes:

[0055] S131, judging the optimal parameter corresponding to each test parameter data according to the test result data;

[0056] S132, obtaining the weight ratio corresponding to each test parameter data;

[0057] S133, determining the optimal spraying parameter data according to the weight ratio corresponding to each test parameter data and the optimal parameter corresponding to each test parameter data.

[0058] For the above steps S131-S133, the weight ratio corresponding to each selected test parameter data is determined, and the test parameter data with a large weight ratio corresponding to the optimal parameter is used as the main influencing factor to obtain the optimal spraying parameter data. Compared with the traditional tunnel navigation system, this method does not require the installation of complex equipment, only requires spraying a QR code on the road surface of the tunnel, which is low in cost. By controlling the QR code size, color difference, asphalt gradation type and road illumination factors, high-precision vehicle positioning can be achieved.

[0059] In an optional implementation, the average road illumination in the reflectivity data is obtained by the following formula:

[0060] E=φNU / KB

[0061] Among them, E represents the average illumination of the road, φ represents the luminous flux of the lamp, N represents the arrangement of street lights, which is 2 for symmetrical arrangement and 1 for unilateral and staggered arrangement, U represents the utilization system, K represents the maintenance factor, which is 2 for asphalt pavement, B represents the width of the pavement, and D represents the distance between poles.

[0062] In this embodiment, the color difference data between the two-dimensional code and the black asphalt are defined by the Lab value method for the color difference of each control test. "L" represents the brightness of the object, and the value is between 0 and 100, representing from black to white; "a" represents the red and green color of the object, a positive value represents red, and a negative value represents green; "b" represents the yellow and blue color of the object, a positive value represents yellow, and a negative value represents blue; △L represents positive, indicating that the test sample is lighter (whiter) than the standard sample; △L represents negative, indicating that the test sample is darker (blacker) than the standard sample; △a represents If △a is positive, it means the test sample is redder (more reddish) than the standard sample; △a is negative, it means the test sample is greener (more greenish) than the standard sample; △b is positive, it means the test sample is yellower (more yellowish) than the standard sample; △b is negative, it means the test sample is bluer (more blueish) than the standard sample; △Eab (or △E) represents the total color difference, but does not represent the direction of the color difference shift. The larger the value, the greater the color difference; △E represents the comprehensive evaluation index of color difference, and its relationship with △L, △a, and △b is: △E=(△L)2+(△a)2+(△b)2.

[0063] This embodiment provides a QR code spraying method for positioning vehicles in tunnels. By obtaining several test parameters required for QR code spraying and conducting tests, the optimal parameters corresponding to vehicle speed, QR code size, color difference, asphalt grading type and road surface illumination factors are determined according to the test results, and then the optimal spraying parameter data is determined based on the optimal parameters to improve the success rate of vehicle recognition in tunnels, ensure positioning accuracy, and reduce recognition costs.

[0064] Example 2

[0065] The two-dimensional code spraying system for tunnel vehicle positioning of this embodiment is as follows: Figure 2 As shown, the two-dimensional code spraying system includes: an acquisition module 210, an execution module 220 and an analysis module 230.

[0066] The acquisition module 210 is used to acquire the test parameter data required for the spraying of the QR code on the road in the tunnel; the test parameter data includes vehicle speed data, QR code size data, color difference data between the QR code and black asphalt, asphalt gradation type data and reflectivity data;

[0067] An execution module 220 is used to design several groups of control experiments according to the test parameter data and execute the test to generate test result data corresponding to the two-dimensional code recognition rate;

[0068] The analysis module 230 is used to analyze the test result data to determine the optimal spraying parameter data.

[0069] In the process of collecting test parameter data, the acquisition module 210 needs to conduct experiments on multiple sets of data to ensure the accuracy of vehicle recognition. The vehicle speed data includes 50km / h, 80km / h, and 120km / h, and the two-dimensional code recognition rate at different vehicle speeds is investigated; the two-dimensional code size data includes 5cm×5cm, 10cm×10cm, and 30cm×30cm, and the influence of the two-dimensional code size on the two-dimensional code recognition rate is investigated; the color difference data between the two-dimensional code and black asphalt includes △E=5, △E=10, and △E=15, and the influence of different color differences on the two-dimensional code recognition rate is investigated; the asphalt gradation type data includes AC, SMA, and OGFC, and the influence of different asphalt gradation types on the clarity of the two-dimensional code is investigated; the reflectivity data of the asphalt pavement irradiated with different light intensities include 5Lx, 10Lx, and 15Lx, and the influence of the reflectivity of different asphalt pavements on the clarity of the two-dimensional code is investigated. Based on the above test parameter data, the influence of vehicle speed, two-dimensional code size, color difference, asphalt gradation type, and reflectivity on the two-dimensional code recognition rate is determined. In this embodiment, AC is ordinary asphalt concrete, which is composed of aggregate, mineral powder and asphalt, and has a closed-chamber suspension structure; SMA is asphalt mastic crushed stone mixture, which is composed of asphalt, fiber stabilizer, fine aggregate and mineral powder to form asphalt mastic, which is filled between the coarse aggregate skeletons of discontinuous grading; OGFC is a skeleton pore structure, with a large proportion of large crushed stone and very little fine aggregate.

[0070] In the process of designing several groups of control experiments and executing the tests according to the test parameter data, the execution module 220 first equips the vehicle with a camera with a special recognition function, such as a laser radar camera, to recognize the QR code on the road surface in the tunnel. The camera is installed in a position that does not affect the driver's line of sight and can illuminate the road surface. Then, a section of asphalt road surface is selected in the tunnel, and a QR code is sprayed according to the collected test result data. The size, color, and shape parameters of the QR code are designed according to the vehicle speed and the characteristics of the asphalt road surface.

[0071] In the first group of tests, recognition tests were carried out at vehicle speeds of 50km / h, 80km / h, and 120km / h, and the success rate of QR code recognition was recorded; in the second group of tests, recognition tests were carried out on sizes of 5cm×5cm, 10cm×10cm, and 30cm×30cm, and the success rate of QR code recognition was recorded; in the third group of tests, recognition tests were carried out with different color differences set, and the success rate of QR code recognition was recorded; in the fourth group of tests, recognition tests were carried out on pavements with asphalt grading types of AC, SMA, and OGFC, and the success rate of QR code recognition was recorded; in the fifth group of tests, recognition tests were carried out under pavement illumination of 5Lx, 10Lx, and 15Lx, and the success rate of QR code recognition was recorded.

[0072] In the process of analyzing the test result data by the analysis module 230, as the vehicle speed increases, the recognition success rate gradually decreases; when the vehicle speed reaches 120km / h, the recognition success rate of the two-dimensional code is significantly reduced. As the size of the two-dimensional code increases, the recognition success rate of the two-dimensional code gradually increases, and when the size of the two-dimensional code reaches 30cm×30cm, the recognition success rate of the two-dimensional code is the highest. As the color difference increases, the recognition success rate of the two-dimensional code gradually increases, and when the color difference reaches △E=15, the recognition success rate of the two-dimensional code is the highest. The recognition success rate of the SMA asphalt pavement is the highest, followed by the AC asphalt pavement, and the recognition success rate of the OGFC asphalt pavement is the lowest. As the road illumination increases, the recognition success rate of the two-dimensional code gradually increases; when the road illumination reaches 15Lx, the recognition success rate of the two-dimensional code is the highest. This method calculates the real-time position and driving trajectory of the vehicle through the recognized two-dimensional code information, combined with the vehicle speed and time parameters, and outputs the calculated positioning information to the vehicle navigation system to provide accurate navigation information for the driver.

[0073] In an optional implementation, the execution module 220 specifically includes:

[0074] The design unit 221 is used to design a plurality of target control tests by taking any one of the parameters of vehicle speed data, QR code size data, color difference data between the QR code and black asphalt, asphalt gradation type data and reflectivity data as a single variable; the target control test includes at least one of the vehicle speed change control test, the QR code size change control test, the QR code and black asphalt color difference change control test, the asphalt gradation type change control test and the reflectivity control test;

[0075] The collecting unit 222 is used to collect the test result data corresponding to the two-dimensional code recognition rate of each group of target control tests.

[0076] In the first set of tests, the design unit 221 sprayed a 10cm×10cm QR code with a color difference of △E=10 on an asphalt gradation type AC road surface, with a road illumination of 10Lx, and performed recognition tests at vehicle speeds of 50km / h, 80km / h, and 120km / h, respectively, and the acquisition unit 222 recorded the QR code recognition success rate. In the second set of tests, the design unit 221 sprayed 5cm×5cm, 10cm×10cm, 30cm×30cm QR codes with a color difference of △E=10 on an asphalt gradation type AC asphalt road surface with a road illumination of 10Lx, set the vehicle speed to 80km / h, and performed recognition tests, respectively, and the acquisition unit 222 recorded the QR code recognition success rate. In the third group of tests, the design unit 221 sprayed two-dimensional codes with a size of 10cm×10cm and a color difference of △E=5, △E=10, and △E=15 on an asphalt road surface with an asphalt gradation type of AC and a road surface illumination of 10Lx, set the vehicle speed to 80km / h, and conducted recognition tests respectively, and the acquisition unit 222 recorded the success rate of two-dimensional code recognition. In the fourth group of tests, the design unit 221 sprayed two-dimensional codes with a size of 10cm×10cm and a color difference of △E=10 on asphalt gradation types of AC, SMA, and OGFC, set the road surface illumination to 10Lx, and the vehicle speed to 80km / h, and conducted recognition tests respectively, and the acquisition unit 222 recorded the success rate of two-dimensional code recognition. In the fifth set of experiments, the design unit 221 sprayed a QR code with a size of 10cm×10cm and a color difference of △E=10 on an asphalt pavement with an asphalt grading type of AC, set the vehicle speed to 80km / h, and conducted recognition tests under road illumination conditions of 5Lx, 10Lx, and 15Lx. The acquisition unit 222 recorded the QR code recognition success rate.

[0077] In an alternative embodiment, Figure 2 As shown, the analysis module 230 specifically includes:

[0078] A judging unit 231 is used to judge the optimal parameter corresponding to each test parameter data according to the test result data;

[0079] An acquisition unit 232 is used to acquire a weight ratio corresponding to each test parameter data;

[0080] The acquisition unit 233 is used to determine the optimal spraying parameter data according to the weight ratio corresponding to each test parameter data and the optimal parameter corresponding to each test parameter data.

[0081] Determine the weight ratio corresponding to each selected test parameter data, take the test parameter data with a large weight ratio corresponding to the optimal parameter as the main influencing factor, and obtain the optimal spraying parameter data. Compared with the traditional tunnel navigation system, this method does not require the installation of complex equipment, only requires spraying a QR code on the road surface of the tunnel, which is low-cost. By controlling the QR code size, color difference, asphalt gradation type and road illumination factors, high-precision vehicle positioning can be achieved.

[0082] In an optional implementation, the average road illumination in the reflectivity data is obtained by the following formula:

[0083] E=φNU / KB

[0084] Among them, E represents the average illumination of the road, φ represents the luminous flux of the lamp, N represents the arrangement of street lights, which is 2 for symmetrical arrangement and 1 for unilateral and staggered arrangement, U represents the utilization system, K represents the maintenance factor, which is 2 for asphalt pavement, B represents the width of the pavement, and D represents the distance between poles.

[0085] In this embodiment, the color difference data between the two-dimensional code and the black asphalt are defined by the Lab value method for the color difference of each control test. "L" represents the brightness of the object, and the value is between 0 and 100, representing from black to white; "a" represents the red and green color of the object, a positive value represents red, and a negative value represents green; "b" represents the yellow and blue color of the object, a positive value represents yellow, and a negative value represents blue; △L represents positive, indicating that the test sample is lighter (whiter) than the standard sample; △L represents negative, indicating that the test sample is darker (blacker) than the standard sample; △a represents If △a is positive, it means the test sample is redder (more reddish) than the standard sample; △a is negative, it means the test sample is greener (more greenish) than the standard sample; △b is positive, it means the test sample is yellower (more yellowish) than the standard sample; △b is negative, it means the test sample is bluer (more blueish) than the standard sample; △Eab (or △E) represents the total color difference, but does not represent the direction of the color difference shift. The larger the value, the greater the color difference; △E represents the comprehensive evaluation index of color difference, and its relationship with △L, △a, and △b is: △E=(△L)2+(△a)2+(△b)2.

[0086] This embodiment provides a QR code spraying system for positioning vehicles in tunnels. The execution module obtains several test parameters required for QR code spraying and conducts tests. According to the test results, the optimal parameters corresponding to vehicle speed, QR code size, color difference, asphalt grading type and road illumination factors are determined. The analysis module then determines the optimal spraying parameter data based on the optimal parameters to improve the success rate of vehicle recognition in tunnels, ensure positioning accuracy, and reduce recognition costs.

[0087] Example 3

[0088] Figure 3The schematic diagram of the structure of an electronic device provided in this embodiment includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the two-dimensional code spraying method for tunnel vehicle positioning in embodiment 1 when executing the program. Figure 3 The electronic device 90 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0089] like Figure 3 As shown, the electronic device 90 may be in the form of a general-purpose computing device, for example, it may be a server device. The components of the electronic device 90 may include, but are not limited to: at least one processor 91, at least one memory 92, and a bus 93 connecting different system components (including the memory 92 and the processor 91).

[0090] The bus 93 includes a data bus, an address bus, and a control bus.

[0091] The memory 92 may include a volatile memory, such as a random access memory (RAM) 921 and / or a cache memory 922 , and may further include a read-only memory (ROM) 923 .

[0092] The memory 92 may also include a program / utility 925 having a set (at least one) of program modules 924, such program modules 924 including but not limited to: an operating system, one or more application programs, other program modules and program data, each of which or some combination may include an implementation of a network environment.

[0093] The processor 91 executes various functional applications and data processing by running the computer programs stored in the memory 92, such as the two-dimensional code spraying method for tunnel vehicle positioning in embodiment 1 of the present invention.

[0094] The electronic device 90 may also communicate with one or more external devices 94 (e.g., keyboards, pointing devices, etc.). Such communication may be performed via an input / output (I / O) interface 95. Furthermore, the model generating device 90 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 96. Figure 3 As shown, the network adapter 96 communicates with other modules of the model-generated device 90 via the bus 93. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the model-generated device 90, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems, etc.

[0095] It should be noted that although several units / modules or sub-units / modules of the electronic device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided into multiple units / modules to be embodied.

[0096] Example 4

[0097] This embodiment provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps in the two-dimensional code spraying method for tunnel vehicle positioning in embodiment 1 are implemented.

[0098] The readable storage medium may include but is not limited to: a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device or any suitable combination of the above.

[0099] In a possible implementation, the present invention can also be implemented in the form of a program product, which includes a program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps in the two-dimensional code spraying method for tunnel vehicle positioning in Example 1.

[0100] Among them, the program code for executing the present invention can be written in any combination of one or more programming languages, and the program code can be executed completely on the user device, partially on the user device, as an independent software package, partially on the user device and partially on a remote device, or completely on the remote device.

[0101] Although the specific embodiments of the present invention are described above, it should be understood by those skilled in the art that this is only for illustration and the protection scope of the present invention is defined by the appended claims. Those skilled in the art may make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, but these changes and modifications all fall within the protection scope of the present invention.

Claims

1. A two-dimensional code spraying method for tunnel vehicle positioning, characterized in that: The two-dimensional code spraying method comprises: Acquire test parameter data required for spraying the QR code on the road in the tunnel; the test parameter data includes vehicle speed data, QR code size data, color difference data between the QR code and black asphalt, asphalt gradation type data and reflectivity data; Design several groups of control experiments according to the test parameter data and perform the tests to generate test result data corresponding to the QR code recognition rate; The test result data are analyzed to determine the optimal spraying parameter data.

2. The two-dimensional code spraying method for tunnel vehicle positioning according to claim 1, characterized in that: The step of designing several groups of control experiments according to the test parameter data and executing the tests to generate test result data corresponding to the two-dimensional code recognition rate includes: Taking any one of the parameters of the vehicle speed data, the two-dimensional code size data, the color difference data between the two-dimensional code and black asphalt, the asphalt gradation type data and the reflectivity data as a single variable, designing several target control tests; the target control test includes at least one of the vehicle speed change control test, the two-dimensional code size change control test, the two-dimensional code and black asphalt color difference change control test, the asphalt gradation type change control test and the reflectivity control test; The test result data corresponding to the two-dimensional code recognition rate of each group of the target control test is collected.

3. The two-dimensional code spraying method for tunnel vehicle positioning according to claim 1, characterized in that: The average road illumination in the reflectivity data is obtained by the following formula: E=φNU / KB Among them, E represents the average illumination of the road, φ represents the luminous flux of the lamp, N represents the arrangement of street lights, which is 2 for symmetrical arrangement and 1 for unilateral and staggered arrangement, U represents the utilization system, K represents the maintenance factor, which is 2 for asphalt pavement, B represents the width of the pavement, and D represents the distance between poles.

4. The two-dimensional code spraying method for tunnel vehicle positioning according to claim 1, characterized in that: The step of analyzing the test result data to determine the optimal spraying parameters corresponding to each of the test parameter data includes: Determine the optimal parameter corresponding to each test parameter data according to the test result data; Obtaining the weight ratio corresponding to each test parameter data; The optimal spraying parameter data is determined according to the weight ratio corresponding to each of the test parameter data and the optimal parameter corresponding to each of the test parameter data.

5. A two-dimensional code spraying system for tunnel vehicle positioning, characterized in that: The two-dimensional code spraying system comprises: An acquisition module is used to acquire test parameter data required for spraying the QR code on the road in the tunnel; the test parameter data includes vehicle speed data, QR code size data, color difference data between the QR code and black asphalt, asphalt gradation type data and reflectivity data; An execution module, used to design several groups of control experiments according to the test parameter data and execute the test to generate test result data corresponding to the two-dimensional code recognition rate; The analysis module is used to analyze the test result data to determine the optimal spraying parameter data.

6. The two-dimensional code spraying system for tunnel vehicle positioning according to claim 5, characterized in that: The execution module comprises: The design unit is used to design a plurality of target control tests by taking any one of the vehicle speed data, the two-dimensional code size data, the color difference data between the two-dimensional code and black asphalt, the asphalt gradation type data and the reflectivity data as a single variable; the target control test includes at least one of a vehicle speed change control test, a two-dimensional code size change control test, a two-dimensional code and black asphalt color difference change control test, an asphalt gradation type change control test and a reflectivity control test; The collecting unit is used to collect the test result data corresponding to the two-dimensional code recognition rate of each group of the target control test.

7. The two-dimensional code spraying system for tunnel vehicle positioning according to claim 5, characterized in that: The average road illumination in the reflectivity data is obtained by the following formula: E=φNU / KB Among them, E represents the average illumination of the road, φ represents the luminous flux of the lamp, N represents the arrangement of street lights, which is 2 for symmetrical arrangement and 1 for unilateral and staggered arrangement, U represents the utilization system, K represents the maintenance factor, which is 2 for asphalt pavement, B represents the width of the pavement, and D represents the distance between poles.

8. The two-dimensional code spraying system for tunnel vehicle positioning according to claim 5, characterized in that: The analysis module comprises: A judgment unit, used for judging the optimal parameter corresponding to each test parameter data according to the test result data; An acquisition unit, used for acquiring a weight ratio corresponding to each test parameter data; A determination unit is used to determine the optimal spraying parameter data according to the weight ratio corresponding to each of the test parameter data and the optimal parameter corresponding to each of the test parameter data.

9. An electronic device, characterized in that: The invention comprises a processor, a memory and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, a two-dimensional code spraying method for tunnel vehicle positioning as described in any one of claims 1 to 4 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the two-dimensional code spraying method for tunnel vehicle positioning according to any one of claims 1 to 4 is implemented.

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