A method for inspecting road parking charges

Abstract

This invention provides a method for road parking fee collection and inspection, belonging to the field of inspection and fee collection technology. The method includes: conducting road inspections on a target road using inspection equipment to obtain the vehicle location points of each target vehicle on the target road, and obtaining a set of road parking surfaces corresponding to the target vehicles; analyzing each road parking surface in the set to obtain the authenticity of parking for the corresponding target vehicle and the corresponding fee standard; and registering and managing fees for the corresponding target vehicles according to the fee standard based on the authenticity of parking. This reduces data management complexity and improves the user parking experience.

Description

Technical Field

[0001] This invention relates to the field of inspection and toll collection technology, and in particular to a method for road parking toll collection inspection. Background Technology

[0002] For cities where roadside parking fee collection systems are stable and citizens have a relatively mature understanding of roadside parking payment, a "geomagnetic + intelligent inspection vehicle" model is adopted to reduce labor costs. The geomagnetic system is used for timing and billing, while the inspection vehicle is used for license plate recognition and automatic binding with parking spaces. The algorithms of the two are integrated to collect fees from vehicles. This method generally starts timing as soon as a vehicle is detected entering the corresponding location (partial or complete). During this process, there may be cases of false parking. If vehicle information is collected every time a vehicle is detected, it will undoubtedly increase the difficulty of data management and cannot guarantee the accuracy of the fee collection, which may lead to dissatisfaction among parking users. Summary of the Invention

[0003] This invention provides a method for inspecting and charging road parking fees, which determines the actual parking situation of vehicles by acquiring the road parking surface set of vehicles, reducing the difficulty of data management, and improving the user parking experience by setting corresponding charging standards.

[0004] This invention provides a method for road parking fee collection and inspection, comprising:

[0005] Step 1: Conduct road inspection on the target road using the inspection equipment, obtain the vehicle location point of each target vehicle on the target road, and obtain the road parking face set of the corresponding target vehicle;

[0006] Step 2: Analyze each road parking surface in the road parking surface set to obtain the authenticity of the parking of the corresponding target vehicle and the charging standard under the authenticity of the parking.

[0007] Step 3: Register and manage the fees for the corresponding target vehicles according to the fee standards under the parking authenticity system.

[0008] Preferably, there are several inspection devices, and each inspection device includes: a vehicle sensing unit, a shooting unit, and a duration recording unit;

[0009] Preferably, step 1 includes:

[0010] The vehicle sensing unit of the inspection equipment senses whether a vehicle is entering the target road. If so, the control time recording unit starts and counts the time when the vehicle enters the target road. At the same time, the shooting unit starts working to acquire video of the vehicle entering at each statistical moment within the statistical time period.

[0011] The vehicle's trajectory location points are analyzed using video, and combined with the road parking line division standard of the target road, the trajectory coverage line and vehicle boundary coverage area based on the target road are obtained at each statistical time, and the road parking area at the corresponding statistical time is obtained.

[0012] Based on the statistical time and the road parking surfaces at the statistical time, a set of road parking surfaces corresponding to the target vehicles is constructed.

[0013] Preferably, the charging standard for each road parking surface in the road parking surface cluster is analyzed to obtain the corresponding target vehicle, including:

[0014] Determine the first moment when road parking spaces are concentrated and the second moment when road parking spaces are consistent;

[0015] Determine the first number of roads with consistent parking surfaces and the first time segment of the second time segment when each road parking surface is consistent, and obtain the first position distribution function for each first time segment;

[0016] Determine the second number of inconsistent road parking surfaces, lock the time position of the first moment, and analyze the continuous and discontinuous segments in all the first moments;

[0017] Based on the third quantity of continuous segments and the fourth quantity of discontinuous segments, and in conjunction with the second positional distribution function of each continuous segment and the third positional distribution function of each discontinuous segment,

[0018] Based on the first location distribution function, the second location distribution function, and the third location distribution function, the global optimal solution for the road parking surface set is obtained;

[0019] When the global optimal solution satisfies the set parking constraints, the first charge is applied to the target vehicle corresponding to the time period of all first time segments according to the charging standard;

[0020] When the global optimal solution does not meet the set parking constraints, the road parking surface at each statistical time point is analyzed by grid analysis to construct a new charging standard for the target vehicle and a second charging is performed.

[0021] Preferably, before conducting road inspections on the target road using inspection equipment, the following steps are included:

[0022] The road coverage area corresponding to each inspection device in the target road is determined. At the same time, the historical usage information of the inspection device is analyzed in multiple dimensions to calculate the effective inspection value of the corresponding inspection device based on the road coverage area entered by the vehicle at a subsequent time. The subsequent time refers to the next time after the operating status of the corresponding inspection device reaches the life cycle time.

[0023] When the effective value of the inspection is greater than or equal to the preset effective value, the optimal service cycle of the corresponding inspection equipment is extended, and after the optimal service cycle is reached, the auxiliary equipment set in the road coverage area is started to perform road inspection.

[0024] When the effective value of the inspection is less than the preset effective value, the auxiliary equipment set in the road coverage area is directly activated to carry out road inspection.

[0025] Preferably, the process of performing grid analysis on the road parking surface at each statistical time point includes:

[0026] Based on the time attribute of the statistical time of each road parking surface, the grid splitting unit of the corresponding road parking surface is obtained from the attribute-parse mapping table, and then the boundary accuracy of the corresponding road parking surface is determined, as well as the boundary distortion coefficient and trajectory distortion coefficient of each road parking surface are determined.

[0027] Based on the boundary distortion coefficient and trajectory distortion coefficient, the surface quality coefficient of the corresponding road parking surface is obtained, and the coefficient sequence of the corresponding target vehicle is constructed. The optimal solution and the second optimal solution of the corresponding target vehicle are obtained by combining the linear weighting method.

[0028] The coefficient ratio is verified based on the ratio of the optimal solution and the second optimal solution to the coefficient sequence, and in combination with the boundary association and trajectory association of the road parking surface at adjacent time points.

[0029] If the verification passes, the corresponding road parking area will be retained;

[0030] If the verification fails, the failed parameters are used to optimize the boundary accuracy, and the boundaries and trajectories of the road parking surface are refined according to the optimized accuracy to obtain a new parking surface, and the original road parking surface is replaced or retained.

[0031] A new pricing structure will be developed based on all retained parking areas.

[0032] Preferably, the corresponding target vehicle is registered and managed for toll collection according to the aforementioned toll standard, including:

[0033] The parking fee for the corresponding target vehicle shall be determined according to the charging standard under the aforementioned parking authenticity.

[0034] The parking fee request for the target vehicle is sent to the vehicle terminal for the driver to pay. At the same time, the entire parking video and payment result based on the target vehicle are sent to the corresponding management terminal and stored.

[0035] Preferably, the boundary accuracy is optimized by obtaining parameters that have not been passed, and the boundary and trajectory of the road parking surface are refined according to the optimized accuracy, including:

[0036] Obtain the verification log during the verification process, and extract the set verification parameters and the process fluctuation index of different set verification parameters from the verification log;

[0037] The process noise coefficient based on the verification process is determined according to the process fluctuation index, and the current verification accuracy is determined according to the set verification parameters and the process fluctuation index.

[0038] Based on the process fluctuation index, the first failed parameter is selected from all the set verification parameters that are greater than the corresponding first preset index, and the second failed parameter is selected that is greater than the corresponding second preset index and not greater than the corresponding first preset index.

[0039] Based on the first failed parameter, the second failed parameter, and the current verification accuracy, the boundary accuracy is optimized.

[0040] The number of subdivisions for each grid unit is determined based on the optimization accuracy, and the centerline of each grid unit is locked. The subdivisions on the centerline are then expanded and filled by N times to achieve fine-grained boundary and trajectory analysis.

[0041] Compared with the prior art, the beneficial effects of this application are as follows:

[0042] By acquiring the roadside parking area set of vehicles, the actual parking situation of vehicles can be determined, reducing the difficulty of data management, and by setting corresponding charging standards, the user parking experience can be improved.

[0043] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0044] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0045] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0046] Figure 1 This is a flowchart of a road parking fee collection and inspection method according to an embodiment of the present invention;

[0047] Figure 2 This is a structural diagram of the road parking surface in an embodiment of the present invention;

[0048] Figure 3 This is a structural diagram of the grid splitting unit in an embodiment of the present invention. Detailed Implementation

[0049] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0050] This invention provides a method for road parking fee collection and inspection, such as... Figure 1 As shown, it includes:

[0051] Step 1: Conduct road inspection on the target road using the inspection equipment, obtain the vehicle location point of each target vehicle on the target road, and obtain the road parking face set of the corresponding target vehicle;

[0052] Step 2: Analyze each road parking surface in the road parking surface set to obtain the authenticity of the parking of the corresponding target vehicle and the charging standard under the authenticity of the parking.

[0053] Step 3: Register and manage the fees for the corresponding target vehicles according to the fee standards under the parking authenticity system.

[0054] Preferably, there are several inspection devices, and each inspection device includes: a vehicle sensing unit, a shooting unit, and a duration recording unit.

[0055] In this embodiment, the vehicle sensing unit can be a ground induction coil, that is, a ground induction coil is set under the ground corresponding to each parking space, and the ground induction coil can be set on the entry boundary line based on the parking space, or the ground of the parking space can be covered.

[0056] In this embodiment, the shooting unit can be a camera, and the duration recording unit is a timer.

[0057] In this embodiment, the purpose of road inspection is to determine whether a target vehicle exists in a parking space on the target road, facilitating the capture of the vehicle's top-down position relative to the ground and its movement trajectory, thereby constructing a road parking surface. The road parking surface set includes road parking surfaces obtained at different times, such as... Figure 2 As shown, A1 is the vehicle's trajectory, and B1 is the top-down view of the vehicle's position relative to the ground.

[0058] In this embodiment, during the analysis of road parking areas, the authenticity of parking is determined by the parking duration under unchanged location conditions, and then a charging standard is issued. Generally, if the parking duration under unchanged location conditions is longer than the preset duration, it is determined to be a genuine parking; otherwise, it is determined to be a fake parking.

[0059] The beneficial effects of the above technical solution are: by obtaining the road parking surface set of vehicles, the actual parking situation of vehicles can be determined, reducing the difficulty of data management, and by setting corresponding charging standards, the user parking experience can be improved.

[0060] This invention provides a method for road parking fee collection and inspection, step 1 of which includes:

[0061] The vehicle sensing unit of the inspection equipment senses whether a vehicle is entering the target road. If so, the control time recording unit starts and counts the time when the vehicle enters the target road. At the same time, the shooting unit starts working to acquire video of the vehicle entering at each statistical moment within the statistical time period.

[0062] The vehicle's trajectory location points are analyzed using video, and combined with the road parking line division standard of the target road, the trajectory coverage line and vehicle boundary coverage area based on the target road are obtained at each statistical time, and the road parking area at the corresponding statistical time is obtained.

[0063] Based on the statistical time and the road parking surfaces at the statistical time, a set of road parking surfaces corresponding to the target vehicles is constructed.

[0064] In this embodiment, the system detects whether there is a pressure signal based on the inductive loop. If there is, it determines that a vehicle has entered and then controls the duration recording unit to start working.

[0065] In this embodiment, trajectory location point analysis is... Figure 2 In the A1 analysis, the road parking line division standard refers to the white line that divides each parking space. That is, the target road is divided based on the white line to obtain a number of parking spaces.

[0066] In this embodiment, the trajectory coverage line is the vehicle movement trajectory at the corresponding time, and the statistical time can be regarded as 2 seconds, because there will be a certain trajectory segment when the vehicle is in motion.

[0067] In this embodiment, the vehicle boundary coverage area is... Figure 2 B1 in the middle.

[0068] In this embodiment, the road parking surface = the trajectory coverage line at the corresponding statistical time + the vehicle boundary coverage surface.

[0069] The beneficial effects of the above technical solution are: by controlling the different units contained in the inspection equipment to start working, the corresponding parameters that need to be acquired are statistically analyzed, and then the road parking set of vehicles is obtained based on the trajectory coverage line and the vehicle boundary coverage area, providing a basis for subsequent parking authenticity and charging standards.

[0070] This invention provides a method for inspecting and charging road parking fees, which analyzes each road parking surface in a set of road parking surfaces to obtain the charging standard for the corresponding target vehicle, including:

[0071] Determine the first moment when road parking spaces are concentrated and the second moment when road parking spaces are consistent;

[0072] Determine the first number of roads with consistent parking surfaces and the first time segment of the second time segment when each road parking surface is consistent, and obtain the first position distribution function for each first time segment;

[0073] Determine the second number of inconsistent road parking surfaces, lock the time position of the first moment, and analyze the continuous and discontinuous segments in all the first moments;

[0074] Based on the third quantity of continuous segments and the fourth quantity of discontinuous segments, and in conjunction with the second positional distribution function of each continuous segment and the third positional distribution function of each discontinuous segment,

[0075] Based on the first location distribution function, the second location distribution function, and the third location distribution function, the global optimal solution for the road parking surface set is obtained;

[0076] When the global optimal solution satisfies the set parking constraints, the first charge is applied to the target vehicle corresponding to the time period of all first time segments according to the charging standard;

[0077] When the global optimal solution does not meet the set parking constraints, the road parking surface at each statistical time point is analyzed by grid analysis to construct a new charging standard for the target vehicle and a second charging is performed.

[0078] In this embodiment, because the trajectory of a vehicle changes constantly during parking on the target road, it is necessary to determine the times when parking surfaces are consistent and inconsistent from the set of parking surfaces. For example, if there are parking surfaces 1, 2, 3, 4, and 5 in chronological order, and parking surfaces 1 and 2 are inconsistent, then the time corresponding to parking surfaces 1 and 2 is considered the first time. If parking surfaces 3, 4, and 5 are consistent, then the time corresponding to parking surfaces 3, 4, and 5 is considered the second time. In this case, the first quantity is 3.

[0079] Since the parking surfaces may be consistent during certain time periods, for example, the parking surfaces are consistent during the t1~t3 period and consistent during the t7~t9 period, the first time period is t1~t3 and t7~t9. At this time, the position distribution functions W(t1~t3, ws1) and W(t7~t9, ws2) for the corresponding time periods are obtained respectively. Among them, ws1 and ws2 can be regarded as the position sets for the corresponding time periods.

[0080] In this embodiment, the second number of inconsistent road parking surfaces is obtained by counting all inconsistent road parking surfaces in the road parking surface set.

[0081] In this embodiment, the inconsistent distribution of road parking surfaces may be continuous or discontinuous. Therefore, by determining the continuous and discontinuous segments, a second location distribution function D2 (continuous segment, distribution position under the continuous segment, road parking surface under the continuous segment) and a third location distribution function D3 (discontinuous segment, distribution position under the discontinuous segment, road parking surface under the discontinuous segment) are constructed.

[0082] In this embodiment, the global optimal solution is obtained by inputting the first position distribution function, the second position distribution function, and the third position distribution function into the function interpretation model. This function interpretation model is obtained by experts analyzing the optimal results of different combinations of position distribution functions and training the neural network model with the function combinations themselves as samples. This makes it convenient to directly obtain the global optimal solution. The purpose of the global optimal solution is to remove the interference of continuous and discontinuous segments on the first time segment, thereby effectively obtaining the final quantity of the first time segment. In other words, in this process, the existence of continuous and discontinuous segments will affect the final charging. If this part can be deleted, the final first time segment is the basis for charging.

[0083] In this embodiment, the preset parking constraint is whether there is only one first time segment and the continuous duration of the first time segment is greater than the set duration. That is, when the global optimal solution satisfies this constraint, the first charge is performed.

[0084] In this embodiment, grid parsing involves dividing the road parking surface into grids and comparing them with the edge lines of parking spaces to determine whether they are within the corresponding boundary lines, thereby determining the charging standard.

[0085] The beneficial effects of the above technical solution are: by analyzing the consistency and inconsistency of road parking surfaces at different times, the distribution function of consistency and inconsistency can be determined, thereby determining the global optimal solution for the set, which facilitates subsequent charging according to the corresponding standards and improves the user parking experience.

[0086] This invention provides a method for road parking fee collection and inspection, which includes, before conducting road inspection on a target road using inspection equipment:

[0087] The road coverage area corresponding to each inspection device in the target road is determined. At the same time, the historical usage information of the inspection device is analyzed in multiple dimensions to calculate the effective inspection value of the corresponding inspection device based on the road coverage area entered by the vehicle at a subsequent time. The subsequent time refers to the next time after the operating status of the corresponding inspection device reaches the life cycle time.

[0088] When the effective value of the inspection is greater than or equal to the preset effective value, the optimal service cycle of the corresponding inspection equipment is extended, and after the optimal service cycle is reached, the auxiliary equipment set in the road coverage area is started to perform road inspection.

[0089] When the effective value of the inspection is less than the preset effective value, the auxiliary equipment set in the road coverage area is directly activated to carry out road inspection.

[0090] In this embodiment, the road coverage range refers to how many parking spaces one inspection device can cover. For example, inspection device 01 can inspect parking space a1 and parking space a2.

[0091] In this embodiment, the multi-dimensional analysis considers various aspects such as the historical shooting sensitivity, historical sensing sensitivity, and the duration of each historical use of the inspection equipment.

[0092] In this embodiment, the effective value of the inspection is calculated as follows:

[0093]

[0094]

[0095] If two or three coefficients are less than 0, the effective value of the inspection is determined to be 0. Otherwise, the three coefficients are multiplied by their respective weights and summed, and the result is taken as the effective value of the inspection.

[0096] In this embodiment, the preset effective value is pre-set and is 0.3.

[0097] In this embodiment, the optimal usage period is determined based on a duration effective coefficient, which is multiplied by the total historical usage time of the inspection equipment and then divided by 2.

[0098] In this embodiment, the auxiliary equipment, which is also the inspection equipment, is mainly used to ensure that the auxiliary equipment continues to work after the inspection equipment reaches its service life, so as to ensure effective inspection of the target road.

[0099] The beneficial effects of the above technical solution are: by analyzing the usage of the inspection equipment, the reliability of the results obtained from subsequent road inspections can be determined, thereby indirectly ensuring the accuracy of subsequent analysis.

[0100] This invention provides a method for inspecting and collecting tolls on roads. The process of performing grid analysis on the road parking surface at each statistical time point includes:

[0101] Based on the time attribute of the statistical time of each road parking surface, the grid splitting unit of the corresponding road parking surface is obtained from the attribute-parse mapping table, and then the boundary accuracy of the corresponding road parking surface is determined, as well as the boundary distortion coefficient and trajectory distortion coefficient of each road parking surface are determined.

[0102] Based on the boundary distortion coefficient and trajectory distortion coefficient, the surface quality coefficient of the corresponding road parking surface is obtained, and the coefficient sequence of the corresponding target vehicle is constructed. The optimal solution and the second optimal solution of the corresponding target vehicle are obtained by combining the linear weighting method.

[0103] The coefficient ratio is verified based on the ratio of the optimal solution and the second optimal solution to the coefficient sequence, and in combination with the boundary association and trajectory association of the road parking surface at adjacent time points.

[0104] If the verification passes, the corresponding road parking area will be retained;

[0105] If the verification fails, the failed parameters are used to optimize the boundary accuracy, and the boundaries and trajectories of the road parking surface are refined according to the optimized accuracy to obtain a new parking surface, and the original road parking surface is replaced or retained.

[0106] A new pricing structure will be developed based on all retained parking areas.

[0107] In this embodiment, the time attribute is related to whether the surface of the corresponding road parking surface is consistent with the time of occurrence of the consistency, and thus the corresponding grid splitting unit can be obtained from the mapping table. The table contains different time attributes and the size of the splitting unit based on the attribute, thereby enabling the splitting of the road parking surface. The grid splitting unit corresponds to different time attributes, and the unit size is different for different attributes. If the time attribute is that the surface is inconsistent and the occurrence time is at the beginning, the size of the corresponding splitting unit is u1. If the time attribute is that the surface is inconsistent and the occurrence time is in the middle, the size of the corresponding splitting unit is u2. At this time, u2 is smaller than u1. That is, the less important the attribute is, the larger the corresponding unit is, which means that the corresponding surface is less representative and the lower the information value.

[0108] In this embodiment, the boundary accuracy is related to the size of the cell. The smaller the cell size, the higher the accuracy, which is obtained by matching the cell size-accuracy mapping table.

[0109] In this embodiment, the formula for calculating the boundary distortion coefficient BJ is as follows:

[0110]

[0111] Where n01 represents the number of grids after the corresponding road parking face is split at the boundary; This represents the length of the boundary line of the road parking surface in the i1th grid. This represents the length of the diagonal of the grid corresponding to the i1th grid. This indicates the position weight of the i1th grid cell based on the boundary line; This indicates the top-view boundary length of the corresponding vehicle; It means except for the i1th one The remaining outside The variance.

[0112] In this embodiment, the formula for calculating the trajectory distortion coefficient GJ is as follows:

[0113]

[0114] Where n02 represents the number of grids after the trajectory is split in the corresponding road parking surface; This represents the length of the trajectory line corresponding to the i2th grid. This represents the length of the diagonal of the grid corresponding to the i2th grid. This represents the position weight of the i2th grid based on the trajectory.

[0115] In this embodiment, the surface quality coefficient = boundary distortion coefficient + trajectory distortion coefficient.

[0116] In this embodiment, the coefficient sequence is: {surface quality coefficient at time 1, surface quality coefficient at time 2, ...}.

[0117] In this embodiment, the linear weighting method calculates a value by weighting each coefficient in the coefficient sequence, which is considered the optimal solution. After removing the maximum and minimum values ​​in the coefficient sequence, the remaining coefficients are weighted to obtain another value, which is considered the second optimal solution.

[0118] In this embodiment, the coefficient ratio is: (2 × surface quality coefficient) / (optimal solution + second optimal solution).

[0119] In this embodiment, boundary association refers to the sum / 2 of the differences in distance between the boundary at the previous time step, the boundary at the next time step, and the boundary at the current time step;

[0120] Trajectory association refers to the sum / 2 of the differences in distance between the boundary of the previous time step and the boundary of the next time step and the trajectory position at the current time step;

[0121] Verification refers to whether the distance difference between the boundary association and the trajectory association is within the set difference range corresponding to the proportional coefficient. If it is, the verification is deemed to be successful. The set difference range is preset. For example, if the coefficient ratio is b1, the corresponding set difference range is (L1, L2).

[0122] In this embodiment, the parameter that fails refers to the association that is not within the set difference range. The purpose of accuracy optimization is to further optimize the boundary and avoid abnormal coefficient ratios due to accuracy analysis errors.

[0123] In this embodiment, the refinement of the boundary and trajectory refers to thickening the corresponding position points and adjusting the offset movement of the point positions.

[0124] In this embodiment, the new charging standard refers to re-analyzing the retained parking areas according to the original analysis process to obtain the continuous segments for charging.

[0125] The beneficial effects of the above technical solution are as follows: by determining the grid splitting unit and boundary accuracy through time attributes, the distortion coefficients of the boundary and trajectory are determined, and then two solutions are determined based on the coefficient sequence, providing a basic judgment for the adjustment of the road parking surface. Furthermore, the rationality of the road parking surface is further ensured by verifying the coefficient ratio, providing a reliable basis for determining the charging standard and indirectly improving the user parking experience.

[0126] This invention provides a method for road parking fee collection and inspection, which includes registering and managing fees for corresponding target vehicles according to the stated fee standard, comprising:

[0127] The parking fee for the corresponding target vehicle shall be determined according to the charging standard under the aforementioned parking authenticity.

[0128] The parking fee request for the target vehicle is sent to the vehicle terminal for the driver to pay. At the same time, the entire parking video and payment result based on the target vehicle are sent to the corresponding management terminal and stored.

[0129] The beneficial effects of the above technical solution are: by sending different results to different ends, both parties can be assured of their understanding of the results, which facilitates management.

[0130] This invention provides a method for inspecting and charging road parking fees, which involves obtaining parameters that fail to meet standards, optimizing the boundary accuracy, and refining the boundary and trajectory of the road parking surface according to the optimized accuracy. The method includes:

[0131] Obtain the verification log during the verification process, and extract the set verification parameters and the process fluctuation index of different set verification parameters from the verification log;

[0132] The process noise coefficient based on the verification process is determined according to the process fluctuation index, and the current verification accuracy is determined according to the set verification parameters and the process fluctuation index.

[0133] Based on the process fluctuation index, the first failed parameter is selected from all the set verification parameters that are greater than the corresponding first preset index, and the second failed parameter is selected that is greater than the corresponding second preset index and not greater than the corresponding first preset index.

[0134] Based on the first failed parameter, the second failed parameter, and the current verification accuracy, the boundary accuracy is optimized.

[0135] The number of subdivisions for each grid unit is determined based on the optimization accuracy, and the centerline of each grid unit is locked. The subdivisions on the centerline are then expanded and filled by N times to achieve fine-grained boundary and trajectory analysis.

[0136] In this embodiment, the verification parameter refers to the comparison process between two correlations and a set difference range. If noise occurs during this process, comparison errors may occur. For example, the original difference distance is u01, which is within the set difference range, but due to the presence of noise, the original difference distance changes to u02, which is no longer within the set difference range. In this case, it is necessary to determine the process noise coefficient to avoid noise interfering with the verification process.

[0137] In this embodiment, the verification log refers to the log information generated during the verification process, mainly for the purpose of complete statistics on the data involved in the verification process. The verification parameters refer to two related parameters, but these two parameters have a pre-defined fluctuation range. For example, the fluctuation index for the boundary-related parameter is... The fluctuation exponent for trajectory association parameters is 2.

[0138] In this embodiment, the process noise figure = / The unit of variation corresponding to the parameter type.

[0139] Current verification accuracy = original accuracy .

[0140] In this embodiment, the first preset index and the second preset index are preset, and the first preset index is greater than the second preset index.

[0141] In this embodiment, the "failed parameter" refers to the associated parameter that is not within the set difference range.

[0142] In this embodiment, the optimized accuracy = current verification accuracy + ((number of first failed parameters + number of second failed parameters) / total number of set verification parameters) × quantity accuracy unit.

[0143] In this embodiment, the number of subdivided units is equal to ceiling ((optimization precision × size of the corresponding mesh subdivision unit) / precision of the corresponding mesh subdivision unit), and ceiling is the rounding up sign. The corresponding unit is subdivided into a mesh with the same number of subdivided units according to this number, and each sub-mesh unit is the corresponding subdivided unit.

[0144] In this embodiment, the center line is the line connecting the two centers of the corresponding boundary line in the grid.

[0145] In this embodiment, N = number of subdivided units / (center length of corresponding grid split unit / diagonal length).

[0146] like Figure 3 As shown, the mesh splitting unit B0 is split into several subdivision units b1, where A1 is the center line of B0. The N-fold expansion is to expand the subdivision unit b1, and the expansion result is b2, which is N b1 (taking one subdivision unit as an example). Then, the boundary and trajectory analysis is carried out on this basis. This expansion can be horizontal or vertical. When the mesh splitting unit is horizontal, vertical expansion is performed, and when the mesh splitting unit is vertical, horizontal expansion is performed.

[0147] The beneficial effects of the above technical solution are: by obtaining the noise figure and process amplitude index during the verification process, the current verification accuracy can be determined, the boundary accuracy can be optimized, the clarity of the parking surface can be determined, and the parking time can be reasonably statistically analyzed, thereby ensuring the rationality of the charging standard.

[0148] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for inspecting and collecting tolls for road parking, characterized in that, include: Step 1: Conduct road inspection on the target road using the inspection equipment, obtain the vehicle location point of each target vehicle on the target road, and obtain the road parking face set of the corresponding target vehicle; Step 2: Analyze each road parking surface in the road parking surface set to obtain the authenticity of the parking of the corresponding target vehicle and the charging standard under the authenticity of the parking. Step 3: Register and manage the fees for the corresponding target vehicles according to the fee standards under the parking authenticity criteria; Before conducting road inspections on the target road using inspection equipment, the following should be included: The road coverage area corresponding to each inspection device in the target road is determined. At the same time, the historical usage information of the inspection device is analyzed in multiple dimensions to calculate the effective inspection value of the corresponding inspection device based on the road coverage area entered by the vehicle at a subsequent time. The subsequent time refers to the next time after the operating status of the corresponding inspection device reaches the life cycle time. When the effective value of the inspection is greater than or equal to the preset effective value, the optimal service cycle of the corresponding inspection equipment is extended, and after the optimal service cycle is reached, the auxiliary equipment set in the road coverage area is started to perform road inspection. When the effective value of the inspection is less than the preset effective value, the auxiliary equipment set in the road coverage area is directly activated to carry out road inspection. The process of performing grid analysis on the road parking surface at each statistical time point includes: Based on the time attribute of the statistical time of each road parking surface, the grid splitting unit of the corresponding road parking surface is obtained from the attribute-parse mapping table, and then the boundary accuracy of the corresponding road parking surface is determined, as well as the boundary distortion coefficient and trajectory distortion coefficient of each road parking surface are determined. Based on the boundary distortion coefficient and trajectory distortion coefficient, the surface quality coefficient of the corresponding road parking surface is obtained, and the coefficient sequence of the corresponding target vehicle is constructed. The optimal solution and the second optimal solution of the corresponding target vehicle are obtained by combining the linear weighting method. The coefficient ratio is verified based on the ratio of the optimal solution and the second optimal solution to the coefficient sequence, and in combination with the boundary association and trajectory association of the road parking surface at adjacent time points. If the verification passes, the corresponding road parking area will be retained; If the verification fails, the failed parameters are used to optimize the boundary accuracy, and the boundaries and trajectories of the road parking surface are refined according to the optimized accuracy to obtain a new parking surface, and the original road parking surface is replaced or retained. A new pricing structure will be developed based on all retained parking areas.

2. The road parking fee collection and inspection method according to claim 1, characterized in that, The inspection equipment consists of several units, and each inspection equipment includes: a vehicle sensing unit, a camera unit, and a duration recording unit.

3. The road parking fee collection and inspection method according to claim 2, characterized in that, Step 1 includes: The vehicle sensing unit of the inspection equipment senses whether a vehicle is entering the target road. If so, the control time recording unit starts and counts the time when the vehicle enters the target road. At the same time, the shooting unit starts working to acquire video of the vehicle entering at each statistical moment within the statistical time period. The vehicle's trajectory location points are analyzed using video, and combined with the road parking line division standard of the target road, the trajectory coverage line and vehicle boundary coverage area based on the target road are obtained at each statistical time, and the road parking area at the corresponding statistical time is obtained. Based on the statistical time and the road parking surfaces at the statistical time, a set of road parking surfaces corresponding to the target vehicles is constructed.

4. The road parking fee collection and inspection method according to claim 1, characterized in that, Analyzing each road parking surface in the aforementioned road parking surface set yields the corresponding charging standard for the target vehicle, including: Determine the first moment when road parking spaces are concentrated and the second moment when road parking spaces are consistent; Determine the first number of roads with consistent parking surfaces and the first time segment of the second time segment when each road parking surface is consistent, and obtain the first position distribution function for each first time segment; Determine the second number of inconsistent road parking surfaces, lock the time position of the first moment, and analyze the continuous and discontinuous segments in all the first moments; Based on the third quantity of continuous segments and the fourth quantity of discontinuous segments, and in conjunction with the second positional distribution function of each continuous segment and the third positional distribution function of each discontinuous segment, Based on the first location distribution function, the second location distribution function, and the third location distribution function, the global optimal solution for the road parking surface set is obtained; When the global optimal solution satisfies the set parking constraints, the first charge is applied to the target vehicle corresponding to the time period of all first time segments according to the charging standard; When the global optimal solution does not meet the set parking constraints, the road parking surface at each statistical time point is analyzed by grid analysis to construct a new charging standard for the target vehicle and a second charging is performed.

5. The road parking fee collection and inspection method according to claim 1, characterized in that, According to the parking fee standards under the stated authenticity, the corresponding target vehicles will be registered and managed for fee collection, including: The parking fee for the corresponding target vehicle shall be determined according to the aforementioned fee schedule; The parking fee request for the target vehicle is sent to the vehicle terminal for the driver to pay. At the same time, the entire parking video and payment result based on the target vehicle are sent to the corresponding management terminal and stored.

6. The road parking fee collection and inspection method according to claim 1, characterized in that, The parameters that fail to meet the requirements are used to optimize the boundary accuracy, and the boundaries and trajectories of the road parking surface are refined according to the optimized accuracy, including: Obtain the verification log during the verification process, and extract the set verification parameters and the process fluctuation index of different set verification parameters from the verification log; The process noise coefficient based on the verification process is determined according to the process fluctuation index, and the current verification accuracy is determined according to the set verification parameters and the process fluctuation index. Based on the process fluctuation index, the first failed parameter is selected from all the set verification parameters that are greater than the corresponding first preset index, and the second failed parameter is selected that is greater than the corresponding second preset index and not greater than the corresponding first preset index. Based on the first failed parameter, the second failed parameter, and the current verification accuracy, the boundary accuracy is optimized. The number of subdivisions for each grid unit is determined based on the optimization accuracy, and the centerline of each grid unit is locked. The subdivisions on the centerline are then expanded and filled by N times to achieve fine-grained boundary and trajectory analysis.

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