An urban road intelligent parking management system based on Internet of Things technology

Abstract

The present invention belongs to the field of traffic management technology, and specifically is an urban road intelligent parking management system based on the Internet of Things technology, comprising a parking space query module, a parking space reservation request module, a reservation authority judgment module, a request control execution module, a parking space locking and tracking module and an urban parking management center; the present invention uses the parking space query module to query the vacant parking spaces in the corresponding area in advance, selects the vacant parking space required for parking and the expected parking time, and issues a parking space reservation request; when the car owner issues the parking space reservation request, the reservation authority of the car owner is analyzed and judged by the reservation authority judgment module; when a permission signal is generated, the corresponding road parking space is locked based on the parking space reservation request; if the corresponding car owner fails to arrive before the expected parking time, the analysis is used to determine whether to generate a continued locking inquiry signal and a parking space lock release signal, thereby realizing effective reservation management of urban road parking spaces with a high level of intelligence and automation.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic management, and in particular to an urban road intelligent parking management system based on Internet of Things technology. Background Art

[0002] Urban road parking refers to the parking services or facilities provided for motor vehicles within the scope of urban roads, mainly parking spaces designated at the edge of roadways, sidewalks or bicycle lanes. With the continuous growth of urban population and the continuous increase in car ownership, the difficulty of urban parking management is increasing, which also brings many inconveniences to citizens' travel and life.

[0003] Currently, when managing urban road parking, it is difficult for users to obtain real-time information about available parking spaces on urban roads in the desired area and make reservations in advance. Furthermore, it is impossible to accurately analyze and determine users' reservation permissions and automatically lock parking spaces when they are deemed to have reservation permissions. This is not conducive to the effective reservation management of urban road parking spaces, and the level of intelligence and automation is low.

[0004] In view of the above technical defects, a solution is now proposed. Summary of the Invention

[0005] The purpose of the present invention is to provide an intelligent parking management system for urban roads based on Internet of Things technology, which solves the problems of low intelligence and automation level in the existing technology, such as difficulty in real-time grasping the vacant parking spaces on urban roads in the required area and making reservations in advance, and failure to gradually and accurately analyze and judge the user's reservation authority and automatically lock the parking space when it is determined that the user has the reservation authority.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] An intelligent parking management system for urban roads based on Internet of Things technology includes a parking space query module, a parking space reservation request module, a reservation authority determination module, a request control execution module, a parking space locking and tracking module, and an urban parking management center. When a car owner needs to park in a parking space on an urban road in a corresponding area, the car owner uses the parking space query module to query the available parking spaces in the corresponding area in advance, selects the desired vacant space and the estimated time to park, and then sends a parking space reservation request through the parking space reservation request module.

[0008] After a car owner sends a parking space reservation request, the reservation authority determination module analyzes and determines the car owner's reservation authority and generates a permission signal or a permission-incompatible signal. If a permission-incompatible signal is generated, the car owner is not allowed to reserve a parking space for that time. If a permission signal is generated, the parking space reservation request module sends the car owner's parking space reservation request to the city parking management center.

[0009] Based on the parking space reservation request of the car owner, the urban parking management center sends a control instruction to the request control execution module. The request control execution module raises the parking space lock on a parking space in the corresponding area to lock the corresponding road parking space, and sends the parking space locking time to the parking space locking tracking module. The parking space locking tracking module starts timekeeping and charging; and after the corresponding road parking space is locked, if the corresponding car owner fails to arrive before the expected parking time, the parking space locking tracking module will analyze to determine whether to generate a continue locking inquiry signal and a parking space lock release signal, and will continue locking inquiry signal and parking space lock release signal to the user terminal of the corresponding car owner.

[0010] Furthermore, when the user terminal receives the continued locking inquiry signal, it sends a reminder message to the car owner. If the car owner requests to continue locking the corresponding parking space, the parking lock on the corresponding parking space is kept raised and the time counting and charging continue; otherwise, the parking lock on the corresponding parking space is lowered and the time counting and charging stop.

[0011] When a parking space lock release signal is generated, the corresponding car owner is notified through the user terminal, so that the parking space lock on the corresponding parking space is lowered to release the parking space lock, and the time and charging are stopped.

[0012] Furthermore, the specific analysis process of the reservation authority judgment module includes:

[0013] Obtain the estimated time of arrival for parking of the corresponding vehicle owner, mark the interval between the current time and the estimated time of arrival for parking as the estimated time, compare the estimated time with a preset estimated time threshold, and generate an authority violation signal if the estimated time exceeds the preset estimated time threshold;

[0014] If the estimated duration does not exceed the preset estimated duration threshold, the arrears information of the corresponding vehicle owner on urban road parking is obtained, the current arrears amount of the corresponding vehicle owner is collected, and the current arrears amount is compared with the preset arrears amount threshold. If the current arrears amount exceeds the preset arrears amount threshold, an authorization violation signal is generated;

[0015] If the current amount of outstanding payments does not exceed the preset outstanding payment threshold, the credit tracing value of the corresponding vehicle owner is obtained through analysis, and the credit tracing value is numerically compared with the preset credit tracing threshold. If the credit tracing value exceeds the preset credit tracing threshold, an authority disqualification signal is generated; if the credit tracing value does not exceed the preset credit tracing threshold, an authority-granting signal is generated.

[0016] Furthermore, the analysis and acquisition method of credit traceability value is as follows:

[0017] The system uses the current date and the end date as the starting date to trace back a retrospective period of L1. The number of times the corresponding car owner issued a parking space reservation request but did not actually park during the retrospective period is counted and marked as a parking space reservation anomaly value. In addition, all payment delay times for the corresponding car owner to pay for the parking space during the retrospective period are obtained, and the average of all payment delay times is calculated to obtain the delay time table value. The number of payment delay times that exceed the preset payment delay time threshold during the retrospective period is marked as the payment delay value. The credit retrospective value is obtained by numerically calculating the parking space reservation anomaly value, the delay time table value, and the payment delay value.

[0018] Furthermore, the parking space lock tracking module performs analysis to determine whether to generate a continued lock inquiry signal and a parking space lock release signal. The specific analysis and judgment process is as follows:

[0019] The excess time of the current moment compared to the corresponding expected parking time is obtained and marked as the approximate overtime, and the preset first time threshold and the preset second time threshold that match the current time period are obtained, and the second preset time threshold > the first preset time threshold > 0; the approximate overtime is numerically compared with the preset first time threshold and the preset second time threshold. If the approximate overtime exceeds the preset first time threshold, a continue locking inquiry signal is generated; if the approximate overtime exceeds the preset second time threshold, a parking space lock release signal is generated.

[0020] Furthermore, if the current time period is a time period when parking spaces are prone to being busy, a preset first time threshold WY1 and a preset second time threshold QY1 are allocated thereto; if the current time period is a time period when parking spaces are prone to being idle, a preset first time threshold WY2 and a preset second time threshold QY2 are allocated thereto; wherein, WY2>WY1>0, QY2>QY1>0.

[0021] Furthermore, the parking space locking and tracking module is in communication with the time-division detection module, which divides each day into twelve time periods, each of which lasts two hours, and sets a detection period of L2 for the number of days preceding the current date.

[0022] The parking space usage status of urban road parking spaces in the corresponding area during the detection period is divided into time periods for analysis, and the corresponding time periods are marked as busy periods or idle periods through analysis, and the marking information of each time period is sent to the parking space locking and tracking module and the urban parking management center.

[0023] Furthermore, the specific analysis process of marking the corresponding time period as a busy parking space period or an idle parking space period is as follows:

[0024] Obtain the real-time vacancy rate of parking spaces in the corresponding area during the corresponding time period on the corresponding date within the detection period, compare the real-time vacancy rate of parking spaces with a preset real-time vacancy rate threshold of parking spaces, and if the real-time vacancy rate of parking spaces exceeds the preset real-time vacancy rate threshold of parking spaces, determine that the corresponding area is in a sufficient parking space state; obtain the total duration of the sufficient parking space state during the corresponding time period on the corresponding date and mark it as the sufficient duration, and mark the average value of the real-time vacancy rate of parking spaces in the corresponding time period as the vacancy detection value;

[0025] The sufficient time and vacancy detection values ​​are numerically compared with the preset insufficient time threshold and the preset vacancy detection threshold, respectively. If the sufficient time or vacancy detection value exceeds the corresponding preset threshold, the corresponding time period is assigned a parking judgment symbol XL-1. The total number of times the corresponding time period is assigned the parking judgment symbol XL-1 during the detection period is obtained and marked as the parking priority judgment value. The average of all sufficient time periods in the corresponding time period during the detection period is calculated to obtain an idle time table value, and the average of all vacancy detection values ​​in the corresponding time period during the detection period is calculated to obtain a vacancy analysis value.

[0026] The period evaluation value is obtained by numerically calculating the parking priority value, idle time meter value and vacancy analysis value of the corresponding period, and the period evaluation value is numerically compared with the preset period evaluation threshold. If the period evaluation value exceeds the preset period evaluation threshold, the corresponding period is marked as a period when parking spaces are likely to be idle; if the period evaluation value does not exceed the preset period evaluation threshold, the corresponding period is marked as a period when parking spaces are likely to be busy.

[0027] Furthermore, the urban parking management center is connected to the regional parking supervision and analysis module in communication. The regional parking supervision and analysis module monitors and analyzes the parking behavior of vehicles in the urban road parking spaces in the corresponding area during the detection period, and determines whether to generate a strong parking supervision signal through analysis. When the strong parking supervision signal is generated, it will be sent to the urban parking management center.

[0028] Furthermore, the specific analysis process for determining whether to generate a strong parking supervision signal is as follows:

[0029] The number of collisions and scratches that occurred when parking in parking spaces on urban roads in the corresponding area during the detection period is obtained and marked as the parking risk frequency value, the number of incorrectly parked vehicles in parking spaces on urban roads in the corresponding area during the detection period is collected and marked as the parking abnormal frequency value, and the duration of incorrect parking when the vehicle is incorrectly parked is collected and marked as the abnormal parking time value. All abnormal parking time values ​​during the detection period are summed to obtain the parking abnormal time value;

[0030] The parking supervision coefficient is obtained by numerically calculating the parking risk frequency value, the parking abnormal frequency value and the parking abnormal time value. The parking supervision coefficient is then compared with a preset parking supervision coefficient threshold. If the parking supervision coefficient exceeds the preset parking supervision coefficient threshold, a strong parking supervision signal is generated.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] 1. In the present invention, a parking space query module searches for available parking spaces in the corresponding area in advance, selects the desired vacant parking space and the estimated time of arrival, and issues a parking space reservation request. When the vehicle owner issues the parking space reservation request, the vehicle owner's reservation authority is analyzed and determined. When an authorization signal is generated, the corresponding road parking space is locked based on the parking space reservation request. If the vehicle owner fails to arrive before the estimated time of arrival, the system determines whether to generate a continued locking inquiry signal and a parking space lock release signal, thereby achieving effective reservation management of urban road parking spaces with a high level of intelligence and automation.

[0033] 2. In the present invention, the regional parking supervision and analysis module monitors and analyzes the parking behavior of vehicles in urban road parking spaces in the corresponding area during the detection period. The analysis determines whether to generate a strong parking supervision signal. When the strong parking supervision signal is generated, parking supervision of the road parking spaces in the corresponding area is strengthened, which is conducive to ensuring parking safety and traffic safety in the corresponding area. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings;

[0035] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0036] Figure 2 This is a system block diagram of Example 2 of the present invention. DETAILED DESCRIPTION

[0037] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0038] Example 1: Figure 1 As shown, the present invention proposes an urban road intelligent parking management system based on Internet of Things technology, which includes a parking space query module, a parking space reservation request module, a reservation authority judgment module, a request control execution module, a parking space locking and tracking module and an urban parking management center;

[0039] When a car owner needs to park in a parking space on an urban road in a corresponding area, he or she uses a user terminal (referring to a user's vehicle-mounted terminal or mobile smart terminal, etc.) and a parking space query module to query available parking spaces in the corresponding area in advance, selects the desired vacant parking space and an estimated time to park, and then sends a parking space reservation request through the parking space reservation request module based on the user terminal. The parking space reservation request includes the desired vacant parking space and the estimated time to park.

[0040] After a car owner submits a parking space reservation request, the reservation authority determination module analyzes and determines the car owner's reservation authority. The analysis generates a permission signal or a permission-incompatible signal. If a permission-incompatible signal is generated, the car owner is not allowed to make a parking space reservation. If a permission signal is generated, the parking space reservation request module sends the car owner's parking space reservation request to the city parking management center. This module can accurately determine whether the car owner has reservation authority, which is conducive to effective supervision of car owners and reasonable parking space reservation. The specific analysis process of the reservation authority determination module is as follows:

[0041] Obtain the estimated time of arrival for parking of the corresponding vehicle owner, mark the interval between the current time and the estimated time of arrival for parking as the estimated time, compare the estimated time with the preset estimated time threshold, and if the estimated time exceeds the preset estimated time threshold, indicating that the interval of the current reservation is too long, generate a permission violation signal;

[0042] If the estimated duration does not exceed the preset estimated duration threshold, the arrears information of the corresponding vehicle owner on urban road parking is obtained, the current arrears amount of the corresponding vehicle owner is collected, and the current arrears amount is compared with the preset arrears amount threshold. If the current arrears amount exceeds the preset arrears amount threshold, it indicates that the vehicle owner currently has too many historical arrears and should pay the arrears in a timely manner, and an authority violation signal is generated;

[0043] If the current outstanding amount does not exceed the preset outstanding amount threshold, the credit retrospective value QX of the corresponding vehicle owner is obtained through analysis. Specifically, the retrospective period is set to L1, starting from the current date and the end date. Preferably, L1 is 45 days.

[0044] The number of times during the retrospective period that the corresponding vehicle owner made a parking space reservation request but did not actually park is marked as a parking space reservation anomaly, and all payment delay times for the corresponding vehicle owner during the retrospective period (referring to the interval between the time of leaving the road parking space after a parking session and the time of actually paying the parking fee) are obtained. The delay time table value is obtained by averaging all payment delay times, and the payment delay time is numerically compared with a preset payment delay time threshold. The number of payment delay times that exceeded the preset payment delay time threshold during the retrospective period is marked as the payment delay value;

[0045] The credit retrospective value QX is calculated by numerically calculating the parking reservation anomaly value YP, the delay time table value NX, and the payment delay value TW using the formula QX=ty×YP+re×NX+su×TW. Ty, re, and su are preset weight coefficients with values ​​greater than zero. A larger value of the credit retrospective value QX indicates a worse credit status of the corresponding vehicle owner in urban road parking during the retrospective period.

[0046] The credit tracing value QX is numerically compared with the preset credit tracing threshold. If the credit tracing value QX exceeds the preset credit tracing threshold, it indicates that the credit status of the corresponding car owner for urban road parking during the tracing period is not good, and the parking space reservation permission cannot be granted to him, and a permission-incompatible signal is generated; if the credit tracing value QX does not exceed the preset credit tracing threshold, it indicates that the credit status of the corresponding car owner for urban road parking during the tracing period is good, and the parking space reservation permission can be granted to him, and a permission-granting signal is generated.

[0047] Based on the parking space reservation request of the car owner, the urban parking management center sends a control instruction to the request control execution module. The request control execution module raises the parking space lock on a parking space in the corresponding area to lock the corresponding road parking space, and sends the parking space locking time to the parking space lock tracking module. The parking space lock tracking module starts timing and charging. When the car owner drives to the corresponding parking space, the request control execution module lowers the parking space lock on the corresponding parking space, and the car owner parks the vehicle in the corresponding parking space, realizing effective reservation management of urban road parking spaces, with a high level of intelligence and automation, significantly improving parking efficiency, and providing great convenience for the lives of urban citizens.

[0048] After locking the corresponding road parking space, if the corresponding vehicle owner fails to arrive before the expected parking time, the parking space lock tracking module will analyze and determine whether to generate a continued locking inquiry signal and a parking space lock release signal. The continued locking inquiry signal and the parking space lock release signal will be sent to the corresponding vehicle owner's user terminal through the Internet of Things, further realizing the intelligent reservation management of urban road parking spaces and significantly reducing the difficulty of reservation management of urban road parking spaces. The specific analysis and judgment process is as follows:

[0049] The duration of the current time exceeding the corresponding expected parking time is obtained and marked as the approximate overtime, and the preset first time threshold and the preset second time threshold that match the current time period are obtained (the second preset time threshold > the first preset time threshold > 0). Specifically, if the current time period is a time period when parking spaces are likely to be busy, the preset first time threshold WY1 and the preset second time threshold QY1 are assigned to it; if the current time period is a time period when parking spaces are likely to be idle, the preset first time threshold WY2 and the preset second time threshold QY2 are assigned to it; wherein WY2>WY1>0, QY2>QY1>0;

[0050] The estimated timeout period is numerically compared with the preset first timeout threshold and the preset second timeout threshold. If the estimated timeout period exceeds the preset first timeout threshold, a continue locking inquiry signal is generated; if the estimated timeout period exceeds the preset second timeout threshold, a parking space lock release signal is generated.

[0051] It should be noted that when the user terminal receives the continued locking inquiry signal, it sends a reminder message to the car owner. If the car owner requests to continue locking the corresponding parking space, the parking lock on the corresponding parking space will remain raised and the time and billing will continue; otherwise, the parking lock on the corresponding parking space will be lowered and the time and billing will be stopped; and when the parking lock release signal is generated, the corresponding car owner will be notified through the user terminal, so that the parking lock on the corresponding parking space will be lowered to release the parking lock and stop the time and billing.

[0052] Furthermore, the parking space locking and tracking module is communicatively connected to the time period detection module. The time period detection module divides each day into twelve time periods, each of which lasts for two hours, and sets a detection period L2 for a number of days going back from the current date; preferably, L2 is thirty days; and performs a time period analysis on the parking space usage of urban road parking spaces in the corresponding area during the detection period, and marks the corresponding time period as a busy time period or an idle time period through the analysis;

[0053] The marking information of each time period is sent to the parking space locking and tracking module and the city parking management center through the Internet of Things. This not only helps managers formulate parking management plans and supervision intensity that match different time periods, but also provides information support for the analysis process of the parking space locking and tracking module, thereby ensuring the accuracy of its analysis results. The specific analysis process is as follows:

[0054] Obtain the real-time parking space vacancy rate of the corresponding area during the corresponding time period on the corresponding date within the detection period (i.e., the ratio of the number of idle parking spaces to the total number of urban road parking spaces in the corresponding area), compare the real-time parking space vacancy rate with a preset real-time parking space vacancy rate threshold, and if the real-time parking space vacancy rate exceeds the preset real-time parking space vacancy rate threshold, indicating that the vacancy rate of urban road parking spaces in the corresponding area is high, the corresponding area is judged to be in a sufficient parking space state;

[0055] The total duration of sufficient parking spaces during the corresponding time period on the corresponding date is obtained and marked as sufficient duration, and the average value of the real-time vacancy rate of parking spaces during the corresponding time period is marked as the vacancy detection value. The sufficient duration and the vacancy detection value are numerically compared with the preset non-sufficient duration threshold and the preset vacancy detection threshold, respectively. If the sufficient duration or the vacancy detection value exceeds the corresponding preset threshold, indicating that parking spaces in the area are not in short supply during the corresponding time period on the corresponding date, the corresponding time period is assigned a parking judgment symbol XL-1.

[0056] The total number of times the corresponding time period in the detection period is assigned the parking judgment symbol XL-1 is obtained and marked as the parking priority judgment value, and the average of all sufficient time periods in the corresponding time period in the detection period is calculated to obtain the idle time table value, and the average of all vacancy detection values ​​in the corresponding time period in the detection period is calculated to obtain the vacancy analysis value;

[0057] The period evaluation value SW is calculated by numerically calculating the parking priority value XF, the idle time meter value QR, and the vacancy analysis value TM for the corresponding period using the formula SW=eq×XF+kp×QR+ru×TM. eq, kp, and ru are preset weight coefficients with values ​​greater than zero. The larger the period evaluation value SW, the less parking space shortage there is on the regional road during the corresponding period within the detection period, and the easier it is to park.

[0058] The time period evaluation value SW is numerically compared with the preset time period evaluation threshold. If the time period evaluation value SW exceeds the preset time period evaluation threshold, it indicates that the regional road parking spaces in the corresponding time period during the detection period are not tight and it is easier to park, and the corresponding time period is marked as a time period with easy parking spaces; if the time period evaluation value SW does not exceed the preset time period evaluation threshold, it indicates that the regional road parking spaces in the corresponding time period during the detection period are tight and it is more difficult to park, and the corresponding time period is marked as a time period with easy parking spaces.

[0059] Example 2: Figure 2As shown, the difference between this embodiment and the first embodiment is that the city parking management center is communicatively connected to the regional parking supervision and analysis module. The regional parking supervision and analysis module monitors and analyzes vehicle parking behavior in urban road parking spaces in a corresponding area during a detection period. The analysis determines whether to generate a strong parking supervision signal. When the strong parking supervision signal is generated, the strong parking supervision signal is sent to the city parking management center via the Internet of Things. Upon receiving the strong parking supervision signal, the city parking management center strengthens parking supervision of road parking spaces in the corresponding area, thereby ensuring parking safety and traffic safety in the corresponding area. The specific analysis process for determining whether to generate a strong parking supervision signal is as follows:

[0060] The number of collisions and scratches that occurred when parking in parking spaces on urban roads in the corresponding area during the detection period is obtained and marked as the parking risk frequency value, the number of incorrectly parked vehicles in parking spaces on urban roads in the corresponding area during the detection period is collected and marked as the parking abnormal frequency value, and the duration of incorrect parking when the vehicle is incorrectly parked is collected and marked as the abnormal parking time value. All abnormal parking time values ​​during the detection period are summed to obtain the parking abnormal time value;

[0061] The parking supervision coefficient GS is calculated by numerically calculating the parking risk frequency value TP, the parking frequency value PX, and the parking time value LF using the formula GS = up × TP + hu × PX + se × LF. Here, up, hu, and se are preset weight coefficients with values ​​greater than zero. A larger value for the parking supervision coefficient GS indicates worse parking behavior in urban road parking spaces in the corresponding area during the monitoring period.

[0062] The parking supervision coefficient GS is numerically compared with the preset parking supervision coefficient threshold. If the parking supervision coefficient GS exceeds the preset parking supervision coefficient threshold, it indicates that the parking behavior of vehicles in the urban road parking spaces in the corresponding area during the detection period is poor, and parking supervision in the corresponding area needs to be strengthened in a timely manner, then a strong parking supervision signal is generated.

[0063] The working principle of the present invention is as follows: when in use, the parking space query module is used to query the vacant parking spaces in the corresponding area in advance, the vacant parking space required for parking and the estimated parking time are selected, and a parking space reservation request is issued through the parking space reservation request module. When the car owner issues a parking space reservation request, the reservation authority judgment module analyzes and judges the car owner's reservation authority. When an authority-incompatible signal is generated, the corresponding car owner is not allowed to make a parking space reservation for the current time. When an authority-qualified signal is generated, the parking space reservation request module sends the car owner's parking space reservation request to the city parking management center, and the city parking management center controls the execution module through the request. The corresponding road parking space is locked, and the parking space lock tracking module starts timing and charging. When the car owner drives to the corresponding parking space, the parking space lock on the corresponding parking space is lowered. After the corresponding road parking space is locked, if the corresponding car owner fails to arrive before the expected parking time, the parking space lock tracking module will analyze to determine whether to generate a continue locking inquiry signal and a parking space lock release signal, thereby realizing effective reservation management of urban road parking spaces, significantly reducing the difficulty of reservation management of urban road parking spaces and improving parking efficiency, providing great convenience for the lives of urban citizens, and having a high level of intelligence and automation.

[0064] The above formulas are all dimensionless and calculated by taking their numerical values. The formula is a formula for the latest real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made based on the contents of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can well understand and use the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. An urban road intelligent parking management system based on Internet of Things technology, characterized by: It includes parking space query module, parking space reservation request module, reservation authority judgment module, request control execution module, parking space locking and tracking module and urban parking management center; The car owner uses the parking space query module to query the available parking spaces in the corresponding area in advance, selects the desired empty parking space and the expected parking time, and sends a parking space reservation request through the parking space reservation request module; After the car owner sends a parking space reservation request, the reservation authority judgment module analyzes and judges the car owner's reservation authority. If a permission-incompatible signal is generated, the car owner is not allowed to make a parking space reservation. If a permission-compliant signal is generated, the parking space reservation request module sends the car owner's parking space reservation request to the city parking management center. Based on the parking space reservation request from the car owner, the city parking management center sends a control instruction to the request control execution module, which causes the request control execution module to raise the parking lock on a parking space in the corresponding area to lock the corresponding road parking space. The parking space lock tracking module starts time counting and charging. After locking the corresponding road parking space, if the corresponding vehicle owner fails to arrive before the estimated parking time, the parking space lock tracking module will analyze and determine whether to generate a continued locking inquiry signal and a parking space lock release signal, and send the continued locking inquiry signal and the parking space lock release signal to the corresponding vehicle owner's user terminal; The specific analysis process of the reservation authority judgment module includes: Obtain the estimated time of arrival for parking of the corresponding vehicle owner, mark the interval between the current time and the estimated time of arrival for parking as the estimated time, compare the estimated time with a preset estimated time threshold, and generate an authority violation signal if the estimated time exceeds the preset estimated time threshold; If the estimated duration does not exceed the preset estimated duration threshold, the arrears information of the corresponding vehicle owner on urban road parking is obtained, the current arrears amount of the corresponding vehicle owner is collected, and the current arrears amount is compared with the preset arrears amount threshold. If the current arrears amount exceeds the preset arrears amount threshold, an authorization violation signal is generated; If the current outstanding amount does not exceed the preset outstanding amount threshold, the credit value of the corresponding vehicle owner is obtained through analysis, and the credit value is compared with the preset credit threshold. If the credit value exceeds the preset credit threshold, an authorization-incompatible signal is generated; if the credit value does not exceed the preset credit threshold, an authorization-enabled signal is generated. The analysis and acquisition method of credit traceability value is as follows: The system uses the current date and the end date as the starting date to trace back a retrospective period of L1. The number of times the corresponding car owner issued a parking space reservation request but did not actually park during the retrospective period is counted and marked as a parking space reservation anomaly value. In addition, all payment delay times for the corresponding car owner to pay for the parking space during the retrospective period are obtained, and the average of all payment delay times is calculated to obtain the delay time table value. The number of payment delay times that exceed the preset payment delay time threshold during the retrospective period is marked as the payment delay value. The credit retrospective value is obtained by numerically calculating the parking space reservation anomaly value, the delay time table value, and the payment delay value.

2. The urban road intelligent parking management system based on Internet of Things technology according to claim 1 is characterized in that: When the user terminal receives the lock-continue inquiry signal, it sends a reminder message to the car owner. If the car owner requests to continue locking the corresponding parking space, the parking lock on the corresponding parking space will remain raised and the time and charge will continue. Otherwise, the parking lock on the corresponding parking space will be lowered and the time and charge will stop. When a parking space lock release signal is generated, the corresponding car owner is notified through the user terminal, so that the parking space lock on the corresponding parking space is lowered to release the parking space lock, and the time and charging are stopped.

3. The urban road intelligent parking management system based on Internet of Things technology according to claim 1 is characterized in that: The analysis and judgment process of the parking space locking and tracking module is as follows: Obtaining the duration of the current time exceeding the corresponding estimated parking time and marking it as an estimated overtime duration, obtaining a preset first duration threshold and a preset second duration threshold that match the current time period, and obtaining the second preset duration threshold > the first preset duration threshold > 0; if the estimated overtime duration exceeds the preset first duration threshold, generating a continued locking inquiry signal; If the timeout exceeds the preset second time threshold, a parking space lock release signal is generated.

4. The urban road intelligent parking management system based on Internet of Things technology according to claim 3 is characterized in that: If the current time period is a time period when parking spaces are prone to being busy, the preset first time threshold WY1 and the preset second time threshold QY1 are allocated to it; if the current time period is a time period when parking spaces are prone to being idle, the preset first time threshold WY2 and the preset second time threshold QY2 are allocated to it; wherein, WY2>WY1>0, QY2>QY1>0.

5. The urban road intelligent parking management system based on Internet of Things technology according to claim 4 is characterized in that: The parking space locking and tracking module is communicated with the time period detection module. The time period detection module divides each day into twelve time periods, and conducts a time period analysis on the parking space usage status of urban road parking spaces in the corresponding area during the detection period. Based on this, the corresponding time period is marked as a busy time period or an idle time period, and the marking information of each time period is sent to the parking space locking and tracking module and the urban parking management center.

6. The urban road intelligent parking management system based on Internet of Things technology according to claim 5 is characterized in that: The analysis and judgment process of parking space busy or idle periods is as follows: The period evaluation value is obtained by numerically calculating the parking priority value, idle time meter value and vacancy analysis value of the corresponding period. If the period evaluation value exceeds the preset period evaluation threshold, the corresponding period is marked as a parking space easy idle period; Otherwise, the corresponding time period will be marked as a busy parking period.

7. The urban road intelligent parking management system based on Internet of Things technology according to claim 1 is characterized in that: The urban parking management center is connected to the regional parking supervision and analysis module in communication. The regional parking supervision and analysis module monitors and analyzes the parking behavior of vehicles in the urban road parking spaces in the corresponding area during the detection period, and sends the strong parking supervision signal to the urban parking management center when it is generated.

8. The urban road intelligent parking management system based on Internet of Things technology according to claim 7 is characterized in that: The specific process of analyzing and determining whether to generate a strong parking supervision signal is as follows: The parking supervision coefficient is obtained by numerically calculating the parking risk frequency value, the parking abnormal frequency value and the parking abnormal time value. If the parking supervision coefficient exceeds a preset parking supervision coefficient threshold, a strong parking supervision signal is generated.

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