Urban road intelligent parking management system based on Internet of Things technology

Abstract

The invention belongs to the technical field of traffic management, and particularly relates to an urban road intelligent parking management system based on the Internet of Things technology, which comprises a parking space query module, a parking space reservation request module, a reservation permission judgment module, a request control execution module, a parking space locking tracking module and an urban parking management center. According to the invention, the parking space query module queries the free parking space of the corresponding area in advance, selects the free parking space needing to be parked, predicts the parking time and sends the parking space reservation request, and analyzes and judges the reservation authority of the vehicle owner through the reservation authority judgment module when the vehicle owner sends the parking space reservation request. According to the invention, when the permission signal is generated, the corresponding road parking space is locked based on the parking space reservation request, and if the corresponding vehicle owner does not arrive before the predicted parking time, whether a continuous locking inquiry signal and a parking space locking release signal are generated is judged through analysis, so that the effective reservation management of the urban road parking space is realized. And the intelligent level and the automation level are high.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic management, and in particular to an intelligent parking management system for urban roads based on the 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 road lanes, sidewalks or bicycle lanes. With the continuous growth of urban population and the continuous increase in the number of cars, the difficulty of urban parking management is increasing, which also brings many inconveniences to citizens' travel life; At present, when managing urban road parking, it is difficult for users to grasp the available parking spaces on urban roads in the desired area in real time and make reservations in advance. It is also impossible 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. This is not conducive to the effective reservation management of urban road parking spaces, and the level of intelligence and automation is low; In view of the above technical defects, a solution is now proposed. Summary of the invention

[0003] The purpose of the present invention is to provide an intelligent parking management system for urban roads based on the Internet of Things technology, which solves the problems that the prior art is difficult to grasp the vacant parking spaces on urban roads in the required area in real time and make reservations in advance, and is unable to gradually and accurately analyze and judge the user's reservation authority and automatically lock the parking space when it is judged that the user has the reservation authority, and has a low level of intelligence and automation.

[0004] To achieve the above object, the present invention provides the following technical solutions: An urban road intelligent parking management system based on Internet of Things technology comprises 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 tracking module and an urban parking management center; when a car owner needs to park in an urban road parking space in a corresponding area, the parking space query module is used to query the vacant parking spaces in the corresponding area in advance, and the vacant parking spaces 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; After the car owner sends a parking space reservation request, the reservation authority judgment module analyzes and judges the car owner's reservation authority, and generates a permission signal or a permission-incompatible signal through analysis. When the permission-incompatible signal is generated, the corresponding car owner is not allowed to make a parking space reservation at that time. When the permission signal is generated, the car owner's parking space reservation request is sent to the city parking management center through the parking space reservation request module; Based on the parking space reservation request of the car owner, the city parking management center sends a control instruction to the request control execution module, and 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, and the parking space locking tracking module starts timing 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 send the continue locking inquiry signal and the parking space lock release signal to the user terminal of the corresponding car owner.

[0005] Furthermore, when the user terminal receives the continued locking inquiry signal, a reminder message is sent 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 in the raised state and the time counting and charging are continued; otherwise, the parking lock on the corresponding parking space is lowered and the time counting and charging are stopped; When the 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 counting and charging are stopped.

[0006] Furthermore, the specific analysis process of the reservation authority judgment module includes: The estimated time of arrival and parking of the corresponding vehicle owner is obtained, the interval between the current time and the estimated time of arrival and parking is marked as the estimated time, and the estimated time is numerically compared with a preset estimated time threshold. If the estimated time exceeds the preset estimated time threshold, a permission incompatibility signal is generated; If the estimated duration does not exceed the preset estimated duration threshold, the arrears information of the corresponding car owner on urban road parking is obtained, the current arrears amount of the corresponding car 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, a permission incompatibility signal is generated; If the current amount of arrears does not exceed the preset arrears threshold, the credit tracing value of the corresponding car 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 incompatibility signal is generated; if the credit tracing value does not exceed the preset credit tracing threshold, an authority signal is generated.

[0007] Furthermore, the analysis and acquisition method of the credit traceability value is as follows: The number of days in the retrospective period is set as L1, and the number of times the corresponding car owner sends a parking space reservation request but does not actually park during the retrospective period is marked as a parking space reservation anomaly value. In addition, all payment delay times for parking space payment by the corresponding car owner during the retrospective period are obtained, and the delay time table value is obtained by averaging all payment delay times, and 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.

[0008] Furthermore, the specific analysis and judgment process of the parking space locking tracking module to analyze and determine whether to generate a continued locking inquiry signal and a parking space locking release signal is as follows: The excess time of the current time 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 matching 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, and 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.

[0009] 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.

[0010] Furthermore, the parking space locking and tracking module is connected to the time-division detection module in communication, and the time-division detection module divides each day into twelve time periods, each time period lasts for two hours, and traces back from the current date and sets the detection period for the number of days as L2; The parking space usage 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 time periods or idle time 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.

[0011] Furthermore, the specific analysis process of marking the corresponding time period as a parking space prone busy time period or a parking space prone idle time period through analysis is as follows: The real-time vacancy rate of parking spaces in the corresponding area during the corresponding time period of the corresponding date within the detection period is obtained, and the real-time vacancy rate of parking spaces is compared with the preset real-time vacancy rate threshold of parking spaces. If the real-time vacancy rate of parking spaces exceeds the preset real-time vacancy rate threshold of parking spaces, it is determined that the corresponding area is in a sufficient parking space state; the total duration of the sufficient parking space state in the corresponding time period of the corresponding date is obtained and marked as the sufficient duration, and the average value of the real-time vacancy rate of parking spaces in 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, 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 within the detection period is obtained and marked as the parking priority judgment value, and all the sufficient durations of the corresponding time period within the detection period are averaged to obtain the idle time table value, and all the vacancy detection values ​​of the corresponding time period within the detection period are averaged to obtain the vacancy analysis value; The time period evaluation value is obtained by numerically calculating the parking priority value, idle time meter value and vacancy analysis value of the corresponding time period, and the time period evaluation value is numerically compared with the preset time period evaluation threshold. If the time period evaluation value exceeds the preset time period evaluation threshold, the corresponding time period is marked as a time period when parking spaces are likely to be idle; if the time period evaluation value does not exceed the preset time period evaluation threshold, the corresponding time period is marked as a time period when parking spaces are likely to be busy.

[0012] Furthermore, the city parking management center is connected to the regional parking supervision and analysis module by 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 is sent to the city parking management center.

[0013] Furthermore, the specific analysis process for determining whether to generate a parking strong supervision signal is as follows: The number of collisions and scratches that occur when parking in the urban road parking spaces in the corresponding area during the detection period is obtained and marked as the parking risk frequency value, and the number of incorrect parking of vehicles in the urban road parking spaces in the corresponding area during the detection period is collected and marked as the parking abnormal frequency value, and when the vehicle is incorrectly parked, the duration of incorrect parking is collected and marked as the abnormal parking time value, and all abnormal parking time values ​​in the detection period are summed up to obtain the parking abnormal time value; 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, and the parking supervision coefficient is numerically 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.

[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. In the present invention, the parking space query module is used to query the vacant parking spaces in the corresponding area in advance, select the vacant parking space required for parking and the estimated parking time, and issue a parking space reservation request. When the car owner issues the parking space reservation request, the car owner's reservation authority is analyzed and judged. When the authority 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 estimated 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; 2. In the present invention, the parking behavior of vehicles in the urban road parking spaces in the corresponding area during the detection period is monitored and analyzed through the regional parking supervision and analysis module. The analysis is used to determine whether to generate a strong parking supervision signal. When the strong parking supervision signal is generated, the parking supervision of the road parking spaces in the corresponding area is strengthened, which is beneficial to ensuring the parking safety and traffic safety in the corresponding area. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings; Figure 1 This is a system block diagram of Embodiment 1 of the present invention; Figure 2 This is a system block diagram of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0017] Embodiment 1: Figure 1 As shown, the present invention proposes an urban road intelligent parking management system based on the Internet of Things technology, including 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 tracking module and an urban parking management center; When a car owner needs to park in a parking space on a city road in a corresponding area, he or she may query the free parking spaces in the corresponding area in advance through a parking space query module based on a user terminal (referring to a user's vehicle-mounted terminal or a mobile smart terminal, etc.), select the desired free parking space and the estimated time to park, and issue a parking space reservation request based on the user terminal and through a parking space reservation request module; wherein the parking space reservation request includes the desired free parking space and the estimated time to park; After the car owner sends a parking space reservation request, the reservation authority judgment module analyzes and judges the car owner's reservation authority, and generates a permission signal or a permission-incompatible signal through analysis. When the permission-incompatible signal is generated, the corresponding car owner is not allowed to make a parking space reservation at that time. When the permission signal is generated, the car owner's parking space reservation request is sent to the city parking management center through the parking space reservation request module, which can accurately determine whether the corresponding car owner has the reservation authority, which is conducive to the effective supervision of the car owner and the reasonable reservation of parking spaces. The specific analysis process of the reservation authority judgment module is as follows: The estimated time of arrival for parking of the corresponding vehicle owner is obtained, the interval between the current time and the estimated time of arrival for parking is marked as the estimated time, and the estimated time is numerically compared with the preset estimated time threshold. If the estimated time exceeds the preset estimated time threshold, it indicates that the interval of the current reservation is too long, and a permission incompatibility signal is generated; If the estimated duration does not exceed the preset estimated duration threshold, the arrears information of the corresponding car owner on urban road parking is obtained, the current arrears amount of the corresponding car 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 car owner currently has too much historical arrears and should pay the arrears in time, and then a permission violation signal is generated; If the current outstanding amount does not exceed the preset outstanding amount threshold, the credit retrospective value QX of the corresponding car owner is obtained through analysis, specifically: the retrospective period is set to L1 from the current date and the end date, preferably, L1 is forty-five days; The number of times that the corresponding car owner issued a parking space reservation request but did not actually park during the retrospective period is marked as a parking space reservation anomaly, and all payment delay times for the corresponding car owner to pay for the parking space during the retrospective period (referring to the interval between the time of leaving the road parking space after a parking is completed and the time of actually paying the parking fee for that time) are obtained, all payment delay times are averaged to obtain the delay time table value, and the payment delay time is numerically compared with the preset payment delay time threshold, and 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 parking space reservation abnormal value YP, the delay time table value NX and the payment delay value TW are numerically calculated by the formula QX=ty×YP+re×NX+su×TW to obtain the credit tracing value QX; wherein ty, re and su are preset weight coefficients with values ​​greater than zero, and the larger the value of the credit tracing value QX, the worse the credit status of the corresponding car owner in urban road parking during the tracing period; 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 in urban road parking during the tracing period is not good, and the parking space reservation authority cannot be opened to him, then 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 in urban road parking during the tracing period is good, and the parking space reservation authority can be opened to him, then a permission signal is generated.

[0018] Based on the parking space reservation request of the car owner, the city parking management center sends a control instruction to the request control execution module, and 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 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 high levels of intelligence and automation, significantly improving parking efficiency, and providing great convenience for the lives of urban citizens.

[0019] 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 continued locking inquiry signal and a parking space lock release signal, and the continued locking inquiry signal and the parking space lock release signal will be sent to the user terminal of the corresponding car owner 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: The excess time of the current time compared to the corresponding expected parking time is obtained and marked as the approximate excess time, 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 busy time period for parking spaces, the preset first time threshold WY1 and the preset second time threshold QY1 are allocated to it; if the current time period is a idle time period for parking spaces, the preset first time threshold WY2 and the preset second time threshold QY2 are allocated to it; wherein, WY2>WY1>0, QY2>QY1>0; The estimated time-out period is numerically compared with the preset first time-out threshold and the preset second time-out threshold. If the estimated time-out period exceeds the preset first time-out threshold, a continue locking inquiry signal is generated; if the estimated time-out period exceeds the preset second time-out threshold, a parking space lock release signal is generated.

[0020] 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 the time and billing will be stopped.

[0021] Further, the parking space locking and tracking module is communicated with the time period detection module, which divides each day into twelve time periods, each of which lasts for two hours, and traces back from the current date and sets the detection period of L2; preferably, L2 is thirty days; the parking space usage status of the urban road parking spaces in the corresponding area during the detection period is analyzed in time periods, and the corresponding time periods are marked as busy time periods or idle time periods through analysis; The marking information of each time period is sent to the parking space locking and tracking module and the urban parking management center through the Internet of Things, which is not only conducive to the management personnel to formulate matching parking management plans and supervision intensity for different time periods, but also can provide 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: The real-time vacancy rate of parking spaces in the corresponding area during the corresponding time period of the corresponding date within the detection period (i.e., the ratio of the number of parking spaces in an idle state to the total number of urban road parking spaces in the corresponding area) is obtained, and the real-time vacancy rate of parking spaces is numerically compared with a preset real-time vacancy rate threshold of parking spaces. If the real-time vacancy rate of parking spaces exceeds the preset real-time vacancy rate threshold of parking spaces, it indicates that the vacancy rate of urban road parking spaces in the corresponding area is high, and it is determined that the corresponding area is in a sufficient parking space state; The total duration of sufficient parking spaces in the corresponding time period of the corresponding date is obtained and marked as sufficient duration, and the average value of the real-time vacancy rate of parking spaces in 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 the parking spaces in the area are not tight in the corresponding time period of the corresponding date, the parking judgment symbol XL-1 is assigned to the corresponding time period; The total number of times the corresponding time period in the detection period is assigned with the parking judgment symbol XL-1 is obtained and marked as the parking priority judgment value, and all sufficient time lengths in the corresponding time period in the detection period are averaged to obtain the idle time table value, and all vacancy detection values ​​in the corresponding time period in the detection period are averaged to obtain the vacancy analysis value; The parking priority value XF, the idle time table value QR and the vacancy analysis value TM of the corresponding time period are numerically calculated by the formula SW=eq×XF+kp×QR+ru×TM to obtain the time period evaluation value SW; wherein eq, kp, ru are preset weight coefficients with values ​​greater than zero, and the larger the value of the time period evaluation value SW is, the less tight the regional road parking spaces are in the corresponding time period during the detection period, and the easier it is to park; 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 parking space free time period; 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 difficult to park, and the corresponding time period is marked as a parking space busy time period.

[0022] Embodiment 2: Figure 2 As shown, the difference between this embodiment and the first embodiment is that the city 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 is sent to the city parking management center through the Internet of Things. When the city parking management center receives the strong parking supervision signal, it strengthens the parking supervision of the road parking spaces in the corresponding area, which is conducive to ensuring the parking safety and traffic safety in the corresponding area. The specific analysis process of determining whether to generate a strong parking supervision signal through analysis is as follows: The number of collisions and scratches that occur when parking in the urban road parking spaces in the corresponding area during the detection period is obtained and marked as the parking risk frequency value, and the number of incorrect parking of vehicles in the urban road parking spaces in the corresponding area during the detection period is collected and marked as the parking abnormal frequency value, and when the vehicle is incorrectly parked, the duration of incorrect parking is collected and marked as the abnormal parking time value, and all abnormal parking time values ​​in the detection period are summed up to obtain the parking abnormal time value; The parking supervision coefficient GS is obtained by numerically calculating the parking risk frequency value TP, the parking frequency value PX and the parking time value LF through the formula GS=up×TP+hu×PX+se×LF; wherein up, hu and se are preset weight coefficients with values ​​greater than zero, and the larger the value of the parking supervision coefficient GS is, the worse the parking behavior of vehicles in the urban road parking spaces in the corresponding area during the detection period is. 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 time, then a strong parking supervision signal is generated.

[0023] The working principle of the present invention is as follows: when in use, the free parking spaces in the corresponding area are queried in advance through the parking space query module, 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 of the car owner is analyzed and judged through the reservation authority judgment module. When a signal of incompatibility with authority is generated, the corresponding car owner is not allowed to make a parking space reservation for the current time. When a signal of having authority is generated, the parking space reservation request of the car owner is sent to the city parking management center through the parking space reservation request module. 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.

[0024] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. 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 explain 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 according to 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 understand and use the present invention well. 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 in that: It 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; 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 estimated time to park, 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. When a permission-incompatible signal is generated, the corresponding car owner is not allowed to make a parking space reservation. When a permission-qualified signal is generated, the car owner's parking space reservation request is sent to the city parking management center through the parking space reservation request module. The city parking management center sends a control instruction to the request control execution module based on the parking space reservation request of the car owner, and the request control execution module causes the parking space lock on a parking space in the corresponding area to be raised to lock the corresponding road parking space, and the parking space locking tracking module starts timing and charging; 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 the continue locking inquiry signal and the parking space lock release signal will be sent to the user terminal of the corresponding car owner.

2. According to claim 1, the urban road intelligent parking management system based on Internet of Things technology is characterized in 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 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 are stopped. When the 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 counting and charging are stopped.

3. According to claim 1, the urban road intelligent parking management system based on Internet of Things technology is characterized in that: The specific analysis process of the reservation authority judgment module includes: The estimated time of arrival for parking of the corresponding vehicle owner is obtained, and the interval between the current time and the estimated time of arrival for parking is marked as the estimated time, and a permission-incompatible signal is generated; if the estimated time does not exceed the preset estimated time threshold, the current arrears amount is numerically compared with the preset arrears amount threshold, and if the current arrears amount exceeds the preset arrears amount threshold, a permission-incompatible signal is generated; If the current amount of arrears does not exceed the preset arrears threshold, the credit tracing value of the corresponding car owner is obtained through analysis. If the credit tracing value exceeds the preset credit tracing threshold, an authority incompatibility signal is generated; if the credit tracing value does not exceed the preset credit tracing threshold, an authority 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: The specific method for analyzing and obtaining the credit traceability value is as follows: The tracing period is set to L1, with the current date and the end date traced back. The number of times the corresponding car owner sent a parking reservation request but did not actually park during the tracing period is marked as a parking reservation anomaly value. The credit tracing value is obtained by numerically calculating the parking reservation anomaly value, the delay time table value and the payment delay value.

5. According to claim 1, the urban road intelligent parking management system based on Internet of Things technology is characterized in that: The analysis and judgment process of the parking space locking and tracking module is as follows: The time duration exceeding the current time compared to the corresponding estimated time to park is obtained and marked as the estimated time duration exceeding, and a preset first time duration threshold and a preset second time duration threshold matching the current time period are obtained, and the second preset time duration threshold>the first preset time duration threshold>0; if the estimated time duration exceeding the preset first time duration threshold, a continued locking inquiry signal is generated; If the time limit exceeds the preset second time threshold, a parking space lock release signal is generated.

6. The urban road intelligent parking management system based on Internet of Things technology according to claim 5 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 thereto; 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 thereto; wherein, WY2>WY1>0, QY2>QY1>0.

7. The urban road intelligent parking management system based on Internet of Things technology according to claim 6 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 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, and sends the marking information of each time period to the parking space locking and tracking module and the urban parking management center.

8. The urban road intelligent parking management system based on Internet of Things technology according to claim 7 is characterized in that: The analysis and judgment process of the busy or idle parking time periods is as follows: The time period evaluation value is obtained by numerically calculating the parking priority value, idle time meter value and vacancy analysis value of the corresponding time period. If the time period evaluation value exceeds the preset time period evaluation threshold, the corresponding time period is marked as a parking space easy idle time period; Otherwise, the corresponding time period will be marked as a busy time period for parking spaces.

9. The urban road intelligent parking management system based on Internet of Things technology according to claim 1 is characterized in that: The city parking management center is connected to the regional parking supervision and analysis module by 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 city parking management center when it is generated.

10. The urban road intelligent parking management system based on Internet of Things technology according to claim 9 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 parking strong supervision signal is generated.

Images