Parking lot vehicle intelligent navigation and unoccupied parking space distribution method

Abstract

The invention provides a parking lot vehicle intelligent navigation and unoccupied parking space distribution method, relates to the technical field of vehicle navigation and resource optimization distribution, and aims at performing targeted guidance on a vehicle through the driving direction of the vehicle at each fork by comprehensively judging the occupation condition of parking spaces in a parking lot and generating guidance data. Therefore, the parking space utilization rate of each area is greatly improved, the time spent by the user for finding the parking space during parking is shortened, the parking experience of the user is improved, the situation that the parking space cannot be found when the user follows the car is reduced, and congestion in the parking lot is avoided.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle navigation and resource optimization allocation, and more particularly, to a parking lot vehicle intelligent navigation and empty parking space allocation method. BACKGROUND

[0002] With the continuous advancement of urbanization and the continuous growth of motor vehicle ownership, parking lot management and scheduling are increasingly becoming an important part of the urban transportation system that cannot be ignored. Traditional parking lot management systems usually rely on manual guidance or simple static signs, which not only is inefficient, but also easily causes waste of parking resources, and cannot effectively cope with the concentrated inflow of vehicles during peak hours. In this context, intelligent parking management technology has gradually emerged, using technologies such as the Internet of Things, big data, and artificial intelligence to dynamically monitor and rationally allocate parking resources, becoming an important means to improve parking lot utilization and optimize user parking experience. Currently, existing intelligent parking systems usually use license plate recognition, parking space sensing, and navigation technology to achieve intelligent management of parking lot resources through dynamic detection of parking space status and vehicle guidance. However, existing technologies still have many shortcomings in terms of accuracy, real-time performance, and user experience, making it difficult to meet the parking navigation needs in complex scenarios.

[0003] The existing intelligent parking system has the following main problems in specific application: First, in terms of parking space allocation, most systems are based on single parking detection data, lacking comprehensive analysis of the overall regional distribution of the parking lot, resulting in suboptimal vehicle navigation paths and increased time for drivers to find parking spaces. Second, existing navigation technology usually relies on mobile devices of vehicle owners or static induction screens for guidance, which requires high real-time performance, but due to signal delay or outdated information on induction screens, navigation information may lag, further affecting parking efficiency. In addition, the guidance strategy for parking lot intersections in existing technologies is relatively simple and does not effectively combine vehicle driving direction and parking area distribution for dynamic adjustment, which can easily lead to traffic congestion or uneven resource allocation within the parking lot. Especially during peak hours, most parking lots cannot achieve efficient guidance and precise shunting of vehicles using existing technologies, ultimately affecting the parking experience of vehicle owners and the operational efficiency of the parking lot. SUMMARY

[0004] To solve the above technical problems, the present application is proposed. The present application provides a parking lot vehicle intelligent navigation and empty parking space allocation method, which can to some extent solve the problem of long time spent by users in finding parking spaces due to the static and fixed nature of the parking lot identification system, which cannot provide real-time dynamic guidance.

[0005] According to one aspect of the present application, a parking lot vehicle intelligent navigation and empty parking space allocation method is provided, which includes: The license plate information of the entering vehicle is collected by a vehicle detection device arranged at the entrance of the parking lot, and the parking space occupation state data is obtained by parking space detectors distributed at each parking space in the parking lot; A dynamic guide screen with double display function is installed at each intersection in the parking lot, the driving direction of the vehicle passing through the intersection is detected based on a gravity sensing device, and the display surface of the corresponding direction is started according to the driving direction; The parking space occupation state data is counted according to the parking lot partition, the number of available parking spaces and the shortest arrival time from each intersection to each area are calculated, and parking guidance data is generated, The parking guidance data is sent to the dynamic guide screen at the corresponding intersection in real time for display, guiding the vehicle to park.

[0006] Further, the driving direction of the vehicle is determined according to the triggering time sequence of the stress sensor array of the gravity sensing device.

[0007] Further, the stress sensor array is arranged in a matrix, if each row of sensors is triggered in turn and the time interval is within a preset interval, it is determined that the vehicle is driving from south to north or from north to south; If the vehicle turns, it is determined according to whether the area where the tire contacts the sensor shifts from one side to the other side.

[0008] Further, the generation of the parking guidance data includes: Each intersection is taken as a node of a graph, the channel between the intersections is taken as an edge, and the weight of the edge is the actual passing distance; A depth-first search algorithm is used to traverse all paths; A distance decay coefficient is calculated according to the total distance of each path; The distance decay coefficient is multiplied by the number of available parking spaces to obtain a weighted available parking space number; According to the weighted available parking space number, the path with the largest value is selected as the recommended path to generate the parking guidance data.

[0009] Further, the calculation of the distance decay coefficient includes: A base decay rate parameter is multiplied by the total distance value, and then the negative index is taken to obtain an exponential decay term; The total distance value is divided by the average driving speed to obtain the expected driving time, and then the ratio is multiplied by a parameter and added by 1, and finally the square root is taken to obtain a speed correction term; The distance standardization parameter is divided by the sum of the total distance value and the distance standardization parameter to obtain a distance penalty term; The three parts are multiplied to obtain the final distance decay coefficient.

[0010] Further, the guiding of the vehicle to park includes: When the vehicle enters the parking lot, the system calculates the target partition and the optimal path, and displays the area on the dynamic guide screen, when the vehicle enters the first fork, the guide information is displayed on the dynamic guide screen according to the calculated optimal path parameters, when it is detected that the vehicle and the guide information displayed on the dynamic guide screen are consistent in driving direction, the original path is kept, and the preset guide information is continuously displayed at the next fork, when it is detected that the vehicle and the guide information displayed on the dynamic guide screen are inconsistent in driving direction, the path parameters from the current position of the vehicle to each partition are recalculated, when the new path parameter calculation is completed, the system selects a new optimal path, and updates the corresponding guide information at the next fork, and if the vehicle does not drive according to the recommended route for multiple times, the recommendation is not performed.

[0011] Further, the guiding vehicle parking further comprises: When multiple vehicles enter the parking lot in sequence, a temporary number is first assigned to each vehicle according to the entering time sequence of the vehicle, for the first vehicle, the system recommends the optimal path and the target partition according to the conventional logic, when the second vehicle enters, the influence of the first vehicle on the pre-occupation of the parking space is considered when calculating the path parameters; When the third vehicle enters, the system will simultaneously track the actual driving state of the previous two vehicles, if the previous two vehicles both go to the target area according to the system suggestion, the target area will not be recommended as the target of the third vehicle, if the first vehicle does not drive according to the recommended route and gives up to go to the target area, the parking space pre-occupation count is updated in real time, and whether the third vehicle can be recommended is re-evaluated.

[0012] Further, when multiple vehicles pass through in close following, different vehicles are distinguished by analyzing the pressure curve waveform of each sensor.

[0013] According to another aspect of the present application, a parking lot vehicle intelligent navigation and empty parking space allocation system is provided, which comprises: A data acquisition module for acquiring vehicle driving direction information and parking space occupation information; A communication module for establishing a communication connection with a parking lot control center through a wired network, receiving a display content instruction issued by the control center, and controlling a corresponding display unit to display parking space guide information according to the display content instruction; A control center for calculating a target area and an optimal route according to the data acquisition module, and constituting parking space guide data to control the display unit to display parking space guide information through the communication module; The display unit comprises a dynamic guide screen with double-sided display function.

[0014] Compared with the prior art, the parking lot vehicle intelligent navigation and empty parking space allocation method provided by the application generates guidance data by comprehensively judging the occupancy of parking spaces in the parking lot, and guides the vehicle according to the driving direction of the vehicle at each fork. In this way, not only the utilization rate of parking spaces in each area is greatly improved, but also the time spent by users in searching for parking spaces is reduced, the user parking experience is improved, the situation of following a car but failing to find a parking space is reduced, and the congestion in the parking lot is avoided. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor. In the drawings: Figure 1 The flow chart of the parking lot vehicle intelligent navigation and empty parking space allocation method according to the embodiment of the present application. DETAILED DESCRIPTION

[0016] In the following, the example embodiments according to the present application will be described in detail with reference to the drawings. Obviously, the described embodiments are only some of the embodiments of the present application, not all embodiments of the present application, and it should be understood that the present application is not limited to the example embodiments described here.

[0017] Figure 1 The system block diagram of the parking lot vehicle intelligent navigation and empty parking space allocation method according to the embodiment of the present application. As shown in Figure 1 The parking lot vehicle intelligent navigation and empty parking space allocation method comprises: S1: collecting the license plate information of the entering vehicle through the vehicle detection device arranged at the entrance of the parking lot, and obtaining the parking space occupancy state data through the parking space detector distributed at each parking space in the parking lot, wherein the parking space occupancy state data comprises the parking space number and the occupancy identifier; The license plate information of the entering vehicle is collected by a vehicle detection device arranged at the entrance of the parking lot, the vehicle detection device comprising a license plate recognition camera and a vehicle sensor, wherein the vehicle sensor is used to detect the arrival of the vehicle to trigger the license plate recognition camera to take a picture; a parking stall detector is arranged at each parking stall of the parking lot, the parking stall detector comprising an ultrasonic sensor and an infrared sensor, wherein the ultrasonic sensor is used to detect whether there is a vehicle directly above the parking stall, and the infrared sensor is used to assist in judging the parking stall occupancy state; data transmission is realized between the parking stall detector and the parking lot control center through a wireless communication network; when the vehicle drives into the parking stall, the ultrasonic sensor detects that the vehicle is located directly above the parking stall, and the infrared sensor detects that the vehicle is blocked, and sends a parking stall occupancy signal to the parking lot control center; after receiving the parking stall occupancy signal, the parking lot control center generates parking stall occupancy state data, the parking stall occupancy state data comprising a parking stall number, an occupancy identifier and an occupancy timestamp; when the vehicle drives away from the parking stall, the ultrasonic sensor and the infrared sensor detect that the parking stall is not occupied by a vehicle, and send a parking stall vacancy signal to the parking lot control center, and the parking lot control center updates the occupancy identifier in the parking stall occupancy state data; the parking lot control center stores the parking stall occupancy state data into a database and establishes an associated record with the license plate information, for subsequent parking stall navigation and fee settlement.

[0018] S2: A dynamic induction screen with double-sided display function is installed at each intersection of the parking lot, the dynamic induction screen being in communication connection with the parking lot control center, the driving direction of the vehicle passing through the intersection being detected based on a gravity sensing device, and the display surface of the corresponding direction being started according to the driving direction; A dynamic induction screen with double-sided display function is installed at each intersection of the parking lot, the dynamic induction screen comprising a front display unit, a back display unit, a trigger controller and a communication module; the dynamic induction screen is made of LED dot matrix display devices, and has high brightness and wide viewing angle characteristics; the dynamic induction screen is installed at the center position of the intersection, the front display unit facing one side of the vehicle coming direction, and the back display unit facing one side of the vehicle going direction; a gravity sensing device is buried at the ground below the dynamic induction screen, the gravity sensing device comprising an array of stress sensors for detecting the gravity distribution when the vehicle passes; the trigger controller receives the vehicle passing data collected by the gravity sensing device, and judges the driving direction of the vehicle according to the trigger time sequence of the array of stress sensors; more specifically: The stress sensor array of the gravity sensing device adopts a 3*3 matrix layout, numbered as the first row, the second row and the third row from south to north, each row containing three transversely juxtaposed sensor units, numbered as A, B and C respectively; when the vehicle enters the intersection area, the trigger controller first determines the row number of the first triggered sensor and records the trigger time stamp of each sensor unit in the row; if the first row sensor is triggered first, the trigger controller waits for the trigger signal of the second row sensor and records the trigger time stamp of each sensor unit in the second row; when the third row sensor is triggered, the trigger controller compares the trigger time sequence of the three rows of sensors; if the trigger time stamps of the three rows of sensors satisfy the condition of increasing from the first row to the third row, and the trigger time interval of adjacent two rows is within the range of 50ms to 200ms, it is determined that the vehicle drives from south to north; if the third row sensor is triggered first, the trigger controller also waits for the trigger signals of the second row and the first row sensors; when the three rows of sensors have all been triggered, if their trigger time stamps satisfy the condition of increasing from the third row to the first row, and the trigger time interval of adjacent two rows is within the range of 50ms to 200ms, it is determined that the vehicle drives from north to south; when the three units of a row of sensors fail to trigger within 20ms, the trigger controller determines that it is an abnormal trigger and will restart the detection process; if the trigger time stamps of the three rows of sensors do not satisfy the strict increasing relationship, or the adjacent trigger time interval exceeds the preset range, the trigger controller also determines that it is an abnormal trigger; after determining the driving direction of the vehicle, the trigger controller immediately starts the display unit of the corresponding direction and continuously monitors the state of the last row of sensors; if the pressure values of all units of the last row of sensors are continuously below the threshold value for 1 second, it is determined that the vehicle has driven out of the detection area.

[0019] In addition to determining the straight movement in the north-south direction, the turning movement of the vehicle also needs to be determined; when the vehicle turns left, the area of the tire in contact with the stress sensor will exhibit a feature of shifting from one side to the other; if the vehicle travels from south to north and turns left, when the first row of sensors is triggered, the right C unit is triggered first, followed by the middle B unit; when the second row of sensors is triggered, the middle B unit is triggered first, followed by the left A unit; when the third row of sensors is triggered, only the left A unit generates a trigger signal; the trigger controller determines that the vehicle turns left by recognizing this trigger feature that shifts from right to left in sequence; similarly, when the vehicle turns right, the trigger position of the stress sensor will exhibit a feature of shifting from left to right; specifically, the first row triggers the A unit first, followed by the B unit; the second row triggers the B unit first, followed by the C unit; the third row only triggers the C unit; when this trigger feature is recognized, the trigger controller determines that the vehicle turns right; if the vehicle travels from north to south, the sensor trigger sequence for turning determination is exactly the opposite; for a left-turning vehicle, the third row triggers the C unit first, the second row triggers the B and A units, and the first row only triggers the A unit; for a right-turning vehicle, the third row triggers the A unit first, the second row triggers the B and C units, and the first row only triggers the C unit; to ensure the accuracy of the turning determination, the trigger controller will also analyze the trigger time interval of adjacent sensor units, which should be less than 30 ms in general; if the trigger time interval of adjacent units in a row exceeds the preset threshold, it is determined to be an abnormal trigger.

[0020] In addition, at the entrance and exit of a busy parking lot, there may be a situation where multiple vehicles follow closely. For this situation, the system sets the minimum interval time of the vehicles to 2 seconds, and when the time interval of two groups of trigger signals is less than 2 seconds, the system will start a special processing mechanism to distinguish different vehicles by analyzing the pressure curve waveform characteristics of each sensor. For example, when the pressure curve generated by the first vehicle passing through starts to drop, the second vehicle has already triggered the sensor, at which time the pressure curve will exhibit a typical double-peak feature, and the system can accurately identify this situation and process the direction determination of the two vehicles respectively.

[0021] More specifically, when a trigger signal is detected that the first pressure value exceeds 100 kg, the trigger controller initiates a waveform recording program to continuously record the pressure value changes within 2 seconds; if within these 2 seconds, the pressure value shows a trend of first rising, then falling, and then rising again, it is likely that the double-vehicle-following situation occurs; at this time, the trigger controller will start the double-peak identification algorithm, first looking for two pressure peak points P1 and P2 in the waveform, and recording their corresponding time points T1 and T2; if there is a clear wave trough V between the two peak points, and the ratio of the wave trough value to the adjacent peak value is less than 0.4, it is confirmed as a double-peak feature; when the double-peak feature is identified, the trigger controller will divide the pressure curve into two segments with the wave trough point as the boundary and process them separately; for the first segment of the curve, the sensor trigger data before T1 is taken for direction judgment; for the second segment of the curve, the sensor trigger data after T2 is taken for direction judgment; if the last row of sensors of the first vehicle has not completely released the pressure, the second vehicle has triggered the first row of sensors, at this time the trigger controller will monitor the state of the first and last rows of sensors; when the tail sensor pressure of the first vehicle drops below the threshold, the direction judgment of the second vehicle is immediately started.

[0022] The communication module establishes a communication connection with the parking lot control center through a wired network, receives the display content instruction issued by the control center, and controls the corresponding display unit to display the parking space guidance information according to the display content instruction; when it is detected that the vehicle has driven away from the fork area, the trigger controller controls the currently working display unit to enter a standby state, reducing energy consumption.

[0023] It is worth noting that although the above description outlines the general process of the stress sensor array determining the driving direction of the vehicle, various complex situations may be encountered in actual application. For example, when an SUV is driving from south to north at a speed of 30 km / h, its front wheels first trigger the B and C units of the first row of sensors (timestamp T1 = 1000 ms), then trigger the A and B units of the second row of sensors (timestamp T2 = 1150 ms), and finally trigger the A unit of the third row of sensors (timestamp T3 = 1280 ms), and the system can determine that the vehicle is making a left turn. When a small car is driving from north to south at a speed of 15 km / h and preparing to make a right turn, it will first trigger the A and B units of the third row of sensors (timestamp T1 = 2000 ms), then trigger the B and C units of the second row of sensors (timestamp T2 = 2200 ms), and finally trigger the C unit of the first row of sensors (timestamp T3 = 2380 ms), and the system determines that the vehicle is making a right turn.

[0024] S3: The parking space occupancy state data is counted according to parking lot partitions, a path prediction algorithm based on distance attenuation is used to calculate the available number of parking spaces and the shortest arrival time from each intersection to each region, and parking guidance data is generated, including the available number of parking spaces, the arrival time and the recommended driving direction; The parking space occupancy state data is counted according to parking lot partitions, including A, B and C zones, and each partition has a number of parking spaces; the parking lot control center counts the number of empty parking spaces in each partition according to the real-time parking space occupancy state data uploaded by the parking space detector; the traffic relationship between intersections and each partition is established based on the parking lot electronic map, each intersection is numbered as D1, D2, D3, etc., and the actual traffic distance between each intersection is recorded.

[0025] A path prediction algorithm based on distance attenuation is used to calculate the path parameters from the current intersection to the target partition, as follows: The parking lot control center first constructs a path calculation graph, taking each intersection as a node and the channel between intersections as an edge, and the weight of the edge is the actual traffic distance; when calculating the path parameters from the current intersection to the target partition, the system uses a depth-first search algorithm to traverse all possible paths; for the starting intersection, the system first obtains all adjacent intersection nodes; if a certain adjacent intersection has not been visited, it is added to the current path and the cumulative distance value is recorded; when the search reaches the entrance intersection of the target partition, a complete path is formed, and the system saves the path information to the path set; if the adjacent nodes of the current intersection have been visited or do not meet the traffic conditions, the system backtracks to the previous intersection and continues searching.

[0026] After all possible paths are traversed, the system begins to calculate the parameters of each path; for each path in the path set, first calculate the total distance value, which is the sum of the distances of all adjacent intersections on the path; then calculate the distance attenuation coefficient according to the total distance value, the farther the distance, the greater the attenuation; after the distance attenuation coefficient is calculated, multiply the current number of empty parking spaces in the target partition by the coefficient to get the weighted available number of parking spaces for the path; for example, a certain partition currently has 30 empty parking spaces, and the total distance of the path to the partition is 50 meters, so the weighted available number of parking spaces for the path is 5; at the same time, the system determines the average driving speed based on the historical driving data of vehicles in the parking lot, which is usually 15 km / h; divide the total distance of the path by the average driving speed to get the estimated time; the system compares the weighted available number of parking spaces of all paths and selects the path with the largest value as the recommended path; if the weighted available number of parking spaces of multiple paths is similar (the difference is less than 1), the path with the shortest estimated time is selected.

[0027] According to the weighted available parking space quantity of each path, a path with the largest value is selected as a recommended path, and parking guidance data is generated, the parking guidance data including an actual available parking space quantity of a target subzone, an estimated time to reach the target subzone along the recommended path, and a direction indication of a next recommended intersection; the parking lot control center updates the parking guidance data every 10 seconds to ensure real-time accuracy of the data.

[0028] The calculation of the distance attenuation coefficient can be represented by the following formula: wherein, is the final distance attenuation coefficient, is a total distance value of a current path (unit: meters), is an average driving speed of a vehicle (unit: meters / second), is a basic attenuation rate parameter (value 0.005), is a time penalty factor (value 0.02), and θ is a distance normalization parameter (value 100).

[0029] It should be noted that the basic attenuation rate parameter λ is determined based on the actual size of the parking lot. Generally, the length of a single passage of a parking lot is between 20-50 meters. Considering that the generally accepted walking distance of users is usually not more than 200 meters, λ is set to 0.005. When the distance is 200 meters, the exponential attenuation term is approximately equal to 0.37, representing the critical point of comfortable walking distance; when the distance reaches 400 meters, the value decreases to 0.135, representing a significant decrease in user acceptance. This parameter value is obtained by analyzing user parking position selection data of multiple commercial parking lots and combining walking comfort surveys.

[0030] The setting of the time penalty factor β: this parameter is related to the actual driving speed of the vehicle in the parking lot. Considering that the speed limit in the parking lot is usually 15-20 kilometers / hour, which is converted to about 4-5.5 meters / second. β is set to 0.02, so that when the speed is 5 meters / second and the distance is 100 meters, the value of the time penalty term is about 0.7, and this attenuation degree meets the psychological expectation of users for 2-3 minutes of searching time. This parameter value is determined by analyzing the actual driving data of vehicles recorded by the parking lot monitoring system and combining user satisfaction surveys.

[0031] Setting of distance normalization parameter θ: Based on the typical size of the parking lot, θ is set to 100, which is approximately the average distance between adjacent partitions of a standard parking lot. When the actual distance is equal to θ, the value of the normalization term is 0.5, indicating a moderate recommendation; when the distance is less than θ, the value of the normalization term tends to 1, indicating a strong recommendation; when the distance is much greater than θ, the value of the normalization term tends to 0, indicating no recommendation. This parameter value is determined by statistical analysis of the layout and actual operation data of multiple parking lots of the same type. These parameter values are set taking into full consideration the physical characteristics of the parking lot, user behavior habits and psychological expectations, and are verified and optimized through statistical analysis of actual operation data and user feedback, ensuring that the distance decay coefficient calculated accurately reflects the actual feasibility and user acceptance of the path.

[0032] It is worth noting that although the above description outlines the general process of the distance decay-based path prediction algorithm, more complex situations may be encountered in actual applications that require special handling. For example, in a practical application case of an underground parking lot in a certain mall, there are three possible paths from the D1 intersection to the A area: the first path passes through D2, with a total distance of 80 meters; the second path passes through D3 and D4, with a total distance of 150 meters; the third path passes through D5, D6 and D7, with a total distance of 200 meters. When there are 45 empty parking spaces in the A area, the weighted available parking space number of the first path is 5, that of the second path is approximately 2.8, and that of the third path is approximately 2.1, and the system will finally select the first path as the recommended path. When temporary regulation occurs at the D2 intersection, the system will automatically reduce the weight of the first path to 0 and recommend the second path instead.

[0033] In addition, in another case, a large number of vehicles enter a certain office building parking lot at the same time during the office peak period. Assuming that the distance from the entrance intersection D1 to the B area and the C area is similar (both 100 meters), and that there are currently 20 empty parking spaces in the B area and 22 empty parking spaces in the C area, the weighted available parking space numbers of the two areas are 1.82 and 2 respectively. Since the difference is less than 1, the system will further analyze other parameters of the two paths. If the path to the B area requires 2 turns and the path to the C area requires 3 turns, considering that turns will reduce the actual driving speed, the system will finally recommend the vehicle to go to the B area.

[0034] It should be noted that the present embodiment only provides an example of a parking lot with three partitions, and does not mean that the present application only supports parking lots with three partitions.

[0035] S4: Real-time sending of the parking space guiding data to the dynamic guidance screen of the corresponding intersection for display to guide the vehicle to park.

[0036] The parking space guidance data is sent to the dynamic guidance screen of the corresponding intersection in real time for display. The display interface of the dynamic guidance screen adopts a partition display mode, and the information of the A zone, B zone and C zone of the parking lot is displayed in columns. The display content of each zone includes zone identification, available parking space quantity, arrival time and direction indication. The zone identification is distinguished by background color, the A zone has a blue background color, the B zone has a green background color, and the C zone has a yellow background color. The available parking space quantity is displayed in the form of a large-size number and is marked with "units" as the unit. The arrival time is displayed in minutes as the unit and is dynamically updated in the form of countdown. The direction indication is indicated by an arrow symbol to guide the direction of the next intersection. The dynamic guidance screen sorts the zones according to the weighted available parking space quantity in the parking space guidance data, and the zone with the highest weighted available parking space quantity is highlighted with a display size enlarged by 1.5 times. When the available parking space quantity of a zone is zero, the zone displays the word "full" and the background color is changed to gray. The dynamic guidance screens are connected in a cascade control mode. When a vehicle passes through the current intersection, the driving direction selected by the vehicle is detected by a gravity sensing device, and the direction information is sent to the parking lot control center. The parking lot control center determines the number of the next dynamic guidance screen according to the driving direction, and sends the updated parking space guidance data to the dynamic guidance screen. After receiving the data, the next dynamic guidance screen preferentially displays the zone information consistent with the driving direction selected by the vehicle, to ensure the continuity of the information. If the driving direction selected by the vehicle is inconsistent with the recommended direction, the parking lot control center re-computes the optimal path based on the current position, and generates new parking space guidance data. The parking lot control center synchronously updates the display content of all the dynamic guidance screens every 10 seconds, to ensure the consistency of the navigation information of the entire parking lot.

[0037] For example, when a vehicle enters the parking lot, the system calculates a target zone and an optimal path, and displays the zone on the dynamic guidance screen. When the vehicle enters the first intersection, the system displays the guiding information on the dynamic guidance screen according to the calculated optimal path parameters. When it is detected that the vehicle is consistent with the driving direction of the guiding information displayed on the dynamic guidance screen, the original path is maintained, and the preset guiding information is continuously displayed at the next intersection. When it is detected that the vehicle is inconsistent with the driving direction of the guiding information displayed on the dynamic guidance screen, the system re-computes the path parameters from the current position of the vehicle to each zone. When the new path parameters are calculated, the system selects a new optimal path, and updates and displays the corresponding guiding information at the next intersection. If the vehicle does not travel according to the recommended route for multiple times, the system does not make recommendations. If the parking space of the original target zone is occupied during the travel of the vehicle, the system immediately displays the information of an alternative zone at the current intersection. If the vehicle is unexpectedly parked before reaching the target zone, the system maintains the current display content for 10 minutes, and then returns to the standby state.

[0038] When the system detects that multiple vehicles enter the parking lot in succession, first, a temporary number is assigned to each vehicle according to the time sequence of the vehicle entering; for the first vehicle, the system recommends the optimal path and target partition according to the conventional logic; when the second vehicle enters, the system will consider the pre-occupancy influence of the first vehicle on the parking space when calculating the path parameters; if there are originally 30 empty spaces in area A, the first vehicle is guided to area A, then the system will reduce the number of available parking spaces by 1 when calculating the path parameters for the second vehicle in area A; when the third vehicle enters, the system will track the actual driving state of the previous two vehicles; if the previous two vehicles both go to area A as recommended by the system, and there are only 2 parking spaces left in area A, then the system will no longer recommend area A as the target for the third vehicle; if the first vehicle does not drive according to the recommended route and gives up going to area A, the system will update the pre-occupancy count in real time and re-evaluate whether area A can be recommended for the third vehicle; when the system detects that a vehicle has successfully parked in a parking space, it will release the pre-occupancy count of that vehicle; if the previous vehicle changes course unexpectedly before reaching the target partition, the system will immediately reallocate the pre-occupied parking space; when multiple vehicles are waiting at the same intersection, the system will display different recommended paths according to the waiting time sequence of the vehicles; if the number of remaining parking spaces in a certain partition is less than or equal to the number of waiting vehicles, the system will only recommend that partition to the first vehicle to arrive; when a certain partition is about to be saturated (with no more than 3 remaining parking spaces), the system will start a saturation warning mechanism and only recommend that partition to the most recent vehicle, while other vehicles will be guided to other partitions; if the total number of remaining parking spaces in all partitions is less than the number of waiting vehicles, the system will display a "parking space tight" warning message at the entrance.

[0039] In summary, the parking lot vehicle intelligent navigation and empty parking space allocation method based on the embodiments of the present application is illustrated, which generates guidance data by comprehensively judging the occupancy of parking spaces in the parking lot, and guides the vehicle according to the driving direction of the vehicle at each intersection. In this way, not only the utilization rate of parking spaces in each area is greatly improved, but also the time spent by users in searching for parking spaces is reduced, the user parking experience is improved, the situation of following a car but not being able to find a parking space is reduced, and congestion in the parking lot is avoided.

[0040] Here, those skilled in the art can understand that the specific operation of each step in the above parking lot vehicle intelligent navigation and empty parking space allocation system has been described in detail above with reference to the description of the parking lot vehicle intelligent navigation and empty parking space allocation method of Figure 1 , and therefore, repeated description thereof will be omitted.

[0041] In summary, the parking lot vehicle intelligent navigation and empty parking space allocation system based on the embodiment of the application is illustrated, which generates guiding data by comprehensively judging the occupancy of parking spaces in the parking lot, and guides the vehicle according to the driving direction of the vehicle at each fork. In this way, not only the utilization rate of parking spaces in each area is greatly improved, but also the time spent by the user in searching for a parking space when parking is reduced, the user parking experience is improved, the situation of following a car but not finding a parking space is reduced, and the congestion in the parking lot is avoided.

Claims

1. A method for intelligent vehicle navigation and vacant parking space allocation in a parking lot, characterized in that, include: The license plate information of vehicles entering the parking lot is collected by a vehicle detection device set up at the entrance of the parking lot, and the parking space occupancy status data is obtained by parking space detectors distributed in each parking space of the parking lot. Dynamic guidance screens with dual-sided display function are installed at each intersection of the parking lot. The direction of the vehicle passing through the intersection is detected by the gravity sensor, and the corresponding display surface is activated according to the direction of the vehicle. The parking space occupancy data is statistically analyzed according to parking lot zones. The number of available parking spaces and the shortest travel time from each intersection to each zone are calculated to generate parking space guidance data. The parking space guidance data is sent in real time to the dynamic guidance screen at the corresponding intersection for display, guiding vehicles to park.

2. The parking lot vehicle intelligent navigation and vacant parking space allocation method according to claim 1, characterized in that, The vehicle's driving direction is determined based on the triggering timing of the stress sensor array of the gravity sensing device.

3. The parking lot vehicle intelligent navigation and vacant parking space allocation method according to claim 2, characterized in that, The stress sensor array is arranged in a matrix. If each row of sensors is triggered sequentially and the time interval is within a preset range, it is determined that the vehicle is traveling from south to north or from north to south. When determining vehicle steering, the system determines vehicle steering based on whether the area of ​​contact between the tire and the sensor shifts from one side to the other.

4. The parking lot vehicle intelligent navigation and vacant parking space allocation method according to claim 1, characterized in that, Generating the parking space guidance data includes: Treat each intersection as a node in the graph, the passages between intersections as edges, and the weight of each edge as the actual travel distance. All paths are traversed using a depth-first search algorithm; Calculate the distance attenuation coefficient based on the total distance of each path; Multiply the distance attenuation coefficient by the number of available parking spaces to obtain the path-weighted number of available parking spaces; Based on the weighted number of available parking spaces, the path with the highest value is selected as the recommended path, and parking guidance data is generated.

5. The parking lot vehicle intelligent navigation and vacant parking space allocation method according to claim 4, characterized in that, The calculation of the distance attenuation coefficient includes: Multiply the base attenuation rate parameter by the total distance value, and then take its negative exponent to obtain the exponential attenuation term; Divide the total distance by the average speed to get the estimated travel time, then multiply this ratio by the parameter and add 1, and finally take the square root to get the speed correction term; Dividing the distance standardization parameter by the sum of the total distance value and the distance standardization parameter yields the distance penalty term; Multiplying these three parts together gives the final distance attenuation coefficient.

6. The parking lot vehicle intelligent navigation and vacant parking space allocation method according to claim 1, characterized in that, The guidance for vehicle parking includes: Once a vehicle enters the parking lot, the system calculates the target zone and the optimal route, displaying this area on a dynamic guidance screen. When the vehicle enters the first intersection, guidance information is displayed on the dynamic guidance screen based on the calculated optimal route parameters. If the vehicle's direction matches the direction displayed on the screen, the system maintains the original route and continues displaying the preset guidance information at the next intersection. If the vehicle's direction does not match the direction displayed on the screen, the system recalculates the route parameters from the vehicle's current location to each zone. After the new route parameters are calculated, the system selects a new optimal route and updates the corresponding guidance information at the next intersection. If the vehicle repeatedly deviates from the recommended route, no further recommendations are made.

7. The parking lot vehicle intelligent navigation and vacant parking space allocation method according to claim 6, characterized in that, The guidance for vehicle parking also includes: When multiple vehicles are detected entering the parking lot in sequence, a temporary number is first assigned to each vehicle based on the order of their entry. For the first vehicle, the system recommends the optimal path and target zone according to conventional logic. When the second vehicle enters, the pre-occupancy of parking spaces by the first vehicle will be taken into account when calculating the path parameters. When the third vehicle enters, the system will simultaneously track the actual driving status of the first two vehicles. If the first two vehicles proceed to the target area as suggested by the system, the target area will no longer be recommended as the target for the third vehicle. If the first vehicle does not follow the suggested route and abandons its journey to the target area, the parking space pre-occupancy count will be updated in real time, and the system will reassess whether it can be recommended for the third vehicle.

8. The parking lot vehicle intelligent navigation and vacant parking space allocation method according to claim 2, characterized in that, include: When multiple vehicles pass closely behind, the different vehicles can be distinguished by analyzing the pressure curve waveforms of each sensor.

9. A parking lot vehicle intelligent navigation and vacant parking space allocation system, characterized in that, The data acquisition module is used to collect information on vehicle driving direction and parking space occupancy. The communication module is used to establish a communication connection with the parking lot control center through a wired network, receive display content instructions issued by the control center, and control the corresponding display unit to display parking space guidance information according to the display content instructions; The control center is used to calculate the target area and optimal route based on the data acquisition module, and to construct parking guidance data. This data is then transmitted through the communication module to control the display unit to display the parking guidance information. The display unit includes a dynamic guidance screen with dual-sided display function.

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