Low-carbon parking guiding method and management system based on user behaviors

Abstract

The invention relates to a low-carbon parking guidance method and management system based on user behaviors, and relates to the field of parking guidance, and the method comprises the steps: collecting a parking instruction sent by a user terminal and a weight condition monitored by a weight monitoring device in a parking lot; collecting the parking preference, the vehicle type and the user position of the user based on the parking instruction; determining an idle parking space based on the weight condition; generating a parking destination based on the parking preference, the vehicle type and the idle parking space; determining a parking route based on the user position and the parking end point; the current position and the current working state of the intelligent parking robot are obtained; a scheduling route and a scheduling number are generated based on the current position, the current working state and the parking route, and the parking route and the scheduling route are output to the intelligent parking robot corresponding to the scheduling number to control movement; and generating voice broadcast information based on the scheduling route and the parking route, and transmitting the voice broadcast information to a voice broadcast system. The parking device has the effect of conveniently and quickly parking.

Description

Technical Field

[0001] The present invention relates to the field of parking guidance, and in particular to a low-carbon parking guidance method and management system based on user behavior. Background Art

[0002] Parking guidance is the process of providing users with real-time parking space information within a parking lot or area through technical means, and assisting them to reach the target parking space efficiently.

[0003] Currently, parking users primarily rely on signs outside the parking lot to determine if there are vacant spaces. After entering a parking lot with available spaces, users move along the path within the parking lot, checking the indicator lights on the spaces or simply observing whether they are available to determine which space is available, ultimately parking.

[0004] When parking, users can only determine the final parking position by looking at the indicator lights on the parking space or directly observing the parking space, which makes it inconvenient to park quickly. Summary of the Invention

[0005] In order to facilitate and quickly park, the present invention provides a low-carbon parking guidance method and management system based on user behavior.

[0006] In a first aspect, the present invention provides a low-carbon parking guidance method based on user behavior, which adopts the following technical solutions: A low-carbon parking guidance method based on user behavior, comprising: S1: Collect the parking instructions sent by the user terminal and the weight monitored by the preset weight monitoring device in the parking lot; S2: collecting the user's parking preference, vehicle type, and user location based on the parking instruction; S3: Determine an available parking space based on the weight condition; S4: generating a parking destination based on the parking preference, the vehicle type, and the available parking space; S5: Determine a parking route based on the user location and the parking destination; S6: Obtain the current position and current working status of the preset intelligent parking robot; S7: generating a dispatch route and a dispatch number based on the current position, the current working state, and the user position, and outputting the parking route and the dispatch route to the intelligent parking robot corresponding to the dispatch number to control movement; S8: Generate voice broadcast information based on the scheduling route and the parking route, and transmit the voice broadcast information to a voice broadcast system.

[0007] By implementing this technical solution, parking instructions and weight monitoring device data are collected to accurately determine available parking spaces. This solution then combines user preferences and vehicle type to find the appropriate parking destination for the user, improving parking space utilization and parking convenience. Route planning determines parking routes based on the user's location and parking destination, and generates dispatch routes and numbers for intelligent parking robots, optimizing movement paths during parking and improving parking efficiency. Furthermore, voice broadcasts provide real-time guidance to users and parking robots, effectively alleviating parking congestion.

[0008] Optionally, generating a parking destination based on the parking preference, the vehicle type, and the available parking space includes: S41: Collecting user historical behavior data based on the parking instruction; S42: generating a preferred parking space based on the historical behavior data and the parking preference; S43: Generate a parking space category based on the user location and the current location; S44: Selecting the vacant parking space based on the parking space category and the preferred parking space to generate a preferred location; S45: Retrieving a carbon emission coefficient based on the vehicle type; S46: Generate a recommended parking spot based on the preferred location and the carbon emission coefficient, and use the recommended parking spot as the parking destination.

[0009] By adopting the above technical solution, a parking space that meets the user's habits is selected from the available parking spaces based on the user's preferences and historical behavior, and the carbon emission coefficient is taken into consideration. The user's habits are combined with environmental protection goals to achieve efficient and environmentally friendly parking.

[0010] Optionally, selecting the vacant parking space based on the parking space category and the preferred parking space to generate a preferred location includes: S441: Extracting charging requirements, automatic parking preferences, vehicle exit preferences, pedestrian exit preferences, and parking environment preferences from the parking preferences; S442: selecting the vacant parking spaces corresponding to the preset first category as first-category parking spaces, and selecting the vacant parking spaces other than the first-category parking spaces as second-category parking spaces; S443: Determine a first-category weight score based on the first-category parking space, the charging requirement, the automatic parking preference, and the vehicle exit preference; S444: Determine a second category weight score based on the second category parking space, the charging demand, the pedestrian exit preference, and the parking environment preference; S445: Combining the first category weight score and the second category weight score to obtain a comprehensive weight score, and sorting the comprehensive weight scores from high to low to obtain a weight score table; S446: Counting the second-category parking spaces corresponding to the second-category weighted scores that meet the preset standard in the weighted score table, and defining them as second-category qualified parking spaces; S447: Determine whether there is a parking space with the first category weight score greater than a preset first category score; S448: If it exists, the corresponding parking space is regarded as a first-class qualified parking space; S449: Selecting the first-category qualified parking space and the second-category qualified parking space as the preferred locations; S44A: If not, determine a secondary location based on the second-category qualified parking space, and use the secondary location as the preferred location.

[0011] By adopting the above technical solution, parking spaces are divided into two categories, each category is further subdivided according to different needs, and then suitable parking spaces are recommended by scoring, thus realizing intelligent parking. This can help users find parking spaces that meet their needs more quickly and improve parking lot utilization efficiency.

[0012] Optionally, generating a recommended parking spot based on the preferred location and the carbon emission coefficient includes: S461: Generate a travel distance based on the preferred location and the user location; S462: Calculating the required amount of carbon emissions based on the travel distance and the carbon emission coefficient; S463: Real-time collection of total carbon emissions and atmospheric carbon concentration in parking lots; S464: Generate a carbon emission standard based on the total carbon emissions and the atmospheric carbon concentration; S465: Determine whether the required carbon emission amount meets the carbon emission standard; S466: If the requirement is met, the preferred position corresponding to the required amount of carbon emissions that meets the carbon emission standard is used as a low-carbon parking position; S467: Generate a recommended parking space table based on the low-carbon parking space and a preset low-carbon preferred weight coefficient; S468: Selecting the preferred position that meets the preset parking selection criteria from the recommended parking table as the recommended parking position; S469: If not satisfied, calculating the difference between the required carbon emission amount and the carbon emission standard as the carbon emission difference; S46A: Extracting a minimum value from the carbon emission differences, and using the preferred position corresponding to the minimum value as the recommended parking position.

[0013] By adopting the above technical solution, the required driving route is calculated based on the user's current location and recommended parking spaces, and the required carbon emission coefficient is then calculated based on the driving route. Combined with the carbon emission coefficient standard, the range of recommended parking spaces is further narrowed to achieve a balance between parking lot resource allocation and carbon emission control.

[0014] Optionally, extracting a minimum value from the carbon emission differences and using the preferred position corresponding to the minimum value as the recommended parking position includes: S46A1: Get the real-time traffic flow in each area of ​​the parking lot; S46A2: When the real-time traffic flow rate is higher than a preset reference flow rate limit, dividing the parking lot into a congested area and a smooth area based on the real-time traffic flow rate; S46A3: Determine whether the recommended parking space is located in the congested area; S46A4: If yes, calculating the congestion probability of the congested area within a preset time period based on the congested area and the real-time traffic volume; S46A5: If the congestion probability exceeds a preset probability value, selecting the preferred location that meets the carbon emission standard in the unobstructed area and selecting it as a candidate parking space; S46A6: Calculating a traffic flow selection reference value for the candidate parking space based on the carbon emission difference of the candidate parking space and the real-time traffic flow in the unobstructed area; S46A7: Select the candidate parking space with the lowest traffic flow selection reference value to update the recommended parking space; S46A8: If the candidate parking space is not available in the unobstructed area, maintaining the recommended parking space unchanged and outputting a preset congestion warning prompt; S46A9: If not, keep the recommended parking position unchanged.

[0015] By adopting this technical solution, traffic congestion in various areas is monitored in real time. If a recommended parking space is in a congested area, the system calculates and predicts the congestion probability for that area. If the probability is too high, the system will re-recommend a parking space in a less congested area. If there are still no suitable spaces, a congestion warning will be triggered. This method can prevent users from wasting time due to congestion and reduce secondary carbon emissions caused by congestion.

[0016] Optionally, generating voice broadcast information based on the scheduling route and the parking route, and transmitting the voice broadcast information to the voice broadcast system includes: S81: Generate an intelligent parking path based on the parking route and the scheduling route; S82: Monitor the intelligent parking path in real time and determine whether there is any abnormality in the intelligent parking path; S83: If not, continue testing; S84: If yes, retrieve the abnormal position based on the intelligent stop path; S85: Generate a new intelligent stop path based on the abnormal location, the user location, and the current location, and define it as an intelligent stop optimization path; S86: Sort the intelligent parking optimization paths from small to large as the optimization distance priority, use the intelligent parking optimization path ranked first in the optimization distance priority as the new intelligent parking path, send the new intelligent parking path to the preset intelligent parking robot and control its execution.

[0017] By adopting the above technical solution and through real-time detection of the smart parking path, any abnormalities in the path can be quickly located, and the optimal path can be planned based on the user's current location, thus achieving the flexibility, real-timeness and reliability of smart parking.

[0018] Optionally, generating voice broadcast information based on the scheduling route and the parking route, and transmitting the voice broadcast information to the voice broadcast system includes: S87: Determine in real time whether the recommended parking space is occupied; S88: If it is occupied, the preferred position other than the recommended parking space and not reserved is used as a parking space to be dispatched; S89: Calculate the distance between the user's location and the parking space to be scheduled and use it as the adjustment distance; S8A: generating a parking dispatch value based on the parking space to be dispatched, the congested area, and the unobstructed area; S8B: Calculating a distance comprehensive weight value based on the adjustment distance, the smooth parking scheduling value, and a preset distance comprehensive weight coefficient; S8C: Sort the distance comprehensive weight values ​​in descending order, use the to-be-scheduled parking space corresponding to the first one in the sort as a new low-carbon parking space, use the new low-carbon parking space as the parking destination, and output a path replanning instruction; S8D: If the parking space is not occupied, continue to use the recommended parking space.

[0019] By adopting the above technical solution, the usage status of the recommended parking spaces is detected in real time. If it is found to be occupied, a preferred location that is not reserved and occupied is immediately searched. Then, based on the congestion situation, an alternative target is selected and the driving route is updated, thereby effectively avoiding additional carbon emissions and waste of user time caused by repeated searches for parking spaces.

[0020] Optionally, the intelligent parking robot corresponding to the dispatch number moves including: S861: Calculate the distance between the user position and the current position as the guidance distance; S862: Determine whether the guidance distance exceeds a preset guidance distance value; S863: If exceeded, generating a guidance correction distance based on the current working state and the guidance distance; S864: Adjust the dispatch number based on the guidance correction distance, the current position, and the working status and use it as the dispatch correction number; S865: Outputting the guidance correction distance to the intelligent parking robot corresponding to the scheduling correction number to control movement; S866: If not exceeded, continue moving.

[0021] By adopting the above technical solution, the distance between the user's current position and the position of the intelligent parking robot is calculated to determine whether the user has deviated from the robot's guidance. If the distance exceeds a certain distance, the guiding robot is flexibly adjusted according to the distance information to ensure efficient parking.

[0022] Optionally, after the user arrives at the recommended parking spot, the method includes: S8661: Collect the berth weight information of the current parking space; S8662: Retrieve the vehicle base weight value from the vehicle type; S8663: When the parking space weight information does not meet the vehicle reference weight value, collecting adjacent weight information of adjacent parking spaces; S8664: Determine whether the adjacent weight information has abnormal changes; S8665: If the adjacent weight information changes abnormally, generating deviation weight information based on the adjacent weight information; S8666: Determine a deviation angle and a deviation distance based on the deviation weight information; S8667: Generate a deviation behavior suggestion based on the deviation angle and the deviation distance and send the suggestion to the intelligent parking robot corresponding to the dispatch number; S8668: If the adjacent weight information does not change abnormally, determine a weight surge based on the berth weight information; S8669: Determine a low-carbon parking suggestion based on the weight surge and send it to the intelligent parking robot corresponding to the dispatch number.

[0023] By employing this technical solution, a weight check is performed after a vehicle is parked in a parking space to determine whether it is fully parked within the parking area. If an anomaly is detected, the offset angle and distance are calculated and the results are pushed to the user, prompting them to make adjustments, thus avoiding risks such as scratches caused by vehicle offset. If no anomalies are detected, the system analyzes the sudden increase in weight in the current parking space to identify whether improper parking is causing increased carbon emissions, and then provides low-carbon suggestions such as optimizing the parking position. The entire process makes parking more accurate, standardized, and environmentally friendly.

[0024] In a second aspect, the present application provides a low-carbon parking guidance management system based on user behavior, which adopts the following technical solutions: A low-carbon parking guidance management system based on user behavior includes an acquisition module for obtaining parking instructions, weight status, current location and current working status; A memory for storing a program for a low-carbon parking guidance method based on user behavior according to any one of claims 1 to 4; The processor can load and execute the program in the memory.

[0025] In summary, this application includes at least one of the following beneficial technical effects: 1. By collecting parking instructions and weight monitoring device data, it accurately determines available parking spaces and, based on the user's parking preferences and vehicle type, finds the appropriate parking destination for the user, improving parking space utilization and user parking convenience. In terms of route planning, the parking route is determined based on the user's location and parking destination, and a dispatch route and number are generated for the intelligent parking robot, optimizing the movement path during the parking process and improving parking efficiency. At the same time, voice broadcast information provides real-time guidance to users and parking robots, effectively alleviating parking congestion. 2. By monitoring the occupancy status of recommended parking spaces in real time, if any are found to be occupied, the system immediately searches for unreserved and unoccupied preferred locations. It then selects alternative locations based on congestion conditions and updates the driving route, effectively avoiding additional carbon emissions and wasted user time caused by repeated searches for parking spaces. 3. After parking, the system performs a weight check to determine whether the vehicle is fully parked within the parking area. If any deviation is detected, the system calculates the offset angle and distance, and then pushes the result to the user, prompting them to make adjustments to avoid risks such as scratches caused by vehicle deviation. If no deviation is detected, the system analyzes the sudden increase in weight in the current parking space to identify whether improper parking is causing increased carbon emissions, and then pushes low-carbon suggestions such as optimizing the parking position. The entire process makes parking more accurate, standardized, and environmentally friendly. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a method flow chart of a low-carbon parking guidance method based on user behavior according to an embodiment of the present invention; Figure 2 This is a flow chart of a method for generating a parking destination based on parking preferences, vehicle types, and available parking spaces according to an embodiment of the present invention. DETAILED DESCRIPTION

[0027] The present invention is further described in detail below with reference to the accompanying drawings and embodiments.

[0028] This application discloses a low-carbon parking guidance method based on user behavior. By combining user behavior with low-carbon requirements, a parking space is recommended and then guided to the space by an intelligent parking robot, reducing the time wasted searching for a suitable parking space. Guidance information is output through a voice broadcast system, allowing users to move to the location of the intelligent parking robot in advance, thereby improving parking efficiency.

[0029] Reference Figure 1 , a low-carbon parking guidance method based on user behavior, comprising the following steps: S1: Collect the parking instructions sent by the user terminal and the weight monitored by the preset weight monitoring device in the parking lot.

[0030] A user terminal refers to an interactive device through which a user receives information, such as a mobile phone, an in-vehicle system, etc. A parking instruction refers to a parking request signal triggered by a user. In this embodiment, a parking instruction is automatically triggered by a gate device set at the entrance of the parking lot. When a vehicle enters the sensing area, a camera preset on the gate device automatically detects that a vehicle has entered and triggers the parking instruction. A weight monitoring device refers to a pressure sensor installed on a parking space in a parking lot. Each parking space is provided with a load-bearing plate, and the pressure sensor is installed at the bottom of the load-bearing plate. Several pressure sensors are arranged on each parking space and are evenly arranged to comprehensively and accurately monitor the pressure distribution on the parking space. The weight situation refers to the parking space load data fed back by the pressure sensor, which is converted into weight after detection by the pressure sensor. This information can better prepare for subsequent data processing.

[0031] S2: Collect the user's parking preference, vehicle type, and user location based on the parking instructions.

[0032] Parking preferences refer to user-defined priority conditions, such as proximity to elevators, charging station spaces, and parking lot exits. Vehicle type refers to vehicle size and energy type, such as small fuel vehicles and new energy vehicles. User location refers to the real-time coordinates of the user's vehicle, located using onboard GPS or mobile phone positioning. When a parking instruction is received, the user's license plate number is recognized by a camera pre-installed on the gate device. The corresponding behavior database is then retrieved based on the license plate number to obtain the parking preference, vehicle type, and user location. The behavior database pre-stores the parking preferences, vehicle types, user locations, and historical behavior data of different users.

[0033] S3: Determine an available parking space based on the weight.

[0034] A vacant parking space refers to an unoccupied parking space. The weight check value for each parking space is retrieved based on the weight information. The sum of these values ​​is then calculated and used as the weight of each parking space. This weight is then used to determine whether a parking space is occupied. If the weight exceeds the preset baseline weight, the space is occupied; if it does not, the space is unoccupied. The baseline weight refers to the pre-entered minimum vehicle weight.

[0035] S4: Generate parking destination based on parking preference, vehicle type and available parking spaces.

[0036] The parking destination refers to the optimal target parking space that is finally screened out, such as parking space A666 in area A. The specific method for generating the parking destination based on parking preferences, vehicle types, and available parking spaces is described in S41 to S46.

[0037] S5: Determine a parking route based on the user's location and the parking destination.

[0038] The parking route is the driving path from the user's current location to the parking destination. The shortest or optimal path between the user's location and the parking destination is searched in the route map as the parking route.

[0039] S6: Obtain the current position and current working status of the preset intelligent parking robot.

[0040] An intelligent parking robot refers to an automated guided vehicle robot. The current position refers to the positioning coordinates of the intelligent parking robot. The current working state refers to the task state machine parameters of the intelligent parking robot, such as idle / working / faulty / charging. In this embodiment, the intelligent parking robot is equipped with a positioning device such as GPS. The robot uses various sensors to obtain its own working status information. For example, the operating current of the motor is monitored by a current sensor preset on the intelligent parking robot. If the current suddenly increases beyond the normal range, it may indicate that the motor is overloaded or has a fault. At the same time, the battery management system preset on the intelligent parking robot monitors the working condition of the battery in real time to determine whether it is in a charging state. By obtaining this relevant information, the intelligent parking robot suitable for guiding the user is screened out.

[0041] S7: Generate a dispatch route and a dispatch number based on the current position, current working status and user position, and output the parking route and the dispatch route to the intelligent parking robot corresponding to the dispatch number to control movement.

[0042] The dispatch route is the optimal path for an intelligent parking robot to reach the location of the user's vehicle. The dispatch number is the identification code of the intelligent parking robot. Based on the user's location, the intelligent parking robot closest to the current location and currently in an idle state is selected. The identification code corresponding to this intelligent parking robot is used as the dispatch number, and the shortest path between the current location of this intelligent parking robot and the user's location is selected as the dispatch route. The parking route and dispatch route are then output to the intelligent parking robot corresponding to the dispatch number to control its movement, thereby bringing the intelligent parking robot corresponding to the dispatch number closer to the user, facilitating subsequent parking guidance by the intelligent parking robot.

[0043] S8: Generate voice broadcast information based on the scheduling route and the parking route, and transmit the voice broadcast information to the voice broadcast system.

[0044] Voice announcements are messages that prompt users to initiate vehicle movement. The voice announcement system refers to audio equipment distributed throughout the parking lot. Voice announcements help users better understand the next direction of movement and prevent congestion. For example, "Please drive straight ahead slowly first, then guide robot R707 to parking space A666 in area A."

[0045] Reference Figure 2 , a low-carbon parking guidance method based on user behavior, further comprising generating a parking destination based on parking preferences, vehicle type, and available parking spaces, the following steps: S41: Collecting user historical behavior data based on parking instructions.

[0046] Historical behavior data refers to the user's past parking records, such as the length of time the user frequently parks, the time period during which the user parks, the parking method, etc. The user's historical behavior data is retrieved from the behavior database.

[0047] S42: Generate a preferred parking space based on historical behavior data and parking preferences.

[0048] Preferred parking spaces are candidate spaces generated by combining historical data and current demand. This is done by retrieving and matching the available parking spaces with historical behavior data and parking preferences. The available spaces that meet one or more of these parameters are selected as preferred spaces.

[0049] S43: Generate a parking space category based on the user's location and current location.

[0050] Parking space categories are labels for parking spaces based on the user's location and current location. Parking space categories are primarily divided into two categories. Category 1 corresponds to vacant spaces between the user's location and current location, while category 2 corresponds to vacant spaces other than category 1. This classification allows you to quickly narrow down your selection process and improve efficiency.

[0051] S44: Selecting an available parking space based on the parking space category and the preferred parking space to generate a preferred location.

[0052] The preferred position refers to the position corresponding to the parking space that is selected first for the vacant parking space. The specific steps of generating the preferred position for the vacant parking space based on the parking space category and the preferred parking space are referred to S441 to S44A.

[0053] S45: Retrieve the carbon emission coefficient based on the vehicle type.

[0054] The carbon emission coefficient is the reference coefficient of carbon dioxide emissions per unit distance traveled by a vehicle type. Different vehicle types have different carbon emission coefficients. The carbon emission coefficient of a vehicle type can be determined by querying a pre-set carbon emission coefficient database. This database pre-stores data on various vehicle types and their corresponding carbon emission coefficients, which are recorded by operators for each vehicle type.

[0055] S46: Generate a recommended parking space based on the preferred location and the carbon emission coefficient, and use the recommended parking space as the parking destination.

[0056] Recommended parking spaces are recommended for users based on a comprehensive consideration of environmental protection and user needs. The distance between the preferred location and the user's location is calculated, and then the distance is calculated with the carbon emission coefficient. The recommended parking spaces are then ranked and selected based on the preferred locations that meet the requirements, balancing environmental protection and user convenience.

[0057] A low-carbon parking guidance method based on user behavior also includes selecting vacant parking spaces based on parking space categories and preferred parking spaces to generate preferred locations, including the following steps: S441: Extracting charging requirements, automatic parking preferences, vehicle exit preferences, pedestrian exit preferences, and parking environment preferences from parking preferences.

[0058] Charging demand refers to the degree to which a vehicle requires charging. Automatic parking preference refers to the degree to which a user prefers to use the automatic parking feature for parking. Vehicle exit preference refers to the degree to which a user prefers a parking space to be close to the vehicle exit. Pedestrian exit preference refers to the degree to which a user prefers a parking space to be close to the pedestrian exit after parking. Parking environment preference refers to the user's required scores for various aspects of the parking environment. Parking preferences include charging demand, automatic parking preference, vehicle exit preference, pedestrian exit preference, and parking environment preference. By extracting charging demand, automatic parking preference, vehicle exit preference, pedestrian exit preference, and parking environment preference from parking preferences, preparation is made for the subsequent calculation of parking space weights.

[0059] S442: Select an empty parking space corresponding to the preset first category as a first-category parking space, and select the empty parking spaces other than the first-category parking spaces as second-category parking spaces.

[0060] Class I parking spaces refer to spaces in the first category. Class II parking spaces refer to spaces in the second category. Classifying parking spaces and defining first and second category parking spaces lays the foundation for subsequent targeted weight calculation and screening recommendations based on different standards.

[0061] S443: Determine a first-category weight score based on the first-category parking space, charging requirements, automatic parking preference, and vehicle exit preference.

[0062] The first-category weighted score refers to the score of the first-category parking space, taking into account factors such as charging demand, automatic parking preference, and vehicle exit preference. A higher score indicates that the parking space more closely meets the user's preferences and needs in these areas. The first-category parking space retrieves the corresponding charging demand satisfaction as the charging satisfaction value, the automatic parking preference satisfaction as the automatic parking preference satisfaction value, and the vehicle exit preference satisfaction as the vehicle exit preference satisfaction value. The first-category weighted score is then calculated using the first-category weighted calculation formula to combine the charging satisfaction value, the automatic parking preference satisfaction value, and the vehicle exit preference satisfaction value. The first-category weighted score is calculated as follows: First-category weighted score = a × charging satisfaction value + b × automatic parking preference satisfaction value + c × vehicle exit preference satisfaction value, where a represents the user's preference for charging, b represents the user's preference for automatic parking, and c represents the user's preference for vehicle exit. a, b, and c are obtained by querying the behavior database. For example, if the user values ​​charging very highly, a = 1; if it doesn't matter at all, a = 0; if it's both acceptable, a = 0.5; and if it's slightly important, a = 0.7. For example, if the charging demand score is 100, the automatic parking preference score is 80, and the vehicle exit preference score is 90, and a = 0.6, b = 0.3, and c = 0.1, then the first-category weight score = 0.6 × 100 + 0.3 × 80 + 0.1 × 90 = 93.

[0063] S444: Determine a second-category weight score based on the second-category parking space, charging demand, pedestrian exit preference, and parking environment preference.

[0064] The second-category weighted score refers to a comprehensive calculation of factors such as charging demand, pedestrian exit preference, and parking environment preference for the second-category parking space. It is used to measure the preferences and needs of the parking space and the user in these specific aspects. The satisfaction of charging demand is retrieved from the second-category parking space and used as the charging satisfaction value. The satisfaction of pedestrian exit preference is retrieved from the second-category parking space and used as the pedestrian exit preference satisfaction value. The satisfaction of parking environment preference is retrieved from the second-category parking space and used as the parking environment preference satisfaction value. The second-category weighted score is then calculated using the second-category weighted formula to calculate the charging demand satisfaction value, pedestrian exit preference satisfaction value, and parking environment preference satisfaction value. The specific second-category weighted score is: Second-category weighted score = a × charging demand satisfaction value + b × pedestrian exit preference satisfaction value + c × parking environment preference satisfaction value.

[0065] S445: Combining the first-category weight score and the second-category weight score to obtain a comprehensive weight score, and sorting the comprehensive weight scores from high to low to obtain a weight score table.

[0066] The combined weighted score combines the first and second weighted scores to comprehensively compare the overall match between all parking spaces and the user's parking preferences. The weighted score table is a table that sorts the scores in the combined weighted score table in descending order. This makes the priority of each parking space clearer.

[0067] S446: Count the second-category parking spaces corresponding to the second-category weighted scores that meet the preset standards in the weighted score table and define them as second-category qualified parking spaces.

[0068] The preset standard refers to the top few parking spaces in the weighted score table. The specific top number can be determined based on experience and actual conditions. Second-category qualified parking spaces refer to the number of second-category parking spaces that meet the preset standard. For example, if the preset standard is 5 and two of the top 5 parking spaces are second-category parking spaces, these two spaces will be considered second-category qualified spaces. This is primarily intended to screen out relatively good second-category parking spaces.

[0069] S447: Determine whether there is a parking space with a first-category weighted score greater than a preset first-category score.

[0070] The first-category score refers to the score that meets the requirements for first-category parking spaces and is pre-entered. By determining whether there are parking spaces with a first-category weighted score greater than the preset first-category score, the user can be checked to see whether there are any parking spaces in the first-category score that relatively meet the user's preferences.

[0071] S448: If it exists, the corresponding parking space will be regarded as the first-class qualified parking space.

[0072] Class I qualified parking spaces are those that meet the Class I criteria. When a Class I weighted score exceeds the preset Class I score, these spaces are considered Class I qualified parking spaces. For example, if the Class I score is 85, then spaces with a Class I weighted score greater than 85 are considered Class I qualified parking spaces.

[0073] S449: Class I and Class II qualified parking spaces are considered as preferred locations.

[0074] After evaluating the first and second category parking spaces, we select the spaces that best meet user expectations and designate them as first and second category qualified spaces, respectively. These spaces are then combined to form the preferred locations. The number of preferred locations selected is variable. For example, if there are two second category qualified spaces and six first category qualified spaces, then there would be eight preferred locations. This approach improves the user's parking experience.

[0075] S44A: If not, determine a secondary location based on the second type of qualified parking space and use the secondary location as the preferred location.

[0076] Secondary locations refer to locations that meet the requirements, selected from either the first or second category of qualified parking spaces. By analyzing the number of second category qualified parking spaces, if the number is zero, the locations corresponding to first category qualified parking spaces that fall within the preset criteria and have a score that meets the first category score are selected as secondary locations. If the number of second category qualified parking spaces is not zero, and a first category parking space does not fall within the preset criteria and has a score that meets the first category score, the locations corresponding to second category parking spaces that fall within the preset criteria are selected as secondary locations. If the number of second category qualified parking spaces is not zero, and a first category parking space falls within the preset criteria and has a score that meets the first category score, the locations corresponding to the first category parking space that falls within the preset criteria and has a score that meets the first category score are selected, and the locations corresponding to the selected first category parking space and the second category qualified parking space are selected as secondary locations. This approach fully considers the different characteristics of parking spaces and the diverse needs of users, resulting in more reasonable parking resource recommendations.

[0077] A low-carbon parking guidance method based on user behavior also includes generating a recommended parking space based on a preferred location and a carbon emission coefficient, including the following steps: S461: Generate a travel distance based on the preferred location and the user location.

[0078] Travel distance refers to the actual distance from the user's current location to the preferred location. Calculating travel distance is accomplished by combining parking maps and path planning algorithms, a technique currently available and not detailed here. Calculating the travel path facilitates subsequent use.

[0079] S462: Calculate the required amount of carbon emissions based on the travel distance and the carbon emission coefficient.

[0080] The required carbon emissions are the amount of carbon dioxide emissions generated by each vehicle traveling the same route. This is calculated by multiplying the distance traveled by the carbon emission coefficient.

[0081] S463: Real-time collection of total carbon emissions and atmospheric carbon concentration in parking lots.

[0082] Total carbon emissions refer to the total emissions generated by all parked vehicles in a parking lot. This is estimated by analyzing historical vehicle parking locations and types, combined with vehicle emission parameters and operating conditions, to estimate the total carbon emissions generated by all vehicles currently operating in the parking lot. Atmospheric carbon concentration refers to the real-time carbon dioxide concentration monitored within the parking lot. This atmospheric carbon concentration is calculated by averaging the carbon dioxide concentration measured by sensors located at several locations within the parking lot.

[0083] S464: Generate carbon emission standards based on total carbon emissions and atmospheric carbon concentration.

[0084] The carbon emission standard refers to the amount of emissions allowed per vehicle under the current circumstances. By calculating the sum of the total carbon emissions of the parking lot monitored in real time and the atmospheric carbon concentration, and then combining this sum with the preset target atmospheric carbon concentration, the difference between the two concentrations is calculated to dynamically adjust the total allowable emissions. Based on the total carbon emissions, the actual number of parking lots today is calculated. The future number of parking lots is calculated by dividing the actual number of parking lots today with the preset planned target number of parking lots. The quotient between the total allowable emissions and the future number of parking lots is then calculated to generate the carbon emission standard, achieving coordinated regulation of carbon emission constraints and changes in parking scale. The planned target number of parking lots refers to the number of parking lots planned for a day that is pre-entered into the parking lot.

[0085] S465: Determine whether the required carbon emission amount meets the carbon emission standard.

[0086] Whether the low-carbon requirements are met is determined by judging whether the required carbon emissions meet the carbon emission standards.

[0087] S466: If the requirements are met, the preferred position corresponding to the required amount of carbon emissions that meet the carbon emission standards will be used as a low-carbon parking position.

[0088] Low-carbon parking refers to preferred parking locations where the amount of carbon dioxide emissions meets the standards. If the carbon emission standards are met, the preferred location corresponding to the standards will be designated as a low-carbon parking location.

[0089] S467: Generate a recommended parking table based on the low-carbon parking spaces and the preset low-carbon preferred weight coefficient.

[0090] The low-carbon preference weighting factor is the priority weight for low-carbon attributes. The recommended parking table is a list of parking spaces sorted by comprehensive rating. The recommended parking table calculates a reference score by multiplying the distance obtained by the low-carbon preference weighting factor with the known low-carbon parking spaces. These scores are then tabulated.

[0091] S468: Select a preferred position that meets a preset parking selection standard from the recommended parking table as a recommended parking position.

[0092] The parking space selection criteria refers to the number of recommended parking spaces that meet the ranking requirements of the comprehensive score. The parking space selection criteria are preset. The final recommendation results are selected based on the preset ranking requirements. First, the sorted recommended parking spaces are preliminarily screened according to the preset parking space selection criteria. Then, the candidate intervals are intercepted according to the ranking. Subsequently, the parking spaces that do not meet the conditions are filtered out. Finally, the final recommendation list is generated by secondary sorting based on the preferences actively set by the user. An example is as follows: the top 3 parking spaces with the highest comprehensive scores are pre-selected as candidates. When the recommended parking spaces are sorted according to the comprehensive score calculated based on the low-carbon weight, the top 3, such as parking spaces A, B, and C, are first intercepted. If parking space B is marked as unavailable because it does not meet the user's preferences, parking space B is eliminated. The distances of the remaining parking spaces A and C are recalculated based on the priority preferences set by the user to finally generate a recommendation list.

[0093] S469: If not met, the difference between the required carbon emission amount and the carbon emission standard is calculated as the carbon emission difference.

[0094] The carbon emission gap refers to the amount by which the required carbon emissions exceed the carbon emission standard. If the standard is not met, the excess amount is calculated by calculating the difference between the required carbon emissions and the carbon emission standard, providing a basis for subsequent compensation strategies.

[0095] S46A: Extract the minimum value from the carbon emission difference and use the preferred position corresponding to the minimum value as the recommended parking position.

[0096] By finding the minimum value of the calculated carbon emission difference, it is possible to select the parking space with the least environmental impact when exceeding the standard, thereby reducing the adverse impact on the environment.

[0097] A low-carbon parking guidance method based on user behavior, further comprising extracting a minimum value from carbon emission differences and using the preferred location corresponding to the minimum value as a recommended parking space, and then performing the following steps: S46A1: Get real-time traffic flow in each area of ​​the parking lot.

[0098] Parking lot zones refer to the divisions between different parking spaces, such as Zone A and Zone B. Real-time traffic flow refers to the density of vehicles within the parking lot at different times. This is calculated by analyzing the number of vehicles detected by cameras installed within the parking lot and the area of ​​the parking lot. Real-time traffic flow in different zones is used to determine congestion conditions and provide data for subsequent delineation of congested areas.

[0099] S46A2: When the real-time traffic flow is higher than the preset benchmark flow limit, the parking lot is divided into a congested area and a smooth area based on the real-time traffic flow.

[0100] The baseline flow rate limit refers to the maximum traffic flow parameter during normal parking area use. Congested areas are areas where real-time traffic exceeds the baseline flow rate, which is prone to congestion or slow traffic. Smooth areas are areas where real-time traffic is lower than the baseline flow rate, indicating higher traffic efficiency. When real-time traffic exceeds the preset baseline flow rate limit, it indicates that congestion has begun to occur in the parking lot. By identifying congested areas, we can provide optimized solutions for subsequent parking space selection.

[0101] S46A3: Determine whether the recommended parking space is located in a congested area.

[0102] By determining whether the recommended parking space is in a congested area, it is determined whether a more reasonable parking space needs to be reselected.

[0103] S46A4: If yes, calculate the congestion probability of the congestion area within the preset time period based on the congestion area and the real-time traffic flow.

[0104] The preset time period refers to a period of time in the future, such as 5 minutes. The congestion probability refers to the predicted probability of encountering congestion on the way to the recommended parking space in the congested area. The real-time traffic flow corresponding to the area surrounding the congested area is retrieved and used as the surrounding traffic flow, and then the difference between the surrounding traffic flow and the real-time traffic flow is calculated and used as the traffic flow difference. The traffic flow difference and the preset time period are used to calculate the change trend of the traffic flow per unit time, and the congestion probability is obtained based on the change trend. Different change trends result in different congestion probabilities, and the congestion probabilities corresponding to different change trends are obtained by querying the preset congestion probability database. The congestion probability database pre-stores the congestion probabilities corresponding to different change trends, and the congestion probability is obtained by the operator calculating and recording different change trends.

[0105] S46A5: If the congestion probability exceeds the preset probability value, a preferred location that meets the carbon emission standards is selected in the unobstructed area and used as a candidate parking space.

[0106] The probability value is the minimum value corresponding to the pre-set probability of causing congestion. Candidate parking spaces are parking spaces in unobstructed areas that meet carbon emission standards. If the congestion probability of a recommended parking space in a congested area exceeds the pre-set probability value, a preferred location that meets carbon emission standards will be selected from the unobstructed area. Finding more suitable parking spaces in unobstructed areas reduces congestion risks and improves parking efficiency.

[0107] S46A6: Calculate the traffic flow selection reference value for the candidate parking spaces based on the carbon emission difference of the candidate parking spaces and the real-time traffic flow in the unblocked area.

[0108] The traffic flow selection reference value refers to the reference value corresponding to the selection of candidate parking spaces based on the congestion caused by traffic flow. The smaller the value, the lower the risk. The carbon emission difference is input into the preset carbon emission impact database to obtain the carbon emission difference impact value. The carbon emission impact database pre-stores a comparison table of different carbon emission differences and corresponding carbon emission difference impact values. The carbon emission impact database is preset. The traffic flow impact value is input into the preset traffic flow impact database to obtain the traffic flow impact value. The traffic flow impact database pre-stores different real-time traffic flows and corresponding traffic flow impact values. The traffic flow impact database is preset. The sum of the carbon emission difference impact value and the traffic flow impact value is then calculated and used as the traffic flow selection reference value. By calculating the traffic flow selection reference value, the potential congestion risk of the candidate parking spaces is estimated, providing a basis for the final selection.

[0109] S46A7: Select the candidate parking space with the lowest traffic flow selection reference value to update the recommended parking space.

[0110] From the calculated traffic flow selection reference values, the one with the smallest traffic flow selection reference value is selected as the candidate parking space, and the recommended parking space is updated. This method optimizes the advancement results and balances environmental protection and traffic efficiency.

[0111] S46A8: If there are no candidate parking spaces in the unobstructed area, the recommended parking space remains unchanged and a preset congestion warning prompt is output.

[0112] Congestion warning prompts are to send congestion risk notifications to users. When there are no suitable candidate parking spaces in the unobstructed area, it means that the user cannot avoid it. In this case, the user will be informed in advance through the preset voice broadcast system of the intelligent robot guiding it, so that the user can be mentally prepared in advance.

[0113] S46A9: If no, keep the recommended stop position unchanged.

[0114] If the recommended parking space is not in a congested area, there is no need to re-recommend it, so the recommended parking space remains unchanged.

[0115] A low-carbon parking guidance method based on user behavior includes generating voice broadcast information based on a scheduling route and a parking route, and transmitting the voice broadcast information to a voice broadcast system, and then including the following steps: S81: Generate an intelligent parking path based on the parking route and scheduling route.

[0116] The intelligent parking path is the entire path covered by the parking route and the dispatching route. The intelligent parking path is obtained by merging the paths covered by the parking route and the dispatching route.

[0117] S82: Monitor the intelligent parking path in real time to determine whether there are any abnormalities in the intelligent parking path.

[0118] Abnormalities refer to unexpected obstacles along the intelligent parking path, such as temporary obstructions or collisions between two vehicles. Pre-set monitors on the intelligent parking robot and other intelligent parking robots monitor the path together and upload data to the parking lot's monitoring system for real-time detection of abnormalities. This allows users to quickly determine the feasibility of the original route and avoid unnecessary unnecessary paths.

[0119] S83: If not, continue testing.

[0120] If no abnormalities are found, the existing route will be maintained while continuing to monitor the route to ensure that the route remains valid.

[0121] S84: If yes, retrieve the abnormal position based on the intelligent stop path.

[0122] An abnormal location is a location on the intelligent stop path where an abnormality occurs. If an abnormality occurs, the intelligent stop path is matched with the abnormal location, and the abnormal location on the intelligent stop path is retrieved as the abnormal location.

[0123] S85: Generate a new intelligent parking path based on the abnormal location, the user location, and the current location, and define it as the intelligent parking optimization path.

[0124] Intelligent parking optimization routes are replanned to avoid unusual locations. Different routes are determined based on the user's location and current location. The route that excludes the unusual location is then selected as the optimized route, ensuring route feasibility and user arrival efficiency.

[0125] S86: Sort the intelligent parking optimization paths from small to large as the optimization distance priority, use the intelligent parking optimization path ranked first in the optimization distance priority as the new intelligent parking path, send the new intelligent parking path to the preset intelligent parking robot and control its execution.

[0126] The optimization distance priority is the priority of the intelligent parking paths in the list of optimized paths, sorted in ascending order by path length. The shortest path is selected from the list as the intelligent parking path, and the intelligent parking robot then guides the vehicle along this path. By selecting the shortest path, user waiting time is reduced, ensuring parking efficiency.

[0127] A low-carbon parking guidance method based on user behavior also includes generating voice broadcast information based on a scheduling route and a parking route, and transmitting the voice broadcast information to a voice broadcast system, including the following steps: S87: Determine in real time whether the recommended parking space is occupied.

[0128] The recommended parking space is ensured to be available by real-time determination of whether it is occupied, preventing users from arriving at a parking space only to discover it is unavailable. This is primarily due to users selecting a parking space on their own, without being guided by the intelligent parking robot. The recommended parking space is determined to be occupied based on the weight converted from parking space load data obtained from the pressure sensor.

[0129] S88: If it is occupied, the preferred location other than the recommended parking space and not reserved will be used as the parking space to be dispatched.

[0130] Unreserved spaces are spaces that haven't been reserved by a user through other systems, including reservations made by users themselves or by intelligent robots. Pending spaces are spaces that can be reallocated. If they are occupied, it means a new space needs to be selected as a pending space. Therefore, pending spaces are defined to facilitate their subsequent use.

[0131] S89: Calculate the distance between the user's location and the parking space to be dispatched and use it as the adjustment distance.

[0132] The adjustment distance refers to the actual driving distance from the user's current location to the scheduled parking space. Calculating the actual driving distance from the user's location to each scheduled parking space is done through a path planning algorithm. This is existing technology and will not be detailed here. Calculating the distance the user travels to the new parking space provides data for subsequent comprehensive considerations.

[0133] S8A: Generates parking dispatch values ​​based on the parking spaces to be dispatched, congested areas, and unobstructed areas.

[0134] The smooth parking dispatch value is a score generated by combining the congestion status and parking space attributes of the area where the parking space to be dispatched is located. The area status coefficient is calculated based on the area where the parking space to be dispatched is located. The area status coefficient is 1 for unobstructed areas and 0.5 for congested areas. The number of unobstructed areas around the parking space to be dispatched is counted to form the number of unobstructed areas. The product of the area status coefficient and the number of unobstructed areas is calculated and used as the smooth parking dispatch value for subsequent use.

[0135] S8B: Calculate the distance comprehensive weight value based on the adjustment distance, the berthing scheduling value and the preset distance comprehensive weight coefficient.

[0136] The distance comprehensive weight coefficient refers to the weight assigned to the adjustment distance and the parking dispatch value in the comprehensive score. The distance comprehensive weight value is the weighted average of the comprehensive score, with a higher value indicating a higher priority. The distance comprehensive weight value is calculated by inputting the adjustment distance, parking dispatch value, and distance comprehensive weight coefficient into the preset distance comprehensive weight value formula. The distance comprehensive weight value formula is: =p × adjustment distance +q × parking dispatch value, where p is the distance weight and q is the parking dispatch weight. This weighted calculation makes the recommended parking space more scientific, and the sum of p and q is 1.

[0137] S8C: Sort the distance comprehensive weight values ​​in descending order, and use the first parking space to be dispatched as the new low-carbon parking space, use the new low-carbon parking space as the parking end point, and output the path replanning instruction.

[0138] Descending sorting refers to sorting from highest to lowest values. A re-routing command refers to an updated navigation path pushed to the user. By selecting the optimal parking space with the highest combined distance weight and updating the user's navigation path in real time, the robot is controlled to move along the newly generated path, improving parking efficiency.

[0139] S8D: If it is not occupied, continue to use the recommended parking space.

[0140] If it is not occupied, continue to the recommended parking space.

[0141] A low-carbon parking guidance method based on user behavior also includes the following steps when the intelligent parking robot corresponding to the dispatch number moves: S861: Calculate the distance between the user's location and the current location as the guidance distance.

[0142] The guidance distance is the distance the smart parking robot needs to travel from its original position to the user's location. The actual distance between the user's location and the current location is calculated to provide basic data for subsequent steps.

[0143] S862: Determine whether the guidance distance exceeds a preset guidance distance value.

[0144] The preset guidance distance value refers to the standard value of the guidance distance of the intelligent parking robot, such as 10m. By judging whether the guidance distance exceeds the preset guidance distance value, it is determined whether the distance needs to be corrected to avoid invalid guidance.

[0145] S863: If exceeded, generate a guidance correction distance based on the current working state and the guidance distance.

[0146] The guidance correction distance is the distance adjusted based on the robot's status and guidance distance. If the guidance distance is exceeded, it means the user has left the guiding smart parking robot and needs to be reassigned. Therefore, the guidance correction distance is calculated to facilitate subsequent adjustment of the dispatch number.

[0147] S864: Adjust the dispatch number based on the guidance correction distance, current position and working status and use it as the dispatch correction number.

[0148] The dispatch correction number is the updated robot dispatch number. Based on the corrected distance and the user's current location, a more suitable robot is selected for the user and a new robot dispatch number is generated.

[0149] S865: Output the guidance correction distance to the intelligent parking robot corresponding to the scheduling correction number to control the movement.

[0150] The new robot dispatch number is sent to the selected robot. After receiving the task number, the robot controls its movement to guide the user's parking.

[0151] S866: If not exceeded, continue moving.

[0152] If the guidance distance is not exceeded, no adjustment is required and the guidance can be continued.

[0153] A low-carbon parking guidance method based on user behavior further includes the following steps after the user arrives at a recommended parking space: S8661: Collect the berth weight information of the current parking space.

[0154] Parking space weight information refers to the weight of the user's car when it arrives at the parking space. It is obtained through a pressure sensor and is used to determine whether the user's car has exceeded the boundary.

[0155] S8662: Get the vehicle base weight value from the vehicle type.

[0156] The vehicle base weight (BW) is the estimated minimum weight of a vehicle, including the vehicle's own weight and the weight of its passengers. Different vehicle types have different BW values, which are obtained by querying a pre-set vehicle weight database. This database contains a table of BW values ​​for different vehicle types, compiled by technicians through the sequential recording of different vehicle types.

[0157] S8663: When the berth weight information does not meet the vehicle reference weight value, the adjacent weight information of the adjacent parking spaces is collected.

[0158] Adjacent parking spaces refer to spaces physically adjacent to the current parking space, such as to the left or right. Adjacent weight information refers to the weight information detected for parking spaces physically adjacent to the current parking space. The weight values ​​for each position in the parking space are retrieved from the parking space weight information and summed to obtain the parking space weight value. If the parking space weight value is less than the vehicle's reference weight value, it indicates that the parking space weight information does not meet the vehicle's reference weight value, indicating that the vehicle is not parked properly. Therefore, the pressure sensors of the adjacent parking spaces are retrieved to obtain the adjacent weight information.

[0159] S8664: Determine whether adjacent weight information has undergone abnormal changes.

[0160] An abnormal change occurs when the weight of adjacent parking spaces increases by more than a preset weight reference value, which is the maximum gravity corresponding to a person walking. By determining whether the weight of adjacent parking spaces exceeds the preset weight reference value, the system determines whether the user's vehicle has exceeded the boundary and whether the user needs to repark the vehicle.

[0161] S8665: If the adjacent weight information undergoes abnormal changes, deviation weight information is generated based on the adjacent weight information.

[0162] Deviation weight information refers to the weight difference between the adjacent parking spaces. If a weight value is detected in an adjacent parking space, indicating that the user's parking is not completely within the basket, the two adjacent weight values ​​before and after the abnormal change are compared and the deviation is used as the deviation weight information. This provides a basis for subsequent reminders to the user to re-park the vehicle.

[0163] S8666: Determine the deviation angle and deviation distance based on the deviation weight information.

[0164] The deviation angle is the angle between the vehicle's center of gravity and the parking space boundary. The deviation angle is the distance the vehicle's actual parking position deviates from the standard position. Deviation weight information includes the specific location of the abnormal deviation and the corresponding deviation value. The deviation weight information is used to retrieve the deviation location. The deviation distance and angle are calculated based on the deviation location and the center position of the current parking space, preparing for the generation of deviation behavior recommendations.

[0165] S8667: Generates deviation behavior suggestions based on the deviation angle and deviation distance and sends them to the intelligent parking robot corresponding to the dispatch number.

[0166] Deviation suggestions are instructions for correcting a vehicle's parking position. These suggestions use the deviation angle and distance, combined with pre-set judgment logic and directional rules, to directly generate adjustment instructions. These deviations are sent to the intelligent parking robot corresponding to the dispatch number, which then prompts the user to make accurate adjustments. Correcting parking deviations improves parking standards and safety.

[0167] S8668: If there is no abnormal change in the adjacent weight information, determine the weight surge based on the berth weight information.

[0168] The weight surge refers to the weight surge at the position corresponding to a certain tire when the user parks. When no abnormality is detected in the adjacent parking spaces, the weight situation of the current parking space should also be monitored. The current berth weight is retrieved through the berth weight information. The current berth weight refers to the weight value of the position where the vehicle is parked, which is monitored in real time by the sensor. The current berth weight and standard weight are input into the preset surge ratio formula. The standard weight refers to the pre-set reference weight value. The surge ratio is thus calculated and used as the weight surge. The surge ratio formula is: surge ratio = [(current berth weight - standard weight) / standard weight] × 100%. By monitoring the surge situation, data support is provided for subsequent low-carbon recommendations.

[0169] S8669: Determine low-carbon parking recommendations based on weight surges and send them to the smart parking robot corresponding to the dispatch number.

[0170] Low-carbon parking suggestions refer to operational suggestions for reducing carbon emissions, which are obtained through pre-input. Through surge weight monitoring, it is determined whether the weight surge is greater than the preset surge benchmark ratio. If it is greater, it is determined that the user braked too hard due to excessive speed when entering the parking frame. When a weight surge is detected when the vehicle enters the parking frame, a preset low-carbon parking suggestion is generated to remind the user to reduce the speed when entering the parking frame. These low-carbon parking suggestions will then be sent to the smart parking robot associated with the corresponding dispatch number, which will convey them to the user. If the weight surge is not greater than, no prompt information will be generated. The guided robot reminds the user to reduce ineffective energy consumption and improve the low-carbon level of the parking lot. The surge benchmark ratio refers to the surge ratio corresponding to normal braking, which is obtained through pre-input.

[0171] Based on the same inventive concept, an embodiment of the present invention provides a low-carbon parking guidance and management system based on user behavior, including: Acquisition module, used to obtain parking instructions, weight status, current position and current working status; A memory for storing a program such as the above-mentioned low-carbon parking guidance method based on user behavior; The processor can load and execute the program in the memory.

[0172] Those skilled in the art will clearly understand that for the sake of convenience and brevity, the division of the above-mentioned functional modules is only used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working processes of the above-mentioned systems, devices, and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0173] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions based on the principles of the present invention are within the scope of protection of the present invention. It should be noted that improvements and modifications that do not depart from the principles of the present invention are within the scope of protection of the present invention.

Claims

1. A low-carbon parking guidance method based on user behavior, characterized in that: include: S1: Collect the parking instructions sent by the user terminal and the weight monitored by the preset weight monitoring device in the parking lot; S2: collecting the user's parking preference, vehicle type, and user location based on the parking instruction; S3: Determine an available parking space based on the weight condition; S4: generating a parking destination based on the parking preference, the vehicle type, and the available parking space; S5: Determine a parking route based on the user location and the parking destination; S6: Obtain the current position and current working status of the preset intelligent parking robot; S7: generating a dispatch route and a dispatch number based on the current position, the current working state, and the user position, and outputting the parking route and the dispatch route to the intelligent parking robot corresponding to the dispatch number to control movement; S8: Generate voice broadcast information based on the scheduling route and the parking route, and transmit the voice broadcast information to a voice broadcast system.

2. The low-carbon parking guidance method based on user behavior according to claim 1, characterized in that: Generating a parking destination based on the parking preference, the vehicle type, and the available parking space includes: S41: Collecting user historical behavior data based on the parking instruction; S42: generating a preferred parking space based on the historical behavior data and the parking preference; S43: Generate a parking space category based on the user location and the current location; S44: Selecting the vacant parking space based on the parking space category and the preferred parking space to generate a preferred location; S45: Retrieving a carbon emission coefficient based on the vehicle type; S46: Generate a recommended parking spot based on the preferred location and the carbon emission coefficient, and use the recommended parking spot as the parking destination.

3. The low-carbon parking guidance method based on user behavior according to claim 2, characterized in that: Selecting the vacant parking space based on the parking space category and the preferred parking space to generate a preferred location includes: S441: Extracting charging requirements, automatic parking preferences, vehicle exit preferences, pedestrian exit preferences, and parking environment preferences from the parking preferences; S442: selecting the vacant parking spaces corresponding to the preset first category as first-category parking spaces, and selecting the vacant parking spaces other than the first-category parking spaces as second-category parking spaces; S443: Determine a first-category weight score based on the first-category parking space, the charging requirement, the automatic parking preference, and the vehicle exit preference; S444: Determine a second category weight score based on the second category parking space, the charging demand, the pedestrian exit preference, and the parking environment preference; S445: Combining the first category weight score and the second category weight score to obtain a comprehensive weight score, and sorting the comprehensive weight scores from high to low to obtain a weight score table; S446: Counting the second-category parking spaces corresponding to the second-category weighted scores that meet the preset standard in the weighted score table, and defining them as second-category qualified parking spaces; S447: Determine whether there is a parking space with the first category weight score greater than a preset first category score; S448: If it exists, the corresponding parking space is regarded as a first-class qualified parking space; S449: Selecting the first-category qualified parking space and the second-category qualified parking space as the preferred locations; S44A: If not, determine a secondary location based on the second-category qualified parking space, and use the secondary location as the preferred location.

4. The low-carbon parking guidance method based on user behavior according to claim 3 is characterized in that: Generating a recommended parking spot based on the preferred location and the carbon emission coefficient includes: S461: Generate a travel distance based on the preferred location and the user location; S462: Calculating the required amount of carbon emissions based on the travel distance and the carbon emission coefficient; S463: Real-time collection of total carbon emissions and atmospheric carbon concentration in parking lots; S464: Generate a carbon emission standard based on the total carbon emissions and the atmospheric carbon concentration; S465: Determine whether the required carbon emission amount meets the carbon emission standard; S466: If the requirement is met, the preferred position corresponding to the required amount of carbon emissions that meets the carbon emission standard is used as a low-carbon parking position; S467: Generate a recommended parking space table based on the low-carbon parking space and a preset low-carbon preferred weight coefficient; S468: Selecting the preferred position that meets the preset parking selection criteria from the recommended parking table as the recommended parking position; S469: If not satisfied, calculating the difference between the required carbon emission amount and the carbon emission standard as the carbon emission difference; S46A: Extracting a minimum value from the carbon emission differences, and using the preferred position corresponding to the minimum value as the recommended parking position.

5. The low-carbon parking guidance method based on user behavior according to claim 4, characterized in that: The method further comprises: extracting a minimum value from the carbon emission differences and using the preferred position corresponding to the minimum value as the recommended parking position; S46A1: Get the real-time traffic flow in each area of ​​the parking lot; S46A2: When the real-time traffic flow rate is higher than a preset reference flow rate limit, dividing the parking lot into a congested area and a smooth area based on the real-time traffic flow rate; S46A3: Determine whether the recommended parking space is located in the congested area; S46A4: If yes, calculating the congestion probability of the congested area within a preset time period based on the congested area and the real-time traffic volume; S46A5: If the congestion probability exceeds a preset probability value, selecting the preferred location that meets the carbon emission standard in the unobstructed area and selecting it as a candidate parking space; S46A6: Calculating a traffic flow selection reference value for the candidate parking space based on the carbon emission difference of the candidate parking space and the real-time traffic flow in the unobstructed area; S46A7: Select the candidate parking space with the lowest traffic flow selection reference value to update the recommended parking space; S46A8: If the candidate parking space is not available in the unobstructed area, maintaining the recommended parking space unchanged and outputting a preset congestion warning prompt; S46A9: If not, keep the recommended parking position unchanged.

6. The low-carbon parking guidance method based on user behavior according to claim 5, characterized in that: Generating voice broadcast information based on the scheduling route and the parking route, and transmitting the voice broadcast information to the voice broadcast system includes: S81: Generate an intelligent parking path based on the parking route and the scheduling route; S82: Monitor the intelligent parking path in real time and determine whether there is any abnormality in the intelligent parking path; S83: If not, continue testing; S84: If yes, retrieve the abnormal position based on the intelligent stop path; S85: Generate a new intelligent stop path based on the abnormal location, the user location, and the current location, and define it as an intelligent stop optimization path; S86: Sort the intelligent parking optimization paths from small to large as the optimization distance priority, use the intelligent parking optimization path ranked first in the optimization distance priority as the new intelligent parking path, send the new intelligent parking path to the preset intelligent parking robot and control its execution.

7. The low-carbon parking guidance method based on user behavior according to claim 6, characterized in that: Generating voice broadcast information based on the scheduling route and the parking route, and transmitting the voice broadcast information to the voice broadcast system includes: S87: Determine in real time whether the recommended parking space is occupied; S88: If it is occupied, the preferred position other than the recommended parking space and not reserved is used as a parking space to be dispatched; S89: Calculate the distance between the user's location and the parking space to be scheduled and use it as the adjustment distance; S8A: generating a parking dispatch value based on the parking space to be dispatched, the congested area, and the unobstructed area; S8B: Calculating a distance comprehensive weight value based on the adjustment distance, the smooth parking scheduling value, and a preset distance comprehensive weight coefficient; S8C: Sort the distance comprehensive weight values ​​in descending order, use the to-be-scheduled parking space corresponding to the first one in the sort as a new low-carbon parking space, use the new low-carbon parking space as the parking destination, and output a path replanning instruction; S8D: If the parking space is not occupied, continue to use the recommended parking space.

8. The low-carbon parking guidance method based on user behavior according to claim 6, characterized in that: The intelligent parking robot corresponding to the dispatch number moves as follows: S861: Calculate the distance between the user position and the current position as the guidance distance; S862: Determine whether the guidance distance exceeds a preset guidance distance value; S863: If exceeded, generating a guidance correction distance based on the current working state and the guidance distance; S864: Adjust the dispatch number based on the guidance correction distance, the current position, and the working status and use it as the dispatch correction number; S865: Outputting the guidance correction distance to the intelligent parking robot corresponding to the scheduling correction number to control movement; S866: If not exceeded, continue moving.

9. The low-carbon parking guidance method based on user behavior according to claim 8, characterized in that: When the user arrives at the recommended parking spot, the following steps are performed: S8661: Collect the berth weight information of the current parking space; S8662: Retrieve the vehicle base weight value from the vehicle type; S8663: When the parking space weight information does not meet the vehicle reference weight value, collecting adjacent weight information of adjacent parking spaces; S8664: Determine whether the adjacent weight information has abnormal changes; S8665: If the adjacent weight information changes abnormally, generating deviation weight information based on the adjacent weight information; S8666: Determine a deviation angle and a deviation distance based on the deviation weight information; S8667: Generate a deviation behavior suggestion based on the deviation angle and the deviation distance and send the suggestion to the intelligent parking robot corresponding to the dispatch number; S8668: If the adjacent weight information does not change abnormally, determine a weight surge based on the berth weight information; S8669: Determine a low-carbon parking suggestion based on the weight surge and send it to the intelligent parking robot corresponding to the dispatch number.

10. A low-carbon parking guidance and management system based on user behavior, characterized in that: include: Acquisition module, used to obtain parking instructions, weight status, current position and current working status; A memory for storing a program for a low-carbon parking guidance method based on user behavior according to any one of claims 1 to 9; The processor can load and execute the program in the memory.

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