Method for analyzing supply-demand relation in real time and automatically adjusting online car-hailing order dispatching radius

Abstract

The invention discloses a method for analyzing a supply-demand relationship in real time and automatically adjusting an online car-hailing order-dispatching radius, which relates to the field of dynamic dispatching of vehicles and comprises the following steps of: 1, acquiring current longitude and latitude information of a passenger in real time through GPS functions of a mobile passenger terminal and a driver terminal, and updating current longitude and latitude information of a driver; urbans and business districts are divided through a tenant saas platform, and minimum and maximum dispatching basic radiuses are allowed in a specific fence configuration business district area. The longitude and latitude information of passengers and drivers is obtained in real time through the GPS function of the mobile passenger and driver terminal, tenants are allowed to divide a city into different business districts according to the longitude and latitude, the area and the traffic condition of the city, the regular hexagon honeycomb is adopted for region division, the whole region is effectively covered, and the service life of the city is prolonged. The supply-demand relationship is effectively balanced through a supply-demand ratio parameter dynamic adjustment mechanism, the distance between the passenger and the driver is calculated by using a Harvern formula, whether the passenger is within the current order dispatching radius is accurately judged, and time and distance waste between the passenger and the driver is reduced.

Description

Technical Field

[0001] The present invention relates to the field of dynamic vehicle scheduling, and in particular to a method for automatically adjusting the dispatch radius of online ride-hailing vehicles by analyzing supply and demand relationships in real time. Background Art

[0002] With the advancement of technology and the widespread adoption of mobile internet, the online ride-hailing industry has experienced rapid growth over the past decade. Consumer demand for transportation is increasing, especially amidst the accelerating pace of urbanization and lifestyles. Online ride-hailing has become a crucial option for daily commutes. However, as the market continues to expand, an imbalance between supply and demand has gradually emerged. Especially during peak hours and in specific areas, passenger demand surges, while the number of available drivers may not be able to keep pace. This results in supply and demand being significantly impacted by external factors, and setting a fixed dispatch radius based on a city is no longer suitable for complex supply and demand scenarios. For example, temporary events such as severe weather and major events can create a supply shortage in certain areas within a certain time and space. Temporary road controls and designated no-order zones can also create a supply surplus within a certain time and space.

[0003] The dispatch radius refers to the maximum distance drivers are considered when assigning orders after receiving a passenger's order. As a key parameter in the dispatch process, it directly affects drivers' order acceptance efficiency and passenger wait times. If the radius is set too small, there may be a shortage of available drivers in high-demand areas, and passengers will have to wait longer for a match. On the other hand, if the radius is set too large, while it can increase the number of available drivers, it may also cause drivers to travel longer distances after accepting orders, increasing their idle time and reducing their enthusiasm for accepting orders. Therefore, it is particularly important to adjust the dispatch radius in real time.

[0004] Existing technologies have the following shortcomings: Existing ride-hailing dispatching technology relies on predictive models based on past data and may not be able to adapt to the ever-changing market environment. In reality, supply and demand are affected by multiple variables. Relying solely on past data for predictions fails to capture unexpected factors in a timely manner, leading to deviations in the prediction results. This not only affects the accuracy of supply and demand matching, but may also lead to longer waiting times for passengers and increased difficulty for drivers to accept orders. In the scenario of a multi-tenant aggregation platform, the needs and operating strategies of each tenant often vary significantly. This diversity makes it impossible for a simple, unified dispatching strategy to meet the personalized needs of all tenants. Sudden changes in supply and demand cannot be quickly responded to through real-time analysis of driver and passenger location information, order volume, driver status, and passenger feedback.

[0005] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not form the prior art that is already known to a person of ordinary skill in the art. Summary of the Invention

[0006] The purpose of the present invention is to provide a method for automatically adjusting the dispatch radius of online car-hailing orders by analyzing the supply and demand relationship in real time, so as to solve the problems in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a method for automatically adjusting the dispatch radius of online ride-hailing services by analyzing supply and demand relationships in real time, comprising the following steps:

[0008] Step 1: Use the GPS function of the mobile passenger terminal and the driver terminal to obtain the passenger's current latitude and longitude information in real time and update the driver's current latitude and longitude information. Use the tenant's SaaS platform to divide the city, business district, and specific fences to configure the minimum and maximum dispatch radius within the business district;

[0009] Step 2: Based on the longitude and latitude information, area information, and plane coordinate system of the tenant's city, a regular hexagonal honeycomb is generated outward to match the boundaries of the operating area. The passenger's current longitude and latitude information and the timestamp of the ride request are fed back to the tenant's SaaS platform via the mobile passenger terminal to calculate the supply-demand ratio parameters.

[0010] Step 3: Use a spatial index algorithm to match the latitude and longitude of the city where the passenger's ride request originated to the regular hexagonal honeycomb. Query the real-time supply and demand status of the area in the regular hexagonal honeycomb corresponding to the current new order. Calculate and adjust the dispatch radius suitable for the passenger's ride request in real time.

[0011] Step 4: Passenger’s current latitude and longitude information Convert it to radians and use the Haversine formula to determine whether the passenger is within the current dispatch radius.

[0012] Preferably, the current latitude and longitude information of the passenger is obtained in real time through the GPS function of the mobile passenger terminal. Whenever the passenger initiates a taxi request, the current latitude and longitude information of the passenger and the timestamp of the taxi request are updated and recorded. The current latitude and longitude information of the driver is updated in real time through the GPS function of the driver terminal, and the driver's current available status is updated and recorded as "online", "accepting orders" and "offline". The tenant SaaS platform allows tenants to use the latitude and longitude information, area information and boundary positioning of the tenant's city, and divide the tenant's city into different business districts according to the business characteristics and traffic conditions of the business district. Connecting to the geographic information system API allows tenants to automatically load regional maps and mark the regional boundaries of cities and business districts by selecting cities and business districts, set fences as polygons of the business district area boundaries, and interact with business district areas according to the tenant's location. The driver's current available status is combined with the driver's current latitude and longitude information to analyze the driver's availability in different business districts. The tenant SaaS platform configures the minimum dispatch base radius allowed in the business district area to be 0.5 kilometers, and the maximum dispatch base radius allowed in the business district area to be 5 kilometers.

[0013] Preferably, the city where the tenant is located is preset as the operating area, connected to the geographic information system API, and the latitude and longitude information, area information, and boundary positioning of the tenant's city are converted into a plane coordinate system. The hexagonal center point is extracted based on the center of the plane coordinate system, and a regular hexagonal honeycomb is generated outward to match the boundary of the operating area and the part exceeding the boundary is filtered out. The radius of each regular hexagonal honeycomb is set to 2.5 kilometers. The number of drivers who are in the "online" state and have no service orders to be served is obtained in real time through the GPS function and available status update of the driver terminal. The passenger's current latitude and longitude information and the timestamp of the ride request are fed back to the tenant's SaaS platform through the mobile passenger terminal to calculate the supply and demand ratio parameter. The specific formula is:

[0014]

[0015] Among them, R represents the supply-demand ratio parameter, D represents the passenger demand in the current regular hexagonal honeycomb, and A represents the number of online drivers who meet the "online" status and have no pending service orders. The supply-demand ratio of each regular hexagonal honeycomb is marked on the map.

[0016] Preferably, the latitude and longitude information of the city where the passenger initiates the ride request is extracted, and the regular hexagonal honeycomb to which the latitude and longitude information of the city where the passenger initiates the ride request belongs is matched through a spatial index algorithm, and the unique identifier of the regular hexagonal honeycomb is recorded. The real-time supply and demand status of the area of the regular hexagonal honeycomb corresponding to the current new order is queried through the tenant SaaS platform backend API interface, and the dispatch radius suitable for the passenger to initiate the ride request is calculated in real time based on the real-time supply and demand status and the radius configured by the tenant SaaS platform. The specific formula is:

[0017]

[0018] Among them, R dynamic R represents the dispatch radius suitable for passengers to initiate ride requests. initial Indicates the basic radius based on the tenant SaaS platform configuration, N request represents the number of passengers who initiate ride requests, D factor It represents the impact factor of the urgency of passenger demand on the dispatch radius. The dispatch radius is adjusted in real time according to the supply-demand ratio parameter. When R dynamic <R, it means that the demand is greater than the number of online drivers who meet the "online" status and have no orders to be served. The dispatch radius is reduced to increase the success rate of each driver's order acceptance. When R dynamic >R, it means that the number of online drivers who meet the "online" status and have no orders to be served is greater than the demand, and the dispatch radius is expanded to meet the order demand of each driver. When R dynamic =R, maintain the current dispatch radius.

[0019] Preferably, the passenger's current latitude and longitude information is Convert it to radians and use the Haversing formula to determine whether the passenger is within the current dispatch radius. The specific formula is:

[0020]

[0021] d=r*C

[0022] Among them, S represents the intermediate variable of the Haversine formula, lat1 and lat2 represent the latitude of the current location of the passenger and the driver respectively, lon1 and lon2 represent the longitude of the current location of the passenger and the driver respectively, C represents the central angle between the current location of the passenger and the driver, d represents the distance between the current location of the passenger and the driver, r represents the radius of the earth, when d is less than R dynamic , it is determined that the passenger is within the current dispatch radius.

[0023] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0024] Through the GPS function of mobile passenger and driver terminals, the longitude and latitude information of passengers and drivers can be obtained in real time. This real-time update mechanism ensures that when a passenger initiates a ride request, his or her current location and request timestamp are immediately recorded. At the same time, the driver's status ("online", "accepting orders", "offline") will also be updated in real time. This high-frequency data update enables dispatch to respond quickly to market demand and improves the passengers' ride-hailing experience. Through the tenant SaaS platform, tenants are allowed to divide the city into different business districts based on the city's longitude and latitude, area and traffic conditions. After connecting to the GIS API, tenants can automatically load regional maps and mark the boundaries of business districts. This business district division not only takes into account business characteristics, but also helps dispatchers better understand the supply and demand situation in each region, thereby optimizing resource allocation. In the operating area, the use of regular hexagonal honeycombs for regional division can more effectively cover the entire area and ensure refined management of passenger needs. The dynamic adjustment mechanism of the supply and demand ratio parameters can effectively balance the supply and demand relationship and improve overall service efficiency. The Haversing formula is used to calculate the distance between the two, accurately judging whether the passenger is within the current dispatch radius, reducing the time and distance waste between passengers and drivers, and improving service quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction to the drawings required for use in the embodiments will be given below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0026] Figure 1 This is a flow chart of a method for automatically adjusting the dispatch radius of online ride-hailing services by analyzing supply and demand relationships in real time according to the present invention. DETAILED DESCRIPTION

[0027] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these example embodiments are provided so that the description of this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art.

[0028] The present invention provides Figure 1 A method for automatically adjusting the radius of online ride-hailing orders by analyzing supply and demand in real time is shown, specifically comprising the following steps:

[0029] Step 1: Use the GPS function of the mobile passenger terminal and the driver terminal to obtain the passenger's current latitude and longitude information in real time and update the driver's current latitude and longitude information. Use the tenant's SaaS platform to divide the city, business district, and specific fences to configure the minimum and maximum dispatch radius within the business district;

[0030] The GPS function of the mobile passenger terminal is used to obtain the passenger's current latitude and longitude information in real time. Whenever a passenger initiates a ride request, the passenger's current latitude and longitude information and the timestamp of the ride request are updated and recorded. The driver's current latitude and longitude information is updated in real time through the GPS function of the driver's terminal, and the driver's current availability status is updated and recorded as "online", "accepting orders" and "offline". The tenant SaaS platform allows tenants to use the latitude and longitude information, area information and boundary positioning of the tenant's city, and divide the tenant's city into different business districts based on the business characteristics and traffic conditions of the business district. Connecting to the geographic information system API allows tenants to automatically load regional maps and mark the regional boundaries of cities and business districts by selecting cities and business districts, set fences as polygons of the business district area boundaries, and interact with business district areas based on the tenant's location. The driver's current availability status is combined with the driver's current latitude and longitude information to analyze the driver's availability in different business districts. The tenant SaaS platform configures the minimum dispatch base radius allowed in the business district to be 0.5 kilometers, and the maximum dispatch base radius allowed in the business district to be 5 kilometers.

[0031] Step 2: Based on the longitude and latitude information, area information, and plane coordinate system of the tenant's city, a regular hexagonal honeycomb is generated outward to match the boundaries of the operating area. The passenger's current longitude and latitude information and the timestamp of the ride request are fed back to the tenant's SaaS platform via the mobile passenger terminal to calculate the supply-demand ratio parameters.

[0032] The tenant's city is preset as the operating area to ensure that each area can effectively serve the surrounding passengers and drivers. The geographic information system API is connected to convert the longitude and latitude information, area information, and boundary positioning of the tenant's city into a plane coordinate system. The center point of the hexagon is extracted based on the center of the plane coordinate system. The hexagonal honeycomb is extended outward to generate a regular hexagonal honeycomb that matches the boundary of the operating area and the part outside the boundary is filtered out. The radius of each regular hexagonal honeycomb is set to 2.5 kilometers. The GPS function and availability status update of the driver terminal are used to obtain the number of drivers who are in the "online" state and have no service orders in real time. The passenger's current longitude and latitude information and the timestamp of the ride request are fed back to the tenant's SaaS platform through the mobile passenger terminal to calculate the supply and demand ratio parameter. The specific formula is:

[0033]

[0034] Among them, R represents the supply-demand ratio parameter, D represents the passenger demand in the current regular hexagonal honeycomb, and A represents the number of online drivers who meet the "online" status and have no pending service orders. By marking the supply-demand ratio of each regular hexagonal honeycomb on the map, dispatchers can quickly understand the supply and demand situation in different areas.

[0035] Step 3: Use a spatial index algorithm to match the latitude and longitude of the city where the passenger's ride request originated to the regular hexagonal honeycomb. Query the real-time supply and demand status of the area in the regular hexagonal honeycomb corresponding to the current new order. Calculate and adjust the dispatch radius suitable for the passenger's ride request in real time.

[0036] Extract the longitude and latitude information of the city where the passenger's ride request is received. Use the spatial index algorithm to match the longitude and latitude information of the city where the passenger's ride request is received to the regular hexagonal honeycomb. Record the unique identifier of the regular hexagonal honeycomb. Query the real-time supply and demand status of the regular hexagonal honeycomb area corresponding to the current new order through the tenant's SaaS platform backend API interface. Calculate the dispatch radius suitable for the passenger's ride request in real time based on the real-time supply and demand status and the radius configured on the tenant's SaaS platform. The specific formula is:

[0037]

[0038] Among them, R dynamic R represents the dispatch radius suitable for passengers to initiate ride requests. initial Indicates the basic radius based on the tenant SaaS platform configuration, N request represents the number of passengers who initiate ride requests, D factor It represents the impact factor of the urgency of passenger demand on the dispatch radius. The dispatch radius is adjusted in real time according to the supply-demand ratio parameter. When R dynamic <R, it means that the demand is greater than the number of online drivers who meet the "online" status and have no orders to be served. The dispatch radius is reduced to increase the success rate of each driver's order acceptance. When R dynamic >R, it means that the number of online drivers who meet the "online" status and have no orders to be served is greater than the demand, and the dispatch radius is expanded to meet the order demand of each driver. When R dynamic =R, maintain the current dispatch radius.

[0039] Step 4: Passenger’s current latitude and longitude information Convert the result to radians and use the Haversing formula to determine whether the passenger is within the current dispatch radius.

[0040] The passenger's current latitude and longitude information is based on Convert it to radians and use the Haversing formula to determine whether the passenger is within the current dispatch radius. The specific formula is:

[0041]

[0042] d=r*C

[0043] Among them, S represents the intermediate variable of the Haversine formula, lat1 and lat2 represent the latitude of the current location of the passenger and the driver respectively, lon1 and lon2 represent the longitude of the current location of the passenger and the driver respectively, C represents the central angle between the current location of the passenger and the driver, d represents the distance between the current location of the passenger and the driver, r represents the radius of the earth, when d is less than R dynamic , it is determined that the passenger is within the current dispatch radius.

[0044] Example 1: A method for automatically adjusting the radius of online ride-hailing orders by analyzing supply and demand in real time in this embodiment includes the following specific steps:

[0045] Step 1: Use the GPS function of the mobile passenger terminal and the driver terminal to obtain the passenger's current latitude and longitude information in real time and update the driver's current latitude and longitude information. Use the tenant's SaaS platform to divide the city, business district, and specific fences to configure the minimum and maximum dispatch radius within the business district;

[0046] Step 2: Based on the longitude and latitude information, area information, and plane coordinate system of the tenant's city, a regular hexagonal honeycomb is generated outward to match the boundaries of the operating area. The passenger's current longitude and latitude information and the timestamp of the ride request are fed back to the tenant's SaaS platform via the mobile passenger terminal to calculate the supply-demand ratio parameters.

[0047] Step 3: Use a spatial index algorithm to match the latitude and longitude of the city where the passenger's ride request originated to the regular hexagonal honeycomb. Query the real-time supply and demand status of the area in the regular hexagonal honeycomb corresponding to the current new order. Calculate and adjust the dispatch radius suitable for the passenger's ride request in real time.

[0048] Step 4: Passenger’s current latitude and longitude information Convert it to radians and use the Haversine formula to determine whether the passenger is within the current dispatch radius.

[0049] Step one achieves precise location tracking and status updates by acquiring GPS information from mobile passenger and driver terminals in real time, significantly improving the response efficiency of the ride-hailing service. When a passenger initiates a ride request, the passenger's latitude and longitude, as well as the request timestamp, are immediately recorded, providing essential data for subsequent dispatch decisions. Driver status ("online," "accepting orders," "offline") is also updated in real time, ensuring the system accurately reflects driver availability. The tenant SaaS platform supports intelligent segmentation of cities and business districts. Integrating a Geographic Information System (GIS) API, tenants can easily load regional maps and annotate business district boundaries. This not only takes into account the commercial characteristics and traffic conditions of a business district, but also dynamically set the minimum (0.5 km) and maximum (5 km) dispatch radius within the business district, ensuring flexible and adaptable dispatch strategies. By analyzing driver availability in different business districts, resource allocation is optimized, improving driver acceptance success rates and the ride-hailing experience for passengers. Real-time location and status analysis enables dispatchers to make quick decisions to meet passengers' immediate needs, ultimately effectively matching supply and demand and enhancing overall service efficiency and reliability.

[0050] Step two significantly improves the accuracy and efficiency of ride-hailing services by converting the longitude, latitude, area, and boundary information of the tenant's city into a planar coordinate system to generate a regular hexagonal cell corresponding to the operating area. The radius of each hexagonal cell is set to 2.5 kilometers to ensure adequate coverage of the surrounding area. The supply-demand ratio calculation formula clearly defines the relationship between passenger demand and the number of available drivers, allowing dispatchers to intuitively understand the supply and demand situation within each cell. Real-time feedback enables dispatching decisions to rapidly respond to market changes. Using a geographic information system API, the supply-demand ratio of each hexagonal cell is plotted on a map, helping dispatchers quickly identify areas of supply and demand imbalance. This visual display improves dispatcher efficiency and enhances overall control over the operating area. By efficiently matching passenger demand with driver supply, the user experience is enhanced, resource allocation is optimized, and service flexibility and responsiveness are increased.

[0051] Step three uses a spatial indexing algorithm to precisely match passenger ride requests to corresponding hexagonal honeycombs, significantly improving efficiency and response speed. Relying on the longitude and latitude of the passenger's ride request, the system quickly identifies the hexagonal honeycomb in which the passenger is located, enabling rapid identification of the passenger's needs. The system then queries the real-time supply and demand status of the hexagonal honeycomb through the tenant's SaaS platform backend API, enabling rapid assessment of the order situation in that area. During the dispatch radius adjustment process, the system dynamically responds to market conditions based on supply-demand ratio parameters. For example, if the system detects that demand exceeds supply, it automatically reduces the dispatch radius to increase each driver's success rate; conversely, it expands the dispatch radius to meet a wider range of demand. By achieving a supply-demand balance within the dispatch radius adjustment strategy, the system avoids the problems of extended passenger wait times and increased driver idleness caused by insufficient supply.

[0052] In step 4, by converting the passenger's longitude and latitude information into radians and applying the Haversine formula, the system can efficiently determine whether the passenger is within the set dispatch radius, improving the accuracy and real-time performance of dispatch. By comparing with the current dispatch radius, it can quickly determine whether the passenger is within the range of available orders. When the calculated distance is less than the set dispatch radius R, the passenger is considered to be within the service range. Especially during high-demand periods, potential serviceable passengers can be quickly identified, thereby improving the driver's acceptance rate and passenger satisfaction.

[0053] Example 2: A method for automatically adjusting the dispatch radius of online ride-hailing services by analyzing supply and demand in real time in this embodiment includes the following specific steps:

[0054] The passenger's current latitude and longitude, obtained in real time through the GPS function of the mobile passenger terminal, are 39.9042°N, 116.4074°E. The timestamp of the ride request is 2024-09-24 08:50:21. The driver's current latitude and longitude are 39.9087°N, 116.3975°E, and their availability status is "Online." The area of the current tenant's city is set to 100 square kilometers. Based on the commercial characteristics and transportation conditions of each business district, the tenant's city is divided into business districts A and B. The radius of business district A is 1 kilometer, and the radius of business district B is 2 kilometers. If the current passenger demand in the regular hexagonal honeycomb is 10, and the number of online drivers who meet the "online" status and have no pending service orders is 5, then the current supply-demand ratio parameter is 2, and the urgency factor of passenger demand is defined as 0.5. The current dispatch radius is 6 kilometers. Since it is larger than the maximum dispatch radius of 5 kilometers, the system sets the dispatch radius to 5 kilometers. After converting the passenger and driver positions into radians, the distance between the current position of the passenger who initiates the ride request and the current position of the driver is 4 kilometers. Since it is smaller than R dynamic , determine whether the passenger is within the current dispatch radius.

[0055] The above description is merely illustrative of certain exemplary embodiments of the present invention. It goes without saying that those skilled in the art will be able to modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and description are illustrative in nature and should not be construed as limiting the scope of protection of the claims.

Claims

1. A method for automatically adjusting the dispatch radius of online ride-hailing services by analyzing supply and demand in real time, characterized by: The following steps are involved: Step 1: Use the GPS function of the mobile passenger terminal and the driver terminal to obtain the passenger's current latitude and longitude information in real time and update the driver's current latitude and longitude information. Use the tenant's SaaS platform to divide the city, business district, and specific fences to configure the minimum and maximum dispatch radius within the business district; Step 2: Based on the longitude and latitude information, area information, and plane coordinate system of the tenant's city, a regular hexagonal honeycomb is generated outward to match the boundaries of the operating area. The passenger's current longitude and latitude information and the timestamp of the ride request are fed back to the tenant's SaaS platform via the mobile passenger terminal to calculate the supply-demand ratio parameters. Step 3: Use a spatial index algorithm to match the latitude and longitude of the city where the passenger's ride request originated to the regular hexagonal honeycomb. Query the real-time supply and demand status of the area in the regular hexagonal honeycomb corresponding to the current new order. Calculate and adjust the dispatch radius suitable for the passenger's ride request in real time. Step 4: Passenger’s current latitude and longitude information Convert it to radians and use the Haversine formula to determine whether the passenger is within the current dispatch radius.

2. The method of automatically adjusting the dispatch radius of online ride-hailing services by analyzing supply and demand in real time according to claim 1, characterized in that: In step 1, the passenger's current latitude and longitude information is obtained in real time through the GPS function of the mobile passenger terminal. Whenever the passenger initiates a taxi request, the passenger's current latitude and longitude information and the timestamp of the taxi request are updated and recorded. The driver's current latitude and longitude information is updated in real time through the GPS function of the driver's terminal, and the driver's current availability status is updated and recorded as "online", "accepting orders", and "offline". The tenant's SaaS platform allows the tenant to use the latitude and longitude information, area information, and boundary positioning of the tenant's city, and divide the tenant's city into different business districts based on the business characteristics and traffic conditions of the business district. Connecting to the geographic information system API allows the tenant to automatically load a regional map and mark the regional boundaries of the city and business district by selecting a city and business district, set the fence as a polygon of the business district area boundary, and interact with the business district area based on the tenant's location. The driver's current availability status is combined with the driver's current latitude and longitude information to analyze the driver's availability in different business districts. The tenant's SaaS platform configures the minimum dispatch base radius allowed in the business district area to be 0.5 kilometers and the maximum dispatch base radius allowed in the business district area to be 5 kilometers.

3. The method of automatically adjusting the dispatch radius of online ride-hailing services by analyzing supply and demand in real time according to claim 1, characterized in that: In the second step, the city where the tenant is located is preset as the operating area, and the geographic information system API is connected. The latitude and longitude information, area information and boundary positioning of the city where the tenant is located are converted into a plane coordinate system, and the hexagonal center point is extracted based on the center of the plane coordinate system. The regular hexagonal honeycomb that conforms to the boundary of the operating area is extended outward and the part beyond the boundary is filtered out. The number of drivers who are in the "online" state and have no pending service orders is obtained in real time through the GPS function and available status update of the driver terminal, and the current latitude and longitude information of the passenger and the timestamp of the ride request are fed back to the tenant SaaS platform through the mobile passenger terminal to calculate the supply and demand ratio parameters, and the supply and demand ratio of each regular hexagonal honeycomb is marked on the map.

4. The method of automatically adjusting the dispatch radius of online ride-hailing services by analyzing supply and demand in real time according to claim 3, characterized in that: The specific formula for calculating the supply-demand ratio parameter is: Among them, R represents the supply-demand ratio parameter, D represents the current passenger demand in the regular hexagonal honeycomb, and A represents the number of online drivers who meet the "online" status and have no pending service orders.

5. The method of automatically adjusting the dispatch radius of online ride-hailing services by analyzing supply and demand in real time according to claim 1, characterized in that: In the step three, the latitude and longitude information of the city where the passenger initiates the ride request is extracted, the regular hexagonal honeycomb to which the latitude and longitude information of the city where the passenger initiates the ride request belongs is matched through the spatial index algorithm, and the unique identifier of the regular hexagonal honeycomb is recorded, and the real-time supply and demand status of the area of the regular hexagonal honeycomb corresponding to the current new order is queried through the tenant SaaS platform back-end API interface, and the dispatch radius suitable for the passenger to initiate the ride request is calculated in real time based on the real-time supply and demand status and the radius configured by the tenant SaaS platform, and the dispatch radius is adjusted in real time based on the supply and demand ratio parameter.

6. The method of automatically adjusting the dispatch radius of online ride-hailing services by analyzing supply and demand in real time according to claim 5, characterized in that: The specific formula for calculating the dispatch radius suitable for a passenger to initiate a ride request is: Among them, R dynamic R represents the dispatch radius suitable for passengers to initiate ride requests. initial Indicates the basic radius based on the tenant SaaS platform configuration, N request represents the number of passengers who initiate ride requests, D factor Indicates the factor that affects the dispatch radius due to the urgency of passenger demand.

7. The method of claim 1 for automatically adjusting the dispatch radius of online ride-hailing services by analyzing supply and demand in real time, characterized in that: In the fourth step, the passenger's current latitude and longitude information is calculated based on the Convert it to radians and use the Haversine formula to determine whether the passenger is within the current dispatch radius.

8. The method of automatically adjusting the dispatch radius of online ride-hailing services by analyzing supply and demand in real time according to claim 7, characterized in that: The specific formula of the Haversine formula is: d=r*C Where S represents the intermediate variable of the Haversian formula, lat1 and lat2 represent the latitudes of the current locations of the passenger and the driver, respectively; lon1 and lon2 represent the longitudes of the current locations of the passenger and the driver, respectively; C represents the central angle between the current locations of the passenger and the driver, d represents the distance between the current locations of the passenger and the driver, and r represents the radius of the Earth.

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