Online car-hailing real-time mileage calibration method and system based on path planning

Abstract

The invention discloses an online car-hailing real-time mileage calibration method and system based on path planning. The invention relates to the technical field of online car hailing. And after receiving a navigation planning completion signal, storing planned path data to a database, including the coordinate points of the path, the road information and the turning points. Calculating the distance between the received positioning point and the nearest point on the current navigation path; judging whether the fault is in a fault-tolerant range or not; if so, entering the step S3; if not, entering the step S4; correcting the positioning point (finely adjusting according to the nearest point of the path); adding the corrected positioning point into the real-time track; calculating real-time mileage and cost according to the real-time track; according to the scheme, the actual driving mileage of the vehicle can be calculated more accurately by receiving, checking and correcting the positioning data uploaded by the driver end in real time and combining the path planning and optimization technology. The problem of mileage deviation caused by inaccurate positioning is effectively solved, and the accuracy and reliability of mileage calculation are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of online car-hailing, specifically to the mileage revision technology in the process of journey planning for online car-hailing, and particularly to an online car-hailing real-time mileage calibration method and system based on path planning. Background Art

[0002] In the current online car-hailing service, the core of the fare calculation lies in the calculation and update of real-time mileage, and its accuracy directly affects the fare settlement and experience satisfaction of both drivers and passengers. This process mainly relies on the geographical location information (i.e., positioning data) periodically uploaded by the driver's device, and a series of algorithms are used to process it to achieve dynamic update and final settlement of the fare. There are two calculation strategies in the current traditional technology:

[0003] (1) Real-time fare push strategy during the journey: This strategy is the currently mainstream adopted method. During the journey, at fixed time intervals, the system calculates the incremental mileage using the spatial distance between the newly uploaded positioning point by the driver's device and the previous valid positioning point. This increment is then accumulated into the total real-time mileage, and the real-time fare is dynamically adjusted accordingly. Since this method mainly relies on simple mathematical calculations, the consumption of server resources is relatively low, improving the system's response speed and processing efficiency. However, its inherent limitation is that if there are deviations in the driver's positioning data (such as positioning drift caused by unstable GPS signals), it may lead to cumulative errors in the incremental mileage, and thus the real-time fare estimate may be too high, affecting the user experience.

[0004] (2) Precise calculation method based on all positioning points: In contrast, another strategy is to analyze all the uploaded positioning points during the entire journey, and through complex algorithms for path optimization and positioning correction to obtain a more accurate real-time mileage. Although this method can significantly improve the accuracy of mileage calculation, due to the need to process a large amount of data in real time, the demand for server resources is relatively high, which may lead to an increase in system processing delay.

[0005] Regardless of the push strategy adopted during the trip, when the trip ends, the system will perform a comprehensive positioning data analysis and correction process. The aim is to review the entire trip trajectory, correct possible positioning errors, recalculate and determine the exact mileage and corresponding fees for the whole journey. Finally, this corrected fee will be pushed to the driver and the passenger as the final settlement price for the trip. However, there is a technical problem in traditional technologies: the inaccuracy of real-time fees during the trip. Especially when there are large deviations in the driver's end positioning data, the cumulative error of incremental mileage will be amplified, resulting in an inflated real-time fee. This not only harms the interests of passengers but may also cause dissatisfaction among drivers because inaccurate fee estimates may affect their income expectations and passenger trust. Therefore, the present invention proposes a real-time mileage calibration method and system for online car-hailing based on path planning. Summary of the Invention

[0006] In view of this, the present invention hopes to provide a real-time mileage calibration method and system for online car-hailing based on path planning to solve or alleviate the technical problems existing in the prior art, that is, how to solve the technical problem that when the positioning at the driver's end is inaccurate, the positioning point may drift to other places, and then the incremental mileage will be larger than the real mileage after accumulation, resulting in an inflated real-time price during the trip. The technical solution of the present invention is realized as follows:

[0007] In the first aspect, a real-time mileage calibration method for online car-hailing based on path planning:

[0008] (I) Overview:

[0009] The present invention aims to ensure that the positioning data uploaded by the driver's end can accurately reflect the actual driving trajectory of the vehicle by combining advanced navigation planning technology and real-time positioning verification mechanism. The solution first stores the planned navigation path as the benchmark for subsequent positioning verification. Then, a strict tolerance range judgment is made for each positioning point uploaded by the driver's end. For the positioning points within the range, they are corrected and accepted to calculate the real-time mileage and fees; for the abnormal positioning points outside the range, a trajectory recalculation process based on all positioning points is triggered to ensure the accuracy of mileage calculation. By continuously receiving, verifying, and correcting the positioning data and combining path optimization technology, the solution can dynamically adjust and optimize the driving trajectory, and finally provide accurate driving mileage and fee information.

[0010] (II) Technical Solution:

[0011] To achieve the above technical objectives, the present invention selects to perform the following operating steps.

[0012] 2.1 Step S1, path planning storage:

[0013] After receiving the signal indicating that the navigation plan is completed, store the planned path data in the database, including the coordinate points, road information, and turning points of the path.

[0014] 2.1.1 Step S100, Extract the planned path data:

[0015] Extract the planned path data from the navigation planning service;

[0016] Organize the starting point, ending point, and waypoints on the path into an ordered list or array;

[0017] Collect and organize the road information passed by the path, including road names, types (expressways or urban roads), and / or speed limits, etc.;

[0018] Mark the locations where turning is required on the path, including coordinates of left turns, right turns, U-turns, and turning points.

[0019] 2.1.2 Step S101, Store the data in the database:

[0020] According to the structure of the path data, insert the assembled path information into the database, including the coordinate points, road information, and turning points of the path.

[0021] 2.2 Step S2, Receive location data:

[0022] Calculate the distance between the received location point and the nearest point on the current navigation path; judge whether it is within the tolerance range; if so, enter Step S3; if not, enter Step S4.

[0023] 2.2.1 Step S200, Receive location data:

[0024] According to the order number or driver ID of the current trip, retrieve the corresponding navigation path data from the database, traverse all the coordinate points on the navigation path, and find the point closest to the received location point.

[0025] Use the geographical distance calculation formula (Haversine formula) to calculate the actual distance between the location point and the nearest path point.

[0026] 2.2.2 Step S201, Judge whether it is within the tolerance range

[0027] Based on a pre-set tolerance range threshold (such as 10 meters, 20 meters, etc.), compare the calculated distance with the tolerance range threshold to judge whether the location point is within the tolerance range.

[0028] 2.3 Step S3, Location correction and acceptance:

[0029] Correct the positioning points (fine-tune according to the nearest point on the path); add the corrected positioning points to the real-time trajectory; calculate the real-time mileage and fare based on the real-time trajectory; send the real-time mileage and fare information to both the driver and the passenger; return to step S2.

[0030] 2.3.1 Step S300, Positioning point correction:

[0031] Step-adjust the received positioning points towards the nearest path point based on longitude and latitude to make them more consistent with the actual driving trajectory.

[0032] 2.3.2 Step S301, Add to real-time trajectory

[0033] Add the corrected positioning points to the real-time trajectory of the current trip. The updated real-time trajectory data is temporarily stored in memory or a database for subsequent processing and querying.

[0034] 2.3.3 Step S302, Calculate real-time mileage and fare

[0035] Calculate the current real-time mileage based on the updated real-time trajectory; calculate the current real-time fare according to the mileage and the preset fare per kilometer, starting price, surcharge, etc.

[0036] 2.3.4 Step S303, Send real-time information

[0037] Package the calculated real-time mileage and fare information into a data packet, send it to both the driver and the passenger, and return to step S2.

[0038] 2.4 Step S4, Exception handling:

[0039] Discard the current abnormal positioning point; trigger the trajectory calculation process based on all positioning points; retrieve and load all positioning points of this trip; perform path optimization and positioning correction to calculate a more accurate real-time trajectory; recalculate the real-time mileage and fare based on the corrected trajectory; send the updated real-time mileage and fare information to both the driver and the passenger.

[0040] 2.4.1 Step S400, Discard abnormal positioning point:

[0041] Exclude this abnormal positioning point to avoid its negative impact on trajectory calculation and fare settlement;

[0042] Due to the appearance of an abnormal positioning point, trigger the trajectory recalculation process based on all positioning points;

[0043] 2.4.2 Step S401, Retrieve and load all positioning points:

[0044] Retrieve all the positioning point data of the trip since its start from the database; load the retrieved full - volume positioning point data into memory to prepare for subsequent trajectory calculation.

[0045] 2.4.3 Step S402, Path Optimization and Positioning Correction:

[0046] Apply a path optimization algorithm based on the full - volume positioning points to smooth and optimize the preliminary trajectory to make it more in line with the actual driving situation; correct each positioning point in the trajectory to ensure they match the road network and eliminate errors.

[0047] 2.4.4 Step S403, Recalculate Real - Time Mileage and Fare:

[0048] Based on the corrected trajectory, recalculate the real - time mileage of the trip; update the real - time fare of the trip according to the new mileage and fare rules; encapsulate the recalculated real - time mileage and fare information into a data packet.

[0049] 2.5 Step S5, Return:

[0050] Receive a trip end signal (such as the driver clicks the end - trip button); analyze and correct the positioning points throughout the journey to ensure the accuracy of the trajectory; recalculate and determine the exact mileage and fare of the whole journey; send the final fare information to both the driver and the passenger as the settlement basis.

[0051] (III) Mechanism for Solving Technical Problems:

[0052] 3.1 Path Planning Storage and Verification:

[0053] Before navigation starts, perform path planning and store the planned path data on the server. Receive the positioning data uploaded by the driver - side in real - time and compare and verify it with the stored path data.

[0054] Set a tolerance range (such as 10 meters) to determine whether the positioning point is within the acceptable deviation range. If the positioning point is within the tolerance range, it is considered valid for subsequent mileage calculation; if it exceeds the tolerance range, it is regarded as an abnormal positioning point.

[0055] For abnormal positioning points, they are not directly used for mileage calculation, but trigger a process of recalculating the trajectory based on the full - volume positioning points. By retrieving and loading all the positioning points of the trip, perform path optimization and positioning correction to obtain a more accurate driving trajectory and mileage. Based on the corrected positioning points and the optimized trajectory, calculate and update the driving mileage and fare in real - time. Ensure that during the trip, the calculation of mileage and fare is always based on the accurate driving trajectory to avoid over - inflation caused by inaccurate positioning.

[0056] 3.2 Path Planning as a Benchmark:

[0057] Generate an ideal driving trajectory through path planning, serving as a benchmark for subsequent positioning verification and mileage calculation. This helps identify and correct deviations and errors in positioning data. Use a tolerance range to filter out minor positioning deviations caused by environmental factors, equipment errors, etc. This helps ensure that only accurate positioning points are used for mileage calculation, reducing the accumulation of errors.

[0058] When encountering abnormal positioning points that cannot be resolved through fault tolerance processing, recalculate the trajectory of all positioning points to obtain a more accurate driving trajectory. Path optimization technology can further adjust and optimize the driving trajectory to make it closer to the actual driving situation of the vehicle.

[0059] During the journey, continuously receive and process new positioning data, and dynamically adjust mileage and fees based on the latest data. This helps ensure that the calculation of mileage and fees is always consistent with the actual driving trajectory of the vehicle, improving the accuracy and fairness of the calculation.

[0060] In the second aspect, an online car-hailing real-time mileage calibration system based on path planning:

[0061] As Figure 2 shown, this system is used to implement the online car-hailing real-time mileage calibration method described above, and it includes:

[0062] (1) User side, including:

[0063] Trip initiation module: Through this module, the user inputs the starting point and destination to initiate a trip request.

[0064] Trip tracking module: The user can view the vehicle's location, estimated arrival time, and real-time mileage information in real time.

[0065] Fee preview and payment module: The user previews the estimated fees before the trip starts, and views the actual fees and makes payments after the trip ends.

[0066] (2) Driver side, including:

[0067] Order receiving module: Receive orders dispatched by the platform in real time and view order details (including passenger information, starting point, destination, etc.).

[0068] Navigation and path planning module: Use the built-in navigation function to obtain the optimal driving route. The path planning information will serve as a benchmark for subsequent positioning verification.

[0069] Positioning data upload module: Collect the vehicle's location information in real time and upload it to the platform side for verification and processing.

[0070] Trip end and fee settlement module: Through this module, view the actual driving mileage and fees, and confirm the settlement information.

[0071] (3) Platform side, including:

[0072] Order management module: receives users' travel requests and dispatches orders to drivers based on certain algorithms and rules.

[0073] Positioning data verification and processing module: Receives the positioning data uploaded by the driver and compares it with the route planning information. Corrects valid positioning data and processes abnormal positioning points.

[0074] Mileage and cost calculation module: Based on the corrected positioning data and optimized path, the vehicle's mileage and costs are calculated and updated in real time.

[0075] Data analysis and optimization module: Analyze the collected travel data, optimize the path planning algorithm and positioning verification mechanism, and improve the overall quality and efficiency of the service.

[0076] Compared with the prior art, the present invention has the following beneficial effects:

[0077] 1. Improve the accuracy of mileage calculation: The present invention can more accurately calculate the actual mileage of the vehicle by receiving, verifying and correcting the positioning data uploaded by the driver in real time, and combining path planning and optimization technology. This effectively solves the mileage deviation problem caused by inaccurate positioning and improves the accuracy and reliability of mileage calculation.

[0078] 2. Reduce the risk of inflated fees: Since the accuracy of mileage calculation is improved in the present invention, the corresponding fee calculation is also more accurate. This avoids the situation of inflated fees due to excessive mileage, protects the rights and interests of passengers, and improves the credibility and competitiveness of online car-hailing services.

[0079] 3. Improve user experience: The accurate mileage and fee calculation of the present invention enables passengers to understand the travel expenses more clearly, reducing unnecessary disputes and complaints caused by fee disputes. At the same time, real-time mileage and fee updates also allow passengers to better understand the progress of the trip, improving the overall user experience.

[0080] 4. Promote the healthy development of the online car-hailing industry: The implementation of the present invention helps to improve the overall quality and level of online car-hailing services and enhance passengers' trust and satisfaction with the online car-hailing industry. This helps to attract more passengers to use online car-hailing services and promote the healthy development of the industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the accompanying drawings required for use in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0082] Figure 1 Schematic diagram of the method flow of the present invention;

[0083] Figure 2 Schematic diagram of the system composition of the present invention. Detailed implementation manners

[0084] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following will make a detailed description of the specific implementation manners of the present invention with reference to the accompanying drawings. Many specific details are set forth in the following description to fully understand the present invention. However, the present invention can be implemented in many other ways different from those described herein. Those skilled in the art can make similar improvements without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below;

[0085] It should be noted that the various embodiments in this specification are described in a progressive manner, and the key point of each embodiment is to illustrate the differences from other embodiments. The same or similar parts among the various embodiments can be referred to each other. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the method part.

[0086] Explanation of related terms:

[0087] (1) Coordinate points of the path, road information, and turning points: These are the path data generated after navigation planning, including the geographical locations (coordinates) of each key point on the path, the road information passed through, and the locations where turning is required.

[0088] (2) Tolerance range: It refers to the maximum deviation distance allowed between the positioning point and the navigation planned path, and is used to determine whether the positioning point is valid.

[0089] (3) Fine-tuning based on the nearest point of the path: When the positioning point deviates from the planned path but is still within the tolerance range, it is corrected by adjusting it to the nearest point on the path to ensure the accuracy of the positioning.

[0090] (4) Abnormal positioning points: These refer to the positioning points that deviate from the tolerance range of the navigation planned path, and these points may be caused by positioning errors or other reasons.

[0091] (5) Full - scale positioning points: Refers to the set of all positioning data points uploaded by the driver's end during the online car - hailing trip, including both valid and abnormal positioning points.

[0092] (6) Retrieval: The process of searching for and extracting the required data in the database, such as retrieving all the positioning point data of a certain trip.

[0093] (7) Route optimization: Adjust the original planned route according to the full - scale positioning point data to more accurately reflect the actual driving trajectory of the vehicle.

[0094] (8) Positioning correction: Correct the positioning points that deviate from the planned route or have errors to ensure the accuracy of mileage and fare calculation.

[0095] (9) Real - time mileage: The driving mileage of the vehicle that is dynamically calculated and updated based on the real - time positioning data uploaded by the driver's end.

[0096] (10) Whole - journey positioning points: Refers to the sum of all positioning points uploaded by the driver's end during the online car - hailing trip from start to end, which is used to finally determine the driving trajectory and mileage.

[0097] (11) Exact mileage: The exact distance that the online car - hailing vehicle travels after positioning correction and route optimization.

[0098] Example 1: As Figure 1 shown, this example discloses an application example of the online car - hailing real - time mileage calibration method based on route planning in online car - hailing operations. On an online car - hailing platform, after the driver takes an order, the platform will plan the optimal route for him and receive the driver's positioning data in real - time during the trip to calibrate the mileage and fare.

[0099] In this example, regarding step S1: Route planning storage:

[0100] Navigation planning completed: After the driver takes an order, the platform plans the optimal route from the starting point to the ending point for him through the navigation service.

[0101] Extract the planned route data (S100): Extract the starting point, ending point, and waypoints of the route from the navigation service and organize them into an ordered list.

[0102] Collect the road information of the route, such as name, type (high - speed road, urban road), speed limit, etc.

[0103] Mark the turning points, including left - turn, right - turn, U - turn, and specific coordinates.

[0104] Store the data in the database (S101): Create or update the trip record in the database and insert the coordinate points, road information, and turning point data of the route.

[0105] In this embodiment, regarding step S2: Receiving positioning data:

[0106] Receiving positioning data (S200): The platform continuously receives the positioning data (longitude, latitude, timestamp) uploaded by the driver terminal. According to the order number or driver ID, the corresponding path data is retrieved from the database.

[0107] Traverse the path coordinate points, use the Haversine formula to calculate the distance between the positioning point and each path point, and find the nearest point.

[0108] Determine whether it is within the tolerance range (S201): Set the tolerance range threshold (such as 10 meters). If the distance between the positioning point and the nearest path point is less than or equal to the threshold, it is considered that the positioning is accurate, and step S3 is entered. Otherwise, it is considered that the positioning is abnormal, and step S4 is entered.

[0109] In this embodiment, regarding step S3: Positioning correction and acceptance:

[0110] Positioning point correction (S300): Fine-tune the abnormal positioning point and move it closer to the nearest path point to ensure that the positioning point is more in line with the actual driving trajectory.

[0111] Add to the real-time trajectory (S301): Add the corrected positioning point to the real-time trajectory of the trip. The real-time trajectory data is stored in memory or the database for subsequent processing.

[0112] Calculate the real-time mileage and fare (S302): Based on the real-time trajectory, calculate the real-time mileage of the current trip. According to the mileage and fare rules (such as per-kilometer fare, starting price, surcharge), calculate the real-time fare.

[0113] Send real-time information (S303): Package the real-time mileage and fare information into a data packet and send it to the driver and the passenger.

[0114] Return to step S2 and continue to receive the next positioning data.

[0115] Through the positioning point correction, the problem of positioning point drift caused by inaccurate positioning at the driver terminal is reduced. The corrected positioning point is more in line with the actual driving trajectory, thus ensuring the accuracy of the mileage and fare. This helps to solve the technical problem of inflated real-time prices during the trip and improves the user experience and platform reputation.

[0116] In this embodiment, regarding step S4: Abnormal handling:

[0117] Discard the abnormal positioning point (S400): Exclude the current abnormal positioning point to avoid its negative impact on trajectory calculation and fare settlement. Trigger the full-scale trajectory recalculation process.

[0118] Retrieve and load all location points (S401): Retrieve all location point data for this trip since the start from the database. Load the data into memory to prepare for recalculating the trajectory.

[0119] Path optimization and location correction (S402): Apply a path optimization algorithm to smooth and optimize the preliminary trajectory formed by all location points. Correct each location point in the trajectory to ensure it matches the road network and eliminate errors.

[0120] Recalculate real-time mileage and fare (S403): Based on the corrected trajectory, recalculate the real-time mileage and fare of the trip. Package the updated information into a data packet and send it to the driver and the passenger.

[0121] When abnormal location data occurs, through the recalculation and optimization of the full trajectory, it can more accurately reflect the actual driving situation. This helps to solve the problems of incorrect mileage and fare calculation caused by inaccurate location, and improves the transparency of the trip and user satisfaction.

[0122] In this embodiment, regarding step S5: Return and settlement:

[0123] After the driver clicks the end trip button, the platform receives the trip end signal. Analyze and correct the location points of the entire trip to ensure the accuracy of the trajectory. Based on the corrected trajectory, recalculate and determine the exact mileage and fare of the whole journey. Send the final fare information to the driver and the passenger as the basis for settlement.

[0124] In the solution provided in this embodiment, through the implementation of the entire process, especially the application of the location correction and exception handling mechanism, the accuracy of mileage and fare calculation for online car-hailing trips can be significantly improved. This not only helps to enhance the user experience and platform reputation, but also reduces disputes and complaints caused by inaccurate location, providing strong support for the sustainable development of online car-hailing operations.

[0125] Embodiment 2: On the basis of Embodiment 1, the following is the Python execution program for the solution described in Embodiment 1:

[0126] import math

[0127] import random

[0128] import time

[0129] # Calculate the distance between two points using the Haversine formula

[0130] def haversine(lon1, lat1, lon2, lat2):

[0131] R = 6371000 # Earth radius, in meters

[0132] phi1 = math.radians(lat1)

[0133] phi2 = math.radians(lat2)

[0134] dphi = math.radians(lat2 - lat1)

[0135] dlambda = math.radians(lon2 - lon1)

[0136] a = math.sin(dphi / 2) ** 2+math.cos(phi1)*math.cos(phi2)*

[0137]

[0138]

[0139]

[0140]

[0141]

[0142] In the above program:

[0143] Route planning storage (S1): Execute route planning using the plan_route function and store the planned route data in an instance of the Database class.

[0144] Receive location data (S2): Receive location data from the driver side using the receive_location_data function. Traverse the coordinate points in the route, calculate the distance between the location point and each route point using the Haversine formula, and find the nearest point.

[0145] Location correction and acceptance (S3): If the location point is within the fault tolerance range, it is considered accurate and added to the real-time trajectory. Calculate the real-time mileage and cost based on the real-time trajectory and send them to the driver and the passenger.

[0146] Exception handling (S4): If the location point exceeds the fault tolerance range, trigger the exception handling process.

[0147] Return and settlement (S5): After the trip ends, analyze and correct the location points throughout the journey, recalculate and determine the exact mileage and cost throughout the journey, and send them to the driver and the passenger as the basis for settlement.

[0148] All of the above embodiments merely represent the implementation manners of the relevant practical applications of the present invention. The descriptions thereof are relatively specific and detailed, but should not be construed as limiting the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all fall within the protection scope of the present invention. Therefore, the protection scope of the invention patent should be subject to the appended claims.

[0149] For those skilled in the art, it can be further realized that the units and algorithm steps of each example described in combination with the embodiments disclosed in this article can be implemented by electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described according to functions in the above description. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered as exceeding the scope of the present invention.

[0150] At the same time, those skilled in the art can understand that all or part of the processes of implementing the methods of all the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to the memory, storage, database, or other media provided in this application and used in the embodiments can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

Claims

1. A real-time mileage calibration method for online car-hailing based on path planning, characterized in that Including: S1, after receiving the signal that the navigation plan is completed, store the planned path data in the database; S2, calculate the distance between the received positioning point and the nearest point on the current navigation path; Judge whether it is within the fault tolerance range; If so, enter step S3; If not, enter step S4. S3, correct the positioning point; add the corrected positioning point to the real-time trajectory; Calculate the real-time mileage and cost according to the real-time trajectory; Send the real-time mileage and cost information to both the driver and the passenger; Return to step S2; S4, discard the current abnormal positioning point; Trigger the trajectory calculation process based on all positioning points; retrieve and load all positioning points of this trip; perform path optimization and positioning correction, and send the updated real-time mileage and cost information to both the driver and the passenger; S5, after receiving the trip end signal, correct all positioning points of the whole journey and recalculate and determine the exact mileage and cost of the whole journey; send the final cost information to both the driver and the passenger as the settlement basis.

2. The real-time mileage calibration method for online car-hailing according to claim 1, characterized in that: In S1, the path data includes the coordinate points, road information and turning points of the path.

3. The real-time mileage calibration method for online car-hailing according to claim 2, wherein: The execution method of S1 includes: S100, extract the planned path data from the navigation planning service; organize the starting point, ending point and passing points on the path into an ordered list or array; collect and organize the road information passed by the path, including road names, types or / and speed limits; mark the locations that need to turn in the path, including the coordinates of left turns, right turns, U-turns and turning points. S101, according to the structure of the path data, insert the assembled path information into the database, including the coordinate points, road information and turning points of the path.

4. The real-time mileage calibration method for online car-hailing according to claim 1, wherein: The execution method of S2 includes: S200, according to the order number of the current trip or the driver ID, retrieve the corresponding navigation path data from the database, traverse all the coordinate points on the navigation path, and find the point closest to the received positioning point; use the geographical distance calculation formula to calculate the actual distance between the positioning point and the nearest path point; S201, based on the preset fault tolerance range threshold, compare the calculated distance with the fault tolerance range threshold to judge whether the positioning point is within the fault tolerance range.

5. The real-time mileage calibration method for online car-hailing according to claim 1, wherein: In S3, the correction is adjusted according to the nearest point of the path.

6. The real-time mileage calibration method for online car-hailing according to claim 5, wherein: The execution method of S3 includes: S300, step-adjust the received positioning point towards the nearest path point with longitude and latitude as the flood control; S301, add the corrected positioning point to the real-time trajectory of the current trip, and temporarily store the updated real-time trajectory data in the memory or database; S302, calculate the current real-time mileage based on the updated real-time trajectory; calculate the current real-time cost according to the mileage and the preset cost per kilometer, starting price and surcharge; S303, encapsulate the calculated real-time mileage and cost information into a data packet, send it to both the driver and the passenger and return to S2.

7. The real-time mileage calibration method for online car-hailing according to claim 1, wherein: In S4, perform path optimization and positioning correction, calculate a relatively accurate real-time trajectory compared to before; recalculate the real-time mileage and cost according to the corrected trajectory.

8. The real-time mileage calibration method for online car-hailing according to claim 7, characterized in that: The execution method of S4 includes: S400, exclude abnormal positioning points; trigger the trajectory recalculation process based on all positioning points; S401. Retrieve all the positioning point data of the trip since its start from the database; load the retrieved full amount of positioning point data into memory; S402. Based on the full amount of positioning points, apply a path optimization algorithm to smooth and optimize the preliminary trajectory; correct each positioning point in the trajectory; S403. Based on the corrected trajectory, recalculate the real-time mileage of the trip; update the real-time cost of the trip according to the new mileage and cost rules.

9. A system for implementing the real-time mileage calibration method of an online car-hailing service according to any one of claims 1 to 8, characterized in that, The system includes: The user side, including: A trip initiation module: Input the starting point and the destination to initiate a trip request; A trip tracking module: View the vehicle's position, estimated arrival time, and real-time mileage information in real time; A cost preview and payment module: Preview the estimated cost before the trip starts, and view the actual cost and make a payment after the trip ends; The driver side, including: An order receiving module: Receive the orders dispatched by the platform in real time and view the order details; A navigation and path planning module: Use the built-in navigation function to obtain the optimal driving route; A positioning data upload module: Collect the vehicle's position information in real time and upload it to the platform side for verification and processing.

10. The system according to claim 9, characterized in that, It also includes the platform side, including: An order management module: Receive the user's trip request and dispatch orders to drivers according to the algorithm; A positioning data verification and processing module: Receive the positioning data uploaded by the driver side, compare and verify it with the path planning information; correct the valid positioning data and process the abnormal positioning points; A mileage and cost calculation module: Based on the corrected positioning data and the optimized path, calculate and update the vehicle's driving mileage and cost in real time.

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