A method and device for reminding of a late arrival of a network car order

Abstract

Embodiments of the present application provide a method and device for reminding a driver of a late arrival of a ride-hailing order, the method comprising: obtaining heartbeat data of a driver terminal ID; if there is a to-be-served order, calculating a driving distance and a driving time of a shortest driving route of a next to-be-served order; calculating a fault tolerance time of a region to which a location of the driver terminal ID belongs according to historical order data of the region; generating a late arrival reminding rule according to the fault tolerance time of the region to which the location of the driver terminal ID belongs, the driving distance and the driving time of the shortest driving route of the next to-be-served order of the driver terminal ID, and reminding the driver terminal ID according to the late arrival reminding rule. In this way, the driver late arrival reminding strategy is optimized, the risk of no car arriving at the scene due to the driver's late arrival of a reservation order can be more intelligently and accurately judged, the complaint rate is reduced, and the experience of the driver on the late arrival reminding strategy is improved.

Description

Technical Field

[0001] This invention generally relates to the Internet field, and more specifically, to a method and device for providing late arrival reminders for ride-hailing orders. Background Technology

[0002] Ride-hailing orders are mainly divided into two types: on-demand rides and pre-booked rides. Pre-booked rides include higher-value orders such as regular reservations, airport pick-up / drop-off reservations, and users can place pre-booked ride orders up to 7 days in advance. The passenger complaint rate for pre-booked rides has consistently been high. The core issues raised by pre-booked ride passenger complaints mainly include:

[0003] 1) The passenger requested compensation from the platform for the airport pick-up order, as the driver was late and the passenger was unable to use the car after arriving at the reserved pick-up point.

[0004] 2) If a user misses their flight due to a driver's lateness, they may request the platform to compensate them for related expenses such as flight rescheduling fees. The compensation amount is often dozens of times higher than the order fee.

[0005] To reduce the pressure on customer service and the high compensation costs associated with the above scenarios, the platform tried a simple reminder strategy, such as sending drivers two reminder messages before the scheduled pick-up time. However, some drivers still failed to depart after receiving the two reminders, resulting in the orders being automatically canceled and reassigned, thus introducing the following problems:

[0006] 1) Since the re-dispatch time is close to the scheduled car rental time, the percentage of successful pick-ups is not high, which affects the overall order cancellation rate after dispatch on the platform and also has a negative impact on the platform's transportation capacity in the channel-side order dispatch decision-making process.

[0007] 2) A significant percentage of drivers whose orders were cancelled called in to complain that their orders were automatically cancelled. After customer service manually verified the driver's location and other information, it was confirmed that the driver had actually arrived near the pick-up point in advance and could pick up the passenger in time. However, because the driver wanted to continue listening to orders (once the driver has set off to pick up a passenger, they can no longer listen to orders), they did not set off for the reserved order. This caused the reminder policy to misjudge and mistakenly cancel the driver's reserved order. This caused the driver to waste a lot of time waiting for the reserved passenger and incur parking fees, which also affected the driver's income and generated negative word-of-mouth for the platform.

[0008] It is evident that the existing reminder strategy has the problem of inaccurate judgment on whether the driver of the reservation is late, resulting in the wrong cancellation of reservation orders. This leads to a high complaint rate on the platform and causes negative word-of-mouth from passengers and drivers. Summary of the Invention

[0009] According to embodiments of the present invention, a late arrival reminder scheme for ride-hailing orders is provided. This scheme optimizes the driver late arrival reminder strategy, enabling more intelligent and accurate assessment of the risk of no available vehicle due to driver lateness, thereby reducing complaint rates and improving drivers' experience with the late arrival reminder strategy.

[0010] In a first aspect of the present invention, a method for providing late arrival reminders for ride-hailing orders is provided. The method includes:

[0011] The LBS server obtains the heartbeat data of the driver's terminal ID; the heartbeat data is sent to the LBS server by the driver's terminal ID in an idle state at preset time intervals;

[0012] If there are pending orders for the driver ID, the LBS server calculates the shortest pick-up route distance (EDA) and travel time (ETA) for the next pending order for the driver ID and sends them to the server.

[0013] The LBS server calculates the fault tolerance time t of the driver's location area based on the historical order data of the area to which the driver's ID belongs, and sends it to the server.

[0014] The server generates late arrival reminder rules based on the fault tolerance time of the region where the driver ID is located, the driving distance EDA of the shortest pick-up route for the driver ID's next pending order, and the driving time ETA, and then reminds the driver ID according to the late arrival reminder rules.

[0015] Furthermore, the driver's heartbeat data includes:

[0016] Driver ID, driver ID location, current time T1, driver ID's next pending order ID, driver ID's next pending order ID's scheduled pick-up time T2, and driver ID's next pending order ID's scheduled pick-up point location.

[0017] Further, the calculation of the shortest pick-up route distance (EDA) for the next pending order of the driver ID includes:

[0018] Starting from the location of the driver's ID, and ending at the location of the reserved pick-up point of the next pending order ID of the driver's ID, calculate the shortest pick-up route distance (EDA) for the next pending order of the driver's ID.

[0019] Further, the ETA (Estimated Time To Arrival) of the shortest pick-up route for the next pending order for the driver ID is calculated, including:

[0020] Starting from the location of the driver's ID, and ending at the location of the reserved pick-up point of the next pending order ID of the driver's ID, calculate the travel time ETA of the shortest pick-up route for the next pending order of the driver's ID.

[0021] Further, the calculation of the fault tolerance time t of the region to which the driver's ID belongs includes:

[0022] Get completed reservations that have not received any complaints within a preset time range;

[0023] Calculate the driving time error value for each of the reservation orders, and obtain the average driving time error value;

[0024] If the average value of the driving time error is greater than 0, then the average value of the driving time error is taken as the fault tolerance time t of the region to which the driver's ID belongs; if the average value of the driving time error is not greater than 0, then the fault tolerance time t of the region to which the driver's ID belongs is 0.

[0025] Furthermore, the error value for the travel time of the aforementioned reservation order is:

[0026] x = D - ETA

[0027] Where x is the error value of the driving time for the reservation order; D is the actual driving time for the pick-up service of the reservation order.

[0028] Furthermore, the late arrival reminder rule is as follows:

[0029] If the next pending order for the driver's ID meets the first condition, there is no risk of being late; otherwise, there is a risk of being late.

[0030] If there is a risk of being late, a countdown of twice the margin of error will begin from the current time, and a warning message will be sent to the driver's ID.

[0031] When the countdown ends, if the driver ID has not sent pick-up information to the pending order, the server will initiate order reassignment to other driver IDs that are in an idle state.

[0032] Furthermore, the first condition is:

[0033] (ETA-t)-(T2-T1)

[0034] Where T1 is the current time; T2 is the scheduled car rental time for the next pending order ID of the driver's ID.

[0035] Furthermore, if the order reassignment is successful, the order information will be sent to the reassigned driver's terminal ID, and the driver's terminal ID will be notified that the order is cancelled;

[0036] If order reassignment fails, a warning message will be sent to the driver's ID.

[0037] In a second aspect of the invention, an electronic device is provided. The electronic device includes at least one processor; and a memory communicatively connected to the at least one processor; the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of the first aspect of the invention.

[0038] It should be understood that the description in the Summary of the Invention is not intended to limit the key or essential features of the embodiments of the present invention, nor is it intended to restrict the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0039] The above and other features, advantages, and aspects of the various embodiments of the present invention will become more apparent from the accompanying drawings and the following detailed description. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein:

[0040] Figure 1 A flowchart illustrating a method for providing late arrival reminders for ride-hailing orders according to an embodiment of the present invention is shown.

[0041] Figure 2 A block diagram of an exemplary electronic device capable of implementing embodiments of the present invention is shown;

[0042] Among them, 200 is an electronic device, 201 is a computing unit, 202 is a ROM, 203 is a RAM, 204 is a bus, 205 is an I / O interface, 206 is an input unit, 207 is an output unit, 208 is a storage unit, and 209 is a communication unit. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] Furthermore, the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0045] In this invention, the driver lateness reminder strategy has been optimized, which can more intelligently and accurately determine the risk of no car arriving due to driver lateness, thereby reducing the complaint rate and improving the driver's experience with the lateness reminder strategy.

[0046] Figure 1 A flowchart illustrating a method for issuing late arrival reminders for ride-hailing orders according to an embodiment of the present invention is shown.

[0047] The method includes:

[0048] S101, The LBS server obtains the heartbeat data of the driver's ID; the heartbeat data is sent to the LBS server by the driver's ID in an idle state at preset time intervals.

[0049] In this embodiment, the heartbeat data includes:

[0050] Driver ID, driver ID location, current time T1, driver ID's next pending order ID, driver ID's next pending order ID's scheduled pick-up time T2, and driver ID's next pending order ID's scheduled pick-up point location.

[0051] In this embodiment, the heartbeat data is sent to the LBS server at preset time intervals, for example, the heartbeat data is reported to the LBS server every 10 seconds.

[0052] In this embodiment, the idle state refers to the state where the driver's account is logged in but has not entered the order service process. When the driver's ID is in an idle state, it can accept orders or provide services for orders that have already been accepted.

[0053] S102. If there are pending orders for the driver ID, the LBS server calculates the shortest pick-up route distance (EDA) and travel time (ETA) for the next pending order for the driver ID and sends them to the server.

[0054] As an embodiment of the present invention, calculating the driving distance EDA of the shortest pick-up route for the next pending order of the driver ID includes:

[0055] Starting from the location of the driver's ID, and ending at the location of the reserved pick-up point of the next pending order ID of the driver's ID, calculate the shortest pick-up route distance (EDA) for the next pending order of the driver's ID.

[0056] As an embodiment of the present invention, calculating the travel time (ETA) of the shortest pick-up route for the next pending order of the driver ID includes:

[0057] Starting from the location of the driver's ID, and ending at the location of the reserved pick-up point of the next pending order ID of the driver's ID, calculate the travel time ETA of the shortest pick-up route for the next pending order of the driver's ID.

[0058] In this embodiment, the driving distance EDA and driving time ETA of the shortest pick-up route for the next pending order of the driver ID can be calculated using a third-party map service, such as Baidu Maps or Gaode Maps.

[0059] S103. The LBS server calculates the fault tolerance time t of the location of the driver ID based on the historical order data of the location of the driver ID, and sends it to the server.

[0060] In this embodiment, to avoid misjudgments caused by real-time changes in road conditions during actual driving, the server configures a fault tolerance duration t for each city. The fault tolerance duration t is calculated from historical order data. The fault tolerance duration t varies for each city, depending on the city's congestion level. For example, cities with severe congestion, such as Beijing and Shanghai, have a longer fault tolerance duration t; while cities with less severe congestion, such as Tieling and Gongzhuling, have a shorter fault tolerance duration t.

[0061] In this embodiment, calculating the fault tolerance time t of the region to which the driver's ID belongs includes:

[0062] Obtain completed reservations without complaints within a preset time range; the preset time range is, for example, the most recent three months or 100 days.

[0063] Calculate the travel time error value for each of the reservation orders to obtain the average travel time error value; the travel time error value for each reservation order is:

[0064] x = D - ETA

[0065] Where x is the error value of the travel time for the reservation order; D is the actual travel time for the pick-up service of the reservation order. The average value of the travel time error values ​​for the reservation orders is denoted as...

[0066] If the average value of the driving time error is greater than 0, then the average value of the driving time error is taken as the fault tolerance time t of the region to which the driver's ID belongs; if the average value of the driving time error is not greater than 0, then the fault tolerance time t of the region to which the driver's ID belongs is 0.

[0067] The area to which it belongs can be a defined range, such as the boundaries of a street block; or it can be the administrative division of a city's urban area.

[0068] S104. The server generates a late arrival reminder rule based on the fault tolerance time of the region to which the driver ID belongs, the driving distance EDA of the shortest pick-up route for the next pending order of the driver ID, and the driving time ETA, and reminds the driver ID according to the late arrival reminder rule.

[0069] In this embodiment, the late arrival reminder rule is as follows:

[0070] If the next pending order for the driver's ID meets the first condition, there is no risk of lateness; otherwise, there is a risk of lateness. The first condition is:

[0071] (ETA-t)-(T2-T1)

[0072] Where T1 is the current time; T2 is the scheduled car rental time for the next pending order ID of the driver's ID.

[0073] If there is a risk of being late, a countdown time of twice the current time will begin, and a warning message will be sent to the driver's ID. This warning message can be sent to the driver's device via a pop-up notification.

[0074] In this embodiment, the countdown timer is set to allow a window period for the driver to depart or for the order to be reassigned. Within the time of ETA-x, the driver may still be able to arrive at the pick-up point on time by subjectively adjusting his driving behavior. At the same time, according to the data statistics of passenger cancellations after dispatch, it is basically the upper limit of the time that passengers can tolerate for the driver to be late. Therefore, the countdown timer is set to twice the tolerance time.

[0075] When the countdown ends, if the driver ID has not sent pick-up information to the pending order, the server will initiate order reassignment to other driver IDs that are in an idle state.

[0076] In this embodiment, the driver's ID sends pick-up information to the pending service order, which can be done by the driver clicking to pick up the driver.

[0077] In the above embodiments, there are two scenarios for order reassignment:

[0078] If the order reassignment is successful, the order information will be sent to the reassigned driver's terminal ID, and the driver's terminal ID will be notified that the order is cancelled;

[0079] If order reassignment fails, a warning message will be sent to the driver's ID.

[0080] Even after the driver's ID receives a warning message, the reassignment process continues until the driver's ID accepts the ride or the order is successfully reassigned.

[0081] According to embodiments of the present invention, the driver lateness reminder strategy has been optimized, which can more intelligently and accurately determine the risk of no car arriving due to driver lateness, thereby reducing the complaint rate and improving the driver's experience with the lateness reminder strategy.

[0082] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0083] According to embodiments of the present invention, an electronic device is also provided.

[0084] Figure 2 A schematic block diagram of an electronic device 200 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0085] Device 200 includes a computing unit 201, which can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) 202 or a computer program loaded from storage unit 208 into random access memory (RAM) 203. The RAM 203 may also store various programs and data required for the operation of device 200. The computing unit 201, ROM 202, and RAM 203 are interconnected via bus 204. Input / output (I / O) interface 205 is also connected to bus 204.

[0086] Multiple components in device 200 are connected to I / O interface 205, including: input unit 206, such as keyboard, mouse, etc.; output unit 207, such as various types of monitors, speakers, etc.; storage unit 208, such as disk, optical disk, etc.; and communication unit 209, such as network card, modem, wireless transceiver, etc. Communication unit 209 allows device 200 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0087] The computing unit 201 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 201 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 201 performs the various methods and processes described above, such as methods S101 to S104. For example, in some embodiments, methods S101 to S104 may be implemented as computer software programs tangibly contained in a machine-readable medium, such as storage unit 208. In some embodiments, part or all of the computer program may be loaded and / or installed on device 200 via ROM 202 and / or communication unit 209. When the computer program is loaded into RAM 203 and executed by the computing unit 201, one or more steps of methods S101 to S104 described above may be performed. Alternatively, in other embodiments, the computing unit 201 may be configured to execute methods S101 to S104 by any other suitable means (e.g., by means of firmware).

[0088] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0089] The program code used to implement the methods of the present invention can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0090] In the context of this invention, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0091] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0092] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0093] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0094] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0095] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for providing late arrival reminders for ride-hailing orders, characterized in that, include: The LBS server obtains the driver's heartbeat data from the driver's ID. The heartbeat data is sent to the LBS server by the driver's ID in an idle state at preset time intervals; If there are pending orders for the driver ID, the LBS server calculates the shortest pick-up route distance (EDA) and travel time (ETA) for the next pending order for the driver ID and sends them to the server. The LBS server calculates the fault tolerance time for the location area of ​​the driver's ID based on historical order data of the area. Send it to the server; The server generates late arrival reminder rules based on the fault tolerance time of the region where the driver ID is located, the driving distance EDA of the shortest pick-up route for the driver ID's next pending order, and the driving time ETA, and then reminds the driver ID according to the late arrival reminder rules. The late arrival reminder rules are as follows: If the next pending order for the driver's ID meets the first condition, there is no risk of being late. Otherwise, there is a risk of being late; If there is a risk of being late, a countdown of twice the margin of error will begin from the current time, and a warning message will be sent to the driver's ID. When the countdown ends, if the driver ID has not sent pick-up information to the pending order, the server will initiate order reassignment to other driver IDs that are in an idle state.

2. The method according to claim 1, characterized in that, The driver's heart rate data includes: Driver ID, Driver ID location, Current time The driver's ID and the next pending order ID, along with the scheduled ride time. The location of the scheduled pick-up point for the next pending order ID of the driver's ID.

3. The method according to claim 2, characterized in that, Calculating the shortest pick-up distance (EDA) for the next pending order for the driver ID includes: Starting from the location of the driver's ID, and ending at the location of the reserved pick-up point of the next pending order ID of the driver's ID, calculate the shortest pick-up route distance (EDA) for the next pending order of the driver's ID.

4. The method according to claim 2, characterized in that, Calculating the ETA (Estimated Time To Arrival) of the shortest pick-up route for the next pending order for the driver ID includes: Starting from the location of the driver's ID, and ending at the location of the reserved pick-up point of the next pending order ID of the driver's ID, calculate the travel time ETA of the shortest pick-up route for the next pending order of the driver's ID.

5. The method according to claim 1, characterized in that, The fault tolerance time for calculating the location region of the driver's ID is then calculated. ,include: Get completed reservations that have not received any complaints within a preset time range; Calculate the driving time error value for each of the reservation orders, and obtain the average driving time error value; If the average value of the driving time error is greater than 0, then the average value of the driving time error is taken as the fault tolerance time of the region to which the driver's ID belongs. If the average value of the driving time error is not greater than 0, then the fault tolerance time for the region to which the driver's ID belongs is... It is 0.

6. The method according to claim 5, characterized in that, The travel time error value for the reserved order is: in, This is the error value for the travel time of the pre-booked order; This refers to the actual driving time for the pick-up service of the pre-booked order.

7. The method according to claim 1, characterized in that, The first condition is: in, The current time; The scheduled ride time for the next pending order ID of the driver's ID.

8. The method according to claim 1, characterized in that, If the order reassignment is successful, the order information will be sent to the reassigned driver's terminal ID, and the driver's terminal ID will be notified that the order is cancelled; If order reassignment fails, a warning message will be sent to the driver's ID.

9. An electronic device comprising at least one processor; and A memory communicatively connected to the at least one processor; characterized in that, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-8.

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