CN109436174B

CN109436174B - Vehicle control method, server and vehicle system

Info

Publication number: CN109436174B
Application number: CN201811143241.6A
Authority: CN
Inventors: 靳洪都; 樊玉明; 胡波
Original assignee: Beijing Mobike Technology Co Ltd
Current assignee: Hanhai Information Technology Shanghai Co Ltd; Mobai Beijing Information Technology Co Ltd
Priority date: 2018-09-28
Filing date: 2018-09-28
Publication date: 2020-04-17
Anticipated expiration: 2038-09-28
Also published as: CN109436174A

Abstract

The invention discloses a vehicle control method, a server and a vehicle control system. The method comprises the following steps: receiving a vehicle use request from a target user sent by a client, and acquiring a vehicle use habit model and a vehicle running path of the target user; determining at least one candidate control parameter set according to the vehicle use habit model and the vehicle running path, and sending the candidate control parameter set to the client so that a target user can select a target control parameter set from the candidate control parameter set; and configuring the target vehicle used by the target user according to the target control parameter set indicated by the client to realize the control of the target vehicle. According to the invention, the vehicle can be adaptively controlled according to the personalized vehicle use requirements of the user, and the vehicle use experience of the user is improved.

Description

Vehicle control method, server and vehicle system

Technical Field

The invention relates to the technical field of vehicle control, in particular to a vehicle control method, a server and a vehicle system.

Background

Along with higher demands of people on shared traffic travel services, shared electric vehicles such as shared electric vehicles and shared electric mopeds also appear, at least part of power for driving the vehicles can be provided through batteries arranged in the vehicles, the remote shared travel demands of users can be met through clean energy, and meanwhile, the pollution to the environment is reduced.

However, at present, control parameters (for example, vehicle speed control parameters, power control parameters, and the like) related to vehicle driving of the shared electric vehicle are usually fixed in a control unit of the shared electric vehicle, and cannot be well adapted to a complex and variable vehicle driving scene in reality, so that it is difficult to meet vehicle use requirements of a user, and vehicle use experience of the user is affected.

Disclosure of Invention

It is an object of the present invention to provide a new solution for controlling a vehicle.

According to a first aspect of the present invention, there is provided a vehicle control method in which a vehicle converts an amount of electric power output from a battery provided in the vehicle into power required for at least partial travel, the method being implemented by a server, comprising:

receiving a vehicle use request from a target user sent by a client, and acquiring a vehicle use habit model and a vehicle running path of the target user;

determining at least one candidate control parameter set according to the vehicle use habit model and the vehicle running path, and sending the candidate control parameter set to the client so that the target user can select a target control parameter set from the candidate control parameter set;

wherein each of the candidate control parameter sets includes at least a vehicle speed control parameter for controlling a vehicle speed and a vehicle power control parameter for controlling a vehicle power;

and configuring a target vehicle used by the target user according to the target control parameter set indicated by the client to realize the control of the target vehicle.

Optionally, the step of obtaining the vehicle usage habit model of the target user includes:

obtaining a historical observation sample sequence of vehicles used by the target user before;

the historical observation sample sequence comprises a plurality of historical observation samples which are sampled and obtained according to a preset sampling time interval in the process that the target user uses the vehicle before;

obtaining a vehicle usage sample set comprising a plurality of vehicle usage samples according to the historical observation sample sequence;

according to the vehicle use sample set, vehicle use characteristic data under a preset vehicle use scene are obtained;

and constructing the vehicle use habit model according to the acquired vehicle use characteristic data.

Optionally, the historical observation samples include vehicle speed, vehicle pedaling frequency, vehicle torque, vehicle output power, vehicle longitudinal acceleration, and vehicle axial angular velocity; the vehicle usage samples comprise total vehicle power, vehicle power ratio, vehicle heading speed, vehicle travel grade and vehicle travel angle;

the step of obtaining a vehicle usage sample set comprising a plurality of vehicle usage samples from the sequence of historical observation samples comprises:

performing data fusion processing on each historical observation sample included in the historical observation sample sequence to obtain the vehicle use sample corresponding to the historical observation sample, so as to form the vehicle use sample set according to the obtained multiple vehicle use samples;

wherein the data fusion process comprises:

determining the total vehicle power according to the vehicle torque, the vehicle pedal frequency and the vehicle output power; determining the vehicle power ratio according to the vehicle torque, the vehicle step frequency and the vehicle output power; determining the heading speed of the vehicle according to the speed of the vehicle, the longitudinal acceleration of the vehicle and the gravity acceleration; determining the vehicle running gradient according to the longitudinal acceleration and the gravity acceleration of the vehicle; and determining the vehicle running bend angle according to the vehicle axial angular speed and the sampling time of the historical observation sample.

Optionally, the vehicle usage samples include total vehicle power, vehicle power ratio, vehicle heading speed, vehicle grade, and vehicle heading angle;

the preset vehicle use scenes at least comprise one of four vehicle use scenes, namely a flat ground cruising scene, a flat ground accelerating scene, a flat ground turning scene and a sloping ground driving scene;

each type of vehicle use scene has a value range of a corresponding scene classification parameter;

the scene classification parameters at least comprise vehicle heading speed, vehicle running gradient and vehicle running bend angle;

the step of obtaining vehicle use characteristic data in a preset vehicle use scene according to the vehicle use sample set to construct the vehicle use habit model comprises:

classifying a plurality of vehicle use samples included in the vehicle use sample set according to the value range of the scene classification parameter of the vehicle use scene to obtain the vehicle use sample corresponding to the vehicle use scene;

determining vehicle use characteristic data under the vehicle use scene according to the vehicle use sample corresponding to the vehicle use scene;

wherein,

when the vehicle using scene is a flat ground cruising scene, the vehicle using characteristic data comprises vehicle cruising speed, vehicle cruising target total power and vehicle cruising power ratio, and the vehicle using characteristic data is obtained by carrying out weighted average on effective samples selected from the vehicle using samples corresponding to the vehicle using scene according to the vehicle course speed;

when the vehicle using scene is a flat ground acceleration scene, the vehicle using characteristic data comprises power ratios corresponding to different vehicle heading speeds, and the vehicle using characteristic data is obtained after classifying the vehicle using samples corresponding to the vehicle using scene according to a preset value interval of the vehicle heading speed and averaging the vehicle power ratios included in the classified vehicle using samples corresponding to the values of the different vehicle heading speeds;

when the vehicle use scene is a flat ground turning scene, the vehicle use characteristic data comprises vehicle speed limits corresponding to different vehicle running bend angles, and the vehicle use characteristic data is obtained after classifying the vehicle use samples corresponding to the vehicle use scene according to preset value intervals of the vehicle bend angles and averaging the vehicle course speeds contained in the classified vehicle use samples corresponding to the values of the different vehicle bend angles;

when the vehicle use scene is a sloping field driving scene, the vehicle use characteristic data comprise vehicle power ratios corresponding to different vehicle driving slopes, and the vehicle use characteristic data are obtained after classifying the vehicle use samples corresponding to the vehicle use scene according to preset value intervals of the vehicle driving slopes and averaging the classified vehicle power ratios included in the vehicle use samples corresponding to the values of the different vehicle driving slopes.

Optionally, each of the vehicle usage samples has a corresponding distance traveled; the method further comprises the following steps:

classifying vehicle use samples in the vehicle use sample set based on a preset travel distance grade to obtain a plurality of classified vehicle use sample sets consisting of vehicle use samples corresponding to different travel distance grades, and respectively executing the step of acquiring the vehicle use characteristic data according to each classified vehicle use sample set;

and/or the presence of a gas in the gas,

the method further comprises the following steps:

according to preset scene classification parameters, clustering all vehicle use samples in the vehicle use sample set to obtain a vehicle use sample set formed by a plurality of clustered vehicle use samples with cluster center samples, and respectively executing the step of acquiring the vehicle use characteristic data according to each clustered vehicle use sample set.

Optionally, the step of constructing the vehicle usage habit model comprises:

after a group of vehicle use characteristic data is obtained every time, obtaining a vehicle use average sample according to all the obtained vehicle use characteristic data, and taking the vehicle use average sample as the vehicle use habit model;

and/or the presence of a gas in the gas,

the method further comprises the following steps:

the step of obtaining a vehicle usage habit model is performed each time a target user uses a vehicle, and the vehicle usage habit model is stored for reading at a later time when the vehicle usage request is received.

Optionally, the vehicle use request includes at least information indicating a destination of the target user; the step of acquiring the vehicle driving path comprises the following steps:

determining a candidate vehicle running path and a candidate vehicle corresponding to the candidate vehicle running path according to the acquired vehicle state information of the available vehicles and the destination of the target user, and providing the candidate vehicle running path and the candidate vehicle corresponding to the candidate vehicle running path to the client for the target user to select;

wherein the vehicle state information at least comprises a geographical position of the vehicle and a current battery level of the vehicle; the candidate vehicle driving path at least comprises a driving route and driving terrain change;

according to the indication of the client, determining a vehicle running path selected by the target user from the candidate vehicle running paths and a corresponding target vehicle;

and/or the presence of a gas in the gas,

the vehicle use request at least comprises information used for indicating the destination of the target user and information used for indicating a target vehicle which is expected to be used by the target user;

the step of acquiring the vehicle driving path comprises the following steps:

determining a candidate vehicle running path according to the acquired vehicle state information of the target vehicle and the destination of the target user, and providing the candidate vehicle running path to the client for the target user to select;

and determining the vehicle running path selected by the target user from the candidate vehicle running paths according to the indication of the client.

Optionally, the vehicle usage habit model includes a vehicle usage average sample in a preset vehicle usage scene; the vehicle driving path at least comprises a driving route and driving terrain change;

the step of determining at least one candidate control parameter set according to the vehicle usage habit model and the vehicle travel path comprises:

determining at least one candidate scene combination corresponding to the vehicle running path according to preset scene division parameters, the vehicle use habit model and the vehicle running path;

wherein the candidate scene combination comprises all vehicle usage scenes expected to be experienced by the target user when the target user drives the vehicle driving path;

for each candidate scene combination, obtaining the vehicle use average sample corresponding to the vehicle use scene included in the candidate scene combination from the vehicle use habit model to determine the vehicle speed control parameter and the vehicle power control parameter corresponding to the vehicle use scene, so as to obtain a candidate control parameter set corresponding to the candidate scene combination.

Alternatively,

the vehicle driving path also comprises a battery replacement place of a target vehicle used by the target user;

the method further comprises the following steps:

when the target vehicle is determined to finish battery replacement at a battery replacement place in the vehicle driving path, providing a corresponding reward value for the target user according to the battery replacement place and vehicle state information before the target vehicle is not used;

wherein the vehicle state information at least includes a geographical location of the vehicle and a current battery level of the vehicle.

According to a second aspect of the present invention, there is provided a server for implementing control of a vehicle that converts an amount of electric power output from a battery provided in the vehicle into power required for at least partial travel, the server comprising:

a memory for storing executable instructions;

a processor for operating the server to execute the vehicle control method according to the control of the executable instructions.

According to a third aspect of the present invention, there is provided a vehicle system comprising:

a server as provided in the first aspect of the invention;

a client;

and a vehicle.

Optionally, the client includes:

a display device;

a memory for storing executable instructions;

a processor configured to execute the client according to the executable instructions, and perform the following method, including:

sending a vehicle use request from a target user to the server;

receiving a candidate control parameter set sent by the server, and displaying the candidate control parameter set to the target user for selection through the display device;

responding to the selection operation of the target user, and indicating a target control parameter set corresponding to the selection operation to the server;

and/or the presence of a gas in the gas,

the vehicle includes:

a battery;

a memory for storing executable instructions;

a processor for operating the vehicle according to the executable instructions, performing a method comprising:

configuring the server according to a target control parameter set received from the server to realize the control of the server on the server;

wherein the set of target control parameters includes at least a vehicle speed control parameter for controlling a vehicle speed and a vehicle power control parameter for controlling a vehicle power.

According to one embodiment of the disclosure, when a user has a vehicle use requirement, a vehicle use habit model and a vehicle driving path of the user are obtained to determine a candidate control parameter set comprising a vehicle speed control parameter for controlling vehicle speed and a vehicle power control parameter for controlling vehicle power, the candidate control parameter set is provided for the user to select, the vehicle used by the user is configured to control the vehicle according to a target control parameter set selected by the user, a vehicle control mode which is adapted to the vehicle use habit and an actual vehicle driving requirement scene is provided for the user to select, the personalized vehicle use requirement of the user is met in a self-adaptive manner, and the vehicle use experience of the user is improved.

Other features of the present invention and advantages thereof will become apparent from the following detailed description of exemplary embodiments thereof, which proceeds with reference to the accompanying drawings.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description, serve to explain the principles of the invention.

Fig. 1 is a block diagram showing an example of a hardware configuration of a vehicle system that can be used to implement an embodiment of the invention.

Fig. 2 shows a flowchart of a vehicle control method of the first embodiment of the invention.

Fig. 3 shows a flowchart of the steps of obtaining a vehicle usage habit model according to the first embodiment of the present invention.

Fig. 4 shows a block diagram of a server of the first embodiment of the present invention.

Fig. 5 shows a block diagram of a vehicle system of a second embodiment of the invention.

Fig. 6 is a schematic diagram of an example of a vehicle control method of the second embodiment of the invention.

Detailed Description

Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that: the relative arrangement of the components and steps, the numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.

The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.

Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.

In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.

< hardware configuration >

As shown in fig. 1, the vehicle system 100 includes a server 1000, a client 2000, a vehicle 3000, and a network 4000.

The server 1000 provides a service point for processes, databases, and communications facilities. The server 1000 may be a unitary server or a distributed server across multiple computers or computer data centers. The server may be of various types, such as, but not limited to, a web server, a news server, a mail server, a message server, an advertisement server, a file server, an application server, an interaction server, a database server, or a proxy server. In some embodiments, each server may include hardware, software, or embedded logic components or a combination of two or more such components for performing the appropriate functions supported or implemented by the server. For example, a server, such as a blade server, a cloud server, etc., or may be a server group consisting of a plurality of servers, which may include one or more of the above types of servers, etc.

In one example, the server 1000 may be as shown in fig. 1, including a processor 1100, a memory 1200, an interface device 1300, a communication device 1400, a display device 1500, an input device 1600. Although the server may also include speakers, microphones, etc., these components are not relevant to the present invention and are omitted here.

The processor 1100 may be, for example, a central processing unit CPU, a microprocessor MCU, or the like. The memory 1200 includes, for example, a ROM (read only memory), a RAM (random access memory), a nonvolatile memory such as a hard disk, and the like. The interface device 1300 includes, for example, a USB interface, a serial interface, an infrared interface, and the like. Communication device 1400 is capable of wired or wireless communication, for example. The display device 1500 is, for example, a liquid crystal display, an LED display touch panel, or the like. The input device 1600 may include, for example, a touch screen, a keyboard, and the like.

In the present embodiment, the client 2000 is an electronic device having a communication function and a service processing function. The client 2000 may be a mobile terminal, such as a mobile phone, a laptop, a tablet, a palmtop, etc. In one example, the client 2000 is a device that performs management operations on the vehicle 3000, such as a mobile phone installed with an Application (APP) that supports operation and management of the vehicle.

As shown in fig. 1, the client 2000 may include a processor 2100, a memory 2200, an interface device 2300, a communication device 2400, a display device 2500, an input device 2600, an output device 2700, a camera device 2800, and the like. The processor 2100 may be a central processing unit CPU, a microprocessor MCU, or the like. The memory 2200 includes, for example, a ROM (read only memory), a RAM (random access memory), a nonvolatile memory such as a hard disk, and the like. The interface device 2300 includes, for example, a USB interface, a headphone interface, and the like. Communication device 2400 is capable of wired or wireless communication, for example. The display device 2500 is, for example, a liquid crystal display panel, a touch panel, or the like. The input device 2600 may include, for example, a touch screen, a keyboard, or a microphone. The output device 2700 is for outputting information, and may be, for example, a speaker for outputting voice information to a user. The image pickup device 2800 is used for image pickup of acquisition information, and is, for example, a camera or the like. .

The vehicle 3000 is any electric vehicle that can share the use right for different users in a time-sharing or time-sharing manner and provides at least part of the driving power by means of a battery, such as a shared electric power-assisted vehicle, a shared electric vehicle, and the like.

As shown in fig. 1, the vehicle 3000 may include a processor 3100, a memory 3200, an interface device 3300, a communication device 3400, an input/output device 3500, a power device 3600, a positioning device 3700, sensors 3800, and so forth. The processor 3100 may be a central processing unit CPU, a microprocessor MCU, or the like. The memory 3200 includes, for example, a ROM (read only memory), a RAM (random access memory), a nonvolatile memory such as a hard disk, and the like. The interface 3300 includes, for example, a USB interface, a headphone interface, and the like. The communication device 3400 can perform wired or wireless communication, for example. The output device of the output/input device 3500 may be, for example, a device that outputs a signal, a display device such as a liquid crystal display panel or a touch panel, or a speaker that outputs voice information, and the input device may include, for example, a touch panel or a keyboard, or a microphone that inputs voice information. The power device 3600 is a device that provides power, and may be, for example, an electric storage device such as a battery that provides at least part of the power for the vehicle to travel by outputting an amount of electricity, it being understood that the power device 3600 may be configured to be detachable. The positioning device 3700 is used to provide positioning function, and may be, for example, a GPS positioning module, a beidou positioning module, etc. The sensors 3800 may be used for devices that acquire vehicle state information, such as accelerometers, gyroscopes, or three, six, nine-axis micro-electromechanical systems (MEMS), torque sensors, and the like.

The network 4000 may be a wireless communication network or a wired communication network, and may be a local area network or a wide area network. In the article management system shown in fig. 1, a vehicle 3000 and a server 1000, and a client 2000 and the server 1000 can communicate with each other via a network 4000. The vehicle 3000 may be the same as the server 1000, and the network 4000 through which the client 2000 communicates with the server 1000 may be different from each other.

It should be understood that although fig. 1 shows only one server 1000, client 2000, vehicle 3000, it is not meant to limit the corresponding number, and multiple servers 1000, clients 2000, vehicles 3000 may be included in the vehicle system 100.

Taking the vehicle 3000 as an example of a shared electric vehicle, the vehicle system 100 is a shared electric vehicle system. The server 1000 is used to provide all the functions necessary to support the use of the shared electric vehicle. The client 2000 may be a mobile phone on which a shared electric vehicle application is installed, which may help a user acquire a corresponding function using the vehicle 3000, and the like.

The vehicle system 100 shown in FIG. 1 is illustrative only and is not intended to limit the invention, its application, or uses in any way.

In an embodiment of the present invention, the memory 1200 of the server 1000 is used for storing instructions for controlling the processor 1100 to operate so as to execute the vehicle notification method provided by the embodiment of the present invention. Although a number of devices are shown in fig. 1 for server 1000, the present invention may relate to only some of the devices, for example, server 1000 may relate to only memory 1200 and processor 1100.

In an embodiment of the present invention, the memory 2200 of the client 2000 is configured to store instructions for controlling the processor 2100 to operate the client 2000 to execute a vehicle control method according to an embodiment of the present invention. Although a number of devices are shown in fig. 1 for client 2000, the present invention may relate to only some of the devices, for example, client 2000 may relate to only memory 2200 and processor 2100.

In an embodiment of the present invention, the memory 3200 of the vehicle 3000 is configured to store instructions for controlling the processor 3100 to operate so as to perform the vehicle control method according to the embodiment of the present invention. Although a plurality of devices are shown for the vehicle 3000 in fig. 1, the present invention may relate only to some of the devices, for example, the vehicle 3000 relates only to the memory 3200 and the processor 3100.

In the above description, the skilled person will be able to design instructions in accordance with the disclosed solution. How the instructions control the operation of the processor is well known in the art and will not be described in detail herein.

The general idea of the embodiment of the invention is to provide a new technical scheme for controlling a vehicle by converting the electric quantity output by a battery arranged on the vehicle into at least partial power required by running, by acquiring the vehicle use habit model and the vehicle running path of the user when the user has the vehicle use requirement, to determine a set of candidate control parameters including a vehicle speed control parameter for controlling vehicle speed and a vehicle power control parameter for controlling vehicle power, to provide to a user for selection, and according to the target control parameter set selected by the user, the vehicle used by the user is configured to control the vehicle, a vehicle control mode which is adapted to the vehicle use habit and the actual vehicle driving scene is provided for the user to select, the personalized vehicle use requirement of the user is met in a self-adaptive manner, and the vehicle use experience of the user is improved.

< first embodiment >

A vehicle control method is provided in the present embodiment. The vehicle can convert the electric quantity output by the battery into power required by at least partial form, for example, an electric moped, an electric vehicle, an electric automobile and the like. In one example, there may be a vehicle 1300 as shown in FIG. 1.

The vehicle control method in the present embodiment is implemented by a server. The server may be in various forms of entities. For example, the server may be a cloud server, or may also be the server 1000 shown in fig. 1.

As shown in fig. 2, the vehicle control method includes: steps S2100-S2300.

Step S2100 receives a vehicle use request from a target user sent by a client, and obtains a vehicle use habit model and a vehicle travel path of the target user.

The client may be an electronic device for a user to obtain vehicle use functions, for example, the client 1200 shown in fig. 1. For example, when there is a vehicle use demand, the user sends a vehicle use request to the server by installing a mobile phone used by the vehicle as a client.

The vehicle use request may include different request contents according to the actual vehicle use demand of the user. For example, information indicating a destination to which the user desires to use the vehicle, information indicating a target vehicle that the user desires to use (for example, a unique vehicle identifier of the target vehicle), a unique user identifier of the user himself/herself, and the like may be included in the vehicle use request.

When receiving a vehicle use request of a target user, the server is triggered to acquire a vehicle use habit model and a vehicle running path of the target user so as to combine subsequent steps, determine a candidate control parameter set (comprising a vehicle speed control parameter and a vehicle power control parameter) which is adapted to the vehicle use habit of the user and an actual vehicle use scene, provide the candidate control parameter set for the user to select, and configure a vehicle used by the user to control the vehicle according to the selection of the user so as to assist the user to acquire an optimal vehicle control mode in the actual vehicle use scene and improve vehicle use experience.

The vehicle usage habit model is a data model that characterizes the user's vehicle usage habits. In the embodiment, the vehicle usage habit model can be obtained according to the actual application requirement or application scenario.

In one example, the step of obtaining the vehicle usage habit model is shown in FIG. 3 and includes steps S2110-S2140.

Step S2110, a historical observation sample sequence of the target user previously using the vehicle is acquired.

In this example, in the historical observation sample sequence, the target user previously uses a plurality of historical observation samples sampled and acquired according to a preset sampling time interval during the vehicle use. The vehicle using process can be a process that a target user uses the vehicle once, namely in the process that the target user uses the vehicle each time, a historical observation sample sequence of the target user in the vehicle using process can be obtained, so that a vehicle using habit model can be obtained later; the vehicle using process may include a process (possibly one or more times) that the target user uses the vehicle each time within a preset statistical time period, that is, the historical observation sample sequence includes a plurality of historical observation samples obtained by sampling the target user according to a preset sampling time interval within a time period of actually using the vehicle within the statistical time period.

The sampling time interval may be set according to an actual application scenario or application requirements, for example, to 1 minute.

Each historical observation sample comprises an observed quantity which is obtained in a sampling time interval and used for observing the vehicle use habits of the user, and the observed quantity can be selected according to a specific application scene or application requirements. For example, the historical observation samples may include observed quantities such as vehicle speed, vehicle cadence, vehicle torque, vehicle output power, vehicle longitudinal acceleration, and vehicle axial angular velocity, which may be sampled by on-board sensors (e.g., cadence and torque sensors, inertial sensors, positioning devices, and voltage ammeters) provided on the vehicle and clients used by a user using the vehicle.

Step S2120, a vehicle usage sample set including a plurality of vehicle usage samples is obtained according to the historical observation sample sequence.

The historical observation sample includes an observation quantity obtained during use of the vehicle by the user for observing the use habit of the vehicle by the user. The vehicle use samples comprise state quantities which represent vehicle use habits of the user. And acquiring a plurality of vehicle use samples in the vehicle use sample set through a plurality of historical observation samples in the historical observation sample sequence so as to acquire a vehicle use habit model capable of accurately embodying the vehicle use habit of the user by combining subsequent steps.

For example, the historical observation samples may include observed quantities in six dimensions of vehicle speed, vehicle pedaling frequency, vehicle torque, vehicle output power, vehicle longitudinal acceleration and vehicle axial angular speed, and correspondingly, the vehicle usage samples include state quantities in five dimensions of vehicle total power, vehicle power ratio, vehicle heading speed, vehicle gradient and vehicle turning angle, and step S2120 may include:

and performing data fusion processing on each historical observation sample included in the historical observation sample sequence to obtain a vehicle use sample corresponding to the historical observation sample, so as to form a vehicle use sample set according to the obtained multiple vehicle use samples.

In this example, one historical observation sample corresponds to one vehicle usage sample. And carrying out data fusion processing on one historical observation sample to obtain a vehicle use sample corresponding to the historical observation sample. A vehicle use sample is obtained by carrying out data fusion processing according to a historical observation sample.

The data fusion processing method comprises the following steps: determining the total power of the vehicle according to the vehicle torque, the vehicle tread frequency and the vehicle output power; determining a vehicle power ratio according to the vehicle torque, the vehicle pedal frequency and the vehicle output power; determining the course speed of the vehicle according to the speed of the vehicle, the longitudinal acceleration of the vehicle and the gravity acceleration; determining the running gradient of the vehicle according to the longitudinal acceleration and the gravitational acceleration of the vehicle; and determining the vehicle running bend angle according to the vehicle axial angular speed and the sampling time of the historical observation sample.

For example, assume that the vehicle torque is v, the vehicle pedal frequency is c, the vehicle torque is M, and the vehicle output power is P_MThe longitudinal acceleration of the vehicle is a_gThe vehicle axial angular velocity is omega, and the historical observation sample Z ═ vc MP_Ma_gω](ii) a Total vehicle power is P and vehicle power ratio is P_PThe vehicle heading speed is v_hThe vehicle travel gradient is S, the vehicle travel angle is R, and the vehicle usage sample X ═ P p_Pv_hS R](ii) a The gravity acceleration is g, and the sampling time corresponding to the historical observation sample is t (it should be understood that the historical observation sample has a certain sampling time interval, and the time difference between the historical observation sample and the sampling start time point can be directly obtained according to the sampling time interval, which is used as the sampling time), and X can be obtained by performing data fusion on Z according to the following formula:

P＝P_M+M×c；

p_P＝M×c/P_M；

R＝ωt。

for each Z included in the sequence of historical observation samples, a corresponding X may be obtained according to the above formula, and a plurality of xs thus obtained may result in a corresponding set of vehicle usage samples.

The vehicle use sample comprising the state quantity of the vehicle use habits of the multi-dimensional representation user can be obtained through the historical observation sample formed by the observation quantity obtained in the multi-dimensional mode, the vehicle use habits of the user can be represented more accurately, and an accurate vehicle use habit model can be obtained by combining the subsequent steps.

Step 2130, according to the vehicle use sample set, obtaining vehicle use characteristic data in a preset vehicle use scene.

The vehicle use sample set comprises a plurality of vehicle use samples, each vehicle use sample comprises a state quantity used for representing the vehicle use habit of a user, and according to the vehicle use sample set, vehicle use characteristic data which can embody the characteristics of the vehicle use habit of the user in one or more preset vehicle use scenes can be obtained, so that a vehicle use habit model is obtained, and the personalized vehicle use habit of the user can be accurately embodied.

The vehicle usage scenario is a specific scenario of using the vehicle by the user, and may be divided according to an actual vehicle usage situation or a vehicle driving state, for example, the preset vehicle usage scenario includes at least one of four types of vehicle usage scenarios, namely a flat ground cruising scenario, a flat ground accelerating scenario, a flat ground turning scenario, and a sloping ground driving scenario.

Each vehicle usage scenario has a value range of a corresponding scenario classification parameter. The scene classification parameters are parameters for dividing a vehicle usage scene, and for example, the scene classification parameters include at least a vehicle heading speed, a vehicle traveling gradient, and a vehicle traveling bend angle.

The value range of the corresponding scene classification parameter of each vehicle use scene can be set according to the actual scene state occurring in the specific vehicle use process, for example, for a flat cruise scene, the vehicle running gradient can be set to be less than 2%, and the fluctuation range of the vehicle heading speed is between-10% and + 10%; for a flat ground acceleration scene, the vehicle running gradient can be set to be less than 2%, and the fluctuation of the vehicle heading speed is continuously increased for more than 10 seconds; for a flat ground turning scene, the running gradient of the vehicle can be set to be less than 2%, and the vehicle bend angle is greater than 30 degrees for more than 5 seconds; for the uphill riding scenario, the vehicle travel grade may be set to be greater than 2%.

Step S2130 may include: steps S2131-S2132.

Step S2131, classifying a plurality of vehicle usage samples included in the vehicle usage sample set according to the value range of the scene classification parameter of the vehicle usage scene, to obtain a vehicle usage sample corresponding to the vehicle usage scene.

Different vehicle use scenes are provided with different value ranges of scene classification parameters. The scene classification parameters at least comprise vehicle heading speed, vehicle running gradient and vehicle running bend angle. Each vehicle use sample comprises the total vehicle power, the vehicle power ratio, the vehicle heading speed, the vehicle running gradient and the vehicle running bend angle, and comprises parameters included in the scene classification parameters, so that the specific value of the scene classification parameter included in each vehicle use sample corresponds to the value range of the scene classification parameter of a certain vehicle use scene. According to the value range of the scene classification parameters of the vehicle use scenes, a plurality of vehicle use samples included in the vehicle use sample set can be classified to obtain vehicle use samples corresponding to each type of vehicle use scenes.

For example, the preset vehicle usage scenarios include four types of vehicle usage scenarios, namely, a flat ground cruising scenario, a flat ground accelerating scenario, a flat ground turning scenario, and a sloping ground driving scenario, and the vehicle usage samples included in the vehicle usage sample set may be divided into four types according to the value ranges of different scene classification parameters of the four types of vehicle usage scenarios of the distance, so as to obtain one or more vehicle usage samples respectively corresponding to the different vehicle usage scenarios.

Step S2132 is to determine vehicle usage characteristic data in the vehicle usage scenario from the vehicle usage sample corresponding to the vehicle usage scenario.

The vehicle use characteristic data is related data of a characteristic that represents a vehicle use habit of a user in a corresponding vehicle use scene.

In order to accurately reflect the characteristics of the vehicle use habits of the user, under different vehicle use scenes, the corresponding vehicle use characteristic data can comprise different data.

For example, when the vehicle usage scenario is a flat ground cruising scenario, the vehicle usage characteristic data includes a vehicle cruising speed, a vehicle cruising target total power, and a vehicle cruising power ratio. In this scenario, according to the vehicle heading speed, the vehicle usage characteristic data can be obtained after weighted averaging is performed on effective samples selected from the vehicle usage samples corresponding to the vehicle usage scenario. The vehicle usage samples include total vehicle power, vehicle power ratio, vehicle heading speed, vehicle grade, and vehicle cornering angle. Assuming that N vehicle use samples correspond to the flat ground cruising scene, dividing the N vehicle use sample pairs according to the vehicle heading speed of each vehicle use sample based on a preset value interval (for example, 1 km/h) of the vehicle heading speed to obtain vehicle use samples belonging to each different vehicle heading speed value interval; respectively calculating weights corresponding to the value intervals of the vehicle heading speed based on the number of vehicle use samples under the value intervals of different vehicle heading speeds, wherein for example, the number of the vehicle use samples under the value intervals of a certain vehicle heading speed is T, and the corresponding weight is T/N; according to the weight corresponding to the value interval of each vehicle heading speed, after the vehicle heading speeds of the vehicle use samples belonging to the value intervals of the corresponding different vehicle heading speeds are weighted, the N vehicle use samples are subjected to descending sorting according to the weighted vehicle heading speeds, and the vehicle use samples with descending sorting order within a preset sorting order range (for example, 70% before descending sorting) are taken as effective samples; for as effective sampleThe vehicle course speed included in each vehicle use sample is weighted by the weight of the value interval of the vehicle course speed to which the vehicle use sample belongs, and then the weighted vehicle course speeds are averaged to obtain the cruising speed v_a(ii) a In a similar weighted average method, the total cruising power P can be obtained from the total power of the vehicles included in each vehicle use sample as a valid sample_aAnd deriving a cruising power ratio p from a vehicle power ratio included in each of the vehicle use samples as valid samples_P[v_a]。

For another example, when the vehicle usage scenario is a flat ground acceleration scenario, the vehicle usage characteristic data includes power ratios corresponding to different vehicle heading speeds. In this scenario, the vehicle usage characteristic data may be obtained by classifying the vehicle usage samples corresponding to the vehicle usage scenario according to a preset value interval of the vehicle heading speed, and then averaging the vehicle power ratios included in the classified vehicle usage samples corresponding to the values of different vehicle heading speeds. Assuming that N vehicle use samples correspond to a flat ground acceleration scene, dividing the N vehicle use samples according to the vehicle heading speed of each vehicle use sample based on a preset value interval (for example, 1 km/h) of the vehicle heading speed to obtain vehicle use samples belonging to each different vehicle heading speed value interval; each value interval of different vehicle heading speeds corresponds to a value of the vehicle heading speed (for example, if the vehicle heading speed is separated from 0 km/h as a starting point and the value interval of the 3 rd vehicle heading speed corresponds to 3 km/h), vehicle use samples belonging to the value interval of each vehicle heading speed are sorted in a descending order, vehicle power ratios included in the vehicle use samples (except for extreme samples sorted outside the preset sorting range) with the sorting order within a preset sorting range (for example, the middle position is 70%) are averaged, and the average value is obtained and used as a vehicle power ratio control p corresponding to the value interval of the vehicle heading speed corresponding to the vehicle heading speed_P[v_h]。

For another example, when the vehicle use scene is a flat ground turning scene, the vehicle use characteristic data includes vehicle speed limits corresponding to different vehicle running bend angles. In this scenario, the vehicle use characteristic data may be obtained by classifying vehicle use samples corresponding to the vehicle use scenario according to preset vehicle corner value intervals, and averaging vehicle heading speeds included in the classified vehicle use samples corresponding to different vehicle corner values. Assuming that N vehicle use samples correspond to a flat ground turning scene, dividing the N vehicle use samples according to the vehicle angle of each vehicle use sample based on a preset value interval (for example, 1 radian) of the vehicle angle to obtain the vehicle use samples belonging to each different value interval of the vehicle angle; the value interval of each different vehicle corner corresponds to the value of one vehicle corner (for example, assuming that the vehicle corners are separated by taking 0 radian as a starting point and the value of the vehicle corner corresponding to the value interval of the 3 rd vehicle corner is 3 radians), after the vehicle use samples belonging to the value interval of each vehicle corner are sorted in a descending order, the vehicle heading speeds included in the vehicle use samples (except the extreme samples sorted outside the preset sorting range) with the sorting order within the preset sorting range (for example, the middle position is 70%) are averaged, and the average value is obtained as the vehicle speed limit v [ R ] corresponding to the value of the vehicle corner corresponding to the value interval of the vehicle corner.

For another example, when the vehicle usage scenario is a sloping road driving scenario, the vehicle usage characteristic data includes a vehicle power ratio corresponding to a different vehicle driving gradient. Under the scene, after the vehicle use characteristic data can classify the vehicle use samples corresponding to the vehicle use scene at preset vehicle running gradient value intervals, vehicle power ratios included in the classified vehicle use samples corresponding to different vehicle running gradient values are averaged to obtain the vehicle use characteristic data. Assuming that N vehicle use samples correspond to a slope driving scene, based on a preset value interval (for example, 0.25%) of the vehicle gradient, the N vehicle use samples are divided according to the vehicle gradient of each vehicle use sample to obtain the value interval belonging to each different vehicle gradientThe vehicle usage sample of (1); each of the different vehicle gradient value intervals corresponds to one vehicle gradient value (for example, assuming that the vehicle gradient value corresponding to the 3 rd vehicle gradient value interval is 0.75%) and is separated by taking 0 as a starting point, after sorting the vehicle use samples belonging to each vehicle gradient value interval in a descending order, averaging the vehicle power ratios included in the vehicle use samples (excluding the extreme samples sorted outside the preset sorting range) with the sorting order within the preset sorting range (for example, the middle position is 70%), and obtaining an average value as the vehicle power ratio p corresponding to the vehicle gradient value interval_P[S]。

In practical applications, the process of using the vehicle by the user may experience a long road, and the process may bring about changes in terrain, vehicle state, user' S own requirements, and the like, so in order to further improve the accuracy of obtaining the vehicle usage characteristic data from the vehicle usage samples, the step S2130 of obtaining the vehicle usage characteristic data according to the vehicle usage sample sequence obtained from the historical observation sample sequence obtained during the process of using the vehicle by the user may be classified according to the travel distance corresponding to the vehicle usage sample, and each classified vehicle usage sample set is executed separately.

Each vehicle usage sample has a corresponding distance traveled. For example, the vehicle usage sample includes a vehicle heading speed, and the vehicle usage sample is obtained from a historical observation sample having a corresponding sampling interval, and a vehicle travel time (a time difference from a sampling start time point) at which the vehicle usage sample is obtained may be determined, and a vehicle travel distance corresponding to the vehicle usage sample may be determined from the vehicle heading speed and the vehicle travel time.

The vehicle control method provided in the present embodiment further includes:

classifying the vehicle use samples in the vehicle use sample set based on a preset travel distance grade to obtain a plurality of classified vehicle use sample sets consisting of vehicle use samples corresponding to different travel distance grades, and respectively executing the step of acquiring the vehicle use characteristic data according to each classified vehicle use sample set.

The driving distance grade can be set according to specific application requirements or application scenarios, for example, the driving distance grade is set to be a driving distance grade every 3 power with 0 km as a starting point.

In an actual application process, due to factors such as terrain change, vehicle state change and user demand change in a vehicle using process of a user, in order to facilitate more efficient and accurate extraction of vehicle use characteristic data corresponding to different vehicle use scenes from more discrete vehicle use samples, the vehicle use samples obtained according to the historical observation sample sequence may include a plurality of vehicle use samples, clustering is performed according to scene classification parameters for dividing the vehicle use scenes, the vehicle use samples are clustered, a vehicle use sample set including the plurality of vehicle use samples and belonging to different clusters is obtained, and step S2130 of the vehicle use characteristic data is respectively executed.

Correspondingly, the vehicle control method provided in the present embodiment further includes:

according to preset scene classification parameters, clustering all vehicle use samples in the vehicle use sample set to obtain a vehicle use sample set which is formed by a plurality of clustered vehicle use samples with clustering center samples, and respectively executing the step of obtaining vehicle use characteristic data according to each clustered vehicle use sample set.

The scene classification parameter is a parameter for dividing a vehicle usage scene. For example, the scene classification parameters include at least a vehicle heading speed, a vehicle traveling gradient, and a vehicle traveling angle.

The clustering process may adopt a hierarchical clustering method, for example, a sample distance (e.g., manhattan distance, chebyshev distance, etc.) reflecting a sample correlation degree is calculated between any two vehicle use samples in the vehicle use sample sets before clustering, dynamic clustering is performed according to the sample distance, a plurality of vehicle use samples belonging to different clusters and respectively corresponding to different clustering center samples are obtained, and a plurality of vehicle use sample sets are correspondingly formed. Each clustered vehicle usage sample set has a cluster center sample belonging to a cluster. In this example, the step of obtaining the vehicle usage characteristic data may also be performed by clustering the vehicle usage samples included in the vehicle usage sample set to the vehicle usage scene according to the vehicle usage scene corresponding to the clustering center sample of each vehicle usage sample set.

Step S2140, a vehicle use habit model is constructed according to the acquired vehicle use characteristic data.

In this example, the step of constructing the vehicle use habit model includes:

after a group of vehicle use characteristic data is obtained each time, vehicle use average samples are obtained according to all the obtained vehicle use characteristic data, and the vehicle use average samples are used as vehicle use habit models.

It should be understood that each group of vehicle usage characteristic data corresponds to different vehicle usage scenarios, and therefore, after one group of vehicle usage characteristic data is acquired each time, all vehicle usage characteristic data acquired in the vehicle usage scenario may be averaged for the type of vehicle usage scenario corresponding to the vehicle usage characteristic data to obtain a vehicle usage average sample in the vehicle usage scenario, so as to obtain vehicle usage average samples in different vehicle usage scenarios as the vehicle usage habit model.

In practical applications, limited by the processing capability of the server, after receiving a vehicle use request of a target user, a processing resource requirement related to obtaining a vehicle use habit model of the target user in real time is large, and there may be a processing delay, and therefore, the vehicle control method provided in this embodiment may further include:

the step of obtaining a vehicle usage habit model is performed each time the target user uses the vehicle, and the vehicle usage habit model is stored for reading at a later time when a vehicle usage request is received.

By acquiring the vehicle use habit model in advance before receiving the vehicle use request and storing and reading the vehicle use habit model, the real-time processing resource consumption of receiving the vehicle use request of the target user can be reduced, and the processing efficiency is improved.

The vehicle travel route is a route leading to a target user to reach a desired destination by vehicle travel.

In one example, the vehicle use request includes at least information indicating a destination of the target user, such as longitude and latitude coordinates of the destination. Correspondingly, the step of acquiring the vehicle running path comprises the following steps: steps S21011-S21012.

Step S21011, according to the acquired vehicle state information of the available vehicles and the destination of the target user, determining a candidate vehicle driving path and a candidate vehicle corresponding to the candidate vehicle driving path, and providing the candidate vehicle driving path and the candidate vehicle driving path to the client for the target user to select.

An available vehicle is a vehicle in an available state near the target user. For example, a vehicle in an available state within a preset geographic radius (e.g., 50 meters) centered at the location of the target user. The available vehicles may be determined based on geographic location information of the target user obtained from the client of the target user and vehicle status information obtained from the vehicle engaged in operation.

The vehicle state information includes at least a geographic location of the vehicle and a current battery level of the vehicle. The vehicle state information may be obtained from the vehicle by querying the vehicle or by periodic reporting by the vehicle.

According to the destination of the target user and the geographic position of the available vehicle, the driving path for each available vehicle to reach the destination can be respectively obtained through a common path planning algorithm or a path planning function provided in a map service, the driving path of the candidate vehicle and the corresponding candidate vehicle are selected according to a preset driving path selection rule, for example, the shortest driving path, simpler terrain transformation of the driving path, smaller vehicle electric quantity consumption and the like, and the driving path of the candidate vehicle and the candidate vehicle can be selected according to whether the current battery electric quantity of each available vehicle is estimated to be enough to support the driving path reaching the destination or whether a battery replacement point exists in the driving path, and the like.

The candidate vehicle driving path at least comprises a driving route and driving terrain change. The travel route is a route for the target user to reach the destination using the candidate vehicle. The driving terrain variation is the terrain variation existing in the driving route, and can comprise flat land distance, gradient magnitude, turning times, turning positions and the like.

S21012, according to the instructions of the client, determining a vehicle driving path selected by the target user from the candidate vehicle driving paths and a corresponding target vehicle.

The target user can check the candidate vehicle running path and the candidate vehicle corresponding to the candidate vehicle running path through the used client, corresponding selection operation is carried out to select the vehicle running path and the target vehicle meeting the self requirement, the client indicates the selection of the target user to the server in a message sending mode and the like, and the server can determine the vehicle running path selected by the target user from the candidate vehicle running path and the corresponding target vehicle to obtain the vehicle running path.

In another example, the vehicle-use request includes at least information indicating a destination of the target user (e.g., longitude and latitude coordinates of the destination, etc.) and information indicating a target vehicle that the target user desires to use (e.g., a vehicle unique identification of the target vehicle, etc.). Correspondingly, the step of acquiring the vehicle running path comprises the following steps: steps S21021-S21022.

Step S21021, determining a candidate vehicle travel path according to the acquired vehicle state information of the target vehicle and the destination of the target user, and providing the candidate vehicle travel path to the client for the target user to select.

According to the destination of the target user and the geographic position of the target vehicle, one or more driving paths for the target vehicle to reach the destination can be obtained through a common path planning algorithm or a path planning function provided in a map service, a candidate vehicle driving path is selected according to a preset driving path selection rule, for example, the driving path is shortest, the terrain transformation of the driving path is simple, the electric quantity consumption of the vehicle is low, and the like, and the candidate vehicle driving path can be selected according to whether the current electric quantity of the battery of the target vehicle is estimated to be enough to support the driving path reaching the destination or whether a battery replacement point exists in the driving path, and the like.

Step S21022, determining a vehicle driving path selected by the target user from the candidate vehicle driving paths according to the instruction of the client.

The target user can check the candidate vehicle running paths through the used client, corresponding selection operation is carried out to select the vehicle running paths meeting the self requirements, the client indicates the selection of the target user to the server in a message sending mode and the like, and therefore the server can obtain the vehicle running paths selected by the target user from the candidate vehicle running paths.

After the vehicle usage habit model and the vehicle travel path of the target user are acquired in step S2100, the process proceeds to:

step S2200, determining at least one candidate control parameter set according to the vehicle use habit model and the vehicle running path, and sending the candidate control parameter set to the client so that the target user can select the target control parameter set from the candidate control parameter set.

At least a vehicle speed control parameter for controlling the vehicle speed and a vehicle power control parameter for controlling the vehicle power are included in the candidate control parameter set.

The vehicle speed control parameters may include a vehicle cruising speed, a vehicle speed limit (turning speed limit) corresponding to different vehicle running angles, and the like. The vehicle power control parameters may include a vehicle cruising target total power, a vehicle cruising power ratio, a power ratio corresponding to different vehicle heading speeds, a vehicle power ratio corresponding to different vehicle traveling grades, and the like.

In one example, the vehicle usage habit model includes a vehicle usage average sample under a preset vehicle usage scene, and the vehicle travel path includes at least a travel route and a travel terrain variation, and step S2200 may include: steps S2210-S2220.

Step S2210, determining at least one candidate scene combination corresponding to the vehicle driving path according to preset scene division parameters, the vehicle use habit model and the vehicle driving path.

The candidate scene combination comprises all vehicle use scenes expected to be experienced by the target user when the target user drives the vehicle driving path.

In this example, the scene division parameter is a parameter for dividing the usage scene of the vehicle, and may be set according to specific requirements, for example, the scene division parameter includes a vehicle traveling gradient, a vehicle traveling bend angle, and the like. According to the scene division parameters, the driving route included in the driving path of the vehicle, the driving terrain change and the vehicle use average sample included in the vehicle use habits under different vehicle use scenes, a plurality of vehicle use scenes possibly experienced by the driving path of the vehicle can be determined, and at least one or more candidate scene combinations are obtained. For example, the distance in the vehicle driving path is short, the terrain is all flat and almost has no change, the vehicle usage habit model comprises samples of average vehicle usage in a flat ground acceleration scene and a flat ground cruise scene, and it can be determined that the candidate scene combination can comprise two combinations of the flat ground acceleration scene and the flat ground cruise scene.

Step S2220, for each candidate scene combination, obtaining a vehicle usage average sample corresponding to the vehicle usage scene included in the candidate scene combination from the vehicle usage habit model to determine a vehicle speed control parameter and a vehicle power control parameter corresponding to the vehicle usage scene, so as to obtain a candidate control parameter set corresponding to the candidate scene combination.

The vehicle use habit model comprises average vehicle use samples under different vehicle use scenes. The average vehicle usage sample can be obtained according to vehicle usage characteristic data obtained under different vehicle usage scenarios, the vehicle usage characteristic data at least comprises characteristic data related to vehicle speed control (such as vehicle heading speed) and characteristic data related to vehicle power control (such as vehicle total power and vehicle power ratio), and the corresponding average vehicle usage sample comprises sample data related to vehicle speed control and sample data related to vehicle power control. According to the vehicle use scenes included in the candidate scene combination, corresponding vehicle use average samples can be correspondingly obtained from the vehicle use habit model, and according to the fact that the vehicle use average samples include sample data related to vehicle speed control and sample data related to vehicle power control, vehicle speed control parameters and vehicle power control parameters corresponding to the vehicle use scenes are determined, and a candidate control parameter set corresponding to the candidate scene combination is obtained.

In this example, a plurality of candidate control parameter sets may be preset according to vehicle usage habit models, historical experiences and application requirements of a plurality of users, each candidate control parameter set corresponds to a vehicle usage type, and for example, the candidate control parameter sets include a sports type that is expected to maintain a high movement speed and a low power ratio, a sightseeing type that is expected to maintain a smooth movement speed, a power saving type that requires general electric power assistance, a power saving type that requires strong electric power assistance, and the like Giving the user a choice.

After step S2200, the process proceeds to:

and step S2300, configuring the target vehicle used by the target user according to the target control parameter set indicated by the client to realize the control of the target vehicle.

The server provides the candidate control parameter set for the target user through the client for selection, the client indicates the target control parameter set corresponding to the selection operation of the user to the server in a message sending mode and the like after receiving the selection operation (such as checking, clicking, editing and the like) of the target user, and the server can configure the target vehicle used by the target user according to the vehicle speed control parameter and the vehicle power control parameter which are included in the target control parameter set indicated by the client, so that the target vehicle runs under the control of the vehicle speed control parameter and the vehicle power control parameter, and the control of the target vehicle is achieved.

In this embodiment, the server provides the candidate control parameter set to the target user through the client for selection, the target user may modify a specific vehicle speed control parameter or vehicle power control parameter in the selected target control parameter set through a configuration interface provided by the client after selection so as to better meet the own requirements, and the client indicates a new target control parameter set obtained after modification to the server so as to configure the target vehicle by the server.

In one example, a battery replacement location of a target vehicle used by a target user may also be included in the vehicle travel path.

The vehicle driving path comprises a battery replacement point of the target vehicle, and the target user can be guided to replace the battery by self at the battery replacement point in the process of driving to the destination by using the target vehicle.

In this example, the vehicle control method further includes:

when the target vehicle is determined to finish the battery replacement at the battery replacement place in the vehicle driving path, the corresponding reward value is provided for the target user according to the battery replacement place and the vehicle state information before the target vehicle is not used.

The vehicle state information of the target vehicle includes at least a geographical location of the vehicle and a current amount of power of the vehicle.

In this case, the battery replacement location may be a location corresponding to a charging cabinet providing a battery available for replacement, the server may determine that the target vehicle completes battery replacement at the battery replacement location by performing communication interaction with the charging cabinet and the target vehicle, determining that an old battery of the target vehicle is stored in the charging cabinet and a new battery provided by the charging cabinet is inserted into the target vehicle, or the server may determine that the target vehicle completes battery replacement at the battery replacement location by performing communication interaction with the target vehicle, determining that an old battery in the target vehicle is replaced with a new battery provided by the battery replacement location, and so on.

In this example, the reward value to be provided to the target user may be determined based on the amount of power of the target vehicle before it is not used and the distance between the geographical location of the target vehicle before it is not used and the battery replacement location, for example, the lower the amount of power of the target vehicle before it is not used, the higher the reward value provided to the target user, the greater the distance between the geographical location of the target vehicle before it is not used and the battery replacement location, the higher the reward value provided to the target user, and the like. The reward value may also be provided to the target user based on the cumulative number of times the battery is replaced by the target user, e.g., the greater the number of times, the higher the reward value provided, etc.

In this example, the reward value provided to the target user may be a user credit, a vehicle usage discount, a vehicle usage red envelope, or the like.

When the battery replacement is completed at the battery replacement place indicated by the target user in the vehicle running path, the reward value is provided for the user, the user can be effectively guided to complete the battery replacement in the vehicle using process by self, the user vehicle use experience is prevented from being influenced due to the fact that the vehicle lacks electric quantity in the vehicle using process, and meanwhile, the labor cost and the time cost caused by the fact that the battery replacement is performed through vehicle operators in the vehicle operation process can be reduced.

< Server >

In the present embodiment, there is also provided a server 200 for implementing control of a vehicle that converts an amount of electric power output from a battery provided in the vehicle into power required for at least partial travel, for example, a vehicle 1300 shown in fig. 1.

The server 200, as shown in fig. 4, includes:

a memory 210 for storing executable instructions;

a processor 220, configured to operate the server according to the control of the executable instruction, and execute the vehicle control method provided in this embodiment.

The server 200 may be any electronic device that provides a data management server, such as a blade server, a cloud server, and the like. The server 200 may also include further devices, for example, a server 1100 as shown in fig. 1.

It should be understood by those skilled in the art that the server 200 may also be any device that can implement the vehicle control method provided in the present embodiment, and the server 200 may be implemented in various ways. For example, server 200 may be implemented by an instruction configuration processor. For example, the server 200 may be implemented by storing instructions in ROM and reading the instructions from ROM into a programmable device when the device is started. For example, the server 200 may be consolidated into a dedicated device (e.g., ASIC). The server 200 may be divided into separate units or may be implemented by combining them together. The server 200 may be implemented in one of the various implementations described above, or may be implemented in a combination of two or more of the various implementations described above.

The embodiments of the present invention have been described above with reference to the drawings, and according to the embodiments, a vehicle control method and a server are provided, where when a user has a vehicle use requirement, a vehicle use habit model and a vehicle driving path of the user are obtained to determine a candidate control parameter set including a vehicle speed control parameter for controlling a vehicle speed and a vehicle power control parameter for controlling a vehicle power, the candidate control parameter set is provided for the user to select, and according to a target control parameter set selected by the user, a vehicle used by the user is configured to control the vehicle, and a vehicle control parameter adapted to a vehicle use habit and an actual vehicle driving required scene of the user is provided for the user to select, so as to adaptively meet the personalized vehicle use requirement of the user, and improve the vehicle use experience of the user.

< second embodiment >

In the present embodiment, there is provided a vehicle system 500, as shown in fig. 5, including:

the server 200 provided in the first embodiment;

a client 300;

and a vehicle 400.

The client 300 is any electronic device that can provide a vehicle use service, for example, a mobile phone in which an application providing a vehicle use server is installed. Client 400 may have various implementations, such as client 1200 shown in FIG. 1.

In one example, the client may be as shown in fig. 5, including:

a display device 310;

a memory 320 for storing executable instructions;

the processor 330, configured to execute the client 200 according to the executable instructions, performs the following method, including: steps S3100-S3300.

In step S3100, a vehicle use request from a target user is transmitted to the server 200.

In this example, a corresponding vehicle use request may be generated by providing a vehicle use interface for a user to input a destination and providing available vehicles in proximity for selection by the user based on the user input destination.

Step S3200, receiving the candidate control parameter set sent by server 200, and displaying the candidate control parameter set to the target user through display device 310 for selection.

Wherein each candidate control parameter set at least comprises a vehicle speed control parameter for controlling the vehicle speed and a vehicle power control parameter for controlling the vehicle power. The manner of obtaining the candidate control parameter set is described in detail in the first embodiment, and is not described herein again.

In step S3300, in response to a selection operation by a target user, a target control parameter set corresponding to the selection operation is indicated to a server.

The selection operation of the target user can be operations such as checking, clicking, editing and the like, the client can indicate a target control parameter set corresponding to the selection operation of the user to the server in a message sending mode and the like, so that the server is triggered to configure a target vehicle used by the target user according to a vehicle speed control parameter and a vehicle power control parameter which are included in the target control parameter set indicated by the client, the target vehicle is made to run according to the control of the vehicle speed control parameter and the vehicle power control parameter, the control of the target vehicle is achieved, the running of the target vehicle meets the vehicle use requirement of the user, and the vehicle use experience of the user is improved.

In this example, the client may further provide a configuration interface for the user to modify a specific vehicle speed control parameter or vehicle power control parameter in the selected target control parameter set so as to better meet the own requirements, and then indicate a new target control parameter set obtained after modification to the server so as to configure the target vehicle by the server.

The vehicle 400 is any vehicle that can provide at least part of the running power by the amount of electric power output from a battery provided to the vehicle. For example, the vehicle 400 may be an electric automobile, an electric scooter, an electric bicycle, or the like. The vehicle 400 may have various physical forms, such as a vehicle 1300 as shown in FIG. 1.

In one example, a vehicle 400, as shown in FIG. 5, includes:

a battery 410;

a memory 420 for storing executable instructions;

a processor 430 for operating the vehicle 400 according to the executable instructions, performing a method comprising:

receiving the target control parameter set received by the server 200 configures itself to implement the control of itself by the server 200.

Wherein the target control parameter set at least comprises a vehicle speed control parameter for controlling the vehicle speed and a vehicle power control parameter for controlling the vehicle power.

The specific method for the server 200 to obtain the target control parameter set is described in detail in the first embodiment, and is not described herein again.

The vehicle 300 configures itself according to the target control parameter set adapted to the vehicle use requirement of the user acquired by the server 200, so that the vehicle control in the vehicle driving process can meet the personalized vehicle use requirement of the user, and the vehicle use experience of the user is improved.

The vehicle control method implemented by the vehicle system 500 provided in the present embodiment will be further illustrated with reference to fig. 6.

In this example, the vehicle 400 is an electric power-assisted vehicle, the server 200 is a background server that supports management and operation functions necessary for providing a vehicle use service, and the client 300 is a mobile phone to which an APP for providing a vehicle use service is installed.

As shown in fig. 6, the vehicle use method includes: steps S501-S506.

In step S501, the target vehicle 400 reports the current vehicle state information to the server 300.

It should be understood that the target vehicle 400 and other vehicles 400 (not shown) report their own vehicle status information to the server.

The vehicle status information includes at least the current geographic location of the vehicle and the current battery level of the vehicle.

In step S502, the client 300 receives the destination input by the target user, and transmits a vehicle use request to the server 300.

The vehicle use request comprises the destination of the target user.

In step S503, the server 300 receives the vehicle use request, obtains the vehicle use habit model and the vehicle driving path of the target user, and determines at least one candidate control parameter set.

The steps of obtaining the vehicle usage habit model and the vehicle driving path of the target user and determining at least one candidate control parameter set are described in detail in the first embodiment, and are not described herein again.

In step S504, the server 300 provides the candidate parameter set to the client 200 for the target user to select the target control parameter set.

In step S505, the client 200 indicates the target control parameter set selected by the target user to the server 300.

In step S506, the server 300 configures the target vehicle 400 according to the target control parameter set.

Based on the vehicle control method shown in fig. 6, an example of the vehicle control method in a specific application scenario may be given.

For example, when xiaoming wants to go from a place a to a place B and wants to stay at the place C for 10 minutes, the xiaoming inputs a starting place, a destination and a midway point through a used mobile phone with an APP of a vehicle use service, the mobile phone generates a vehicle use request and sends the vehicle use request to a server to obtain a candidate vehicle driving route and a corresponding candidate vehicle and show the candidate vehicle to the xiaoming, the xiaoming obtains 3 vehicles around the xiaoming, wherein 2 vehicles have sufficient electric quantity, 1 vehicle needs to be subjected to midway battery replacement, and obtains 3 candidate driving routes, the xiaoming selects a route place C as a target vehicle of which the vehicle driving route of a battery replacement place corresponds to which the battery needs to be replaced, and the mobile phone indicates the vehicle driving route and the target vehicle to the server.

The server obtains a Xiaoming vehicle use habit model, finds that the Xiaoming selects a cruising speed of 15km/h more, but the speed requirements are various, the riding is more flexible, the pedaling frequency and the pedaling force which are relaxed after the speed is rapidly increased are favored, the riding type bicycle belongs to a sports rider, and the vehicle running path selected by the Xiaoming has no larger ramp but has more intersections. In summary, the server provides a candidate control parameter set including a target cruising speed of 15km/h and reflecting more sensitive force feedback according to the method provided in the first embodiment, and provides the candidate control parameter set for the Xiaoming selection, the Xiaoming selection is not modified, the riding is started, the mobile phone indicates the candidate control parameter set as the target control parameter set to the server, and the server immediately sends the target control parameter set to the target vehicle to control the target vehicle to run.

The riding process can be easily kept at 15km/h, the acceleration is flexible after the vehicle is parked at the intersection, the riding distance is long, the riding process is very comfortable because the battery replacing place included in the vehicle running path is selected to replace a battery with sufficient electric quantity, and the whole riding process is very comfortable, and because the battery replacing task is completed in the midway, when the riding is finished, the server discounts the cost provided by the riding process: the riding fee enjoys the reward of 7 folds.

The vehicle system provided in the embodiment has been described above with reference to the drawings and examples, the vehicle system includes a server, a client and a vehicle, the server may receive a vehicle usage request sent by the client from a user, obtain a vehicle usage habit model and a vehicle driving path of the user, determine a candidate control parameter set including a vehicle speed control parameter for controlling a vehicle speed and a vehicle power control parameter for controlling a vehicle power, provide the candidate control parameter set to the user through the client for selection, configure the vehicle used by the user to control the vehicle according to a target control parameter set selected by the user and indicated by the client, provide the vehicle control mode adapted to the vehicle usage habit and an actual vehicle driving scene for the user to select, and adaptively meet the personalized vehicle usage requirement of the user, the vehicle using experience of the user is improved.

The present invention may be a system, method and/or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied therewith for causing a processor to implement various aspects of the present invention.

The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.

The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.

The computer program instructions for carrying out operations of the present invention may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, aspects of the present invention are implemented by personalizing an electronic circuit, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA), with state information of computer-readable program instructions, which can execute the computer-readable program instructions.

Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.

These computer-readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.

The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions. It is well known to those skilled in the art that implementation by hardware, by software, and by a combination of software and hardware are equivalent.

Having described embodiments of the present invention, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein. The scope of the invention is defined by the appended claims.

Claims

1. A vehicle control method in which a vehicle converts an amount of electric power output from a battery provided in the vehicle into power required for at least partial travel, the method being implemented by a server, comprising:

configuring a target vehicle used by the target user according to the target control parameter set indicated by the client to realize control on the target vehicle;

the vehicle use request at least comprises information used for indicating the destination of the target user; the step of acquiring the vehicle driving path comprises the following steps:

and/or the presence of a gas in the gas,

the step of acquiring the vehicle driving path comprises the following steps:

2. The method of claim 1, wherein the step of obtaining a vehicle usage habit model for a target user comprises:

3. The method of claim 2, wherein the historical observation samples include vehicle speed, vehicle cadence, vehicle torque, vehicle output power, vehicle longitudinal acceleration, and vehicle axial angular velocity; the vehicle usage samples comprise total vehicle power, vehicle power ratio, vehicle heading speed, vehicle travel grade and vehicle travel angle;

wherein the data fusion process comprises:

4. The method of claim 2, wherein the vehicle usage samples include total vehicle power, vehicle power ratio, vehicle heading speed, vehicle grade, and vehicle cornering angle;

wherein,

5. The method of claim 2, wherein,

each of the vehicle usage samples has a corresponding distance traveled; the method further comprises the following steps:

and/or the presence of a gas in the gas,

the method further comprises the following steps:

6. The method of claim 2, wherein,

the step of constructing the vehicle use habit model comprises the following steps:

and/or the presence of a gas in the gas,

the method further comprises the following steps:

7. The method of claim 1, wherein,

the vehicle use habit model comprises a vehicle use average sample under a preset vehicle use scene; the vehicle driving path at least comprises a driving route and driving terrain change;

8. The method of claim 1, wherein,

the method further comprises the following steps:

9. A server for implementing control of a vehicle that converts an amount of electric power output from a battery provided in the vehicle into at least part of power required for traveling, the server comprising:

a first memory to store a first executable instruction;

a first processor for operating the server to perform the vehicle control method according to the control of the first executable instruction, according to any one of claims 1 to 8.

10. A vehicle system, comprising:

the server of claim 9;

a client;

and a vehicle.

11. The system of claim 10, wherein,

the client comprises:

a display device;

a second memory for storing second executable instructions;

a second processor configured to execute the client according to the second executable instruction, and perform the following method, including:

sending a vehicle use request from a target user to the server;

and/or the presence of a gas in the gas,

the vehicle includes:

a battery;

a third memory for storing third executable instructions;

a third processor for operating the vehicle according to the third executable instructions, performing a method comprising: