WO2022033487A1 - 驾驶模式的控制方法、装置、设备、程序及存储介质 - Google Patents

驾驶模式的控制方法、装置、设备、程序及存储介质 Download PDF

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Publication number
WO2022033487A1
WO2022033487A1 PCT/CN2021/111858 CN2021111858W WO2022033487A1 WO 2022033487 A1 WO2022033487 A1 WO 2022033487A1 CN 2021111858 W CN2021111858 W CN 2021111858W WO 2022033487 A1 WO2022033487 A1 WO 2022033487A1
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WIPO (PCT)
Prior art keywords
target
vehicle
driving mode
sample
state data
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PCT/CN2021/111858
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English (en)
French (fr)
Inventor
吴迪
杨雪静
韩松
刘寒
张峻
Original Assignee
长城汽车股份有限公司
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Application filed by 长城汽车股份有限公司 filed Critical 长城汽车股份有限公司
Priority to US18/020,308 priority Critical patent/US20230303081A1/en
Priority to EP21855539.9A priority patent/EP4195179A4/en
Publication of WO2022033487A1 publication Critical patent/WO2022033487A1/zh

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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
    • G08G1/0112—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from the vehicle, e.g. floating car data [FCD]
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/18—Propelling the vehicle
    • B60W30/182—Selecting between different operative modes, e.g. comfort and performance modes
    • G—PHYSICS
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    • G08G1/09—Arrangements for giving variable traffic instructions
    • G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
    • G08G1/096708—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control
    • B—PERFORMING OPERATIONS; TRANSPORTING
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    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
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    • G05D1/02—Control of position or course in two dimensions
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    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0217—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with energy consumption, time reduction or distance reduction criteria
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
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    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0287—Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling
    • G05D1/0291—Fleet control
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    • G08G1/096725—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control where the received information generates an automatic action on the vehicle control
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    • G08G1/096733—Systems involving transmission of highway information, e.g. weather, speed limits where a selection of the information might take place
    • G08G1/096741—Systems involving transmission of highway information, e.g. weather, speed limits where a selection of the information might take place where the source of the transmitted information selects which information to transmit to each vehicle
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    • G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
    • G08G1/096766—Systems involving transmission of highway information, e.g. weather, speed limits where the system is characterised by the origin of the information transmission
    • G08G1/096775—Systems involving transmission of highway information, e.g. weather, speed limits where the system is characterised by the origin of the information transmission where the origin of the information is a central station
    • H—ELECTRICITY
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    • H04W4/30—Services specially adapted for particular environments, situations or purposes
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    • B—PERFORMING OPERATIONS; TRANSPORTING
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    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0019—Control system elements or transfer functions
    • B60W2050/0022—Gains, weighting coefficients or weighting functions
    • B—PERFORMING OPERATIONS; TRANSPORTING
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    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0062—Adapting control system settings
    • B60W2050/0075—Automatic parameter input, automatic initialising or calibrating means
    • B60W2050/0095—Automatic control mode change
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2556/00—Input parameters relating to data
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2556/00—Input parameters relating to data
    • B60W2556/45—External transmission of data to or from the vehicle
    • B60W2556/50—External transmission of data to or from the vehicle of positioning data, e.g. GPS [Global Positioning System] data
    • B—PERFORMING OPERATIONS; TRANSPORTING
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    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
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    • B60W2756/00—Output or target parameters relating to data
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    • H—ELECTRICITY
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Definitions

  • the present disclosure relates to the technical field of electronic control, and in particular, to a driving mode control method, device, device, program, and storage medium.
  • the present disclosure aims to solve one of the technical problems in the related art at least to a certain extent.
  • the first objective of the present disclosure is to propose a driving mode control method, so as to solve the technical problems in the prior art that the driving mode control is inaccurate and the operation is troublesome.
  • the second object of the present disclosure is to provide a driving mode control device.
  • a third object of the present disclosure is to propose a computing processing device.
  • a fourth object of the present disclosure is to propose a computer program.
  • a fifth object of the present disclosure is to propose a computer-readable storage medium.
  • the embodiment of the first aspect of the present disclosure provides a driving mode control method, which is applied to a control platform, and the method includes:
  • the location information includes the target location
  • the target position determine the state data of at least one sample vehicle pre-stored by the control platform, where the sample vehicle is a vehicle that has traveled through the target position;
  • a target driving mode is determined according to the state data of the sample vehicle, and the target driving mode is sent to the target vehicle, so that the target vehicle runs according to the target driving mode.
  • determining the state data of at least one sample vehicle pre-stored by the control platform according to the target position includes:
  • Acquire state data of the sample vehicle where the state data includes a driving mode, power consumption, and fuel consumption of the sample vehicle when driving on the target road section.
  • determining a target driving mode according to state data of the sample vehicles includes:
  • the target driving mode is determined according to the energy consumption corresponding to each of the driving modes.
  • determining the average power consumption and average fuel consumption corresponding to each of the driving modes according to the state data of the plurality of sample vehicles includes:
  • the average power consumption corresponding to the first driving mode is determined according to the power consumption of each of the sample vehicles when driving in the first driving mode, and the first weighting coefficient corresponding to each of the sample vehicles.
  • a driving mode is any of the driving modes;
  • determining the energy consumption corresponding to each of the driving modes according to the average power consumption and average fuel consumption corresponding to each of the driving modes includes:
  • the method further includes: acquiring status data sent by the target vehicle, and storing the status data of the target vehicle.
  • the method before the storing of the state data of the target vehicle, the method further includes:
  • the power consumption included in the status data of the target vehicle is less than or equal to the power threshold, and the fuel consumption included in the status data of the target vehicle is less than or equal to the fuel threshold, determine the power consumption of the target vehicle. Status data is valid;
  • the storing of the state data of the target vehicle includes:
  • the state data of the target vehicle is valid, the state data of the target vehicle is stored.
  • the embodiment of the first aspect of the present disclosure proposes a driving mode control method.
  • the control platform first obtains position information sent by a target vehicle, where the position information includes the target position, and then determines at least one sample vehicle pre-stored by the control platform according to the target position.
  • the sample vehicle is a vehicle that has traveled through the target position.
  • the target driving mode is determined according to the status data of the sample vehicle, and the target driving mode is sent to the target vehicle, so that the target vehicle can drive according to the target driving mode.
  • the present disclosure determines the corresponding sample vehicle through the location information of the target vehicle, so as to determine the target driving mode suitable for the current driving of the target vehicle according to the state data of the sample vehicle, so that the target vehicle can drive according to the target driving mode.
  • the driver does not need to manually switch the driving mode, which can improve the accuracy and convenience of controlling the driving mode.
  • the embodiment of the second aspect of the present disclosure provides a driving mode control device, which is applied to a control platform, and the device includes:
  • an acquisition module configured to acquire position information sent by the target vehicle, where the position information includes the target position
  • a determination module configured to determine, according to the target position, the state data of at least one sample vehicle pre-stored by the control platform, where the sample vehicle is a vehicle that has traveled through the target position;
  • the control module is configured to determine a target driving mode according to the state data of the sample vehicle, and send the target driving mode to the target vehicle, so that the target vehicle runs according to the target driving mode.
  • the determining module includes:
  • a first determination submodule configured to determine the target road section to which the target position belongs
  • a second determination sub-module configured to determine the sample vehicle that has traveled through the target road section within a preset time period before the current moment
  • the acquisition sub-module is configured to acquire the state data of the sample vehicle, where the state data includes the driving mode, power consumption and fuel consumption of the sample vehicle when driving on the target road section.
  • control module is configured to:
  • the target driving mode is determined according to the energy consumption corresponding to each of the driving modes.
  • control module is configured to:
  • the average power consumption corresponding to the first driving mode is determined according to the power consumption of each of the sample vehicles when driving in the first driving mode, and the first weighting coefficient corresponding to each of the sample vehicles.
  • a driving mode is any of the driving modes;
  • control module is configured to:
  • the apparatus further includes:
  • the storage module is used for acquiring the status data sent by the target vehicle and storing the status data of the target vehicle.
  • the apparatus further includes:
  • a judging module configured to determine whether the state data of the target vehicle is valid according to a preset electric power threshold value and a fuel quantity threshold value before the state data of the target vehicle is stored;
  • the judging module is further configured to, if the power consumption included in the status data of the target vehicle is less than or equal to the power threshold, and the fuel consumption included in the status data of the target vehicle is less than or equal to the fuel consumption a threshold value, determining that the state data of the target vehicle is valid;
  • the storage module is used for:
  • the state data of the target vehicle is valid, the state data of the target vehicle is stored.
  • An embodiment of the second aspect of the present disclosure provides a driving mode control device.
  • the control platform first obtains position information sent by a target vehicle, where the position information includes the target position, and then determines at least one sample vehicle pre-stored by the control platform according to the target position.
  • the sample vehicle is a vehicle that has traveled through the target position.
  • the target driving mode is determined according to the status data of the sample vehicle, and the target driving mode is sent to the target vehicle, so that the target vehicle can drive according to the target driving mode.
  • the present disclosure determines the corresponding sample vehicle through the location information of the target vehicle, so as to determine the target driving mode suitable for the current driving of the target vehicle according to the state data of the sample vehicle, so that the target vehicle can drive according to the target driving mode.
  • the driver does not need to manually switch the driving mode, which can improve the accuracy and convenience of controlling the driving mode.
  • a computing processing device including:
  • One or more processors when the computer readable code is executed by the one or more processors, the computing processing device executes the driving mode control method proposed by the embodiment of the first aspect of the present disclosure.
  • a fourth aspect of the present disclosure provides a computer program, including computer-readable codes, which, when the computer-readable codes are executed on a computing and processing device, cause the computing and processing device to execute the first step of the present disclosure.
  • the control method of the driving mode proposed by the embodiment.
  • the fifth aspect of the present disclosure provides a computer-readable storage medium, in which the computer program proposed by the fourth aspect of the present disclosure is stored.
  • FIG. 1 is a flowchart of a method for controlling a driving mode according to an exemplary embodiment
  • FIG. 2 is a flowchart of another driving mode control method according to an exemplary embodiment
  • FIG. 3 is a flowchart of another driving mode control method according to an exemplary embodiment
  • FIG. 4 is a flowchart of another driving mode control method according to an exemplary embodiment
  • FIG. 5 is a flowchart of another driving mode control method according to an exemplary embodiment
  • Fig. 6 is a block diagram showing a control device of a driving mode according to an exemplary embodiment
  • FIG. 7 is a block diagram of a control device for another driving mode according to an exemplary embodiment
  • FIG. 8 is a block diagram of a control device for another driving mode according to an exemplary embodiment
  • FIG. 9 is a block diagram of a control device for another driving mode according to an exemplary embodiment.
  • FIG. 10 is a schematic structural diagram of a computing processing device according to an exemplary embodiment
  • Fig. 11 is a schematic diagram of a storage unit for portable or fixed program codes for implementing the method according to the present invention, according to an exemplary embodiment.
  • the application scenario can include a control platform and a vehicle, and the control platform and the vehicle can communicate through WLAN (English: Wireless Local Area Networks, Chinese: Wireless Local Area Network), Telematics (Chinese: Vehicle Information Service), V2X (English: Vehicle to Everything, Chinese: Internet of Vehicles), 4G (English: the 4th Generation mobile communication technology, Chinese: the fourth generation of mobile communication technology) and 5G (English: the 5th Generation mobile communication technology, Chinese: The fifth generation of mobile communication technology) A protocol to communicate to enable data transfer.
  • the control platform may be set on the server or on the terminal device, which is not specifically limited in the present disclosure.
  • Servers may include but are not limited to: physical servers, server clusters or cloud servers, etc.
  • Terminal devices may be mobile terminals such as tablet computers, smart TVs, PDAs (English: Personal Digital Assistants, Chinese: Personal Digital Assistants), portable computers, etc. It can be a stationary terminal such as a desktop computer.
  • the vehicle can be a car, but is not limited to a traditional car, a pure electric car or a hybrid car.
  • the driving mode control method and device provided by the present disclosure can also be applied to other types of motor vehicles or non-motor vehicles .
  • Fig. 1 is a flowchart of a method for controlling a driving mode according to an exemplary embodiment. As shown in Fig. 1 , the method is applied to a control platform and includes the following steps:
  • Step 101 Acquire location information sent by the target vehicle, where the location information includes the target location.
  • the radar such as millimeter wave radar, microwave radar
  • GPS English: Global Positioning System, Chinese: Global Positioning System
  • BDS English: BeiDou Navigation Satellite System
  • GPS English: BeiDou Navigation Satellite System, Chinese: Beidou satellite navigation system
  • the position information can include the target position, and can also include other information such as the current time.
  • the target location may include the street or national road where the vehicle (ie, the target vehicle) is located, and may also include the longitude and latitude where the target vehicle is located, which is not specifically limited in the present disclosure.
  • the position information can be sent to the control platform through the controller of the target vehicle, and the control platform obtains the position information.
  • the controller can be MCU (English: Microcontroller Unit, Chinese: Micro Control Unit), ECU (English: Electronic Control Unit, Chinese: Electronic Control Unit) or BCM (English: Body Control Module, Chinese: Body Controller) and so on. Only one controller can be set on the target vehicle to implement all the control logic of the target vehicle, or multiple controllers can be set to implement different control logics of the target vehicle respectively.
  • the target vehicle can be set to control the lights. Lighting controller, rescue controller for assisting safety rescue, etc.
  • the target vehicle sends the location information to the control platform, it can also send the identification code of the target vehicle to the control platform.
  • the identification code (English: Vehicle Identification Number, abbreviation: VIN) consists of a group of 17-digit alphanumerics (English letters and numbers) that conform to the standard (such as GB16735).
  • the identification code of each target vehicle is unique, that is, an identification The code can only uniquely identify a target vehicle. In this way, when there are multiple target vehicles sending position information to the control platform, the control platform can identify the obtained multiple position information according to the identification code of the target vehicle to determine the target vehicle corresponding to each position information.
  • the network connection state of the communication network between the target vehicle and the control platform can also be obtained. If the network connection status is normal, the location information and the identification code of the target vehicle can be directly sent to the control platform. If the network connection status is abnormal, the location information can be stored first, and then the network connection status can be continuously obtained. When the network connection status is normal, the location information and the identification code of the target vehicle are sent to the control platform, so that the control The platform obtains the location information corresponding to each target vehicle.
  • Step 102 determine the state data of at least one sample vehicle pre-stored by the control platform, where the sample vehicle is a vehicle that has passed the target position.
  • Step 103 Determine a target driving mode according to the state data of the sample vehicle, and send the target driving mode to the target vehicle, so that the target vehicle runs in accordance with the target driving mode.
  • the control platform may determine the state data of at least one sample vehicle from the pre-stored state data of a large number of vehicles according to the target location in the location information. It can be understood that the control platform receives a large number of state data uploaded by the vehicle in advance, and stores the state data. After the control platform receives the location information, it can screen the state data of a large number of vehicles according to the target location therein, so as to obtain the state data of at least one sample vehicle suitable for the target vehicle.
  • the sample vehicle is a vehicle that has traveled through the target position.
  • the state data may include the driving mode, power consumption, and fuel consumption of the sample vehicle when driving on the target road section, and may also include the time when the sample vehicle travels on the target road section, and the like.
  • the driving modes may include, for example, an Auto (Chinese: automatic) mode, an EV mode, a Sport mode, a Save mode, and an AWD (English: All-Wheel Drive, Chinese: full-time four-wheel drive) mode.
  • the position information and status data of the vehicle can be sent to the control platform, and the control platform can store the position information and status data of the vehicle.
  • the state data of a large number of vehicles stored in the preset database can be screened according to the target position to obtain one or more sample vehicles that have passed the target position, so as to obtain the status of each sample vehicle. data.
  • the sample vehicles can be analyzed according to the time when the sample vehicles traveled through the target location and a specified period (for example, from the current time to 3 days before the current time). The vehicle status data is filtered. If the time when the sample vehicle travels through the target position belongs to the specified time period, the state data of the sample vehicle can be retained. If the time when the sample vehicle passes the target position does not belong to the specified time period, the state data of the sample vehicle may be ignored or the state data of the sample vehicle may be deleted, which is not limited in the present disclosure.
  • the control platform After the control platform acquires the state data of the sample vehicles, it can determine the target driving mode according to the state data of each sample vehicle according to preset rules.
  • the preset rule may be, for example, a pre-established functional relationship or a model, or the like.
  • the target driving mode may be one or multiple (for example, two).
  • the most economical driving mode can be determined according to the state data of each sample vehicle, and then the most economical driving mode can be determined as the target driving mode, or the two most economical driving modes can be determined according to the state data of each sample vehicle, and then The two most economical driving modes are determined as the target driving modes.
  • the most frequently used driving mode may also be determined according to the state data of multiple sample vehicles, and then the most frequently used driving mode is determined as the target driving mode.
  • the control center determines the target driving mode, it can send the target driving mode to the target vehicle according to the identification code of the target vehicle, and the target vehicle receives the target driving mode.
  • the target driving mode is one
  • the controller can directly control the target vehicle according to the target driving mode to make the target vehicle drive according to the target driving mode.
  • Corresponding prompt information such as prompt information in the form of voice, is generated to prompt the driver of the target vehicle to switch the current driving mode to the target driving mode.
  • the controller can generate corresponding prompt information according to the multiple target driving modes, so that the driver of the target vehicle can drive in the multiple target driving modes.
  • a target driving mode suitable for the target vehicle is selected, so that the target vehicle drives according to the target driving mode selected by the driver.
  • the control platform first obtains the position information sent by the target vehicle, wherein the position information includes the target position, and then determines the status data of at least one sample vehicle pre-stored by the control platform according to the target position, and the sample vehicle is a vehicle that has driven.
  • the vehicle at the target position finally determines the target driving mode according to the state data of the sample vehicle, and sends the target driving mode to the target vehicle, so that the target vehicle runs according to the target driving mode.
  • the present disclosure determines the corresponding sample vehicle through the location information of the target vehicle, so as to determine the target driving mode suitable for the current driving of the target vehicle according to the state data of the sample vehicle, so that the target vehicle can drive according to the target driving mode.
  • the driver does not need to manually switch the driving mode, which can improve the accuracy and convenience of controlling the driving mode.
  • Fig. 2 is a flowchart showing another driving mode control method according to an exemplary embodiment. As shown in Fig. 2 , step 102 includes:
  • Step 1021 Determine the target road section to which the target position belongs.
  • Step 1022 Determine a sample vehicle that has traveled through the target road section within a preset time period before the current moment.
  • Step 1023 Acquire state data of the sample vehicle, where the state data includes the driving mode, power consumption, and fuel consumption of the sample vehicle when driving on the target road section.
  • the target road segment to which the target vehicle belongs may be determined according to the target position, and then a preset time period (eg, 48h) before the current moment may be determined.
  • a preset time period eg, 48h
  • the state data of the sample vehicles that have traveled through the target road section within the preset time period before the current time can be screened from the state data of multiple vehicles pre-stored in the control platform.
  • the state data may include the driving mode, power consumption, fuel consumption, etc. of the sample vehicle when driving on the target road section.
  • the location information of the vehicle and the travel time of each location can be stored in the preset database of the control platform, then the control platform can first determine the target road section, according to the target road section. A large amount of state data is filtered to obtain one or more sample vehicles that have traveled through the target road section, thereby obtaining the state data of each sample vehicle. Then, the travel time of each sample vehicle traveling through the target road section can be screened according to the preset time period before the current moment.
  • the travel time of the sample vehicle traveling through the target road section is within the preset time period before the current moment, it means that the road conditions of the target road section at the current moment are close to the road conditions when the sample vehicle traveled the target road section, so the reference value of the state data of the sample vehicle If it is relatively high, the state data of the sample vehicle can be retained at this time. If the driving time of the sample vehicle over the target road section is not within the preset time period before the current moment, it means that the road conditions of the target road section at the current moment may have changed, which is different from the road conditions when the sample vehicle traveled through the target road section. The reference value of the state data is relatively low. In this case, the state data of the sample vehicle may be ignored, or the state data of the sample vehicle may be deleted, which is not limited in the present disclosure.
  • Fig. 3 is a flowchart showing another driving mode control method according to an exemplary embodiment. As shown in Fig. 3, there are multiple driving modes, and there are multiple sample vehicles. Step 103 includes:
  • Step 1031 according to the state data of the plurality of sample vehicles, determine the average power consumption and the average fuel consumption corresponding to each driving mode.
  • Step 1032 Determine the energy consumption corresponding to each driving mode according to the average power consumption and average fuel consumption corresponding to each driving mode.
  • Step 1033 Determine the target driving mode according to the energy consumption corresponding to each driving mode.
  • the average power consumption and the average fuel consumption corresponding to each driving mode may be determined according to the state data of a plurality of sample vehicles. For example, the average power consumption and the average fuel consumption corresponding to each driving mode can be determined according to the maximum power consumption and the maximum fuel consumption of each sample vehicle, or the average power consumption and Average fuel consumption to determine the average battery consumption and average fuel consumption for each driving mode. Then, the energy consumption corresponding to each driving mode can be determined according to the average power consumption and the average fuel consumption corresponding to each driving mode. Then, the target driving mode can be determined according to the energy consumption corresponding to each driving mode. For example, the driving mode with the lowest energy consumption may be determined as the target driving mode. In another implementation manner, a preset number (eg, 3) driving modes with the lowest energy consumption may also be determined as the target driving mode. This is not specifically limited.
  • step 1031 may include:
  • the first weighting coefficient and the second weighting coefficient corresponding to the sample vehicle are determined according to the travel time of the sample vehicle traveling through the target road section.
  • the average power consumption corresponding to the first driving mode is determined, and the first driving mode is any driving mode model.
  • the average fuel consumption corresponding to the first driving mode is determined according to the fuel consumption of each sample vehicle when driving in the first driving mode and the second weighting coefficient corresponding to each sample vehicle.
  • the average power consumption and average fuel consumption corresponding to each driving mode for each sample vehicle, according to the state data of the sample vehicle, determine the power consumption of the sample vehicle when driving according to each driving mode. consumption and oil consumption. Then, the first weighting coefficient and the second weighting coefficient corresponding to the sample vehicle may be determined according to the travel time of the sample vehicle traveling through the target road section. The second weighting coefficient may be the same as the first weighting coefficient, or may be different from the second weighting coefficient. There may be multiple first weighting coefficients, and each first weighting coefficient corresponds to the power consumption of each sample vehicle in each driving mode. There may be multiple second weighting coefficients, and each second weighting coefficient corresponds to the fuel consumption of each sample vehicle in each driving mode.
  • the first weighting coefficient and the second weighting coefficient corresponding to each type of driving may be determined by querying a preset relationship table.
  • the preset relationship table the closer the travel time of the sample vehicle to the target road section in a certain driving mode is to the current time, the greater the first weighting coefficient (or the second weighting coefficient), and the travel time of the sample vehicle to travel through the target road section is greater.
  • the farther away from the current time the smaller the first weighting coefficient (or the second weighting coefficient), which can be understood as the first weighting coefficient (or the second weighting coefficient), and (current time - the travel time of the sample vehicle traveling through the target road segment) inversely proportional.
  • the determined sum of the plurality of first weighting coefficients is 1, and the sum of the plurality of determined second weighting coefficients is 1.
  • the average power consumption corresponding to the first driving mode can be determined according to the power consumption of each sample vehicle when driving in the first driving mode, and the first weighting coefficient corresponding to each sample vehicle, wherein the first driving mode is any A driving mode.
  • the average power consumption corresponding to each driving mode can be expressed as:
  • K 1 represents the first weighting coefficient corresponding to the first sample vehicle in each driving mode
  • K 2 represents the first weighting coefficient corresponding to the second sample vehicle in each driving mode
  • K S represents the S th
  • K 1 +K 2 +...+K S 1. If the S sample vehicles are arranged according to the travel time of the target road section from near to far, that is, the travel time of the first sample vehicle driving the target road section is closest to the current time, the second sample vehicle is second, and so on, then K 1 >K 2 >... >K S .
  • the average fuel consumption corresponding to the first driving mode can be determined according to the fuel consumption of each sample vehicle when driving in the first driving mode and the second weighting coefficient corresponding to each sample vehicle.
  • the average fuel consumption corresponding to each driving mode can be expressed as:
  • F 1 represents the second weighting coefficient corresponding to the first sample vehicle in each driving mode
  • F 2 represents the second weighting coefficient corresponding to the second sample vehicle in each driving mode
  • an implementation manner of determining the energy consumption corresponding to each driving mode may include:
  • Step 1) Determine the electricity consumption time and oil consumption time of each sample vehicle.
  • Step 2) Determine the third weighting coefficient and the fourth weighting coefficient according to the electricity consumption time and oil consumption time of each sample vehicle.
  • Step 3 Take the product of the average power consumption corresponding to each driving mode and the third weighting coefficient, and the sum of the product of the average fuel consumption corresponding to each driving mode and the fourth weighting coefficient as the energy corresponding to this driving mode consume.
  • the electricity consumption time and the fuel consumption time of each sample vehicle may be continuously determined, and then according to the electricity consumption time of each sample vehicle Time and oil use time, determine the third weighting factor (eg M1) and the fourth weighting factor (eg M2).
  • the third weighting coefficient may be, for example, the ratio of the electricity consumption time of all the sample vehicles to the sum of the electricity consumption time and the fuel consumption time of all the sample vehicles
  • the fourth weighting coefficient may be, for example, the fuel consumption time of all the sample vehicles to the total of the sample vehicles. The ratio of the sum of electricity time and oil time.
  • the product of the average power consumption corresponding to each driving mode and the third weighting coefficient can be calculated as the product of the average fuel consumption corresponding to each driving mode and the fourth weighting coefficient. and, as the energy consumption corresponding to this driving mode.
  • Fig. 4 is a flowchart showing another driving mode control method according to an exemplary embodiment. As shown in Fig. 4 , the method further includes:
  • Step 104 acquiring the status data sent by the target vehicle.
  • Step 105 store the state data of the target vehicle.
  • control platform can also acquire the status data sent by the target vehicle, and store the status data of the target vehicle in a preset database. For example, after the control platform obtains the state data of the target vehicle, it can store the state data of the target vehicle in a preset database according to the identification code of the target vehicle, so that the control platform can determine the driving modes of other vehicles according to the state data.
  • Fig. 5 is a flowchart showing another driving mode control method according to an exemplary embodiment. As shown in Fig. 5, before step 105, the method further includes:
  • Step 106 Determine whether the state data of the target vehicle is valid according to the preset electric power threshold and fuel quantity threshold.
  • Step 107 If the power consumption included in the state data of the target vehicle is less than or equal to the power threshold, and the fuel consumption included in the state data of the target vehicle is less than or equal to the fuel threshold, it is determined that the state data of the target vehicle is valid.
  • Step 105 includes:
  • the state data of the target vehicle is valid, the state data of the target vehicle is stored.
  • the power consumption and the fuel consumption included in the state data of the target vehicle may be judged according to the preset power threshold and the fuel threshold, so as to determine whether the state data of the target vehicle is valid.
  • the preset power threshold may be, for example, 20 kWh/100 kilometers
  • the preset fuel threshold may be, for example, 10 liters/100 kilometers. If the power consumption included in the status data of the target vehicle is less than or equal to the power threshold, and the fuel consumption included in the status data of the target vehicle is less than or equal to the fuel threshold, indicating that the status data of the target vehicle is reasonable, then the target vehicle can be determined Status data is valid.
  • the status data uploaded by the target vehicle may be abnormal, so it can be determined that the status data of the target vehicle is invalid. If the state data of the target vehicle is valid, the state data of the target vehicle may be stored. If the state data of the target vehicle is invalid, the state data can be discarded, and then the state data of the target vehicle can be obtained again.
  • the control platform first obtains the position information sent by the target vehicle, wherein the position information includes the target position, and then determines the state data of at least one sample vehicle pre-stored by the control platform according to the target position, and the sample vehicle is a vehicle that has driven.
  • the vehicle at the target position finally determines the target driving mode according to the state data of the sample vehicle, and sends the target driving mode to the target vehicle, so that the target vehicle runs according to the target driving mode.
  • the present disclosure determines the corresponding sample vehicle through the location information of the target vehicle, so as to determine the target driving mode suitable for the current driving of the target vehicle according to the state data of the sample vehicle, so that the target vehicle can drive according to the target driving mode.
  • the driver does not need to manually switch the driving mode, which can improve the accuracy and convenience of controlling the driving mode.
  • Fig. 6 is a block diagram showing a control device for a driving mode according to an exemplary embodiment. As shown in Fig. 6 , the device 200 is applied to a control platform, including:
  • the obtaining module 201 is configured to obtain the position information sent by the target vehicle, where the position information includes the target position.
  • the determination module 202 is configured to determine, according to the target position, the state data of at least one sample vehicle pre-stored by the control platform, where the sample vehicle is a vehicle that has traveled through the target position.
  • the control module 203 is configured to determine the target driving mode according to the state data of the sample vehicle, and send the target driving mode to the target vehicle, so that the target vehicle runs according to the target driving mode.
  • FIG. 7 is a block diagram of another driving mode control device according to an exemplary embodiment.
  • the determining module 202 includes:
  • the first determination sub-module 2021 is used to determine the target road segment to which the target position belongs.
  • the second determination sub-module 2022 is configured to determine the sample vehicles that have traveled through the target road section within a preset time period before the current moment.
  • the obtaining sub-module 2023 is used for obtaining state data of the sample vehicle, where the state data includes the driving mode, power consumption, and fuel consumption of the sample vehicle when driving on the target road section.
  • control module 203 is used for:
  • the average power consumption and average fuel consumption corresponding to each driving mode are determined.
  • the energy consumption corresponding to each driving mode is determined according to the average power consumption and average fuel consumption corresponding to each driving mode.
  • the target driving mode is determined according to the energy consumption corresponding to each driving mode.
  • control module 203 is used to:
  • For each sample vehicle according to the state data of the sample vehicle, determine the electricity consumption and fuel consumption of the sample vehicle when the sample vehicle is driven in each driving mode.
  • the first weighting coefficient and the second weighting coefficient corresponding to the sample vehicle are determined according to the travel time of the sample vehicle traveling through the target road section.
  • the average power consumption corresponding to the first driving mode is determined according to the power consumption of each sample vehicle when driving in the first driving mode, and the first weighting coefficient corresponding to each sample vehicle, and the first driving mode is any driving mode.
  • the average fuel consumption corresponding to the first driving mode is determined according to the fuel consumption of each sample vehicle when driving in the first driving mode and the second weighting coefficient corresponding to each sample vehicle.
  • control module 203 is used to:
  • the third weighting coefficient and the fourth weighting coefficient are determined according to the electricity consumption time and the oil consumption time of each sample vehicle.
  • Fig. 8 is a block diagram showing another driving mode control device according to an exemplary embodiment. As shown in Fig. 8 , the device 200 further includes:
  • the storage module 204 is configured to acquire the status data sent by the target vehicle and store the status data of the target vehicle.
  • FIG. 9 is a block diagram of another driving mode control device according to an exemplary embodiment. As shown in FIG. 9 , the device 200 further includes:
  • the judging module 205 is configured to determine whether the state data of the target vehicle is valid according to a preset electric power threshold value and a fuel quantity threshold value before storing the state data of the target vehicle.
  • the judgment module 205 is further configured to determine that the state data of the target vehicle is valid if the power consumption included in the state data of the target vehicle is less than or equal to the power threshold, and the fuel consumption included in the state data of the target vehicle is less than or equal to the fuel threshold .
  • the storage module 204 is used to:
  • the state data of the target vehicle is valid, the state data of the target vehicle is stored.
  • the control platform first obtains the position information sent by the target vehicle, wherein the position information includes the target position, and then determines the state data of at least one sample vehicle pre-stored by the control platform according to the target position, and the sample vehicle is a vehicle that has driven.
  • the vehicle at the target position finally determines the target driving mode according to the state data of the sample vehicle, and sends the target driving mode to the target vehicle, so that the target vehicle runs according to the target driving mode.
  • the present disclosure determines the corresponding sample vehicle through the location information of the target vehicle, so as to determine the target driving mode suitable for the current driving of the target vehicle according to the state data of the sample vehicle, so that the target vehicle can drive according to the target driving mode.
  • the driver does not need to manually switch the driving mode, which can improve the accuracy and convenience of controlling the driving mode.
  • the present disclosure also proposes a computing processing device, including:
  • One or more processors when the computer readable code is executed by the one or more processors, the computing processing device executes the aforementioned driving mode control method.
  • the present disclosure also proposes a computer program, comprising computer-readable codes, which, when the computer-readable codes are executed on a computing processing device, cause the computing processing device to perform the aforementioned control of the driving mode method.
  • the present disclosure also proposes a computer-readable storage medium in which the aforementioned computer program is stored.
  • FIG. 10 provides a schematic structural diagram of a computing processing device according to an embodiment of the present disclosure.
  • the computing processing device typically includes a processor 310 and a computer program product or computer readable medium in the form of a memory 330 .
  • the memory 330 may be electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read Only Memory), EPROM, hard disk, or ROM.
  • the memory 330 has storage space 350 for program code 351 for performing any of the method steps in the above-described methods.
  • storage space 350 for program code may include individual program codes 351 for implementing various steps in the above methods, respectively. These program codes can be read from or written to one or more computer program products.
  • These computer program products include program code carriers such as hard disks, compact disks (CDs), memory cards or floppy disks. Such computer program products are typically portable or fixed storage units as shown in FIG. 11 .
  • the storage unit may have storage segments, storage spaces, etc. arranged similarly to the storage 330 in the server of FIG. 10 .
  • the program code may, for example, be compressed in a suitable form.
  • the storage unit includes computer readable code 351', i.e. code readable by a processor such as 310 for example, which when executed by a server, causes the server to perform the various steps in the methods described above.
  • first and second are only used for descriptive purposes, and should not be construed as indicating or implying relative importance or implying the number of indicated technical features. Thus, a feature delimited with “first”, “second” may expressly or implicitly include at least one of that feature.
  • plurality means at least two, such as two, three, etc., unless expressly and specifically defined otherwise.
  • a "computer-readable medium” can be any device that can contain, store, communicate, propagate, or transport the program for use by or in connection with an instruction execution system, apparatus, or apparatus.
  • computer readable media include the following: electrical connections with one or more wiring (electronic devices), portable computer disk cartridges (magnetic devices), random access memory (RAM), Read Only Memory (ROM), Erasable Editable Read Only Memory (EPROM or Flash Memory), Fiber Optic Devices, and Portable Compact Disc Read Only Memory (CDROM).
  • the computer readable medium may even be paper or other suitable medium on which the program may be printed, as the paper or other medium may be optically scanned, for example, followed by editing, interpretation, or other suitable medium as necessary process to obtain the program electronically and then store it in computer memory.
  • portions of the present disclosure may be implemented in hardware, software, firmware, or a combination thereof.
  • various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system.
  • a suitable instruction execution system For example, if implemented in hardware as in another embodiment, it can be implemented by any one of the following techniques known in the art, or a combination thereof: discrete with logic gates for implementing logic functions on data signals Logic circuits, application specific integrated circuits with suitable combinational logic gates, Programmable Gate Arrays (PGA), Field Programmable Gate Arrays (FPGA), etc.
  • each functional unit in each embodiment of the present disclosure may be integrated into one processing module, or each unit may exist physically alone, or two or more units may be integrated into one module.
  • the above-mentioned integrated modules can be implemented in the form of hardware, and can also be implemented in the form of software function modules. If the integrated modules are implemented in the form of software functional modules and sold or used as independent products, they may also be stored in a computer-readable storage medium.
  • the above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, and the like.

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Abstract

一种驾驶模式的控制方法、装置、设备、程序及存储介质，涉及电子控制技术领域，应用于控制平台，该方法包括：获取目标车辆发送的位置信息，位置信息包括目标位置（101），根据目标位置，确定控制平台预先存储的至少一个样本车辆的状态数据，样本车辆为行驶过目标位置的车辆（102），根据样本车辆的状态数据确定目标驾驶模式，并将目标驾驶模式发送至目标车辆，以使目标车辆按照目标驾驶模式行驶（103）。通过目标车辆的位置信息确定对应的样本车辆，从而根据样本车辆的状态数据确定适合于目标车辆当前行驶的目标驾驶模式，使得目标车辆能够按照目标驾驶模式行驶。无需驾驶员手动切换驾驶模式，能够提高控制驾驶模式的准确度和便捷度。

Description

驾驶模式的控制方法、装置、设备、程序及存储介质
相关申请的交叉引用
本公开要求在2020年08月10日提交中国专利局、申请号为202010796617.4、名称为“驾驶模式的控制方法和装置”的中国专利申请的优先权，其全部内容通过引用结合在本公开中。
技术领域
本公开涉及电子控制技术领域，尤其涉及一种驾驶模式的控制方法、装置、设备、程序及存储介质。
背景技术
随着电子控制技术的不断发展，车辆上设置的可供驾驶员选择的驾驶模式越来越多，例如EV(英文：Electric Vehicle，中文：电动汽车)模式、Sport(中文：运动)模式、Save(中文：电量预留)模式等驾驶模式。通常情况下，驾驶员根据驾驶习惯、驾驶经验等，通过设置在车辆上的HUT(英文：Head Unit，中文：终端信息展现单元)手动选择不同的驾驶模式，操作麻烦，容易分散驾驶员的注意力。并且，当驾驶员对某一位置的路况不熟悉时，容易出现选择的驾驶模式不适合当前路况的问题。
发明内容
本公开旨在至少在一定程度上解决相关技术中的技术问题之一。
为此，本公开的第一个目的在于提出一种驾驶模式的控制方法，以解决现有技术中存在的，驾驶模式控制不准确、操作麻烦的技术问题。
本公开的第二个目的在于提出一种驾驶模式的控制装置。
本公开的第三个目的在于提出一种计算处理设备。
本公开的第四个目的在于提出一种计算机程序。
本公开的第五个目的在于提出一种计算机可读存储介质。
为达上述目的，本公开第一方面实施例提出了一种驾驶模式的控制方法，应用于控制平台，所述方法包括：
获取目标车辆发送的位置信息，所述位置信息包括目标位置；
根据所述目标位置，确定所述控制平台预先存储的至少一个样本车辆的状态数据，所述样本车辆为行驶过所述目标位置的车辆；
根据所述样本车辆的状态数据确定目标驾驶模式，并将所述目标驾驶模式发送至所述目标车辆，以使所述目标车辆按照所述目标驾驶模式行驶。
根据本公开的一个实施例，所述根据所述目标位置，确定所述控制平台预先存储的至少一个样本车辆的状态数据，包括：
确定所述目标位置所属的目标路段；
确定在当前时刻之前预设时长内行驶过所述目标路段的所述样本车辆；
获取所述样本车辆的状态数据，所述状态数据包括所述样本车辆行驶在所述目标路段时的驾驶模式、电量消耗、油量消耗。
根据本公开的一个实施例，所述驾驶模式为多种，所述样本车辆为多个，所述根据所述样本车辆的状态数据确定目标驾驶模式，包括：
根据多个所述样本车辆的状态数据，确定每种所述驾驶模式对应的平均电量消耗和平均油量消耗；
根据每种所述驾驶模式对应的平均电量消耗和平均油量消耗，确定每种所述驾驶模式对应的能量消耗；
根据每种所述驾驶模式对应的能量消耗，确定目标驾驶模式。
根据本公开的一个实施例，所述根据多个所述样本车辆的状态数据，确定每种所述驾驶模式对应的平均电量消耗和平均油量消耗，包括：
针对每个所述样本车辆，根据该样本车辆的状态数据，确定该样本车辆按照每种所述驾驶模式行驶时的电量消耗和油量消耗；
根据该样本车辆行驶过所述目标路段的行驶时间，确定该样本车辆对应的第一加权系数和第二加权系数；
根据每个所述样本车辆按照第一驾驶模式行驶时的电量消耗，和每个所述样本车辆对应的所述第一加权系数，确定所述第一驾驶模式对应的平均电量消耗，所述第一驾驶模式为任一种所述驾驶模式；
根据每个所述样本车辆按照所述第一驾驶模式行驶时的油量消耗，和每个所述样本车辆对应的所述第二加权系数，确定所述第一驾驶模式对应的平均油量消耗。
根据本公开的一个实施例，所述根据每种所述驾驶模式对应的平均电量消耗和平均 油量消耗，确定每种所述驾驶模式对应的能量消耗，包括：
确定每个所述样本车辆的用电时间和用油时间；
根据每个所述样本车辆的用电时间和用油时间，确定第三加权系数和第四加权系数；
将每种所述驾驶模式对应的平均电量消耗和所述第三加权系数的乘积，与每种所述驾驶模式对应的平均油量消耗和所述第四加权系数的乘积的和，作为该种驾驶模式对应的能量消耗。
根据本公开的一个实施例，所述方法还包括：获取所述目标车辆发送的状态数据，并存储所述目标车辆的状态数据。
根据本公开的一个实施例，在所述存储所述目标车辆的状态数据之前，所述方法还包括：
根据预设的电量阈值和油量阈值，确定所述目标车辆的状态数据是否有效；
若所述目标车辆的状态数据中包括的电量消耗小于或等于所述电量阈值，且所述目标车辆的状态数据中包括的油量消耗小于或等于所述油量阈值，确定所述目标车辆的状态数据有效；
所述存储所述目标车辆的状态数据，包括：
若所述目标车辆的状态数据有效，存储所述目标车辆的状态数据。
本公开第一方面实施例提出了一种驾驶模式的控制方法，控制平台首先获取目标车辆发送的位置信息，其中位置信息包括目标位置，然后根据目标位置，确定控制平台预先存储的至少一个样本车辆的状态数据，样本车辆为行驶过目标位置的车辆，最后根据样本车辆的状态数据确定目标驾驶模式，并将目标驾驶模式发送至目标车辆，以使目标车辆按照目标驾驶模式行驶。本公开通过目标车辆的位置信息确定对应的样本车辆，从而根据样本车辆的状态数据确定适合于目标车辆当前行驶的目标驾驶模式，使得目标车辆能够按照目标驾驶模式行驶。无需驾驶员手动切换驾驶模式，能够提高控制驾驶模式的准确度和便捷度。
为达上述目的，本公开第二方面实施例提出了一种驾驶模式的控制装置，应用于控制平台，所述装置包括：
获取模块，用于获取目标车辆发送的位置信息，所述位置信息包括目标位置；
确定模块，用于根据所述目标位置，确定所述控制平台预先存储的至少一个样本车辆的状态数据，所述样本车辆为行驶过所述目标位置的车辆；
控制模块，用于根据所述样本车辆的状态数据确定目标驾驶模式，并将所述目标驾驶模式发送至所述目标车辆，以使所述目标车辆按照所述目标驾驶模式行驶。
根据本公开的一个实施例，所述确定模块，包括：
第一确定子模块，用于确定所述目标位置所属的目标路段；
第二确定子模块，用于确定在当前时刻之前预设时长内行驶过所述目标路段的所述样本车辆；
获取子模块，用于获取所述样本车辆的状态数据，所述状态数据包括所述样本车辆行驶在所述目标路段时的驾驶模式、电量消耗、油量消耗。
根据本公开的一个实施例，所述驾驶模式为多种，所述样本车辆为多个，所述控制模块，用于：
根据多个所述样本车辆的状态数据，确定每种所述驾驶模式对应的平均电量消耗和平均油量消耗；
根据每种所述驾驶模式对应的平均电量消耗和平均油量消耗，确定每种所述驾驶模式对应的能量消耗；
根据每种所述驾驶模式对应的能量消耗，确定目标驾驶模式。
根据本公开的一个实施例，所述控制模块，用于：
针对每个所述样本车辆，根据该样本车辆的状态数据，确定该样本车辆按照每种所述驾驶模式行驶时的电量消耗和油量消耗；
根据该样本车辆行驶过所述目标路段的行驶时间，确定该样本车辆对应的第一加权系数和第二加权系数；
根据每个所述样本车辆按照第一驾驶模式行驶时的电量消耗，和每个所述样本车辆对应的所述第一加权系数，确定所述第一驾驶模式对应的平均电量消耗，所述第一驾驶模式为任一种所述驾驶模式；
根据每个所述样本车辆按照所述第一驾驶模式行驶时的油量消耗，和每个所述样本车辆对应的所述第二加权系数，确定所述第一驾驶模式对应的平均油量消耗。
根据本公开的一个实施例，所述控制模块，用于：
确定每个所述样本车辆的用电时间和用油时间；
根据每个所述样本车辆的用电时间和用油时间，确定第三加权系数和第四加权系数；
将每种所述驾驶模式对应的平均电量消耗和所述第三加权系数的乘积，与每种所述 驾驶模式对应的平均油量消耗和所述第四加权系数的乘积的和，作为该种驾驶模式对应的能量消耗。
根据本公开的一个实施例，所述装置还包括：
存储模块，用于获取所述目标车辆发送的状态数据，并存储所述目标车辆的状态数据。
根据本公开的一个实施例，所述装置还包括：
判断模块，用于在所述存储所述目标车辆的状态数据之前，根据预设的电量阈值和油量阈值，确定所述目标车辆的状态数据是否有效；
所述判断模块，还用于若所述目标车辆的状态数据中包括的电量消耗小于或等于所述电量阈值，且所述目标车辆的状态数据中包括的油量消耗小于或等于所述油量阈值，确定所述目标车辆的状态数据有效；
所述存储模块，用于：
若所述目标车辆的状态数据有效，存储所述目标车辆的状态数据。
本公开第二方面实施例提出了一种驾驶模式的控制装置，控制平台首先获取目标车辆发送的位置信息，其中位置信息包括目标位置，然后根据目标位置，确定控制平台预先存储的至少一个样本车辆的状态数据，样本车辆为行驶过目标位置的车辆，最后根据样本车辆的状态数据确定目标驾驶模式，并将目标驾驶模式发送至目标车辆，以使目标车辆按照目标驾驶模式行驶。本公开通过目标车辆的位置信息确定对应的样本车辆，从而根据样本车辆的状态数据确定适合于目标车辆当前行驶的目标驾驶模式，使得目标车辆能够按照目标驾驶模式行驶。无需驾驶员手动切换驾驶模式，能够提高控制驾驶模式的准确度和便捷度。
为达上述目的，本公开第三方面实施例提出了一种计算处理设备，包括：
存储器，其中存储有计算机可读代码；以及
一个或多个处理器，当所述计算机可读代码被所述一个或多个处理器执行时，所述计算处理设备执行本公开第一方面实施例所提出的驾驶模式的控制方法。
为达上述目的，本公开第四方面实施例提出了一种计算机程序，包括计算机可读代码，当所述计算机可读代码在计算处理设备上运行时，导致所述计算处理设备执行本公开第一方面实施例所提出的驾驶模式的控制方法。
为达上述目的，本公开第五方面实施例提出了一种计算机可读存储介质，其中存储 了本公开第四方面实施例所提出的计算机程序。
本公开附加的方面和优点将在下面的描述中部分给出，部分将从下面的描述中变得明显，或通过本公开的实践了解到。
附图说明
本公开上述的和/或附加的方面和优点从下面结合附图对实施例的描述中将变得明显和容易理解，其中：
图1是根据一示例性实施例示出的一种驾驶模式的控制方法的流程图；
图2是根据一示例性实施例示出的另一种驾驶模式的控制方法的流程图；
图3是根据一示例性实施例示出的另一种驾驶模式的控制方法的流程图；
图4是根据一示例性实施例示出的另一种驾驶模式的控制方法的流程图；
图5是根据一示例性实施例示出的另一种驾驶模式的控制方法的流程图；
图6是根据一示例性实施例示出的一种驾驶模式的控制装置的框图；
图7是根据一示例性实施例示出的另一种驾驶模式的控制装置的框图；
图8是根据一示例性实施例示出的另一种驾驶模式的控制装置的框图；
图9是根据一示例性实施例示出的另一种驾驶模式的控制装置的框图；
图10是根据一示例性实施例示出的一种计算处理设备的结构示意图；
图11是根据一示例性实施例示出的一种用于便携式或者固定实现根据本发明的方法的程序代码的存储单元的示意图。
具体实施方式
下面详细描述本公开的实施例，所述实施例的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的，旨在用于解释本公开，而不能理解为对本公开的限制。
下面参考附图描述本公开实施例的驾驶模式的控制方法、装置、设备、程序及存储介质。
在介绍本公开提供的驾驶模式的控制方法、装置、设备、程序及存储介质之前，首先对本公开各个实施例所涉及的应用场景进行介绍。该应用场景可以包括控制平台和车辆，控制平台和车辆之间可以通过WLAN(英文：Wireless Local Area Networks，中文：无线局域网)、Telematics(中文：汽车信息服务)、V2X(英文：Vehicle to Everything， 中文：车联网)、4G(英文：the 4th Generation mobile communication technology，中文：第四代移动通信技术)和5G(英文：the 5th Generation mobile communication technology，中文：第五代移动通信技术)中的任一种协议进行通信，以实现数据传输。其中控制平台可以设置在服务器上，也可以设置在终端设备上，本公开对此不做具体限定。服务器可以包括但不限于：实体服务器，服务器集群或云端服务器等，终端设备例如可以是平板电脑、智能电视、PDA(英文：Personal Digital Assistant，中文：个人数字助理)、便携计算机等移动终端，也可以是台式计算机等固定终端。该车辆可以是汽车，但不限于传统汽车、纯电动汽车或是混动汽车，除此之外，本公开提供的驾驶模式的控制方法和装置还可以适用于其他类型的机动车或非机动车。
图1是根据一示例性实施例示出的一种驾驶模式的控制方法的流程图，如图1所示，该方法应用于控制平台，包括以下步骤：
步骤101，获取目标车辆发送的位置信息，位置信息包括目标位置。
举例来说，车辆启动之后，可以通过设置在车辆上的雷达(例如毫米波雷达、微波雷达)、GPS(英文：Global Positioning System，中文：全球定位系统)、BDS(英文：BeiDou Navigation Satellite System，中文：北斗卫星导航系统)等获取车辆的位置信息，其中位置信息可以包括目标位置，还可以包括当前时间等其他信息。目标位置可以包括该车辆(即目标车辆)所在的街道、国道，还可以包括目标车辆所处的经度和纬度等，本公开对此不做具体限定。获取位置信息之后，可以通过目标车辆的控制器将位置信息发送至控制平台，由控制平台获取位置信息。控制器可以是MCU(英文：Microcontroller Unit，中文：微控制单元)、ECU(英文：Electronic Control Unit，中文：电子控制单元)或者BCM(英文：Body Control Module，中文：车身控制器)等。目标车辆上可以仅设置一个控制器，用以实现目标车辆的全部控制逻辑，也可以设置多个控制器，用以分别实现目标车辆的不同控制逻辑，例如目标车辆上可以设置用于控制灯光的灯光控制器，用于辅助安全救援的救援控制器等。目标车辆在向控制平台发送位置信息的同时，还可以将目标车辆的标识码发送至控制平台。标识码(英文：Vehicle Identification Number，简称：VIN)由一组符合标准(例如GB16735)的17位英数(英文字母和数字)组成，每个目标车辆的标识码都是唯一的，即一个标识码只能唯一标识一个目标车辆。这样，在有多个目标车辆向控制平台发送位置信息时，控制平台就能根据目标车辆的标识码对获取到的多个位置信息进行标识，以确定每个位置信息对应的目标车辆。
进一步的，通过控制器发送位置信息和标识码之前，还可以先获取目标车辆和控制平台之间通信网络的网络连接状态。若网络连接状态为正常，那么可以直接将位置信息和目标车辆的标识码发送至控制平台。若网络连接状态为异常，那么可以先将位置信息存储起来，然后持续地获取网络连接状态，在网络连接状态为正常时，再将位置信息和目标车辆的标识码发送至控制平台，以使控制平台获取每个目标车辆对应的位置信息。
步骤102，根据目标位置，确定控制平台预先存储的至少一个样本车辆的状态数据，样本车辆为行驶过目标位置的车辆。
步骤103，根据样本车辆的状态数据确定目标驾驶模式，并将目标驾驶模式发送至目标车辆，以使目标车辆按照目标驾驶模式行驶。
示例的，控制平台获取位置信息之后，可以根据位置信息中的目标位置，在预先存储的大量车辆的状态数据中，确定至少一个样本车辆的状态数据。可以理解为，控制平台预先接收了大量车辆上传的状态数据，并将这些状态数据进行存储。当控制平台接收到位置信息后，可以根据其中的目标位置，对大量车辆的状态数据进行筛选，以得到适合于目标车辆的至少一个样本车辆的状态数据。其中，样本车辆为行驶过目标位置的车辆。状态数据可以包括样本车辆行驶在目标路段时的驾驶模式、电量消耗、油量消耗，还可以包括样本车辆行驶在目标路段的时间等。驾驶模式例如可以包括Auto(中文：自动)模式、EV模式、Sport模式、Save模式、AWD(英文：All-Wheel Drive，中文：全时四驱)模式。举个例子，车辆在行驶的过程中，可以将车辆的位置信息和状态数据发送至控制平台，由控制平台将该车辆的位置信息和状态数据存储起来。那么当控制平台确定目标位置之后，可以根据目标位置对预设数据库中存储的大量车辆的状态数据进行筛选，以获取一个或多个行驶过目标位置的样本车辆，从而获取每个样本车辆的状态数据。在另一种实现方式中，还可以在获取一个或多个样本车辆的状态数据之后，根据样本车辆行驶过目标位置的时间和指定时段(例如当前时间至当前时间之前3天)对多个样本车辆的状态数据进行筛选。若样本车辆行驶过目标位置的时间属于指定时段，那么可以保留该样本车辆的状态数据。若样本车辆行驶过目标位置的时间不属于指定时段，那么可以将该样本车辆的状态数据忽略，也可以将该样本车辆的状态数据删除，本公开对此不做限定。
控制平台获取了样本车辆的状态数据之后，可以按照预设规则根据每个样本车辆的状态数据确定目标驾驶模式。预设规则例如可以是预先建立的函数关系或模型等。目标 驾驶模式可以是一个，也可以是多个(例如2个)。例如可以根据每个样本车辆的状态数据确定最经济的驾驶模式，然后将最经济的驾驶模式确定为目标驾驶模式，也可以根据每个样本车辆的状态数据确定最经济的两个驾驶模式，然后将最经济的两个驾驶模式确定为目标驾驶模式。在另一种实现方式中，还可以根据多个样本车辆的状态数据确定使用的次数最多的驾驶模式，然后将使用的次数最多的驾驶模式确定为目标驾驶模式。控制中心在确定了目标驾驶模式的同时，可以根据目标车辆的标识码将目标驾驶模式发送至目标车辆，由目标车辆接收目标驾驶模式。在目标驾驶模式为一个的场景中，目标车辆接收到目标驾驶模式之后，控制器可以直接根据目标驾驶模式控制目标车辆，以使目标车辆按照目标驾驶模式行驶，控制器也可以根据目标驾驶模式生成相应的提示信息，例如生成语音形式的提示信息，以提示目标车辆的驾驶员将当前的驾驶模式切换为目标驾驶模式。在目标驾驶模式为多个的场景中，目标车辆接收到多个目标驾驶模式之后，控制器可以根据多个目标驾驶模式生成相应的提示信息，以使目标车辆的驾驶员能够在多个目标驾驶模式中，选择一个适合目标车辆的目标驾驶模式，从而使目标车辆按照驾驶员选择的目标驾驶模式行驶。
综上所述，本公开中控制平台首先获取目标车辆发送的位置信息，其中位置信息包括目标位置，然后根据目标位置，确定控制平台预先存储的至少一个样本车辆的状态数据，样本车辆为行驶过目标位置的车辆，最后根据样本车辆的状态数据确定目标驾驶模式，并将目标驾驶模式发送至目标车辆，以使目标车辆按照目标驾驶模式行驶。本公开通过目标车辆的位置信息确定对应的样本车辆，从而根据样本车辆的状态数据确定适合于目标车辆当前行驶的目标驾驶模式，使得目标车辆能够按照目标驾驶模式行驶。无需驾驶员手动切换驾驶模式，能够提高控制驾驶模式的准确度和便捷度。
图2是根据一示例性实施例示出的另一种驾驶模式的控制方法的流程图，如图2所示，步骤102包括：
步骤1021，确定目标位置所属的目标路段。
步骤1022，确定在当前时刻之前预设时长内行驶过目标路段的样本车辆。
步骤1023，获取样本车辆的状态数据，状态数据包括样本车辆行驶在目标路段时的驾驶模式、电量消耗、油量消耗。
举例来说，确定目标位置之后，可以根据目标位置确定目标车辆所属的目标路段，然后可以确定在当前时刻之前的预设时长(例如48h)。确定了目标路段和当前时刻之前 的预设时长后，就可以在控制平台预先存储的多个车辆的状态数据中，筛选出在当前时刻之前预设时长内行驶过目标路段的样本车辆的状态数据。其中，状态数据可以包括样本车辆行驶在目标路段时的驾驶模式、电量消耗、油量消耗等。
举个例子，可以将车辆行驶的位置信息和行驶过每一位置的行驶时间存储在控制平台的预设数据库中，那么控制平台可以在确定目标路段之后，先根据目标路段对预设数据库中的大量状态数据进行筛选，以获取一个或多个行驶过目标路段的样本车辆，从而获取每个样本车辆的状态数据。然后可以根据当前时刻之前预设时长对每个样本车辆行驶过目标路段的行驶时间进行筛选。若样本车辆行驶过目标路段的行驶时间在当前时刻之前预设时长内，那么说明当前时刻目标路段的路况与该样本车辆行驶过目标路段时的路况接近，因此该样本车辆的状态数据的参考价值比较高，此时可以保留该样本车辆的状态数据。若样本车辆行驶过目标路段的行驶时间不在当前时刻之前预设时长内，那么说明当前时刻目标路段的路况可能已经发生变化，与该样本车辆行驶过目标路段时的路况不同，因此该样本车辆的状态数据的参考价值比较低，此时可以将该样本车辆的状态数据忽略，也可以将该样本车辆的状态数据删除，本公开对此不做限定。
图3是根据一示例性实施例示出的另一种驾驶模式的控制方法的流程图，如图3所示，驾驶模式为多种，样本车辆为多个，步骤103包括：
步骤1031，根据多个样本车辆的状态数据，确定每种驾驶模式对应的平均电量消耗和平均油量消耗。
步骤1032，根据每种驾驶模式对应的平均电量消耗和平均油量消耗，确定每种驾驶模式对应的能量消耗。
步骤1033，根据每种驾驶模式对应的能量消耗，确定目标驾驶模式。
示例的，在确定目标驾驶模式时，可以根据多个样本车辆的状态数据，确定每种驾驶模式对应的平均电量消耗和平均油量消耗。例如可以根据每个样本车辆的最大电量消耗和最大油量消耗来确定每种驾驶模式对应的平均电量消耗和平均油量消耗，也可以根据每个样本车辆行驶过目标路段时的平均电量消耗和平均油量消耗来确定每种驾驶模式对应的平均电量消耗和平均油量消耗。然后可以根据每种驾驶模式对应的平均电量消耗和平均油量消耗，确定每种驾驶模式对应的能量消耗。之后可以根据每种驾驶模式对应的能量消耗，确定目标驾驶模式。例如可以将能量消耗最低的驾驶模式确定为目标驾驶模式，在另一种实现方式中，也可以将能量消耗最低的预设数量个(例如3个)驾驶模 式确定为目标驾驶模式，本公开对此不做具体限定。
可选地，步骤1031的实现方式可以包括：
首先，针对每个样本车辆，根据该样本车辆的状态数据，确定该样本车辆按照每种驾驶模式行驶时的电量消耗和油量消耗。
之后，根据该样本车辆行驶过目标路段的行驶时间，确定该样本车辆对应的第一加权系数和第二加权系数。
然后，根据每个样本车辆按照第一驾驶模式行驶时的电量消耗，和每个样本车辆对应的第一加权系数，确定第一驾驶模式对应的平均电量消耗，第一驾驶模式为任一种驾驶模式。
最后，根据每个样本车辆按照第一驾驶模式行驶时的油量消耗，和每个样本车辆对应的第二加权系数，确定第一驾驶模式对应的平均油量消耗。
举例来说，在确定每种驾驶模式对应的平均电量消耗和平均油量消耗时，可以针对每个样本车辆，根据该样本车辆的状态数据，确定该样本车辆按照每种驾驶模式行驶时的电量消耗和油量消耗。然后可以根据该样本车辆行驶过目标路段的行驶时间，确定该样本车辆对应的第一加权系数和第二加权系数。第二加权系数可以与第一加权系数相同，也可以与第二加权系数不同。其中，第一加权系数可以是多个，每个第一加权系数分别对应每个样本车辆在每种驾驶模式下的电量消耗。第二加权系数可以是多个，每个第二加权系数分别对应每个样本车辆在每种驾驶模式下的油量消耗。在确定第一加权系数和第二加权系数时，可以通过查询预设的关系表的方式来确定每种驾驶对应的第一加权系数和第二加权系数。在预设的关系表中，样本车辆以某种驾驶模式行驶过目标路段的行驶时间越接近当前时间，第一加权系数(或第二加权系数)越大，样本车辆行驶过目标路段的行驶时间离当前时间越远，第一加权系数(或第二加权系数)越小，可以理解为第一加权系数(或第二加权系数)，和(当前时间-样本车辆行驶过目标路段的行驶时间)成反比。确定的多个第一加权系数的和为1，确定的多个第二加权系数的和为1。之后，可以根据每个样本车辆按照第一驾驶模式行驶时的电量消耗，和每个样本车辆对应的第一加权系数，确定第一驾驶模式对应的平均电量消耗，其中，第一驾驶模式为任一种驾驶模式。
举个例子，当S个样本车辆分别按照5种驾驶模式A、B、C、D、E行驶时，每种驾驶模式对应的平均电量消耗可以表示为：
Figure PCTCN2021111858-appb-000001
Figure PCTCN2021111858-appb-000002
Figure PCTCN2021111858-appb-000003
Figure PCTCN2021111858-appb-000004
Figure PCTCN2021111858-appb-000005
其中，K 1表示第一个样本车辆在每种驾驶模式下对应的第一加权系数，K 2表示第二个样本车辆在每种驾驶模式下对应的第一加权系数，K S表示第S个样本车辆在每种驾驶模式下对应的第一加权系数，K 1+K 2+……+K S＝1。若S个样本车辆按照行驶过目标路段的行驶时间由近到远排列，即第一个样本车辆行驶过目标路段的行驶时间最接近当前时间，第二个样本车辆次之，以此类推，那么K 1>K 2>……>K S。
Figure PCTCN2021111858-appb-000006
表示第一个样本车辆在驾驶模式A下的电量消耗，
Figure PCTCN2021111858-appb-000007
表示第二个样本车辆在驾驶模式A下的电量消耗，
Figure PCTCN2021111858-appb-000008
表示第S个样本车辆在驾驶模式A下的电量消耗，
Figure PCTCN2021111858-appb-000009
表示驾驶模式A对应的平均电量消耗。同样的，
Figure PCTCN2021111858-appb-000010
分别表示第一个样本车辆在驾驶模式B、C、D、E下的电量消耗，
Figure PCTCN2021111858-appb-000011
分别表示第二个样本车辆在驾驶模式B、C、D、E下的电量消耗，
Figure PCTCN2021111858-appb-000012
分别表示第S个样本车辆在驾驶模式B、C、D、E下的电量消耗。
Figure PCTCN2021111858-appb-000013
分别表示驾驶模式B、C、D、E对应的平均电量消耗。
同样的，可以根据每个样本车辆按照第一驾驶模式行驶时的油量消耗，和每个样本车辆对应的第二加权系数，确定第一驾驶模式对应的平均油量消耗。当S个样本车辆分别按照5种驾驶模式A、B、C、D、E行驶时，每种驾驶模式对应的平均油量消耗可以表示为：
Figure PCTCN2021111858-appb-000014
Figure PCTCN2021111858-appb-000015
Figure PCTCN2021111858-appb-000016
Figure PCTCN2021111858-appb-000017
Figure PCTCN2021111858-appb-000018
其中，F 1表示第一个样本车辆在每种驾驶模式下对应的第二加权系数，F 2表示第二个样本车辆在每种驾驶模式下对应的第二加权系数，F S表示第S个样本车辆在每种驾驶模式下对应的第二加权系数，F 1+F 2+……+F S＝1。若S个样本车辆按照行驶过目标路段的行驶时间由近到远排列，即第一个样本车辆行驶过目标路段的行驶时间最接近当前时间，第二个样本车辆次之，以此类推，那么F 1>F 2>……>F S。
Figure PCTCN2021111858-appb-000019
表示第一个样本车辆在驾驶模式A下的油量消耗，
Figure PCTCN2021111858-appb-000020
表示第二个样本车辆在驾驶模式A下的油量消耗，
Figure PCTCN2021111858-appb-000021
表示第S个样本车辆在驾驶模式A下的油量消耗，
Figure PCTCN2021111858-appb-000022
表示驾驶模式A对应的平均油量消耗。同样的，
Figure PCTCN2021111858-appb-000023
分别表示第一个样本车辆在驾驶模式B、C、D、E下的油量消耗，
Figure PCTCN2021111858-appb-000024
分别表示第二个样本车辆在驾驶模式B、C、D、E下的油量消耗，
Figure PCTCN2021111858-appb-000025
分别表示第S个样本车辆在驾驶模式B、C、D、E下的油量消耗。
Figure PCTCN2021111858-appb-000026
分别表示驾驶模式B、C、D、E对应的平均油量消耗。
具体的，根据每种驾驶模式对应的平均电量消耗和平均油量消耗，确定每种驾驶模式对应的能量消耗的实现方式可以包括：
步骤1)确定每个样本车辆的用电时间和用油时间。
步骤2)根据每个样本车辆的用电时间和用油时间，确定第三加权系数和第四加权系数。
步骤3)将每种驾驶模式对应的平均电量消耗和第三加权系数的乘积，与每种驾驶模式对应的平均油量消耗和第四加权系数的乘积的和，作为该种驾驶模式对应的能量消耗。
在一种实现方式中，确定了每种驾驶模式对应的平均电量消耗和平均油量消耗之后，可以继续确定每个样本车辆的用电时间和用油时间，然后根据每个样本车辆的用电时间和用油时间，确定第三加权系数(例如M1)和第四加权系数(例如M2)。第三加权系数例如可以是全部样本车辆的用电时间占全部样本车辆的用电时间和用油时间之和的比例，第四加权系数例如可以是全部样本车辆的用油时间占全部样本车辆的用电时间和用油时间之和的比例。确定第三加权系数和第四加权系数之后，可以将每种驾驶模式对应的平均电量消耗和第三加权系数的乘积，与每种驾驶模式对应的平均油量消耗和第四加 权系数的乘积的和，作为该种驾驶模式对应的能量消耗。
当S个样本车辆分别按照5种驾驶模式A、B、C、D、E行驶时，每种驾驶模式对应的能量消耗可以表示为：
Figure PCTCN2021111858-appb-000027
Figure PCTCN2021111858-appb-000028
Figure PCTCN2021111858-appb-000029
Figure PCTCN2021111858-appb-000030
Figure PCTCN2021111858-appb-000031
其中，C A、C B、C C、C D、C E分别表示驾驶模式A、B、C、D、E对应的能量消耗，M 1+M 2＝1。
图4是根据一示例性实施例示出的另一种驾驶模式的控制方法的流程图，如图4所示，该方法还包括：
步骤104，获取目标车辆发送的状态数据。
步骤105，存储目标车辆的状态数据。
举例来说，控制平台还可以获取目标车辆发送的状态数据，并将目标车辆的状态数据存储到预设数据库中。例如控制平台获取目标车辆的状态数据之后，可以根据目标车辆的标识码将目标车辆的状态数据存储到预设数据库中，以便控制平台能够根据该状态数据对其他车辆的驾驶模式进行确定。
图5是根据一示例性实施例示出的另一种驾驶模式的控制方法的流程图，如图5所示，在步骤105之前，该方法还包括：
步骤106，根据预设的电量阈值和油量阈值，确定目标车辆的状态数据是否有效。
步骤107，若目标车辆的状态数据中包括的电量消耗小于或等于电量阈值，且目标车辆的状态数据中包括的油量消耗小于或等于油量阈值，确定目标车辆的状态数据有效。
步骤105包括：
若目标车辆的状态数据有效，存储目标车辆的状态数据。
示例的，获取目标车辆的状态数据之后，可以根据预设的电量阈值和油量阈值，对目标车辆的状态数据中包括的电量消耗和油量消耗进行判断，以确定目标车辆的状态数据是否有效。预设的电量阈值例如可以是20千瓦时/百公里，预设的油量阈值例如可以是10升/百公里。若目标车辆的状态数据中包括的电量消耗小于或等于电量阈值，且目 标车辆的状态数据中包括的油量消耗小于或等于油量阈值，说明目标车辆的状态数据合理，那么可以确定目标车辆的状态数据有效。否则，表明目标车辆上传的状态数据可能存在异常，那么可以确定目标车辆的状态数据无效。若目标车辆的状态数据有效，那么可以将目标车辆的状态数据存储起来。若目标车辆的状态数据无效，那么可以将该状态数据丢弃，然后重新获取目标车辆的状态数据。
综上所述，本公开中控制平台首先获取目标车辆发送的位置信息，其中位置信息包括目标位置，然后根据目标位置，确定控制平台预先存储的至少一个样本车辆的状态数据，样本车辆为行驶过目标位置的车辆，最后根据样本车辆的状态数据确定目标驾驶模式，并将目标驾驶模式发送至目标车辆，以使目标车辆按照目标驾驶模式行驶。本公开通过目标车辆的位置信息确定对应的样本车辆，从而根据样本车辆的状态数据确定适合于目标车辆当前行驶的目标驾驶模式，使得目标车辆能够按照目标驾驶模式行驶。无需驾驶员手动切换驾驶模式，能够提高控制驾驶模式的准确度和便捷度。
图6是根据一示例性实施例示出的一种驾驶模式的控制装置的框图，如图6所示，该装置200应用于控制平台，包括：
获取模块201，用于获取目标车辆发送的位置信息，位置信息包括目标位置。
确定模块202，用于根据目标位置，确定控制平台预先存储的至少一个样本车辆的状态数据，样本车辆为行驶过目标位置的车辆。
控制模块203，用于根据样本车辆的状态数据确定目标驾驶模式，并将目标驾驶模式发送至目标车辆，以使目标车辆按照目标驾驶模式行驶。
图7是根据一示例性实施例示出的另一种驾驶模式的控制装置的框图，如图7所示，确定模块202包括：
第一确定子模块2021，用于确定目标位置所属的目标路段。
第二确定子模块2022，用于确定在当前时刻之前预设时长内行驶过目标路段的样本车辆。
获取子模块2023，用于获取样本车辆的状态数据，状态数据包括样本车辆行驶在目标路段时的驾驶模式、电量消耗、油量消耗。
可选地，驾驶模式为多种，样本车辆为多个，控制模块203用于：
根据多个样本车辆的状态数据，确定每种驾驶模式对应的平均电量消耗和平均油量消耗。
根据每种驾驶模式对应的平均电量消耗和平均油量消耗，确定每种驾驶模式对应的能量消耗。
根据每种驾驶模式对应的能量消耗，确定目标驾驶模式。
可选地，控制模块203用于：
针对每个样本车辆，根据该样本车辆的状态数据，确定该样本车辆按照每种驾驶模式行驶时的电量消耗和油量消耗。
根据该样本车辆行驶过目标路段的行驶时间，确定该样本车辆对应的第一加权系数和第二加权系数。
根据每个样本车辆按照第一驾驶模式行驶时的电量消耗，和每个样本车辆对应的第一加权系数，确定第一驾驶模式对应的平均电量消耗，第一驾驶模式为任一种驾驶模式。
根据每个样本车辆按照第一驾驶模式行驶时的油量消耗，和每个样本车辆对应的第二加权系数，确定第一驾驶模式对应的平均油量消耗。
可选地，控制模块203用于：
确定每个样本车辆的用电时间和用油时间。
根据每个样本车辆的用电时间和用油时间，确定第三加权系数和第四加权系数。
将每种驾驶模式对应的平均电量消耗和第三加权系数的乘积，与每种驾驶模式对应的平均油量消耗和第四加权系数的乘积的和，作为该种驾驶模式对应的能量消耗。
图8是根据一示例性实施例示出的另一种驾驶模式的控制装置的框图，如图8所示，该装置200还包括：
存储模块204，用于获取目标车辆发送的状态数据，并存储目标车辆的状态数据。
图9是根据一示例性实施例示出的另一种驾驶模式的控制装置的框图，如图9所示，该装置200还包括：
判断模块205，用于在存储目标车辆的状态数据之前，根据预设的电量阈值和油量阈值，确定目标车辆的状态数据是否有效。
判断模块205，还用于若目标车辆的状态数据中包括的电量消耗小于或等于电量阈值，且目标车辆的状态数据中包括的油量消耗小于或等于油量阈值，确定目标车辆的状态数据有效。
存储模块204用于：
若目标车辆的状态数据有效，存储目标车辆的状态数据。
关于上述实施例中的装置，其中各个部分执行操作的具体方式已经在有关该方法的实施例中进行了详细描述，此处将不做详细阐述说明。
综上所述，本公开中控制平台首先获取目标车辆发送的位置信息，其中位置信息包括目标位置，然后根据目标位置，确定控制平台预先存储的至少一个样本车辆的状态数据，样本车辆为行驶过目标位置的车辆，最后根据样本车辆的状态数据确定目标驾驶模式，并将目标驾驶模式发送至目标车辆，以使目标车辆按照目标驾驶模式行驶。本公开通过目标车辆的位置信息确定对应的样本车辆，从而根据样本车辆的状态数据确定适合于目标车辆当前行驶的目标驾驶模式，使得目标车辆能够按照目标驾驶模式行驶。无需驾驶员手动切换驾驶模式，能够提高控制驾驶模式的准确度和便捷度。
为了实现上述实施例，本公开还提出了一种计算处理设备，包括：
存储器，其中存储有计算机可读代码；以及
一个或多个处理器，当所述计算机可读代码被所述一个或多个处理器执行时，所述计算处理设备执行前述的驾驶模式的控制方法。
为了实现上述实施例，本公开还提出了一种计算机程序，包括计算机可读代码，当所述计算机可读代码在计算处理设备上运行时，导致所述计算处理设备执行前述的驾驶模式的控制方法。
为了实现上述实施例，本公开还提出了一种计算机可读存储介质，其中存储了前述的计算机程序。
图10为本公开实施例提供了一种计算处理设备的结构示意图。该计算处理设备通常包括处理器310和以存储器330形式的计算机程序产品或者计算机可读介质。存储器330可以是诸如闪存、EEPROM(电可擦除可编程只读存储器)、EPROM、硬盘或者ROM之类的电子存储器。存储器330具有用于执行上述方法中的任何方法步骤的程序代码351的存储空间350。例如，用于程序代码的存储空间350可以包括分别用于实现上面的方法中的各种步骤的各个程序代码351。这些程序代码可以从一个或者多个计算机程序产品中读出或者写入到这一个或者多个计算机程序产品中。这些计算机程序产品包括诸如硬盘，紧致盘(CD)、存储卡或者软盘之类的程序代码载体。这样的计算机程序产品通常为如图11所示的便携式或者固定存储单元。该存储单元可以具有与图10的服务器中的存储器330类似布置的存储段、存储空间等。程序代码可以例如以适当形式进行压缩。通常，存储单元包括计算机可读代码351’，即可以由例如诸如310之类的处理器读取的代码，这 些代码当由服务器运行时，导致该服务器执行上面所描述的方法中的各个步骤。
在本说明书的描述中，参考术语“一个实施例”、“一些实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本公开的至少一个实施例或示例中。在本说明书中，对上述术语的示意性表述不必须针对的是相同的实施例或示例。而且，描述的具体特征、结构、材料或者特点可以在任一个或多个实施例或示例中以合适的方式结合。此外，在不相互矛盾的情况下，本领域的技术人员可以将本说明书中描述的不同实施例或示例以及不同实施例或示例的特征进行结合和组合。
此外，术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括至少一个该特征。在本公开的描述中，“多个”的含义是至少两个，例如两个，三个等，除非另有明确具体的限定。
流程图中或在此以其他方式描述的任何过程或方法描述可以被理解为，表示包括一个或更多个用于实现定制逻辑功能或过程的步骤的可执行指令的代码的模块、片段或部分，并且本公开的优选实施方式的范围包括另外的实现，其中可以不按所示出或讨论的顺序，包括根据所涉及的功能按基本同时的方式或按相反的顺序，来执行功能，这应被本公开的实施例所属技术领域的技术人员所理解。
在流程图中表示或在此以其他方式描述的逻辑和/或步骤，例如，可以被认为是用于实现逻辑功能的可执行指令的定序列表，可以具体实现在任何计算机可读介质中，以供指令执行系统、装置或设备(如基于计算机的系统、包括处理器的系统或其他可以从指令执行系统、装置或设备取指令并执行指令的系统)使用，或结合这些指令执行系统、装置或设备而使用。就本说明书而言，"计算机可读介质"可以是任何可以包含、存储、通信、传播或传输程序以供指令执行系统、装置或设备或结合这些指令执行系统、装置或设备而使用的装置。计算机可读介质的更具体的示例(非穷尽性列表)包括以下：具有一个或多个布线的电连接部(电子装置)，便携式计算机盘盒(磁装置)，随机存取存储器(RAM)，只读存储器(ROM)，可擦除可编辑只读存储器(EPROM或闪速存储器)，光纤装置，以及便携式光盘只读存储器(CDROM)。另外，计算机可读介质甚至可以是可在其上打印所述程序的纸或其他合适的介质，因为可以例如通过对纸或其他介质进行光学扫描，接着进行编辑、解译或必要时以其他合适方式进行处理来以电子方式获得所 述程序，然后将其存储在计算机存储器中。
应当理解，本公开的各部分可以用硬件、软件、固件或它们的组合来实现。在上述实施方式中，多个步骤或方法可以用存储在存储器中且由合适的指令执行系统执行的软件或固件来实现。如，如果用硬件来实现和在另一实施方式中一样，可用本领域公知的下列技术中的任一项或他们的组合来实现：具有用于对数据信号实现逻辑功能的逻辑门电路的离散逻辑电路，具有合适的组合逻辑门电路的专用集成电路，可编程门阵列(PGA)，现场可编程门阵列(FPGA)等。
本技术领域的普通技术人员可以理解实现上述实施例方法携带的全部或部分步骤是可以通过程序来指令相关的硬件完成，所述的程序可以存储于一种计算机可读存储介质中，该程序在执行时，包括方法实施例的步骤之一或其组合。
此外，在本公开各个实施例中的各功能单元可以集成在一个处理模块中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个模块中。上述集成的模块既可以采用硬件的形式实现，也可以采用软件功能模块的形式实现。所述集成的模块如果以软件功能模块的形式实现并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。
上述提到的存储介质可以是只读存储器，磁盘或光盘等。尽管上面已经示出和描述了本公开的实施例，可以理解的是，上述实施例是示例性的，不能理解为对本公开的限制，本领域的普通技术人员在本公开的范围内可以对上述实施例进行变化、修改、替换和变型。

Claims (17)

  1. 一种驾驶模式的控制方法，其特征在于，应用于控制平台，所述方法包括：
    获取目标车辆发送的位置信息，所述位置信息包括目标位置；
    根据所述目标位置，确定所述控制平台预先存储的至少一个样本车辆的状态数据，所述样本车辆为行驶过所述目标位置的车辆；
    根据所述样本车辆的状态数据确定目标驾驶模式，并将所述目标驾驶模式发送至所述目标车辆，以使所述目标车辆按照所述目标驾驶模式行驶。
  2. 根据权利要求1所述的方法，其特征在于，所述根据所述目标位置，确定所述控制平台预先存储的至少一个样本车辆的状态数据，包括：
    确定所述目标位置所属的目标路段；
    确定在当前时刻之前预设时长内行驶过所述目标路段的所述样本车辆；
    获取所述样本车辆的状态数据，所述状态数据包括所述样本车辆行驶在所述目标路段时的驾驶模式、电量消耗、油量消耗。
  3. 根据权利要求2所述的方法，其特征在于，所述驾驶模式为多种，所述样本车辆为多个，所述根据所述样本车辆的状态数据确定目标驾驶模式，包括：
    根据多个所述样本车辆的状态数据，确定每种所述驾驶模式对应的平均电量消耗和平均油量消耗；
    根据每种所述驾驶模式对应的平均电量消耗和平均油量消耗，确定每种所述驾驶模式对应的能量消耗；
    根据每种所述驾驶模式对应的能量消耗，确定目标驾驶模式。
  4. 根据权利要求3所述的方法，其特征在于，所述根据多个所述样本车辆的状态数据，确定每种所述驾驶模式对应的平均电量消耗和平均油量消耗，包括：
    针对每个所述样本车辆，根据该样本车辆的状态数据，确定该样本车辆按照每种所述驾驶模式行驶时的电量消耗和油量消耗；
    根据该样本车辆行驶过所述目标路段的行驶时间，确定该样本车辆对应的第一加权系数和第二加权系数；
    根据每个所述样本车辆按照第一驾驶模式行驶时的电量消耗，和每个所述样本车辆对应的所述第一加权系数，确定所述第一驾驶模式对应的平均电量消耗，所述第一驾驶模式为任一种所述驾驶模式；
    根据每个所述样本车辆按照所述第一驾驶模式行驶时的油量消耗，和每个所述样本车辆对应的所述第二加权系数，确定所述第一驾驶模式对应的平均油量消耗。
  5. 根据权利要求3所述的方法，其特征在于，所述根据每种所述驾驶模式对应的平均电量消耗和平均油量消耗，确定每种所述驾驶模式对应的能量消耗，包括：
    确定每个所述样本车辆的用电时间和用油时间；
    根据每个所述样本车辆的用电时间和用油时间，确定第三加权系数和第四加权系数；
    将每种所述驾驶模式对应的平均电量消耗和所述第三加权系数的乘积，与每种所述驾驶模式对应的平均油量消耗和所述第四加权系数的乘积的和，作为该种驾驶模式对应的能量消耗。
  6. 根据权利要求1所述的方法，其特征在于，所述方法还包括：
    获取所述目标车辆发送的状态数据，并存储所述目标车辆的状态数据。
  7. 根据权利要求6所述的方法，其特征在于，在所述存储所述目标车辆的状态数据之前，所述方法还包括：
    根据预设的电量阈值和油量阈值，确定所述目标车辆的状态数据是否有效；
    若所述目标车辆的状态数据中包括的电量消耗小于或等于所述电量阈值，且所述目标车辆的状态数据中包括的油量消耗小于或等于所述油量阈值，确定所述目标车辆的状态数据有效；
    所述存储所述目标车辆的状态数据，包括：
    若所述目标车辆的状态数据有效，存储所述目标车辆的状态数据。
  8. 一种驾驶模式的控制装置，其特征在于，应用于控制平台，所述装置包括：
    获取模块，用于获取目标车辆发送的位置信息，所述位置信息包括目标位置；
    确定模块，用于根据所述目标位置，确定所述控制平台预先存储的至少一个样本车辆的状态数据，所述样本车辆为行驶过所述目标位置的车辆；
    控制模块，用于根据所述样本车辆的状态数据确定目标驾驶模式，并将所述目标驾驶模式发送至所述目标车辆，以使所述目标车辆按照所述目标驾驶模式行驶。
  9. 根据权利要求8所述的装置，其特征在于，所述确定模块，包括：
    第一确定子模块，用于确定所述目标位置所属的目标路段；
    第二确定子模块，用于确定在当前时刻之前预设时长内行驶过所述目标路段的所述 样本车辆；
    获取子模块，用于获取所述样本车辆的状态数据，所述状态数据包括所述样本车辆行驶在所述目标路段时的驾驶模式、电量消耗、油量消耗。
  10. 根据权利要求9所述的装置，其特征在于，所述驾驶模式为多种，所述样本车辆为多个，所述控制模块，用于：
    根据多个所述样本车辆的状态数据，确定每种所述驾驶模式对应的平均电量消耗和平均油量消耗；
    根据每种所述驾驶模式对应的平均电量消耗和平均油量消耗，确定每种所述驾驶模式对应的能量消耗；
    根据每种所述驾驶模式对应的能量消耗，确定目标驾驶模式。
  11. 根据权利要求10所述的装置，其特征在于，所述控制模块，用于：
    针对每个所述样本车辆，根据该样本车辆的状态数据，确定该样本车辆按照每种所述驾驶模式行驶时的电量消耗和油量消耗；
    根据该样本车辆行驶过所述目标路段的行驶时间，确定该样本车辆对应的第一加权系数和第二加权系数；
    根据每个所述样本车辆按照第一驾驶模式行驶时的电量消耗，和每个所述样本车辆对应的所述第一加权系数，确定所述第一驾驶模式对应的平均电量消耗，所述第一驾驶模式为任一种所述驾驶模式；
    根据每个所述样本车辆按照所述第一驾驶模式行驶时的油量消耗，和每个所述样本车辆对应的所述第二加权系数，确定所述第一驾驶模式对应的平均油量消耗。
  12. 根据权利要求10所述的装置，其特征在于，所述控制模块，用于：
    确定每个所述样本车辆的用电时间和用油时间；
    根据每个所述样本车辆的用电时间和用油时间，确定第三加权系数和第四加权系数；
    将每种所述驾驶模式对应的平均电量消耗和所述第三加权系数的乘积，与每种所述驾驶模式对应的平均油量消耗和所述第四加权系数的乘积的和，作为该种驾驶模式对应的能量消耗。
  13. 根据权利要求8所述的装置，其特征在于，所述装置还包括：
    存储模块，用于获取所述目标车辆发送的状态数据，并存储所述目标车辆的状态数 据。
  14. 根据权利要求13所述的装置，其特征在于，所述装置还包括：
    判断模块，用于在所述存储所述目标车辆的状态数据之前，根据预设的电量阈值和油量阈值，确定所述目标车辆的状态数据是否有效；
    所述判断模块，还用于若所述目标车辆的状态数据中包括的电量消耗小于或等于所述电量阈值，且所述目标车辆的状态数据中包括的油量消耗小于或等于所述油量阈值，确定所述目标车辆的状态数据有效；
    所述存储模块，用于：
    若所述目标车辆的状态数据有效，存储所述目标车辆的状态数据。
  15. 一种计算处理设备，其特征在于，包括：
    存储器，其中存储有计算机可读代码；以及
    一个或多个处理器，当所述计算机可读代码被所述一个或多个处理器执行时，所述计算处理设备执行如权利要求1-7中任一项所述的驾驶模式的控制方法。
  16. 一种计算机程序，包括计算机可读代码，当所述计算机可读代码在计算处理设备上运行时，导致所述计算处理设备执行根据权利要求1-7中任一项所述的驾驶模式的控制方法。
  17. 一种计算机可读存储介质，其中存储了如权利要求16所述的计算机程序。
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