WO2024082829A1 - 基于场景的预测性换挡规律自适应方法及相关设备 - Google Patents

基于场景的预测性换挡规律自适应方法及相关设备 Download PDF

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Publication number
WO2024082829A1
WO2024082829A1 PCT/CN2023/115341 CN2023115341W WO2024082829A1 WO 2024082829 A1 WO2024082829 A1 WO 2024082829A1 CN 2023115341 W CN2023115341 W CN 2023115341W WO 2024082829 A1 WO2024082829 A1 WO 2024082829A1
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Prior art keywords
lane
speed
gear
vehicle speed
current
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Ceased
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PCT/CN2023/115341
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English (en)
French (fr)
Inventor
武晓俊
刘学武
王秀发
熊杰
邓云飞
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Guangzhou Automobile Group Co Ltd
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Guangzhou Automobile Group Co Ltd
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Publication of WO2024082829A1 publication Critical patent/WO2024082829A1/zh
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Classifications

    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16H—GEARING
    • F16H61/00—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing
    • F16H61/02—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by the signals used
    • F16H61/0202—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by the signals used the signals being electric
    • F16H61/0204—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by the signals used the signals being electric for gearshift control, e.g. control functions for performing shifting or generation of shift signal
    • F16H61/0213—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by the signals used the signals being electric for gearshift control, e.g. control functions for performing shifting or generation of shift signal characterised by the method for generating shift signals
    • 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
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/10—Conjoint control of vehicle sub-units of different type or different function including control of change-speed gearings
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16H—GEARING
    • F16H59/00—Control inputs to control units of change-speed- or reversing-gearings for conveying rotary motion
    • F16H59/36—Inputs being a function of speed
    • F16H59/44—Inputs being a function of speed dependent on machine speed, e.g. the vehicle speed
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16H—GEARING
    • F16H59/00—Control inputs to control units of change-speed- or reversing-gearings for conveying rotary motion
    • F16H59/60—Inputs being a function of ambient conditions
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16H—GEARING
    • F16H61/00—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing
    • F16H61/02—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by the signals used
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F16—ENGINEERING ELEMENTS AND UNITS; GENERAL MEASURES FOR PRODUCING AND MAINTAINING EFFECTIVE FUNCTIONING OF MACHINES OR INSTALLATIONS; THERMAL INSULATION IN GENERAL
    • F16H—GEARING
    • F16H61/00—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing
    • F16H2061/0075—Control functions within control units of change-speed- or reversing-gearings for conveying rotary motion ; Control of exclusively fluid gearing, friction gearing, gearings with endless flexible members or other particular types of gearing characterised by a particular control method
    • F16H2061/0087—Adaptive control, e.g. the control parameters adapted by learning

Definitions

  • the present application relates to the field of vehicle technology, and in particular to a scenario-based predictive shift schedule adaptive method, device, electronic device, and computer-readable storage medium.
  • the shifting rules of a multi-speed transmission determine the shifting timing of the transmission.
  • the purpose of gear switching is to coordinate the power and economy of the system.
  • most of the current shifting rules give fixed levels of optional shifting rules based on the current vehicle state parameters and the driver's historical operation information. For example, there are shifting rules for economy, shifting rules that are moderate in both economy and power, and shifting rules for driving performance. These shifting rules are fixed and cannot be changed, and human drivers need to adapt to the characteristics of the vehicle's shifting rules.
  • the driver's expectations between economy and power are constantly changing according to the current vehicle state and the scene in front of the vehicle. Fixed shifting rules cannot automatically adapt to the driver's expectations.
  • the embodiments of the present application provide a scenario-based predictive shift schedule adaptation method, device, electronic device and computer-readable storage medium.
  • a scenario-based predictive shift schedule includes: obtaining a reference vehicle speed on the lane where the current vehicle is traveling according to the scene information obtained during the current vehicle's driving process; determining the shifting speed corresponding to the adaptive shifting rule according to the shifting decision factor corresponding to the reference vehicle speed on the lane; determining a target gear according to the gear speed of the current vehicle at the current moment, the gear speed of the current vehicle at the previous moment, and the gear speed corresponding to the adaptive shifting rule, and performing operations based on the target gear.
  • a scenario-based predictive gear shifting schedule adaptive device comprising: a reference speed determination module, configured to convert the scene information acquired during the current vehicle's driving process to obtain the reference speed of the lane where the current vehicle is traveling; a gear shifting speed determination module, configured to determine the gear shifting speed corresponding to the adaptive gear shifting schedule according to the gear shifting decision factor corresponding to the reference speed on the lane; an execution module, configured to determine the target gear according to the gear speed of the current vehicle at the current moment, the gear speed of the current vehicle at the previous moment and the gear shifting speed corresponding to the adaptive gear shifting schedule, and perform execution operations based on the target gear.
  • an electronic device comprising: a memory storing computer-readable instructions; and a processor reading the computer-readable instructions stored in the memory to execute any of the above-mentioned scenario-based predictive shift schedule adaptation methods.
  • a computer-readable storage medium on which computer-readable instructions are stored.
  • the computer-readable instructions are executed by a processor of a computer, the computer executes the scenario-based predictive shift schedule adaptation method as described above.
  • a computer program product including a computer program, which, when executed by a processor, implements the steps in the scenario-based predictive shift schedule adaptation method as described above.
  • the scene information acquired during the current vehicle's driving process is converted to obtain a reference speed on the lane where the current vehicle is driving, and the shift speed corresponding to the adaptive shift rule is determined according to the shift decision factor corresponding to the reference speed on the lane, and then the target gear is determined according to the gear speed of the current vehicle at the current moment, the gear speed of the current vehicle at the previous moment, and the gear speed corresponding to the adaptive shift rule, and the operation is performed based on the target gear.
  • the reference speed on the lane is obtained based on the scene information conversion, which can fully reflect the scene information while reducing the input information dimension of the adaptive shift decision.
  • FIG1 is a schematic diagram of an implementation environment of a scenario-based predictive shift schedule adaptive method according to an exemplary embodiment
  • FIG2 is a flow chart of a scenario-based predictive shift schedule adaptive method according to an exemplary embodiment of the present application
  • FIG3 is a flow chart of an exemplary embodiment of step S210 in the scenario-based predictive shift schedule adaptive method shown in FIG2 ;
  • FIG4 is a flow chart of an exemplary embodiment of step S310 in the scenario-based predictive shift schedule adaptive method shown in FIG3 ;
  • FIG5 is a flow chart of an exemplary embodiment of step S320 in the scenario-based predictive shift schedule adaptive method shown in FIG3 ;
  • FIG6 is a flow chart of an exemplary embodiment of step S330 in the scenario-based predictive shift schedule adaptive method shown in FIG3 ;
  • FIG. 7 is a flow chart of an exemplary embodiment of step S220 in the scenario-based predictive shift schedule adaptive method shown in FIG. 2 ;
  • FIG8 is a flow chart of an exemplary embodiment of step S710 in the scenario-based predictive shift schedule adaptive method shown in FIG2 ;
  • FIG. 9 is a flow chart of an exemplary embodiment of step S720 in the scenario-based predictive shift schedule adaptive method shown in FIG. 2 ;
  • FIG. 10 is a flow chart of an exemplary embodiment of step S230 in the scenario-based predictive shift schedule adaptive method shown in FIG. 2 ;
  • FIG11 is a flow chart of an exemplary embodiment before step S220 in the scenario-based predictive shift schedule adaptive method shown in FIG2 ;
  • FIG. 12 is a diagram showing the steps of the scenario-based predictive shift schedule adaptive method shown in FIG. A flowchart of an exemplary embodiment of S1130;
  • FIG. 13 is a flow chart of an exemplary embodiment after step S1110 in the scenario-based predictive shift schedule adaptive method shown in FIG. 12 ;
  • FIG. 14 is a flow chart of an exemplary embodiment of step S1330 in the scenario-based predictive shift schedule adaptive method shown in FIG. 13 ;
  • FIG. 15 is a flow chart of an exemplary embodiment after step S1110 in the scenario-based predictive shift schedule adaptive method shown in FIG. 12 ;
  • FIG. 16 is a flow chart of an exemplary embodiment of step S1530 in the scenario-based predictive shift schedule adaptive method shown in FIG. 15 ;
  • FIG17 is a schematic diagram of the relationship between lanes and the reference vehicle speeds corresponding to each lane in the scenario-based predictive shift schedule adaptive method shown in the present application;
  • FIG18 is a block diagram of a scenario-based predictive shift schedule adaptive device according to an exemplary embodiment of the present application.
  • FIG. 19 shows a schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application.
  • a and/or B can represent the following three situations: A exists alone, A and B exist at the same time, and B exists alone.
  • the character "/" generally indicates that the related objects are in an "or” relationship.
  • the shifting rules of a multi-speed transmission determine the shifting timing of the transmission.
  • the purpose of gear switching is to coordinate the power and economy of the system.
  • most of the current shifting rules give fixed levels of optional shifting rules based on the current vehicle state parameters and the driver's historical operation information. For example, there are shifting rules for economy, shifting rules that are moderate in both economy and power, and shifting rules for drivability. These shifting rules are fixed and cannot be changed, and human drivers need to adapt to the characteristics of the vehicle's shifting rules.
  • the driver's expectations between economy and power are constantly changing according to the current vehicle state and the scene in front of the vehicle. Fixed shifting rules cannot automatically adapt to the driver's expectations.
  • the embodiments of the present application propose a scene-based predictive gear shifting rule adaptive method, device, electronic device and computer-readable storage medium. Specifically: the scene information acquired during the current vehicle's driving process is converted to obtain a reference speed on the lane where the current vehicle is driving, and the gear shifting speed corresponding to the adaptive gear shifting rule is determined according to the gear shifting decision factor corresponding to the reference speed on the lane, and then the target gear is determined according to the gear speed of the current vehicle at the current moment, the gear speed of the current vehicle at the previous moment and the gear shifting speed corresponding to the adaptive gear shifting rule, and the operation is performed based on the target gear, thereby obtaining the reference speed on the lane based on the scene information conversion, which can fully reflect the scene information while reducing the input information dimension of the adaptive gear shifting decision.
  • Fig. 1 is a schematic diagram of an implementation environment of a scenario-based predictive shift schedule adaptive method according to an exemplary embodiment.
  • the implementation environment includes a scenario information acquisition terminal 110 and a service terminal 120.
  • the scenario information acquisition terminal is arranged on the vehicle, specifically, it can be arranged in the direction of the front of the vehicle.
  • the scenario information acquisition terminal 110 and the service terminal 120 establish a wired or wireless network connection in advance.
  • the The scene information acquisition terminal 110 in the head direction acquires the scene information of the current vehicle during driving, and sends the scene information to the server 120.
  • the server 120 receives the scene information, converts the scene information, obtains the reference speed of the current vehicle on the lane, and determines the shift speed corresponding to the adaptive shifting rule based on the shifting decision corresponding to the reference speed on the lane, and then determines the target gear according to the gear speed of the current vehicle at the current moment, the gear speed of the current vehicle at the previous moment and the gear speed corresponding to the adaptive shifting rule, and performs operations based on the target gear.
  • the scene information acquisition terminal 110 shown in FIG1 can be any device that supports scene information acquisition, such as a sensor, but is not limited to this.
  • the service end 120 shown in FIG1 can be a server, for example, it can be an independent physical server, or it can be a server cluster or distributed system composed of multiple physical servers, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms, etc., which are not limited here.
  • the scene information acquisition terminal 110 can communicate with the service end 120 through wireless networks such as 3G (third generation mobile information technology), 4G (fourth generation mobile information technology), and 5G (fifth generation mobile information technology), which are not limited here.
  • FIG. 2 is a flow chart of a scenario-based predictive shift schedule adaptive method shown in an exemplary embodiment of the present application.
  • the method can be applied to the implementation environment shown in FIG. 1, and is specifically executed by the server 120 in the implementation environment. It should be understood that the method can also be applied to other exemplary implementation environments, and is specifically executed by devices in other implementation environments. This embodiment does not limit the implementation environment to which the method is applicable.
  • the scenario-based predictive shift schedule adaptive method includes at least steps S210 to S230, which are described in detail as follows:
  • Step S210 converting the scene information obtained during the current vehicle driving process to obtain a reference speed of the current vehicle driving lane.
  • scene information includes near-field sensor information or map information.
  • Maps include navigation maps, ADAS maps or high-precision maps.
  • near-field sensor information includes the number and type of targets in the scene in front of the vehicle during driving, the position of the target in the scene, relative speed and acceleration, and the targets include but are not limited to vehicles, pedestrians, road signs, intersections, traffic lights, etc.
  • Map information includes road grade, road type, road speed limit, road intersections, road curvature, road slope, road traffic flow, traffic sign type and location, etc.
  • this embodiment converts multi-dimensional and complex scene information to obtain a unified reference speed.
  • the server converts the scene information into a reference speed on the lane.
  • the embodiments of the present application can not only obtain the reference vehicle speed in the current vehicle driving lane based on the scene information obtained during the current vehicle driving process, but also determine the reference vehicle speed in the left lane or the right lane based on the scene information during the vehicle driving process on the left or right side of the current vehicle driving lane.
  • Step S220 determining the shifting vehicle speed corresponding to the adaptive shifting rule according to the shifting decision factor corresponding to the reference vehicle speed on the lane.
  • the gear shift decision factor is determined based on the reference vehicle speed. If there is a current vehicle driving lane, a left lane and a right lane, the gear shift decision factor includes a gear shift decision factor determined based on the reference vehicle speed in the current vehicle driving lane, a gear shift decision factor determined based on the reference vehicle speed in the left lane and a gear shift decision factor determined based on the reference vehicle speed in the right lane.
  • Adaptive shifting schedule refers to the shifting schedule determined based on scene information.
  • the gear shifting vehicle speed corresponding to the adaptive gear shifting rule refers to the gear shifting vehicle speed determined according to the adaptive gear shifting rule.
  • the server determines the shift speed corresponding to the adaptive shift rule according to the shift decision factor corresponding to the reference speed on the lane. Specifically, the server can determine the shift speed corresponding to the adaptive shift rule according to the shift decision factors corresponding to the reference speed on the lane where the current vehicle is traveling, the reference speed on the left lane, and the reference speed on the right lane.
  • Step S230 determining the target gear according to the gear speed of the current vehicle at the current moment, the gear speed of the current vehicle at the previous moment, and the gear shift speed corresponding to the adaptive gear shifting rule, and performing the operation based on the target gear.
  • the gear speed at the current moment refers to the vehicle speed corresponding to the current gear.
  • the gear speed at the previous moment refers to the vehicle speed corresponding to the gear at the previous moment before the current moment.
  • the server calculates the current vehicle's gear speed at the current moment, the current vehicle's gear speed at the previous moment, and the
  • the target gear position is determined based on the vehicle speed at the target position and the shifting speed corresponding to the adaptive shifting rule, and the operation is performed based on the target gear position.
  • the scenario-based predictive shift schedule adaptive method of this embodiment converts the scenario information obtained during the current vehicle's driving process to obtain the reference speed on the lane where the current vehicle is driving, and determines the shift speed corresponding to the adaptive shift schedule according to the shift decision factor corresponding to the reference speed on the lane, and then determines the target gear according to the gear speed of the current vehicle at the current moment, the gear speed of the current vehicle at the previous moment, and the gear speed corresponding to the adaptive shift schedule, and performs operations based on the target gear, thereby obtaining the reference speed on the lane based on the scenario information conversion, which can fully reflect the scenario information while reducing the input information dimension of the adaptive shift decision.
  • Fig. 3 is a flow chart of an exemplary embodiment of step S210 in the scenario-based predictive shift schedule adaptive method shown in Fig. 2.
  • the explicit reference speed, implicit reference speed and resistance reference speed on the current vehicle driving lane are determined according to the first scenario element, the second scenario element and the third scenario element in the scenario information, and then the reference speed on the current vehicle driving lane is determined according to the explicit reference speed, the implicit reference speed and the resistance reference speed.
  • step S210 converting the scene information obtained during the current vehicle driving process to obtain the reference speed of the current vehicle driving lane also includes at least steps S310 to S340, which are described in detail as follows:
  • Step S310 determining an explicit reference vehicle speed on the lane according to a first scene element in the scene information.
  • the first scene element includes traffic speed information, which refers to explicit scene information, specifically, scene elements that directly include speed information.
  • traffic speed information includes road speed limits, obstacles, and traffic flows.
  • the explicit reference speed refers to the explicit reference speed of the current vehicle driving lane determined based on the first scenario element.
  • the server determines an explicit reference vehicle speed on the lane according to a first scene element in the scene information.
  • the server may further illustrate this step using steps S311 to S312 shown in FIG. 4 , as follows:
  • Step S311 obtaining the speed of the road speed limit, the speed of the obstacle and the speed of the traffic flow.
  • Step S312 Select the minimum speed among the speed limit of the road, the speed of the obstacle and the speed of the traffic flow as the explicit reference speed on the lane.
  • the speed limit of the road refers to the speed limit of the road in the scene information ahead of the current vehicle during driving.
  • the speed limit sign in the front scene shows the speed limit.
  • the speed of the obstacle refers to the speed of the obstacle relative to the current vehicle in the scene information ahead of the current vehicle during the driving process.
  • the speed of traffic flow refers to the speed of the traffic flow in the scene information ahead of the current vehicle during the driving process.
  • the server uses the minimum speed among the speed limit of the road, the speed of the obstacle and the speed of the traffic flow as the explicit reference speed of the current vehicle in the lane. It should be noted that if the first scene element also includes other speeds, then the minimum speed among all speeds is used as the explicit reference speed of the lane.
  • V explicit the explicit reference speed on the current vehicle driving lane
  • V speed limit the speed of the road speed limit
  • V obstacle the speed of the obstacle
  • V traffic flow the speed of the traffic flow
  • Step S320 determining an implicit reference vehicle speed on the lane according to a second scene element in the scene information, where the second scene element includes road attribute information.
  • the second scene element includes road attribute information, which refers to implicit scene information, specifically, scene elements that do not directly include speed information but have restrictions on road speed.
  • the road attribute information includes road type, road curvature, and the like.
  • the implicit reference speed refers to the implicit reference speed of the current vehicle driving lane determined based on the second scenario element.
  • the server determines an implicit reference vehicle speed on the lane according to the second scene element in the scene information.
  • the server may further illustrate this step using steps S321 to S322 shown in FIG. 5 , as follows:
  • Step S321 obtaining a road type speed corresponding to the road type and a road curvature speed corresponding to the road curvature.
  • Step S322 Select the minimum speed of the road type speed and the road curvature speed as the implicit reference speed on the lane.
  • the road curvature speed corresponding to the road curvature can also be determined by looking up a table.
  • the road curvature is represented by C road curvature
  • the road curvature speed V road curvature F 3 (C road curvature ), where function F 2 can be a preset table function difference or a preset fitting function.
  • the server uses the minimum speed of the road type speed and the road curvature speed as the implicit reference vehicle speed on the current vehicle driving lane.
  • Vimplicit the implicit reference speed on the current vehicle driving lane
  • the road type speed is represented as VRoadType
  • the road curvature speed is represented as VRoadCurvature
  • the server may also preset a priority value logic to determine the implicit reference speed. For example, if the server sets the priority of the road type to be higher than the road curvature, the road type speed may be used as the implicit reference speed.
  • Step S330 determining a resistance reference speed on the lane according to a third scene element in the scene information, where the third scene element includes scene resistance information.
  • the third scene element includes scene resistance information, which refers to scene elements that do not include speed information and have restrictions on road driving speed, but include scene elements that have an impact on vehicle driving resistance.
  • scene resistance information includes road grade, road slope, etc.
  • the resistance reference speed refers to the resistance reference speed on the current vehicle driving lane determined based on the third scenario element.
  • the server determines the resistance reference vehicle speed on the lane according to the third scene element in the scene information.
  • the server may further illustrate this step by using steps S331 to S332 shown in FIG. 6 , as follows:
  • Step S331 determining a target resistance according to a road grade resistance corresponding to the road grade and a road gradient resistance corresponding to the road gradient.
  • the road class resistance is determined by looking up the table based on the road class.
  • the target resistance is the resistance sum between the road grade resistance and the road slope resistance.
  • the server calculates the resistance sum between the road grade resistance and the road slope resistance, and uses the resistance sum as the target resistance.
  • Step S332 determining the resistance reference vehicle speed on the lane according to the acquired sight distance, resistance distance and target resistance.
  • the resistance distance refers to the distance corresponding to the position where the resistance value of the target resistance is not zero.
  • the sight distance refers to the sight range of the scene in front of the vehicle while it is driving.
  • the server determines the resistance reference speed on the lane according to the sight distance, the resistance distance and the target resistance. Exemplarily, the server calculates the difference between the achieved distance and the resistance distance, and calculates the ratio between the difference and the preset distance. If the remainder of the ratio is zero, the resistance value of the target resistance is determined as the resistance reference speed on the lane where the current vehicle is traveling; if the remainder of the ratio is one, the resistance reference speed on the lane where the current vehicle is traveling is determined to be zero.
  • the resistance reference speed satisfies the following formula:
  • Dis refers to the line of sight distance
  • Dis resistance refers to the resistance distance
  • 2Dis period refers to the preset distance
  • Dis period is the square wave period, which can be the resolution of the distance within the line of sight or its integer multiple
  • V resistance (Dis) is the resistance reference speed
  • R resistance refers to the target resistance.
  • Step S340 determining a reference speed on the lane where the vehicle is currently traveling according to the explicit reference speed, the implicit reference speed and the resistance reference speed on the lane.
  • the server selects the minimum reference speed from the explicit reference speed and the implicit reference speed, calculates the sum of the minimum reference speed and the resistance reference speed, and uses the sum of the speeds as the reference speed on the road where the vehicle is currently traveling.
  • the scenario-based predictive shift schedule adaptive method of this embodiment determines the explicit reference speed, implicit reference speed and resistance reference speed of the current vehicle driving lane according to the first scenario element, the second scenario element and the third scenario element in the scenario information, and then determines the implicit reference speed and resistance reference speed of the current vehicle driving lane according to the first scenario element, the second scenario element and the third scenario element in the scenario information.
  • the explicit reference speed, implicit reference speed and resistance reference speed are used to determine the reference speed on the corresponding lane, thereby converting the scene information into the reference speed on the lane, reducing the input dimension of the subsequent target gear determination, and avoiding the complexity of the target gear determination.
  • Fig. 7 is a flow chart of an exemplary embodiment of step S220 in the scenario-based predictive shift schedule adaptive method shown in Fig. 2.
  • the shift speed corresponding to the adaptive shift schedule is determined according to the shift decision fusion factor determined by the shift decision factors corresponding to the reference speed on the current vehicle driving lane, the reference speed on the left lane on the left side of the driving lane, and the reference speed on the right lane on the right side of the driving lane.
  • the process of determining the shift speed corresponding to the adaptive shift rule according to the shift decision factor corresponding to the reference speed of the current vehicle in the lane at step S220 at least includes steps S710 to S720, which are described in detail as follows:
  • Step S710 integrating the shift decision factors corresponding to the reference speed on the driving lane, the reference speed on the left lane on the left side of the driving lane, and the reference speed on the right lane on the right side of the driving lane, to obtain a shift decision fusion factor.
  • the reference speed on the left lane and the reference speed on the right lane can be determined based on the scene information of the vehicle driving process in the corresponding lanes.
  • the determination method can refer to the reference speed on the current vehicle driving lane, which will not be repeated here.
  • the shift decision fusion factor is determined based on the shift decision factor corresponding to the reference speed on the current vehicle driving lane, the shift decision factor corresponding to the reference speed on the left lane, and the shift decision factor corresponding to the reference speed on the right lane.
  • the server may further illustrate this step using steps S711 to S713 shown in FIG. 8 , as follows:
  • Step S711 calculating the second product of the shift decision factor and the corresponding coefficient of the reference speed on the driving lane, the reference speed on the left lane, and the reference speed on the right lane, to obtain a plurality of first Double product.
  • the gear shift decision factor corresponding to the reference speed in the current vehicle's driving lane is expressed as Fac1
  • the coefficient corresponding to Fac1 is K1
  • the gear shift decision factor corresponding to the reference speed in the left lane is expressed as Fac2
  • the coefficient corresponding to Fac2 is K2
  • the gear shift decision factor corresponding to the reference speed in the right lane is expressed as Fac3
  • the second product includes Fac1*K1, Fac2*K2 and Fac3*K3.
  • Step S712 selecting the maximum gear shift decision factor among the gear shift decision factors.
  • the maximum gear shift decision factor is selected from the gear shift decision factor corresponding to the reference speed on the current vehicle lane, the gear shift decision factor corresponding to the reference speed on the left lane, and the gear shift decision factor corresponding to the reference speed on the right lane.
  • Step S713 determine the ratio between the sum of the plurality of second products and the maximum gear shift decision factor as the gear shift decision fusion factor.
  • the server determines the ratio between the sum of the plurality of second products and the maximum gear shift decision factor as the gear shift decision fusion factor. It should be noted that the gear shift decision fusion factor has a value range of 0-1.
  • the shift decision fusion factor satisfies the following formula:
  • constant A refers to the maximum gear shift decision factor.
  • Step S720 determining the shifting vehicle speed corresponding to the adaptive shifting rule according to the throttle opening and the shifting decision fusion factor.
  • the throttle opening refers to the degree of opening and closing of the accelerator pedal. Among them, the throttle opening determines the amount of fuel injection controlled by the engine.
  • the server determines the shifting vehicle speed corresponding to the adaptive shifting rule according to the throttle opening and the shifting decision fusion factor.
  • the server may further illustrate this step using steps S721 to S723 shown in FIG. 9 , as follows:
  • Step S721 obtaining the corresponding minimum gear shifting speed and maximum gear shifting speed according to the throttle opening.
  • the server can determine the minimum gear shifting speed and the maximum gear shifting speed according to the function corresponding to the throttle opening.
  • the server can also directly determine the minimum gear shifting speed and the maximum gear shifting speed by looking up a table according to the throttle opening.
  • Step S722 calculating a first product of a difference between a maximum gear shifting speed and a minimum gear shifting speed and a gear shifting blending factor.
  • Step S723 calculating the sum of the minimum gear-shifting vehicle speed and the first product, and using the sum as the gear-shifting vehicle speed corresponding to the adaptive gear-shifting rule.
  • V adp V min +(V max -V min )*Fac.
  • the scenario-based predictive shift schedule adaptive method of this embodiment obtains a shift decision fusion factor based on the shift decision factors corresponding to the reference vehicle speed on the fused driving lane, the reference vehicle speed on the left lane on the left side of the driving lane, and the reference vehicle speed on the right lane on the right side of the driving lane, and determines the shift speed corresponding to the adaptive shift schedule according to the throttle opening and the shift decision fusion factor.
  • the shift decision factor corresponding to the reference vehicle speed obtained by converting the scenario information and the actual throttle opening can be used to determine the shift speed corresponding to the adaptive shift schedule, reflecting the decisive influence of the scenario information and the driver's driving style on the shift speed corresponding to the adaptive shift schedule.
  • Fig. 10 is a flow chart of an exemplary embodiment of step S230 in the scenario-based predictive shift schedule adaptive method shown in Fig. 2.
  • the process of determining the target gear position according to the gear speed of the current vehicle at the current moment, the gear speed of the current vehicle at the previous moment, and the gear shift speed corresponding to the adaptive shift schedule at step S230 at least includes steps S1010 to S1020, which are described in detail as follows:
  • Step S1010 if the gear speed of the current vehicle at the previous moment is less than the gear speed corresponding to the adaptive shifting rule, and the gear speed of the current vehicle at the current moment is greater than or equal to the gear speed corresponding to the adaptive shifting rule, then determine the highest gear of the gear wheel in the vehicle as the target gear.
  • Step S1020 if the gear speed of the current vehicle at the previous moment is greater than the gear speed corresponding to the adaptive shifting rule, and the gear speed of the current vehicle at the current moment is less than or equal to the gear speed corresponding to the adaptive shifting rule, then determine that the lowest gear of the gear wheel in the vehicle is the target gear.
  • the highest gear refers to the largest gear in the gear dial, such as the fifth gear in a manual transmission.
  • the lowest gear refers to the smallest gear in the gear shift, such as the first gear in a manual transmission.
  • the server After determining the gear shift speed corresponding to the adaptive gear shift rule, the server determines the relationship between the gear speed of the current vehicle at the previous moment, the gear speed of the current vehicle at the current moment, and the gear shift speed corresponding to the adaptive gear shift rule, and determines the target gear according to the relationship.
  • the highest gear of the gear disk in the vehicle is determined to be the target gear; if the server determines that the gear speed of the current vehicle at the previous moment is greater than the gear speed corresponding to the adaptive gear shifting rule, and the gear speed of the current vehicle at the current moment is less than or equal to the gear speed corresponding to the adaptive gear shifting rule, then the lowest gear of the gear disk in the vehicle is determined to be the target gear, thereby achieving the target gear according to the gear speed corresponding to the adaptive gear shifting rule determined according to the scene information, which can fully reflect the influence of the scene information on the target gear.
  • the scenario-based predictive shifting schedule adaptive method of this embodiment determines the target gear according to the gear speed of the current vehicle at the previous moment, the gear speed corresponding to the adaptive shifting schedule and the gear speed of the current vehicle at the current moment, thereby being able to determine the target gear in combination with the driver's driving habits.
  • FIG11 is a flow chart of an exemplary embodiment before step S220 in the scenario-based predictive shift schedule adaptive method shown in FIG2.
  • the scenario-based predictive shift schedule adaptive method of the embodiment of the present application at least further includes steps S1110 to S1130, which are described in detail as follows:
  • Step S1110 dividing the current lane, the left lane and the right lane within the sight distance according to the preset distance, to obtain a plurality of lane segments in each lane.
  • the embodiment of the present application needs to divide the current lane, the left lane, and the right lane within the line of sight distance to obtain multiple lane segments on the current lane, multiple lane segments on the left lane, and multiple lane segments on the right lane.
  • Step S1120 calculating a first reference vehicle speed difference between a reference vehicle speed corresponding to a first lane segment and a reference vehicle speed corresponding to a second lane segment of adjacent lane segments in the current lane.
  • the lane segment away from the vehicle's front direction is determined as the first lane segment
  • the lane segment close to the vehicle's front direction is determined as the second lane segment in the adjacent lane segments.
  • the server calculates the speed difference between the reference speed corresponding to the first lane segment and the reference speed corresponding to the second lane segment in the adjacent lane segments in the current lane, and uses the speed difference as the first reference speed difference.
  • the reference speed corresponding to the first lane segment and the reference speed corresponding to the second lane segment in the adjacent lane segments can refer to the calculation method of the reference speed on the lane where the current vehicle is traveling. That is to say, the reference vehicle speed corresponding to the first lane segment and the reference vehicle speed corresponding to the second lane segment in the adjacent lane segments are determined according to the scene information in the corresponding lane segments.
  • Vreference (n) the reference speed corresponding to the first lane segment of the adjacent lane segment in the current lane
  • Vreference (n-1) the reference speed corresponding to the second lane segment of the adjacent lane segment in the current lane
  • Vreference (n-1) the first reference speed difference
  • Vreference (n) -Vreference (n-1) the first reference speed difference
  • Step S1130 determining a shift decision factor corresponding to the reference speed of the current lane according to the first reference speed difference and the first sight line position ratio of the first lane segment in the current lane in the sight line distance.
  • the proportion of the first sight line position of the first lane segment in the current lane in the sight line distance is determined according to the ratio between the first lane segment distance and the sight line distance.
  • the server determines a gear shift decision factor corresponding to the reference vehicle speed of the current lane according to the first reference vehicle speed difference and the first sight line position ratio.
  • the server may further illustrate this step using steps S1131 to S1132 shown in FIG. 12 , as follows:
  • Step S1131 determining a first sight line position ratio according to a ratio between a lane segment distance corresponding to a first lane segment of adjacent lane segments in the current lane and a sight line distance and a preset value.
  • the first sight position ratio is represented by
  • Step S1132 The sum of the products of the first reference vehicle speed differences corresponding to the adjacent lane segments in the current lane segment and the corresponding first sight line position proportions is used as a shift decision factor corresponding to the reference vehicle speed of the current lane.
  • the scenario-based predictive shifting rule adaptive method of this embodiment determines the first reference speed difference according to the reference speed corresponding to the first lane segment and the reference speed corresponding to the second lane segment of the adjacent lane segment obtained by dividing the current lane segment, and determines the shifting decision factor corresponding to the reference speed of the current lane according to the first reference speed difference and the first sight position proportion of the first lane segment in the sight distance in the current lane, thereby being able to predict the shifting decision factor corresponding to the reference speed of the adjacent lane segment in the current lane. Get the gear shift decision factor for the current lane.
  • FIG13 is a flow chart of an exemplary embodiment after step S1110 in the scenario-based predictive shift schedule adaptive method shown in FIG12.
  • the scenario-based predictive shift schedule adaptive method of the embodiment of the present application at least further includes steps S1310 to S1330, which are described in detail as follows:
  • Step S1310 calculating a second reference vehicle speed difference between a reference vehicle speed corresponding to a first lane segment of adjacent lane segments in the left lane and a reference vehicle speed of a corresponding lane segment in the current lane.
  • the server calculates the speed difference between the reference speed corresponding to the first lane segment of the adjacent lane segment in the left lane and the reference speed corresponding to the lane segment in the current lane, and uses the speed difference as the second reference speed difference.
  • the reference speed corresponding to the first lane segment in the adjacent lane segment and the reference speed corresponding to the second lane segment can refer to the calculation method of the reference speed on the lane where the current vehicle is traveling, that is, the reference speed corresponding to the first lane segment in the adjacent lane segment and the reference speed corresponding to the second lane segment are determined according to the scene information in the corresponding lane segment in the left lane.
  • Vreferenceleft(n) the reference speed corresponding to the first lane segment of the adjacent lane segments in the left lane
  • Vreference(n) the reference speed of the corresponding lane segment in the current lane
  • Step S1320 calculating a third reference vehicle speed difference between a reference vehicle speed corresponding to a second lane segment of an adjacent lane segment in the left lane and a reference vehicle speed of a corresponding lane segment in the current lane.
  • the server obtains a third reference vehicle speed difference according to a vehicle speed difference between a reference vehicle speed corresponding to a second lane segment of an adjacent lane segment in the left lane and a reference vehicle speed corresponding to a lane segment in the current lane.
  • the reference speed corresponding to the second lane segment of the adjacent lane segment in the left lane is expressed as Vreference left (n-1)
  • the reference speed of the corresponding lane segment in the current lane is expressed as Vreference (n-1)
  • Step S1330 determining a shift decision factor corresponding to the reference speed of the left lane according to the second reference speed difference, the third reference speed difference, and the second sight line position ratio of the first lane segment of adjacent lane segments in the left lane in the sight line distance.
  • the second sight line position ratio refers to the vehicle position corresponding to the first lane segment of the adjacent lane segment in the left lane. It is determined by the ratio between the track section distance and the sight distance.
  • the server determines a shift decision factor corresponding to the reference speed of the left lane according to the second reference speed difference, the third reference speed difference, and the second sight line position ratio.
  • the server may further illustrate this step using steps S1331 to S1333 shown in FIG. 14 , as follows:
  • Step S1331 calculating a fourth reference vehicle speed difference between the second reference vehicle speed difference and the third reference vehicle speed difference.
  • the server obtains a fourth reference speed difference according to the second reference speed difference and the third reference speed difference.
  • the fourth reference speed difference can be expressed as ( Vreference left (n) - Vreference (n) ) - ( Vreference left (n-1) - Vreference (n-1) ).
  • Step S1332 determining the second sight line position ratio according to a ratio between a lane segment distance corresponding to a first lane segment of adjacent lane segments in the left lane and a sight line distance and a preset value.
  • the server calculates the ratio between the lane segment distance corresponding to the first lane segment of adjacent lane segments in the lane and the sight distance, and uses the sum of the negative of the ratio and a preset value as the second sight position ratio.
  • the preset value may be one.
  • the second sight position ratio can be expressed as
  • Step S1333 The sum of the products of the fourth reference vehicle speed differences corresponding to the adjacent lane segments in the left lane and the corresponding second sight line position proportions is used as the shift decision factor corresponding to the reference vehicle speed of the left lane.
  • the scenario-based predictive shifting rule adaptive method of this embodiment determines the second reference speed difference according to the reference speed corresponding to the first lane segment of the adjacent lane segment obtained by dividing the left lane segment and the reference speed of the corresponding lane segment in the current lane, determines the third reference speed difference according to the reference speed corresponding to the second lane segment in the adjacent lane segment in the left lane and the reference speed of the corresponding lane segment in the current lane, and determines the shift decision factor corresponding to the reference speed of the left lane according to the second reference speed difference, the third reference speed difference and the proportion of the second line of sight position, thereby being able to predict the shift decision factor of the left lane through the reference speed corresponding to the adjacent lane segment in the left lane.
  • FIG15 is a flow chart of an exemplary embodiment after step S1110 in the scenario-based predictive shift schedule adaptive method shown in FIG12.
  • the scenario-based predictive shift schedule adaptive method of the embodiment of the present application further includes at least steps S1510 to S1530, which are described in detail as follows:
  • Step S1510 calculating a fifth reference vehicle speed difference between a reference vehicle speed corresponding to a first lane segment of adjacent lane segments in the right lane and a reference vehicle speed of a corresponding lane segment in the current lane.
  • the server obtains a fifth reference speed difference value according to a speed difference between a reference speed corresponding to a first lane segment of adjacent lane segments in the right lane and a reference speed corresponding to a lane segment in the current lane.
  • Vreferenceright(n) the reference vehicle speed corresponding to the first lane segment of the adjacent lane segments in the right lane
  • Vreference(n) the reference vehicle speed of the corresponding lane segment in the current lane
  • Vreference(n) the fifth reference vehicle speed difference
  • Step S1520 calculating a sixth reference vehicle speed difference between a reference vehicle speed corresponding to a second lane segment of an adjacent lane segment in the right lane and a reference vehicle speed of a corresponding lane segment in the current lane.
  • the server obtains a sixth reference speed difference value according to a speed difference between a reference speed corresponding to a second lane segment of an adjacent lane segment in the right lane and a reference speed corresponding to a lane segment in the current lane.
  • Vreference right (n-1) the reference speed corresponding to the second lane segment of the adjacent lane segment in the right lane
  • Vreference (n-1) the reference speed of the corresponding lane segment in the current lane
  • Step S1530 determining a shift decision factor corresponding to the reference speed of the right lane according to the fifth reference speed difference, the sixth reference speed difference, and the third sight line position ratio of the first lane segment of adjacent lane segments in the right lane in the sight line distance.
  • the third sight line position ratio is determined based on a ratio between a lane segment distance corresponding to a first lane segment of adjacent lane segments in the right lane and a sight line distance.
  • the server determines a shift decision factor corresponding to the reference speed of the right lane based on the fifth reference speed difference, the sixth reference speed difference, and the third sight line position ratio.
  • the server may further illustrate this step using steps S1531 to S1533 shown in FIG. 16 , as follows:
  • Step S1531 calculating a seventh reference vehicle speed difference between the fifth reference vehicle speed difference and the sixth reference vehicle speed difference.
  • the server obtains a seventh reference speed difference according to the fifth reference speed difference and the sixth reference speed difference.
  • the seventh reference speed difference can be expressed as ( Vreference right (n) - Vreference (n) ) - ( Vreference right (n-1) - Vreference (n-1) ).
  • Step S1532 determining a third sight line position ratio according to a ratio between a lane segment distance corresponding to a first lane segment of adjacent lane segments in the right lane and a sight line distance and a preset value.
  • the server calculates the ratio between the lane segment distance corresponding to the first lane segment of the adjacent lane segments in the right lane and the sight distance, and uses the sum of the negative of the ratio and a preset value as the second sight position ratio.
  • the preset value may be one.
  • the third sight position ratio can be represented as
  • Step S1533 The sum of the products of the seventh reference speed differences corresponding to the adjacent lane segments in the right lane and the corresponding third sight line position proportions is used as a shift decision factor corresponding to the reference speed of the right lane.
  • the scenario-based predictive shift schedule adaptive method of this embodiment determines the fifth reference speed difference according to the reference speed corresponding to the first lane segment of the adjacent lane segment obtained by dividing the right lane segment and the reference speed of the corresponding lane segment in the current lane, determines the sixth reference speed difference according to the reference speed corresponding to the second lane segment in the adjacent lane segment in the right lane and the reference speed of the corresponding lane segment in the current lane, and determines the shift decision factor corresponding to the reference speed of the left lane according to the fifth reference speed difference, the sixth reference speed difference and the third line of sight position ratio, thereby being able to predict the shift decision factor of the right lane through the reference speed corresponding to the adjacent lane segment in the right lane.
  • Figure 17 represents the distance corresponding to each lane segment
  • the vertical axis represents the current lane, the left lane, and the right lane, that is, the current lane, the left lane of the current lane, and the right lane of the current lane.
  • Each lane segment corresponds to a reference speed, and the reference speed corresponding to each lane segment can be determined according to the scene information of the lane segment.
  • the reference speed Vzhong2 corresponding to this lane segment is less than the reference speed Vzhong1 corresponding to the first lane segment.
  • the reference speed corresponding to this lane segment is Vzhong4 . It can be seen that the reference speed corresponding to each lane segment is related to the scene information.
  • FIG18 is a block diagram of a scenario-based predictive shift schedule adaptive device according to an exemplary embodiment of the present application.
  • the exemplary scenario-based predictive shift schedule adaptive device 1800 includes a reference vehicle speed determination module 181, a shift vehicle speed determination module 182, and an execution module 183. Specifically:
  • the reference vehicle speed determination module 181 is configured to determine a reference vehicle speed on a lane in which the vehicle is currently traveling according to scene information acquired during the current vehicle traveling process.
  • the gear shifting speed determining module 182 is configured to determine the gear shifting speed corresponding to the adaptive gear shifting rule according to the gear shifting decision factor corresponding to the reference vehicle speed on the lane.
  • the execution module 183 is configured to determine the target gear according to the gear speed of the current vehicle at the current moment, the gear speed of the current vehicle at the previous moment, and the shift speed corresponding to the adaptive shifting rule, and perform the execution operation based on the target gear.
  • the reference speed on the lane where the current vehicle is traveling is obtained by converting the scene information acquired during the current vehicle's driving process, and the shift speed corresponding to the adaptive shift schedule is determined according to the shift decision factor corresponding to the reference speed on the lane.
  • the target gear is determined according to the gear speed of the current vehicle at the current moment, the gear speed of the current vehicle at the previous moment, and the shift speed corresponding to the adaptive shift schedule, and the operation is performed based on the target gear.
  • the reference speed on the lane is obtained based on the scene information conversion, which can fully reflect the scene information while reducing the input information dimension of the adaptive shift decision.
  • the reference speed determination module 181 includes: an explicit reference speed determination module, an implicit reference speed determination module, a resistance reference speed determination module and a reference speed determination module on the current vehicle driving lane. Specifically:
  • the explicit reference speed determination module is configured to determine the explicit reference speed on the lane according to a first scene element in the scene information, where the first scene element includes traffic speed information.
  • the implicit reference vehicle speed determination module is configured to determine the implicit reference vehicle speed on the lane according to the second scene element in the scene information, where the second scene element includes road attribute information.
  • the resistance reference vehicle speed determination module is configured to determine the resistance reference vehicle speed on the lane according to a third scene element in the scene information, where the third scene element includes scene resistance information.
  • the reference speed determination module on the lane where the vehicle is currently traveling is configured to determine the reference speed on the lane where the vehicle is currently traveling according to the explicit reference speed, the implicit reference speed and the resistance reference speed on the lane.
  • the implicit reference vehicle speed determination module includes: a traffic speed information acquisition module and a first selection module. Specifically:
  • the traffic speed information acquisition module is configured to acquire the speed of the road speed limit, the speed of the obstacle and the speed of the traffic flow.
  • the first selection module is configured to select the minimum speed among the speed of the road speed limit, the speed of the obstacle and the speed of the traffic flow as the explicit reference speed on the lane.
  • the implicit reference vehicle speed determination module includes: a road attribute information acquisition module and a second selection module. Specifically:
  • the road attribute information acquisition module is configured to acquire a road type speed corresponding to a road type and a road curvature speed corresponding to a road curvature.
  • the second selection module is configured to select the minimum speed of the road type speed and the road curvature speed as the implicit reference speed on the lane.
  • the resistance reference speed determination module includes: a target resistance determination module and a lane resistance reference speed determination module. Specifically:
  • the target resistance determination module is configured to determine the target resistance according to the road grade resistance corresponding to the road grade and the road slope resistance corresponding to the road slope.
  • the module for determining the resistance reference vehicle speed on the lane is configured to determine the resistance reference vehicle speed on the lane according to the acquired sight distance, resistance distance and target resistance.
  • the resistance reference vehicle speed determination module includes: a first ratio calculation module, a first judgment module and a second judgment module. Specifically:
  • the first ratio calculation module is configured to calculate the ratio between the difference between the line of sight distance and the resistance distance and the preset distance.
  • the first judgment module is configured to determine the resistance value of the target resistance as the resistance reference vehicle speed on the current vehicle driving lane if the remainder of the ratio is equal to zero.
  • the second judgment module is configured to determine that the resistance reference speed on the current vehicle driving lane is zero if the remainder of the ratio is equal to one.
  • the gear shift vehicle speed determination module 182 includes: a gear shift decision factor fusion module and a gear shift vehicle speed determination module corresponding to the adaptive gear shift rule. Specifically:
  • the gear shift decision factor fusion module is configured to fuse the gear shift decision factors corresponding to the reference vehicle speed on the driving lane, the reference vehicle speed on the left lane on the left side of the driving lane, and the reference vehicle speed on the right lane on the right side of the driving lane to obtain the gear shift decision fusion factor.
  • the gear shifting vehicle speed determination module corresponding to the adaptive gear shifting rule is configured to determine the gear shifting vehicle speed corresponding to the adaptive gear shifting rule according to the throttle opening and the gear shifting decision fusion factor.
  • the gear shifting speed determination module corresponding to the adaptive gear shifting rule includes: a minimum gear shifting speed and a maximum gear shifting speed acquisition module, a first product calculation module, and a product sum calculation module. Specifically:
  • the minimum gear shifting speed and the maximum gear shifting speed obtaining module are configured to obtain the corresponding minimum gear shifting speed and the maximum gear shifting speed according to the throttle opening.
  • the first product calculation module is configured to calculate a first product between a difference between a maximum gear shifting speed and a minimum gear shifting speed and a gear shifting fusion factor.
  • the product sum calculation module is configured to calculate the sum between the minimum gear shifting vehicle speed and the first product, and use the sum as the gear shifting vehicle speed corresponding to the adaptive gear shifting rule.
  • the shift decision factor fusion module includes: a second product calculation module, a maximum shift decision factor selection module and a shift decision fusion factor determination module. Specifically:
  • the second product calculation module is configured to calculate the second product between the shift decision factor and the corresponding coefficient of the reference speed on the driving lane, the reference speed on the left lane, and the reference speed on the right lane to obtain multiple second products.
  • the maximum gear shift decision factor selection module is configured to select the maximum gear shift decision factor among the gear shift decision factors.
  • the shift decision fusion factor determination module is configured to determine a ratio between a sum of the plurality of second products and a maximum shift decision factor as the shift decision fusion factor.
  • the execution module 183 includes: a third judgment module and a fourth judgment module. Specifically:
  • the third judgment module is configured to determine that the highest gear of the gear disk in the vehicle is the target gear if the gear speed of the current vehicle at the previous moment is less than the gear speed corresponding to the adaptive gear shifting rule, and the gear speed of the current vehicle at the current moment is greater than or equal to the gear speed corresponding to the adaptive gear shifting rule.
  • the fourth judgment module is configured to determine the gear speed of the current vehicle if the gear speed of the current vehicle at the previous moment is greater than the gear speed corresponding to the adaptive gear shifting rule, and the gear speed of the current vehicle at the current moment is less than or equal to the adaptive gear shifting rule.
  • the gear shifting speed corresponding to the gear shifting rule determines that the lowest gear of the vehicle's gear plate is the target gear.
  • the device of the embodiment of the present application further includes: a division module, a first reference speed difference determination module and a gear shifting decision factor determination module corresponding to the reference speed of the current lane. Specifically:
  • the division module is configured to divide the current lane, the left lane and the right lane within the sight distance according to the preset distance to obtain multiple lane segments in each lane.
  • the first reference speed difference determination module is configured to calculate a first reference speed difference between a reference speed corresponding to a first lane segment and a reference speed corresponding to a second lane segment of adjacent lane segments in a current lane.
  • the module for determining the gear shift decision factor corresponding to the reference vehicle speed of the current lane is configured to determine the gear shift decision factor corresponding to the reference vehicle speed of the current lane according to the first reference vehicle speed difference and the proportion of the first lane segment in the first sight line position in the sight line distance in the current lane.
  • the gear shift decision factor determination module corresponding to the reference vehicle speed of the current lane includes: a first sight position proportion calculation module and a first action module. Specifically:
  • the first sight line position ratio calculation module is configured to determine the first sight line position ratio according to a ratio between a lane segment distance corresponding to a first lane segment of adjacent lane segments in a current lane and a sight line distance and a preset value.
  • the first module is configured to use the product of the first reference speed difference corresponding to each adjacent lane segment in the current lane segment and the corresponding first sight line position ratio as the shift decision factor corresponding to the reference speed of the current lane.
  • the device of the embodiment of the present application further includes: a second reference speed difference calculation module, a third reference speed difference calculation module and a shift decision factor determination module corresponding to the reference speed of the left lane. Specifically:
  • the second reference speed difference calculation module is configured to calculate a second reference speed difference between a reference speed corresponding to a first lane segment of adjacent lane segments in the left lane and a reference speed corresponding to a lane segment in the current lane.
  • the third reference speed difference calculation module is configured to calculate a third reference speed difference between a reference speed corresponding to a second lane segment of adjacent lane segments in the left lane and a reference speed of a corresponding lane segment in the current lane.
  • the gear shift decision factor determination module corresponding to the reference vehicle speed of the left lane is configured to determine the gear shift decision factor according to the second reference vehicle speed.
  • the speed difference, the third reference speed difference and the second sight line position ratio of the first lane segment of adjacent lane segments in the left lane in the sight line distance determine the shift decision factor corresponding to the reference speed of the left lane.
  • the gear shift decision factor determination module corresponding to the reference speed of the left lane includes: a fourth reference speed difference calculation module, a second sight position ratio calculation module and a second action module. Specifically:
  • the fourth reference vehicle speed difference calculation module is configured to calculate a fourth reference vehicle speed difference between the second reference vehicle speed difference and the third reference vehicle speed difference.
  • the second sight line position ratio calculation module is configured to determine the second sight line position ratio according to a ratio between a lane segment distance corresponding to a first lane segment of adjacent lane segments in a left lane and a sight line distance and a preset value.
  • the second module is configured to use the product of the fourth reference speed difference corresponding to each adjacent lane segment in the left lane and the corresponding second sight line position ratio as the shift decision factor corresponding to the reference speed of the left lane.
  • the device of the embodiment of the present application further includes: a fifth reference speed difference calculation module, a sixth reference speed difference calculation module and a shift decision factor determination module corresponding to the reference speed of the right lane. Specifically:
  • the fifth reference speed difference calculation module is configured to calculate a fifth reference speed difference between a reference speed corresponding to a first lane segment of adjacent lane segments in the right lane and a reference speed of a corresponding lane segment in the current lane.
  • the sixth reference speed difference calculation module is configured to calculate a sixth reference speed difference between a reference speed corresponding to a second lane segment of an adjacent lane segment in the right lane and a reference speed of a corresponding lane segment in the current lane.
  • the module for determining the gear shift decision factor corresponding to the reference speed of the right lane is configured to determine the gear shift decision factor corresponding to the reference speed of the right lane based on the fifth reference speed difference, the sixth reference speed difference, and the third sight line position proportion of the first lane segment of adjacent lane segments in the right lane in the sight line distance.
  • the gear shift decision factor determination module corresponding to the reference speed of the right lane includes: a seventh reference speed difference calculation module, a third sight position ratio calculation module and a third as module. Specifically:
  • the seventh reference vehicle speed difference calculation module is configured to calculate a seventh reference vehicle speed difference between the fifth reference vehicle speed difference and the sixth reference vehicle speed difference.
  • the third sight line position ratio calculation module is configured to determine the third sight line position ratio according to a ratio between a lane segment distance corresponding to a first lane segment of adjacent lane segments in a right lane and a sight line distance and a preset value.
  • the third module is configured to use the product of the seventh reference speed difference corresponding to each adjacent lane segment in the right lane and the corresponding third sight line position ratio as the shift decision factor corresponding to the reference speed of the right lane.
  • scenario-based predictive shift schedule adaptive device provided in the above embodiment and the scenario-based predictive shift schedule adaptive method provided in the above embodiment belong to the same concept, wherein the specific manner in which each module and unit performs operations has been described in detail in the method embodiment, and will not be repeated here.
  • the scenario-based predictive shift schedule adaptive device provided in the above embodiment can allocate the above functions to different functional modules as needed, that is, divide the internal structure of the device into different functional modules to complete all or part of the functions described above, and this is not limited here.
  • An embodiment of the present application also provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, the electronic device implements the scenario-based predictive shift schedule adaptive method provided in the above-mentioned embodiments.
  • Fig. 19 shows a schematic diagram of a computer system of an electronic device suitable for implementing an embodiment of the present application. It should be noted that the computer system 1900 of the electronic device shown in Fig. 19 is only an example and should not bring any limitation to the functions and scope of use of the embodiment of the present application.
  • the computer system 1900 includes a central processing unit (CPU) 1901, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 1902 or the program loaded from the storage part 1908 to the random access memory (RAM) 1903, such as executing the method described in the above embodiment.
  • CPU 1901, ROM 1902 and RAM 1903 are connected to each other through bus 1904.
  • I/O Input/output
  • the following components are connected to the I/O interface 1905: an input section 1906 including a keyboard, a mouse, etc.; an output section 1907 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker; a storage section including a hard disk, etc. 1908; and a communication section 1909 including a network interface card such as a LAN (Local Area Network) card, a modem, etc.
  • the communication section 1909 performs communication processing via a network such as the Internet.
  • a drive 1910 is also connected to the I/O interface 1905 as needed.
  • a removable medium 1911 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1910 as needed, so that a computer program read therefrom is installed into the storage section 1908 as needed.
  • an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart.
  • the computer program can be downloaded and installed from a network through a communication section 1909, and/or installed from a removable medium 1911.
  • CPU central processing unit
  • the computer-readable medium shown in the embodiment of the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two.
  • the computer-readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above.
  • Computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.
  • a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable computer program.
  • This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above.
  • a computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device.
  • a computer program contained on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.
  • Each square frame in can represent a module, a program segment, or a part of code, and the above-mentioned module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function.
  • the functions marked in the square frame can also occur in a sequence different from that marked in the accompanying drawings. For example, two square frames represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved.
  • each square frame in the block diagram or flow chart, and the combination of the square frames in the block diagram or flow chart can be realized by a dedicated hardware-based system that performs the specified function or operation, or can be realized by a combination of dedicated hardware and computer instructions.
  • the units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor.
  • the names of these units do not constitute limitations on the units themselves in some cases.
  • Another aspect of the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the scenario-based predictive shift schedule adaptive method as described above.
  • the computer-readable storage medium may be included in the electronic device described in the above embodiment, or may exist independently without being assembled into the electronic device.
  • Another aspect of the present application also provides a computer program product or a computer program, the computer program product or the computer program includes a computer instruction, the computer instruction is stored in a computer-readable storage medium.
  • the processor of the computer device reads the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the computer device executes the scenario-based predictive shift schedule adaptive method provided in each of the above embodiments.

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Abstract

本申请实施例揭示了一种基于场景的预测性换挡规律自适应方法及相关设备。该基于场景的预测性换挡规律自适应方法包括：根据当前车辆行驶过程中获取的场景信息转换得到当前车辆行驶车道上的基准车速；根据车道上的基准车速对应的换挡决策因子确定自适应换挡规律对应的换挡车速；根据当前车辆在当前时刻的档位车速、当前车辆在前一时刻的档位车速以及自适应换挡规律对应的换挡车速确定目标档位，并基于目标档位进行执行操作。

Description

基于场景的预测性换挡规律自适应方法及相关设备
本申请要求于2022年10月18日提交中国专利局，申请号为202211276755.5、申请名称为“基于场景的预测性换挡规律自适应方法及相关设备”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及车辆技术领域，具体涉及一种基于场景的预测性换挡规律自适应方法、装置、电子设备以及计算机可读存储介质。
背景技术
随着汽车行业智能化与电气化的进程以及汽车产品越来越消费品化，汽车产品对人和景的自适应智能控制越来越紧迫。车辆根据场景信息进行自主的智能控制越来越重要。
多挡位变速器的换挡规律决定了变速器的换挡时机，挡位的切换目的为协调系统的动力性和经济性，但是目前的换挡规律大多从车辆当前状态参数以及驾驶员历史操作信息中给出固定级别的可选换挡规律，例如，包含针对经济性的换挡规律、经济性和动力性均中庸的换挡规律、针对驾驶性的换挡规律，这些换挡规律固定且不可改变，人类驾驶员需要适应车辆换挡规律的特点。而驾驶员在经济性和动力性之间的期望是根据当前车辆状态和车辆前方出现的场景不断变化的，固定的换挡规律无法自动适应驾驶员的期望。
因此，如何将车辆行驶过程中前方出现的场景适应到车辆换挡规律中成为亟待解决的问题。
发明内容
为解决上述技术问题，本申请的实施例提供了一种基于场景的预测性换挡规律自适应方法、装置、电子设备以及计算机可读存储介质。
根据本申请实施例的一个方面，提供了一种基于场景的预测性换挡规律 自适应方法，所述基于场景的预测性换挡规律自适应方法包括：根据当前车辆行驶过程中获取的场景信息转换得到所述当前车辆行驶车道上的基准车速；根据所述车道上的基准车速对应的换挡决策因子确定自适应换挡规律对应的换挡车速；根据所述当前车辆在当前时刻的档位车速、所述当前车辆在前一时刻的档位车速以及所述自适应换挡规律对应的换挡车速确定目标档位，并基于所述目标档位进行执行操作。
根据本申请实施例的一个方面，提供了一种基于场景的预测性换挡规律自适应装置，所述装置包括：基准车速确定模块，配置为根据当前车辆行驶过程中获取的场景信息转换得到所述当前车辆行驶车道上的基准车速；换挡车速确定模块，配置为根据所述车道上的基准车速对应的换挡决策因子确定自适应换挡规律对应的换挡车速；执行模块，配置为根据所述当前车辆在当前时刻的档位车速、所述当前车辆在前一时刻的档位车速以及所述自适应换挡规律对应的换挡车速确定目标档位，并基于所述目标档位进行执行操作。
根据本申请实施例的一个方面，提供了一种电子设备，包括：存储器，存储有计算机可读指令；处理器，读取存储器存储的计算机可读指令，以执行上述任一项的基于场景的预测性换挡规律自适应方法。
根据本申请实施例的一个方面，提供了一种计算机可读存储介质，其上存储有计算机可读指令，当所述计算机可读指令被计算机的处理器执行时，使计算机执行如上所述的基于场景的预测性换挡规律自适应方法。
根据本申请实施例的一个方面，还提供了一种计算机程序产品，包括计算机程序，该计算机程序被处理器执行时实现如上所述的基于场景的预测性换挡规律自适应方法中的步骤。
在本申请的实施例提供的技术方案中，通过将当前车辆行驶过程中获取的场景信息转换得到当前车辆行驶车道上的基准车速，并根据车道上的基准车速对应的换档决策因子确定自适应换挡规律对应的换挡车速，进而根据所述当前车辆在当前时刻的档位车速、所述当前车辆在前一时刻的档位车速以及所述自适应换挡规律对应的换挡车速确定目标档位，并基于所述目标档位进行执行操作，由此基于场景信息转换得到车道上的基准车速，能够在充分体现场景信息的同时减小自适应换挡决策的输入信息维度。
应当理解的是，以上的一般描述和后文的细节描述仅是示例性和解释性 的，并不能限制本申请。
附图说明
此处的附图被并入说明书中并构成本说明书的一部分，示出了符合本申请的实施例，并与说明书一起用于解释本申请的原理。显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术者来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。在附图中：
图1是一示例性实施例示出的基于场景的预测性换挡规律自适应方法的实施环境示意图；
图2是本申请的一示例性实施例示出的基于场景的预测性换挡规律自适应方法的流程图；
图3是图2所示的基于场景的预测性换挡规律自适应方法中步骤S210的一示例性实施例的流程图；
图4是图3所示的基于场景的预测性换挡规律自适应方法中步骤S310的一示例性实施例的流程图；
图5是图3所示的基于场景的预测性换挡规律自适应方法中步骤S320的一示例性实施例的流程图；
图6是图3所示的基于场景的预测性换挡规律自适应方法中步骤S330的一示例性实施例的流程图；
图7是图2所示的基于场景的预测性换挡规律自适应方法中步骤S220的一示例性实施例的流程图；
图8是图2所示的基于场景的预测性换挡规律自适应方法中步骤S710的一示例性实施例的流程图；
图9是图2所示的基于场景的预测性换挡规律自适应方法中步骤S720的一示例性实施例的流程图；
图10是图2所示的基于场景的预测性换挡规律自适应方法中步骤S230的一示例性实施例的流程图；
图11是图2所示的基于场景的预测性换挡规律自适应方法中步骤S220之前的一示例性实施例的流程图；
图12是图11所示的基于场景的预测性换挡规律自适应方法中步骤 S1130的一示例性实施例的流程图；
图13是图12所示的基于场景的预测性换挡规律自适应方法中步骤S1110之后的一示例性实施例的流程图；
图14是图13所示的基于场景的预测性换挡规律自适应方法中步骤S1330的一示例性实施例的流程图；
图15是图12所示的基于场景的预测性换挡规律自适应方法中步骤S1110之后的一示例性实施例的流程图；
图16是图15所示的基于场景的预测性换挡规律自适应方法中步骤S1530的一示例性实施例的流程图；
图17是本申请示出的基于场景的预测性换挡规律自适应方法中车道与各车道对应基准车速之间的关系示意图；
图18是本申请的一示例性实施例示出的基于场景的预测性换挡规律自适应装置的框图；
图19示出了适于用来实现本申请实施例的电子设备的计算机系统的结构示意图。
具体实施方式
这里将详细地对示例性实施例执行说明，其示例表示在附图中。下面的描述涉及附图时，除非另有表示，不同附图中的相同数字表示相同或相似的要素。以下示例性实施例中所描述的实施方式并不代表与本申请相一致的所有实施方式。相反，它们仅是与如所附权利要求书中所详述的、本申请的一些方面相一致的装置和方法的例子。
附图中所示的方框图仅仅是功能实体，不一定必须与物理上独立的实体相对应。即，可以采用软件形式来实现这些功能实体，或在一个或多个硬件模块或集成电路中实现这些功能实体，或在不同网络和/或处理器装置和/或微控制器装置中实现这些功能实体。
附图中所示的流程图仅是示例性说明，不是必须包括所有的内容和操作/步骤，也不是必须按所描述的顺序执行。例如，有的操作/步骤还可以分解，而有的操作/步骤可以合并或部分合并，因此实际执行的顺序有可能根据实际情况改变。
在本申请中提及的“多个”是指两个或者两个以上。“和/或”描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。字符“/”一般表示前后关联对象是一种“或”的关系。
首先说明的是，汽车行业智能化与电气化的进程以及汽车产品越来越消费品化，汽车产品对人和景的自适应智能控制越来越紧迫。车辆根据场景信息进行自主的智能控制越来越重要。
多挡位变速器的换挡规律决定了变速器的换挡时机，挡位的切换目的为协调系统的动力性和经济性，但是目前的换挡规律大多从车辆当前状态参数以及驾驶员历史操作信息中给出固定级别的可选换挡规律，例如，包含针对经济性的换挡规律、经济性和动力性均中庸的换挡规律、针对驾驶性的换挡规律，这些换挡规律固定且不可改变，人类驾驶员需要适应车辆换挡规律的特点。而驾驶员在经济性和动力性之间的期望是根据当前车辆状态和车辆前方出现的场景不断变化的，固定的换挡规律无法自动适应驾驶员的期望。
因此，如何将车辆行驶过程中前方出现的场景适应到车辆换挡规律中成为亟待解决的问题。
基于此，为了实现基于场景信息的换挡规律自适应，本申请实施例提出了一种基于场景的预测性换挡规律自适应方法、装置、电子设备以及计算机可读存储介质，具体的：通过将当前车辆行驶过程中获取的场景信息转换得到当前车辆行驶车道上的基准车速，并根据车道上的基准车速对应的换档决策因子确定自适应换挡规律对应的换挡车速，进而根据当前车辆在当前时刻的档位车速、当前车辆在前一时刻的档位车速以及自适应换挡规律对应的换挡车速确定目标档位，并基于目标档位进行执行操作，由此基于场景信息转换得到车道上的基准车速，能够在充分体现场景信息的同时减小自适应换挡决策的输入信息维度。
图1是一示例性实施例示出的基于场景的预测性换挡规律自适应方法的实施环境示意图。该实施环境包括场景信息获取端110和服务端120，场景信息获取端设置于车辆上，具体可以设置于车辆车头方向上，场景信息获取端110与服务端120预先建立有线或者无线的网络连接。
如图1所示，基于场景的预测性换挡规律自适应过程中，安装于车辆车 头方向上的场景信息获取端110获取当前车辆行驶过程中的场景信息，并将该场景信息发送至服务端120，服务端120接收场景信息，并将场景信息进行转换处理，得到当前车辆行驶车道上的基准车速，并根据车道上的基准车速对应的换挡决策因此确定自适应换挡规律对应的换挡车速，进而根据当前车辆在当前时刻的档位车速、当前车辆在前一时刻的档位车速以及自适应换挡规律对应的换挡车速确定目标档位，并基于目标档位进行执行操作。
其中，图1所示的场景信息获取端110可以是传感器等任意支持场景信息获取的装置，但并不限于此。图1所示的服务端120可以是服务器，例如可以是独立的物理服务器，也可以是多个物理服务器构成的服务器集群或者分布式系统，还可以是提供云服务、云数据库、云计算、云函数、云存储、网络服务、云通信、中间件服务、域名服务、安全服务、CDN(Content Delivery Network，内容分发网络)、以及大数据和人工智能平台等基础云计算服务的云服务器，在此也不进行限制。场景信息获取端110可以通过3G(第三代的移动信息技术)、4G(第四代的移动信息技术)、5G(第五代的移动信息技术)等无线网络与服务端120进行通信，本处也不对此进行限制。
请参阅图2，图2是本申请的一示例性实施例示出的基于场景的预测性换挡规律自适应方法的流程图。该方法可以应用于图1所示的实施环境，并由该实施环境中的服务端120具体执行。应理解的是，该方法也可以适用于其它的示例性实施环境，并由其它实施环境中的设备具体执行，本实施例不对该方法所适用的实施环境进行限制。
下面以服务器作为具体的执行主体来对本申请实施例提出的基于场景的预测性换挡规律自适应方法进行详细介绍。
如图2所示，在一示例性的实施例中，基于场景的预测性换挡规律自适应方法至少包括步骤S210至步骤S230，详细介绍如下：
步骤S210，根据当前车辆行驶过程中获取的场景信息转换得到当前车辆行驶车道上的基准车速。
首先需要说明的是，场景信息包括近场传感器信息或地图信息。地图包括导航地图、adas地图或高精地图。其中，近场传感器信息包括车辆行驶过程中车头前方场景的目标物数量、类型、目标在场景中的位置、相对速度以及加速度，而目标物包括但不限于车辆、行人、道路标识、路口、交通灯等。 地图信息包含道路等级、道路类型、道路限速、道路路口、道路曲率、道路坡度、道路交通流、交通标识类型及位置等。
考虑到车辆行驶过程中场景信息的维度及复杂度的问题，若将多维度或复杂化的场景信息直接用于自适应换挡规律的输入信息，将导致增加换挡规律的计算复杂性，因此，本实施例对多维度及复杂度的场景信息进行转换，得到统一的基准车速。具体的，服务器将场景信息转化为车道上的基准车速。
需要说明的是，本申请实施例不仅可以根据当前车辆行驶过程中获取的场景信息转化得到当前车辆行驶车道上的基准车速，还可以根据当前车辆行驶车道左侧或右侧上的车辆行驶过程中的场景信息确定左车道或右车道上的基准车速。
步骤S220，根据车道上的基准车速对应的换挡决策因子确定自适应换挡规律对应的换挡车速。
换挡决策因子是基于基准车速确定的。若存在当前车辆行驶车道、左车道和右车道时，换挡决策因子包括基于当前车辆行驶车道上的基准车速确定的换挡决策因子，基于左车道上的基准车速确定的换挡决策因子和基于右车道上的基准车速确定的换挡决策因子。
自适应换挡规律是指根据场景信息确定的换挡规律。
自适应换挡规律对应的换挡车速是指根据自适应换挡规律确定的换挡车速。
服务器根据车道上的基准车速对应的换挡决策因子确定自适应换挡规律对应的换挡车速。具体的，服务器可根据当前车辆行驶车道上的基准车速、左车道上的基准车速和右车道上的基准车速各自对应的换挡决策因子确定自适应换挡规律对应的换挡车速。
步骤S230，根据当前车辆在当前时刻的档位车速、当前车辆在前一时刻的档位车速以及自适应换挡规律对应的换挡车速确定目标档位，并基于目标档位进行执行操作。
当前时刻的档位车速是指当前档位所对应车速。
前一时刻的档位车速是指时间早于当前时刻的前一时刻的档位所对应车速。
服务器根据当前车辆在当前时刻的档位车速、当前车辆在前一时刻的档 位车速以及自适应换挡规律对应的换挡车速确定目标档位，并基于目标档位进行执行操作。
可以看出，本实施例的基于场景的预测性换挡规律自适应方法通过将当前车辆行驶过程中获取的场景信息转换得到当前车辆行驶车道上的基准车速，并根据车道上的基准车速对应的换档决策因子确定自适应换挡规律对应的换挡车速，进而根据当前车辆在当前时刻的档位车速、当前车辆在前一时刻的档位车速以及自适应换挡规律对应的换挡车速确定目标档位，并基于目标档位进行执行操作，由此基于场景信息转换得到车道上的基准车速，能够在充分体现场景信息的同时减小自适应换挡决策的输入信息维度。
图3是图2所示的基于场景的预测性换挡规律自适应方法中步骤S210的一示例性实施例的流程图。在图3所示的实施例中，根据场景信息中的第一场景要素、第二场景要和第三场景要确定当前车辆行驶车道上的显性基准车速、隐性基准车速和阻力基准车速，进而根据显性基准车速、隐性基准车速和阻力基准车速确定当前车辆行驶车道上的基准车速。
如图3所示，在一示例性实施例中，在步骤S210根据当前车辆行驶过程中获取的场景信息转换得到当前车辆行驶车道上的基准车速至少还包括步骤S310至步骤S340，详细介绍如下：
步骤S310，根据场景信息中的第一场景要素确定车道上的显性基准车速。
第一场景要素包括交通速度信息，是指显性的场景信息，具体是指直接包括速度信息的场景要素。示例性的，交通速度信息包括道路限速、障碍物和交通流等。
显性基准车速是指根据第一场景要素确定的当前车辆行驶车道上的显性基准车速。
服务器根据场景信息中的第一场景要素确定车道上的显性基准车速。
作为一示例的，服务器可采用图4中示出的步骤S311～步骤S312进一步对本步骤进行说明，详情如下：
步骤S311，获取道路限速的速度、障碍物的速度和交通流的速度。
步骤S312，选取道路限速的速度、障碍物的速度和交通流的速度中的最小速度为车道上的显性基准车速。
道路限速的速度是指当前车辆在行驶过程前方场景信息中的道路限速， 例如，前方场景中的限速牌显示的限速速度。
障碍物的速度是指当前车辆在行驶过程前方场景信息中障碍物相对当前车辆的速度。
交通流的速度是指当前车辆在行驶过程前方场景信息中车流的车速。
服务器将道路限速的速度、障碍物的速度和交通流的速度中的最小速度作为当前车辆行驶车道上的显性基准车速。需要说明的是，若第一场景要素中还包括其他速度，则此时将所有速度中的最小速度作为车道上的显性基准车速。
另，若将当前车辆行驶车道上的显性基准车速表示为V显性，道路限速的速度表示为V限速，障碍物的速度表示为V障碍物，交通流的速度表示为V交通流，则当前车辆行驶车道上的显性基准车速满足下式：
V显性＝min(V交通流,V障碍物,V限速)。
步骤S320，根据场景信息中的第二场景要素确定车道上的隐性基准车速，第二场景要素包括道路属性信息。
第二场景要素包括道路属性信息，是指隐性的场景信息，具体是指不直接包括速度信息但是对道路行驶速度有限制的场景要素。示例性的，道路属性信息包括道路类型、道路曲率等。
隐性基准车速是指根据第二场景要素确定的当前车辆行驶车道上的隐性基准车速。
服务器根据场景信息中的第二场景要素确定车道上的隐性基准车速。
作为一示例的，服务器可采用图5中示出的步骤S321～步骤S322进一步对本步骤进行说明，详情如下：
步骤S321，获取道路类型对应的道路类型速度和道路曲率对应的道路曲率速度。
步骤S322，选取道路类型速度和道路曲率速度中的最小速度为车道上的隐性基准车速。
道路类型对应的道路类型速度可通过查表确定。例如，道路类型表示为L道路类型，则道路类型速度V道路类型＝F2(L道路类型)，其中，函数F2可以为查表表格。
道路曲率对应的道路曲率速度也可通过查表确定。例如，道路曲率表示为C道路曲率，则道路曲率速度V道路曲率＝F3(C道路曲率)，其中，函数F2可以为预设的查表函数差值，也可以为预设的拟合函数。
服务器将道路类型速度和道路曲率速度中的最小速度作为当前车辆行驶车道上的隐性基准车速。
需要说明的是，若将当前车辆行驶车道上的隐性基准车速表示为V隐性，道路类型速度表示为V道路类型，道路曲率速度表示为V道路曲率，则当前车辆行驶车道上的隐性基准车速满足下式：
V隐性＝min(V道路类型,V道路曲率)。
另外，服务器也可以预设设置的优先级取值逻辑确定隐性基准车速。示例性的，若服务器设置道路类型的优先级高于道路曲率，则可将道路类型速度作为隐性基准车速。
步骤S330，根据场景信息中的第三场景要素确定车道上的阻力基准车速，第三场景要素包括场景阻力信息。
第三场景要素包括场景阻力信息，是指不包括速度信息和对道路行驶速度有限制的场景要素，但是包括对车辆行驶阻力有影响的场景要素。示例性的，场景阻力信息包括道路等级、道路坡度等。
阻力基准车速是指根据第三场景要素确定的当前车辆行驶车道上的阻力基准车速。
服务器根据场景信息中的第三场景要素确定车道上的阻力基准车速。
作为一示例的，服务器可采用图6中示出的步骤S331～步骤S332进一步对本步骤进行说明，详情如下：
步骤S331，根据道路等级对应的道路等级阻力和道路坡度对应的道路坡度阻力确定目标阻力。
道路等级阻力是基于道路等级进行查表确定的。例如，道路等级表示为Class道路等级，则道路等级阻力R道路等级＝F5(Class道路等级)，其中，函数F5可以为查表表格。
道路坡度阻力是基于道路坡度进行查表确定的。例如，道路坡度表示为Slope道路坡度，则道路坡度阻力R道路坡度＝F6(Slope道路坡度)，其中，函数F6可 以为查表表格或者线性拟合函数。
目标阻力是道路等级阻力与道路坡度阻力之间的阻力和。
服务器计算道路等级阻力与道路坡度阻力之间的阻力和，将阻力和作为目标阻力。
步骤S332，根据获取的视线距离、阻力距离和目标阻力确定车道上的阻力基准车速。
阻力距离是指目标阻力的阻力值不为零的位置对应的距离。
视线距离是指车辆行驶过程中前方场景的视线范围。
服务器根据视线距离、阻力距离和目标阻力确定车道上的阻力基准车速。示例性的，服务器通过计算实现距离和阻力距离之间的差值，并计算差值与预设距离之间的比值，若比值的余数等于零，则将目标阻力的阻力值确定为当前车辆行驶车道上的阻力基准车速；若比值的余数等于一，则确定当前车辆行驶车道上的阻力基准车速为零。
具体的，阻力基准车速满足下式：
其中，mod函数是指取余数，Dis是指视线距离，Dis阻力是指阻力距离，2Dis周期是指预设距离，Dis周期为方波周期，可以为视线范围内距离的分辨率或其整数倍，V阻力(Dis)为阻力基准车速，R阻力是指目标阻力。
步骤S340，根据车道上的显性基准车速、隐性基准车速和阻力基准车速确定当前车辆行驶车道上的基准车速。
服务器选取显性基准车速、隐性基准车速中的最小基准车速，并计算最小基准车速与阻力基准车速之间车速和，并将车速和作为当前车辆行驶道路上的基准车速。
示例性的，基准车速满足下式：
V基准＝min(V显性+V隐性)+V阻力。
可以看出，本实施例的基于场景的预测性换挡规律自适应方法根据场景信息中的第一场景要素、第二场景要素和第三场景要素分别确定当前车辆行驶车道上的显性基准车速、隐性基准车速和阻力基准车速，进而根据车道上 的显性基准车速、隐性基准车速和阻力基准车速确定对应车道上的基准车速，由此实现将场景信息转化为车道上的基准车速，减少后续目标档位确定的输入维度，避免了目标档位确定的复杂性。
图7是图2所示的基于场景的预测性换挡规律自适应方法中步骤S220的一示例性实施例的流程图。在图7所示的实施例中，根据当前车辆行驶车道上的基准车速、行驶车道左侧的左车道上的基准车速、行驶车道右侧的右车道上的基准车速各自对应的换挡决策因子确定的换挡决策融合因子，确定自适应换挡规律对应的换挡车速。
如图7所示，在一示例性实施例中，在步骤S220根据当前车辆在车道上的基准车速对应的换挡决策因子确定自适应换挡规律对应的换挡车速的过程至少还包括步骤S710至步骤S720，详细介绍如下：
步骤S710，融合行驶车道上的基准车速、行驶车道左侧的左车道上的基准车速、行驶车道右侧的右车道上的基准车速各自对应的换挡决策因子，得到换挡决策融合因子。
左车道上的基准车速和右车道上的基准车速可基于对应车道上的车辆行驶过程的场景信息确定，确定方式可参阅关于当前车辆行驶车道上的基准车速，再次不进行赘述。
需要说明的是，若当前车辆行驶车道左侧不存在左车道时，左车道的基准车速取当前车辆行驶车道上的基准车速，也就是说，V基准左＝V基准，其中，V基准左表示左车道的基准车速，V基准表示当前车辆行驶车道上的基准车速。
同理，若当前车道行驶右侧不存在右车道时，右车道的基准车速取当前车辆行驶车道上的基准车速，也就是说，V基准右＝V基准，其中，V基准右表示右车道的基准车速，V基准表示当前车辆行驶车道上的基准车速。
换挡决策融合因子基于当前车辆行驶车道上的基准车速对应的换挡决策因子、左车道上的基准车速对应的换挡决策因子以及右车道上的基准车速对应的换挡决策因子确定。
作为一示例的，服务器可采用图8中示出的步骤S711～步骤S713进一步对本步骤进行说明，详情如下：
步骤S711，计算行驶车道上的基准车速、左车道上的基准车速、右车道上的基准车速各自的换挡决策因子与对应系数之间的第二乘积，得到多个第 二乘积。
若当前车辆行驶车道上的基准车速对应的换挡决策因子表示为Fac1，Fac1对应的系数为K1，左车道上的基准车速对应的换挡决策因子表示为Fac2，Fac2对应的系数为K2，右车道上的基准车速对应的换挡决策因子表示为Fac3，Fac3对应的系数为K3，则第二乘积包括Fac1*K1，Fac2*K2和Fac3*K3。
步骤S712，选取各换挡决策因子中的最大换挡决策因子。
最大换挡决策因子是从当前车辆行驶车道上的基准车速对应的换挡决策因子、左车道上的基准车速对应的换挡决策因子和右车道上的基准车速对应的换挡决策因子中选取得到。
步骤S713，将多个第二乘积之和与最大换挡决策因子之间的比值确定为换挡决策融合因子。
服务器将多个第二乘积之和与最大换挡决策因子之间的比值确定为换挡决策融合因子。需要说明的是，换挡决策融合因子的取值范围为0～1。
示例性的，换挡决策融合因子满足下式：
其中，A常量是指最大换挡决策因子。
步骤S720，根据油门开度和换挡决策融合因子确定自适应换挡规律对应的换挡车速。
油门开度是指油门踏板的开合程度。其中，油门开度决定了发动机控制的喷油量多少。
服务器根据油门开度和换挡决策融合因子确定自适应换挡规律对应的换挡车速。
作为一示例的，服务器可采用图9中示出的步骤S721～步骤S723进一步对本步骤进行说明，详情如下：
步骤S721，根据油门开度获取对应的最低换挡车速和最高换挡车速。
服务器可根据油门开度对应的函数确定最低换挡车速和最高换挡车速。服务器还可直接根据油门开度查表确定最低换挡车速和最高换挡车速。
步骤S722，计算最高换挡车速与最低换挡车速的差值与换挡融合因子之间的第一乘积。
示例性的，若最高换挡车速表示为Vmax，最低换挡车速表示为Vmin，则第一乘积为(Vmax-Vmin)*Fac。
步骤S723，计算最低换挡车速与第一乘积之间的和，将和作为自适应换挡规律对应的换挡车速。
示例性的，若自适应换挡对应的换挡车速表示为Vadp，则自适应换挡对应的换挡车速满足下式：
Vadp＝Vmin+(Vmax-Vmin)*Fac。
可以看出，本实施例的基于场景的预测性换挡规律自适应方法根据融合行驶车道上的基准车速、所述行驶车道左侧的左车道上的基准车速、所述行驶车道右侧的右车道上的基准车速各自对应的换挡决策因子，得到换挡决策融合因子，并根据油门开度和换挡决策融合因子确定自适应换挡规律对应的换挡车速，由此能够基于场景信息转化得到的基准车速对应的换挡决策因子，以及实际的油门开度确定自适应换挡规律对应的换挡车速，体现场景信息和驾驶员驾驶风格对自适应换挡规律对应的换挡车速的决定性影响。
图10是图2所示的基于场景的预测性换挡规律自适应方法中步骤S230的一示例性实施例的流程图。如图10所示，在一示例性实施例中，在步骤S230根据当前车辆在当前时刻的档位车速、当前车辆在前一时刻的档位车速以及自适应换挡规律对应的换挡车速确定目标档位的过程至少还包括步骤S1010至步骤S1020，详细介绍如下：
步骤S1010，若当前车辆在前一时刻的档位车速小于自适应换挡规律对应的换挡车速，且当前车辆在当前时刻的档位车速大于等于自适应换挡规律对应的换挡车速，则确定车辆中档位盘的最高档位为目标档位。
步骤S1020，若当前车辆在前一时刻的档位车速大于自适应换挡规律对应的换挡车速，且当前车辆在当前时刻的档位车速小于等于自适应换挡规律对应的换挡车速，则确定车辆中档位盘的最低档位为目标档位。
最高档位是指档位盘中的最大档，例如手动挡中的第五档。
最低档位是指档位盘中的额最小档，例如手动挡中的第一档。
服务器在确定自适应换挡规律对应的换挡车速后，判断当前车辆在前一时刻的档位车速、当前车辆在当前时刻的档位车速与自适应换挡规律对应的换挡车速之间的大小关系，并根据大小关系确定目标档位。具体的，服务器若 判定在前一时刻的档位车速小于自适应换挡规律对应的换挡车速，且当前车辆在当前时刻的档位车速大于等于自适应换挡规律对应的换挡车速，则确定车辆中档位盘的最高档位为目标档位；服务器若判定当前车辆在前一时刻的档位车速大于自适应换挡规律对应的换挡车速，且当前车辆在当前时刻的档位车速小于等于自适应换挡规律对应的换挡车速，则确定车辆中档位盘的最低档位为目标档位，由此实现根据场景信息确定的自适应换挡规律对应的换挡车速得到目标档位，能够充分体现场景信息对目标档位的影响。
可以看出，本实施例的基于场景的预测性换挡规律自适应方法根据当前车辆在前一时刻的档位车速、自适应换挡规律对应的换挡车速和当前车辆在当前时刻的档位车速确定目标档位，由此能够结合驾驶员驾驶习惯确定目标档位。
图11是图2所示的基于场景的预测性换挡规律自适应方法中步骤S220之前的一示例性实施例的流程图。如图11所示，在一示例性实施例中，在步骤S220根据车道上的基准车速对应的换挡决策因子确定自适应换挡规律对应的换挡车速的过程之前，本申请实施例的基于场景的预测性换挡规律自适应方法至少还包括步骤S1110至步骤S1130，详细介绍如下：
步骤S1110，按照预设距离分别将视线距离内的当前车道、左车道和右车道进行划分，得到各车道中的多个车道段。
考虑到视线距离内的基准车速在服务器中是离散化表述的，因此，本申请实施例需对视线距离内的当前车道、左车道和右车道进行划分，得到当前车道上的多个车道段、左车道上的多个车道段和右车道上的多个车道段。
步骤S1120，计算当前车道中相邻车道段的第一车道段对应的基准车速和第二车道段对应的基准车速之间的第一基准车速差值。
由于本申请实施例将车道分为多个车道段，因此在相邻车道段中，将远离车辆车头方向的车道段确定为第一车道段，将靠近车辆车头方向的车道段确定为第二车道段，服务器计算当前车道中相邻车道段的第一车道段对应的基准车速和第二车道段对应的基准车速之间的车速差值，并将车速差值作为第一基准车速差值。需要说明的是，相邻车道段中第一车道段对应的基准车速和第二车道段对应的基准车速可参阅当前车辆行驶车道上的基准车速的计算方 式，也就是说，相邻车道段中第一车道段对应的基准车速和第二车道段对应的基准车速根据对应车道段内的场景信息确定。
例如，若当前车道中相邻车道段的第一车道段对应的基准车速表示为V基准(n)，当前车道中相邻车道段的第二车道段对应的基准车速表示为V基准(n-1)，则第一基准车速差值表示为V基准(n)-V基准(n-1)，其中n＝2,3,4…N，当n＝1时，V基准(n-1)取当前车辆的车速。
步骤S1130，根据第一基准车速差值、当前车道中第一车道段在视线距离中的第一视线位置占比确定当前车道的基准车速对应的换挡决策因子。
当前车道中第一车道段在视线距离中的第一视线位置占比是根据第一车道段距离与视线距离之间的比值确定的。
服务器根据第一基准车速差值和第一视线位置占比确定当前车道的基准车速对应的换挡决策因子。
作为一示例的，服务器可采用图12中示出的步骤S1131～步骤S1132进一步对本步骤进行说明，详情如下：
步骤S1131，根据当前车道中相邻车道段的第一车道段对应的车道段距离和视线距离之间的比值与预设数值确定第一视线位置占比。
若当前车道中相邻车道段的第一车道段对应的车道段距离表示为Dis(n)，视线距离表示为Dis视线，则第一视线位置占比表示为
步骤S1132，将当前车道段中各相邻车道段对应的第一基准车速差值与对应的第一视线位置占比之间的乘积和作为当前车道的基准车速对应的换挡决策因子。
由上可知，当前车道的基准车速对应的换挡决策因子满足下式：
可以看出，本实施例的基于场景的预测性换挡规律自适应方法根据划分当前车道段得到的相邻车道段的第一车道段对应的基准车速和第二车道段对应的基准车速确定第一基准车速差值，并根据第一基准车速差值、当前车道中第一车道段在视线距离中的第一视线位置占比确定当前车道的基准车速对应的换挡决策因子，由此能够通过当前车道中相邻车道段对应的基准车速预测 得到当前车道的换挡决策因子。
图13是图12所示的基于场景的预测性换挡规律自适应方法中步骤S1110之后的一示例性实施例的流程图。如图13所示，在一示例性实施例中，在步骤S1110按照预设距离分别将视线距离内的当前车道、左车道和右车道进行划分，得到各车道中的多个车道段的过程之后，本申请实施例的基于场景的预测性换挡规律自适应方法至少还包括步骤S1310至步骤S1330，详细介绍如下：
步骤S1310，计算左车道中相邻车道段的第一车道段对应的基准车速与当前车道中对应车道段的基准车速之间的第二基准车速差值。
服务器计算左车道中相邻车道段的第一车道段对应的基准车速与当前车道中对应车道段的基准车速之间的车速差值，并将车速差值作为第二基准车速差值。需要说明的是，相邻车道段中第一车道段对应的基准车速和第二车道段对应的基准车速可参阅当前车辆行驶车道上的基准车速的计算方式，也就是说，相邻车道段中第一车道段对应的基准车速和第二车道段对应的基准车速根据左车道中对应车道段内的场景信息确定。
例如，若左车道中相邻车道段的第一车道段对应的基准车速表示为V基准左(n)，当前车道中对应车道段的基准车速表示为V基准(n)，则第二基准车速差值表示为V基准左(n)-V基准(n)，其中n＝2,3,4…N。
步骤S1320，计算左车道中相邻车道段的第二车道段对应的基准车速与当前车道中对应车道段的基准车速之间的第三基准车速差值。
服务器根据左车道中相邻车道段的第二车道段对应的基准车速与当前车道中对应车道段的基准车速之间的车速差值得到第三基准车速差值。
例如，左车道中相邻车道段的第二车道段对应的基准车速表示为V基准左(n-1)，当前车道中对应车道段的基准车速表示为V基准(n-1)，则第三基准车速差值表示为V基准左(n-1)-V基准(n-1)，其中n＝2,3,4…N，n＝1时，V基准左(n-1)取当前车辆的车速。
步骤S1330，根据第二基准车速差值、第三基准车速差值以及左车道中相邻车道段的第一车道段在视线距离中的第二视线位置占比确定左车道的基准车速对应的换挡决策因子。
第二视线位置占比是指基于左车道中相邻车道段的第一车道段对应的车 道段距离和视线距离之间的比值确定的。
服务器根据第二基准车速差值、第三基准车速差值和第二视线位置占比确定左车道的基准车速对应的换挡决策因子。
作为一示例的，服务器可采用图14中示出的步骤S1331～步骤S1333进一步对本步骤进行说明，详情如下：
步骤S1331，计算第二基准车速差值和第三基准车速差值之间的第四基准车速差值。
服务器根据第二基准车速差值和第三基准车速差值得到第四基准车速差值。具体的，第四基准车速差值可表示为(V基准左(n)-V基准(n))-(V基准左(n-1)-V基准(n-1))。
步骤S1332，根据左车道中相邻车道段的第一车道段对应的车道段距离和视线距离之间的比值与预设数值确定第二视线位置占比。
服务器计算车道中相邻车道段的第一车道段对应的车道段距离和视线距离之间的比值，并将比值的负数与预设数值之和作为第二视线位置占比。其中，预设数值可以为一。
示例性的，若左车道中相邻车道段的第一车道段对应的车道段距离表示为Dis左(n)，视线距离表示为Dis视线，则第二视线位置占比可表示为
步骤S1333，将左车道中各相邻车道段对应的第四基准车速差值与对应的第二视线位置占比之间的乘积和作为左车道的基准车速对应的换挡决策因子。
由上可知，左车道的基准车速对应的换挡决策因子满足下式：
可以看出，本实施例的基于场景的预测性换挡规律自适应方法根据划分左车道段得到的相邻车道段的第一车道段对应的基准车速和当前车道中对应车道段的基准车速确定第二基准车速差值，根据左车道中相邻车道段中第二车道段对应的基准车速和当前车道中对应车道段的基准车速确定第三基准车速差值，并根据第二基准车速差值、第三基准车速差值以及第二视线位置占比确定左车道的基准车速对应的换挡决策因子，由此能够通过左车道中相邻车道段对应的基准车速预测得到左车道的换挡决策因子。
图15是图12所示的基于场景的预测性换挡规律自适应方法中步骤S1110之后的一示例性实施例的流程图。如图15所示，在一示例性实施例中，在步骤S1110按照预设距离分别将视线距离内的当前车道、左车道和右车道进行划分，得到各车道中的多个车道段的过程之后，本申请实施例的基于场景的预测性换挡规律自适应方法至少还包括步骤S1510至步骤S1530，详细介绍如下：
步骤S1510，计算右车道中相邻车道段的第一车道段对应的基准车速与当前车道中对应车道段的基准车速之间的第五基准车速差值。
服务器根据右车道中相邻车道段的第一车道段对应的基准车速与当前车道中对应车道段的基准车速之间的车速差值得到第五基准车速差值。
示例性的，若右车道中相邻车道段的第一车道段对应的基准车速表示为V基准右(n)，当前车道中对应车道段的基准车速表示为V基准(n)，则第五基准车速差值表示为V基准右(n)-V基准(n)。
步骤S1520，计算右车道中相邻车道段的第二车道段对应的基准车速与当前车道中对应车道段的基准车速之间的第六基准车速差值。
服务器根据右车道中相邻车道段的第二车道段对应的基准车速与当前车道中对应车道段的基准车速之间的车速差值得到第六基准车速差值。
示例性的，若右车道中相邻车道段的第二车道段对应的基准车速表示为V基准右(n-1)，当前车道中对应车道段的基准车速表示为V基准(n-1)，则第六基准车速差值表示为V基准右(n-1)-V基准(n-1)，其中n＝2,3,4…N，n＝1时，V基准右(n-1)取当前车辆的车速。
步骤S1530，根据第五基准车速差值、第六基准车速差值以及右车道中相邻车道段的第一车道段在视线距离中的第三视线位置占比确定右车道的基准车速对应的换挡决策因子。
第三视线位置占比是基于右车道中相邻车道段的第一车道段对应的车道段距离和视线距离之间的比值确定的。
服务器第五基准车速差值、第六基准车速差值和第三视线位置占比确定右车道的基准车速对应的换挡决策因子。
作为一示例的，服务器可采用图16中示出的步骤S1531～步骤S1533进一步对本步骤进行说明，详情如下：
步骤S1531，计算第五基准车速差值和第六基准车速差值之间的第七基准车速差值。
服务器根据述第五基准车速差值和第六基准车速差值得到第七基准车速差值。具体的，第七基准车速差值可表示为(V基准右(n)-V基准(n))-(V基准右(n-1)-V基准(n-1))。
步骤S1532，根据右车道中相邻车道段的第一车道段对应的车道段距离和视线距离之间的比值与预设数值确定第三视线位置占比。
服务器计算右道中相邻车道段的第一车道段对应的车道段距离和视线距离之间的比值，并将比值的负数与预设数值之和作为第二视线位置占比。其中，预设数值可以为一。
示例性的，若右车道中相邻车道段的第一车道段对应的车道段距离表示为Dis右(n)，视线距离表示为Dis视线，则第三视线位置占比可表示为
步骤S1533，将右车道中各相邻车道段对应的第七基准车速差值与对应的第三视线位置占比之间的乘积和作为右车道的基准车速对应的换挡决策因子。
由上可知，右车道的基准车速对应的换挡决策因子满足下式：
可以看出，本实施例的基于场景的预测性换挡规律自适应方法根据划分右车道段得到的相邻车道段的第一车道段对应的基准车速和当前车道中对应车道段的基准车速确定第五基准车速差值，根据右车道中相邻车道段中第二车道段对应的基准车速和当前车道中对应车道段的基准车速确定第六基准车速差值，并根据第五基准车速差值、第六基准车速差值以及第三视线位置占比确定左车道的基准车速对应的换挡决策因子，由此能够通过右车道中相邻车道段对应的基准车速预测得到右车道的换挡决策因子。
为详细描述当前车道、左车道、右车道上各车道段距离与各车道段对应基准车速之间的关系，可继续参阅图17，图17中的横坐标代表被划分的各车道段对应的距离，纵坐标代表当前车道、左车道、右车道，也即当前车道、当前车道的左侧车道、当前车道的右侧车道，每一车道段对应有基准车速，每个车道段对应的基准车速可根据该车道段的场景信息确定。示例性的，当前车道上 的第二个车道段上因存在坡道，此车道段对应的基准车速V中2小于第一车道段对应的基准车速V中1。另一示例性的，当前车道上的第四车道段上因存在障碍物，此车道段对应的基准车速为V中4。由此可知，各车道段对应的基准车速与场景信息相关。
图18是本申请的一示例性实施例示出的基于场景的预测性换挡规律自适应装置的框图。该示例性的基于场景的预测性换挡规律自适应装置1800包括基准车速确定模块181、换挡车速确定模块182和执行模块183。具体的:
基准车速确定模块181，配置为根据当前车辆行驶过程中获取的场景信息确定当前车辆行驶车道上的基准车速。
换挡车速确定模块182，配置为根据车道上的基准车速对应的换挡决策因子确定自适应换挡规律对应的换挡车速。
执行模块183，配置为根据当前车辆在当前时刻的档位车速、当前车辆在前一时刻的档位车速以及自适应换挡规律对应的换挡车速确定目标档位，并基于目标档位进行执行操作。
在该示例性的基于场景的预测性换挡规律自适应装置中，通过将当前车辆行驶过程中获取的场景信息转换得到当前车辆行驶车道上的基准车速，并根据车道上的基准车速对应的换档决策因子确定自适应换挡规律对应的换挡车速，进而根据当前车辆在当前时刻的档位车速、当前车辆在前一时刻的档位车速以及自适应换挡规律对应的换挡车速确定目标档位，并基于目标档位进行执行操作，由此基于场景信息转换得到车道上的基准车速，能够在充分体现场景信息的同时减小自适应换挡决策的输入信息维度。
在上述示例性的实施例基础上，基准车速确定模块181包括：显性基准车速确定模块、隐性基准车速确定模块、阻力基准车速确定模块和当前车辆行驶车道上的基准车速确定模块。具体的：
显性基准车速确定模块，配置为根据场景信息中的第一场景要素确定车道上的显性基准车速，第一场景要素包括交通速度信息。
隐性基准车速确定模块，配置为根据场景信息中的第二场景要素确定车道上的隐性基准车速，第二场景要素包括道路属性信息。
阻力基准车速确定模块，配置为根据场景信息中的第三场景要素确定车道上的阻力基准车速，第三场景要素包括场景阻力信息。
当前车辆行驶车道上的基准车速确定模块，配置为根据车道上的显性基准车速、隐性基准车速和阻力基准车速确定当前车辆行驶车道上的基准车速。
在上述示例性的实施例基础上，隐性基准车速确定模块包括：交通速度信息获取模块和第一选取模块。具体的：
交通速度信息获取模块，配置为获取道路限速的速度、障碍物的速度和交通流的速度。
第一选取模块，配置为选取道路限速的速度、障碍物的速度和交通流的速度中的最小速度为车道上的显性基准车速。
在上述示例性的实施例基础上，隐性基准车速确定模块包括：道路属性信息获取模块和第二选取模块。具体的：
道路属性信息获取模块，配置为获取道路类型对应的道路类型速度和道路曲率对应的道路曲率速度。
第二选取模块，配置为选取道路类型速度和道路曲率速度中的最小速度为车道上的隐性基准车速。
在上述示例性的实施例基础上，阻力基准车速确定模块包括：目标阻力确定模块和车道上的阻力基准车速确定模块。具体的：
目标阻力确定模块，配置为根据道路等级对应的道路等级阻力和道路坡度对应的道路坡度阻力确定目标阻力。
车道上的阻力基准车速确定模块，配置为根据获取的视线距离、阻力距离和目标阻力确定车道上的阻力基准车速。
在上述示例性的实施例基础上，阻力基准车速确定模块包括：比值第一计算模块、第一判断模块和第二判断模块。具体的：
比值第一计算模块，配置为计算视线距离与阻力距离之间的差值与预设距离之间的比值。
第一判断模块，配置为若比值的余数等于零，则将目标阻力的阻力值确定为当前车辆行驶车道上的阻力基准车速。
第二判断模块，配置为若比值的余数等于一，则确定当前车辆行驶车道上的阻力基准车速为零。
在上述示例性的实施例基础上，换挡车速确定模块182包括：换挡决策因子融合模块和自适应换挡规律对应的换挡车速确定模块。具体的：
换挡决策因子融合模块，配置为融合行驶车道上的基准车速、行驶车道左侧的左车道上的基准车速、行驶车道右侧的右车道上的基准车速各自对应的换挡决策因子，得到换挡决策融合因子。
自适应换挡规律对应的换挡车速确定模块，配置为根据油门开度和换挡决策融合因子确定自适应换挡规律对应的换挡车速。
在上述示例性的实施例基础上，自适应换挡规律对应的换挡车速确定模块包括：最低换挡车速和最高换挡车速获取模块、第一乘积计算模块、乘积和计算模块。具体的：
最低换挡车速和最高换挡车速获取模块，配置为根据油门开度获取对应的最低换挡车速和最高换挡车速。
第一乘积计算模块，配置为计算最高换挡车速与最低换挡车速的差值与换挡融合因子之间的第一乘积。
乘积和计算模块，配置为计算最低换挡车速与第一乘积之间的和，将和作为自适应换挡规律对应的换挡车速。
在上述示例性的实施例基础上，换挡决策因子融合模块包括：第二乘积计算模块、最大换挡决策因子选取模块和换挡决策融合因子确定模块。具体的：
第二乘积计算模块，配置为计算行驶车道上的基准车速、左车道上的基准车速、右车道上的基准车速各自的换挡决策因子与对应系数之间的第二乘积，得到多个第二乘积。
最大换挡决策因子选取模块，配置为选取各换挡决策因子中的最大换挡决策因子。
换挡决策融合因子确定模块，配置为将多个第二乘积之和与最大换挡决策因子之间的比值确定为换挡决策融合因子。
在上述示例性的实施例基础上，执行模块183包括：第三判断模块和第四判断模块。具体的：
第三判断模块，配置为若当前车辆在前一时刻的档位车速小于自适应换挡规律对应的换挡车速，且当前车辆在当前时刻的档位车速大于等于自适应换挡规律对应的换挡车速，则确定车辆中档位盘的最高档位为目标档位。
第四判断模块，配置为若当前车辆在前一时刻的档位车速大于自适应换挡规律对应的换挡车速，且当前车辆在当前时刻的档位车速小于等于自适应 换挡规律对应的换挡车速，则确定车辆中档位盘的最低档位为目标档位。
在上述示例性的实施例基础上，在换挡车速确定模块182之前，本申请实施例的装置还包括：划分模块、第一基准车速差值确定模块和当前车道的基准车速对应的换挡决策因子确定模块。具体的：
划分模块，配置为按照预设距离分别将视线距离内的当前车道、左车道和右车道进行划分，得到各车道中的多个车道段。
第一基准车速差值确定模块，配置为计算当前车道中相邻车道段的第一车道段对应的基准车速和第二车道段对应的基准车速之间的第一基准车速差值。
当前车道的基准车速对应的换挡决策因子确定模块，配置为根据第一基准车速差值、当前车道中第一车道段在视线距离中的第一视线位置占比确定当前车道的基准车速对应的换挡决策因子。
在上述示例性的实施例基础上，当前车道的基准车速对应的换挡决策因子确定模块包括：第一视线位置占比计算模块和第一作为模块。具体的：
第一视线位置占比计算模块，配置为根据当前车道中相邻车道段的第一车道段对应的车道段距离和视线距离之间的比值与预设数值确定第一视线位置占比。
第一作为模块，配置为将当前车道段中各相邻车道段对应的第一基准车速差值与对应的第一视线位置占比之间的乘积和作为当前车道的基准车速对应的换挡决策因子。
在上述示例性的实施例基础上，在划分模块之后，本申请实施例的装置还包括：第二基准车速差值计算模块、第三基准车速差值计算模块和左车道的基准车速对应的换挡决策因子确定模块。具体的：
第二基准车速差值计算模块，配置为计算左车道中相邻车道段的第一车道段对应的基准车速与当前车道中对应车道段的基准车速之间的第二基准车速差值。
第三基准车速差值计算模块，配置为计算左车道中相邻车道段的第二车道段对应的基准车速与当前车道中对应车道段的基准车速之间的第三基准车速差值。
左车道的基准车速对应的换挡决策因子确定模块，配置为根据第二基准 车速差值、第三基准车速差值以及左车道中相邻车道段的第一车道段在视线距离中的第二视线位置占比确定左车道的基准车速对应的换挡决策因子。
在上述示例性的实施例基础上，左车道的基准车速对应的换挡决策因子确定模块包括：第四基准车速差值计算模块、第二视线位置占比计算模块和第二作为模块。具体的：
第四基准车速差值计算模块，配置为计算第二基准车速差值和第三基准车速差值之间的第四基准车速差值。
第二视线位置占比计算模块，配置为根据左车道中相邻车道段的第一车道段对应的车道段距离和视线距离之间的比值与预设数值确定第二视线位置占比。
第二作为模块，配置为将左车道中各相邻车道段对应的第四基准车速差值与对应的第二视线位置占比之间的乘积和作为左车道的基准车速对应的换挡决策因子。
在上述示例性的实施例基础上，在划分模块之后，本申请实施例的装置还包括：第五基准车速差值计算模块、第六基准车速差值计算模块和右车道的基准车速对应的换挡决策因子确定模块。具体的：
第五基准车速差值计算模块，配置为计算右车道中相邻车道段的第一车道段对应的基准车速与当前车道中对应车道段的基准车速之间的第五基准车速差值。
第六基准车速差值计算模块，配置为计算右车道中相邻车道段的第二车道段对应的基准车速与当前车道中对应车道段的基准车速之间的第六基准车速差值。
右车道的基准车速对应的换挡决策因子确定模块，配置为根据第五基准车速差值、第六基准车速差值以及右车道中相邻车道段的第一车道段在视线距离中的第三视线位置占比确定右车道的基准车速对应的换挡决策因子。
在上述示例性的实施例基础上，右车道的基准车速对应的换挡决策因子确定模块包括：第七基准车速差值计算模块、第三视线位置占比计算模块和第三作为模块。具体的：
第七基准车速差值计算模块，配置为计算第五基准车速差值和第六基准车速差值之间的第七基准车速差值。
第三视线位置占比计算模块，配置为根据右车道中相邻车道段的第一车道段对应的车道段距离和视线距离之间的比值与预设数值确定第三视线位置占比。
第三作为模块，配置为将右车道中各相邻车道段对应的第七基准车速差值与对应的第三视线位置占比之间的乘积和作为右车道的基准车速对应的换挡决策因子。
需要说明的是，上述实施例所提供的基于场景的预测性换挡规律自适应装置与上述实施例所提供的基于场景的预测性换挡规律自适应方法属于同一构思，其中各个模块和单元执行操作的具体方式已经在方法实施例中进行了详细描述，此处不再赘述。上述实施例所提供的基于场景的预测性换挡规律自适应装置在实际应用中，可以根据需要而将上述功能分配由不同的功能模块完成，即将装置的内部结构划分成不同的功能模块，以完成以上描述的全部或者部分功能，本处也不对此进行限制。
本申请的实施例还提供了一种电子设备，包括：一个或多个处理器；存储装置，用于存储一个或多个程序，当所述一个或多个程序被所述一个或多个处理器执行时，使得所述电子设备实现上述各个实施例中提供的基于场景的预测性换挡规律自适应方法。
图19示出了适于用来实现本申请实施例的电子设备的计算机系统的结构示意图。需要说明的是，图19示出的电子设备的计算机系统1900仅是一个示例，不应对本申请实施例的功能和使用范围带来任何限制。
如图19所示，计算机系统1900包括中央处理单元(Central Processing Unit，CPU)1901，其可以根据存储在只读存储器(Read-Only Memory，ROM)1902中的程序或者从储存部分1908加载到随机访问存储器(Random Access Memory，RAM)1903中的程序而执行各种适当的动作和处理，例如执行上述实施例中所述的方法。在RAM 1903中，还存储有系统操作所需的各种程序和数据。CPU 1901、ROM 1902以及RAM 1903通过总线1904彼此相连。输入/输出(Input/Output，I/O)接口1905也连接至总线1904。
以下部件连接至I/O接口1905：包括键盘、鼠标等的输入部分1906；包括诸如阴极射线管(Cathode Ray Tube，CRT)、液晶显示器(Liquid Crystal Display，LCD)等以及扬声器等的输出部分1907；包括硬盘等的储存部分 1908；以及包括诸如LAN(Local Area Network，局域网)卡、调制解调器等的网络接口卡的通信部分1909。通信部分1909经由诸如因特网的网络执行通信处理。驱动器1910也根据需要连接至I/O接口1905。可拆卸介质1911，诸如磁盘、光盘、磁光盘、半导体存储器等等，根据需要安装在驱动器1910上，以便于从其上读出的计算机程序根据需要被安装入储存部分1908。
特别地，根据本申请的实施例，上文参考流程图描述的过程可以被实现为计算机软件程序。例如，本申请的实施例包括一种计算机程序产品，其包括承载在计算机可读介质上的计算机程序，该计算机程序包含用于执行流程图所示的方法的计算机程序。在这样的实施例中，该计算机程序可以通过通信部分1909从网络上被下载和安装，和/或从可拆卸介质1911被安装。在该计算机程序被中央处理单元(CPU)1901执行时，执行本申请的系统中限定的各种功能。
需要说明的是，本申请实施例所示的计算机可读介质可以是计算机可读信号介质或者计算机可读存储介质或者是上述两者的任意组合。计算机可读存储介质例如可以是电、磁、光、电磁、红外线、或半导体的系统、装置或器件，或者任意以上的组合。计算机可读存储介质的更具体的例子可以包括但不限于：具有一个或多个导线的电连接、便携式计算机磁盘、硬盘、随机访问存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器(Erasable Programmable Read Only Memory，EPROM)、闪存、光纤、便携式紧凑磁盘只读存储器(Compact Disc Read-Only Memory，CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合。在本申请中，计算机可读的信号介质可以包括在基带中或者作为载波一部分传播的数据信号，其中承载了计算机可读的计算机程序。这种传播的数据信号可以采用多种形式，包括但不限于电磁信号、光信号或上述的任意合适的组合。计算机可读的信号介质还可以是计算机可读存储介质以外的任何计算机可读介质，该计算机可读介质可以发送、传播或者传输用于由指令执行系统、装置或者器件使用或者与其结合使用的程序。计算机可读介质上包含的计算机程序可以用任何适当的介质传输，包括但不限于：无线、有线等等，或者上述的任意合适的组合。
附图中的流程图和框图，图示了按照本申请各种实施例的系统、方法和计算机程序产品的可能实现的体系架构、功能和操作。其中，流程图或框图 中的每个方框可以代表一个模块、程序段、或代码的一部分，上述模块、程序段、或代码的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。也应当注意，在有些作为替换的实现中，方框中所标注的功能也可以以不同于附图中所标注的顺序发生。例如，两个接连地表示的方框实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，这依所涉及的功能而定。也要注意的是，框图或流程图中的每个方框、以及框图或流程图中的方框的组合，可以用执行规定的功能或操作的专用的基于硬件的系统来实现，或者可以用专用硬件与计算机指令的组合来实现。
描述于本申请实施例中所涉及到的单元可以通过软件的方式实现，也可以通过硬件的方式来实现，所描述的单元也可以设置在处理器中。其中，这些单元的名称在某种情况下并不构成对该单元本身的限定。
本申请的另一方面还提供了一种计算机可读存储介质，其上存储有计算机程序，该计算机程序被处理器执行时实现如前所述的基于场景的预测性换挡规律自适应方法。该计算机可读存储介质可以是上述实施例中描述的电子设备中所包含的，也可以是单独存在，而未装配入该电子设备中。
本申请的另一方面还提供了一种计算机程序产品或计算机程序，该计算机程序产品或计算机程序包括计算机指令，该计算机指令存储在计算机可读存储介质中。计算机设备的处理器从计算机可读存储介质读取该计算机指令，处理器执行该计算机指令，使得该计算机设备执行上述各个实施例中提供的基于场景的预测性换挡规律自适应方法。
上述内容，仅为本申请的较佳示例性实施例，并非用于限制本申请的实施方案，本领域普通技术人员根据本申请的主要构思和精神，可以十分方便地进行相应的变通或修改，故本申请的保护范围应以权利要求书所要求的保护范围为准。

Claims (19)

  1. 一种基于场景的预测性换挡规律自适应方法，其特征在于，所述方法包括：
    根据当前车辆行驶过程中获取的场景信息转换得到所述当前车辆行驶车道上的基准车速；
    根据所述车道上的基准车速对应的换挡决策因子确定自适应换挡规律对应的换挡车速；
    根据所述当前车辆在当前时刻的档位车速、所述当前车辆在前一时刻的档位车速以及所述自适应换挡规律对应的换挡车速确定目标档位，并基于所述目标档位进行执行操作。
  2. 根据权利要求1所述的方法，其特征在于，所述根据当前车辆行驶过程中获取的场景信息转换得到所述当前车辆行驶车道上的基准车速的步骤，包括：
    根据所述场景信息中的第一场景要素确定所述车道上的显性基准车速，所述第一场景要素包括交通速度信息；
    根据所述场景信息中的第二场景要素确定所述车道上的隐性基准车速，所述第二场景要素包括道路属性信息；
    根据所述场景信息中的第三场景要素确定所述车道上的阻力基准车速，所述第三场景要素包括场景阻力信息；
    根据所述车道上的显性基准车速、隐性基准车速和阻力基准车速确定所述当前车辆行驶车道上的基准车速。
  3. 根据权利要求2所述的方法，其特征在于，所述交通速度信息包括道路限速、障碍物和交通流，所述根据所述场景信息中的第一场景要素确定所述车道上的显性基准车速的步骤，包括：
    获取所述道路限速的速度、所述障碍物的速度和所述交通流的速度；
    选取所述道路限速的速度、所述障碍物的速度和所述交通流的速度中的最小速度为所述车道上的显性基准车速。
  4. 根据权利要求2所述的方法，其特征在于，所述道路属性信息包括道路类型和道路曲率，所述根据所述场景信息中的第二场景要素确定所述车道 上的隐性基准车速的步骤，包括：
    获取所述道路类型对应的道路类型速度和所述道路曲率对应的道路曲率速度；
    选取所述道路类型速度和道路曲率速度中的最小速度为所述车道上的隐性基准车速。
  5. 根据权利要求2所述的方法，其特征在于，所述场景阻力信息包括道路等级和道路坡度，所述根据所述场景信息中的第三场景要素确定所述车道上的阻力基准车速的步骤，包括：
    根据所述道路等级对应的道路等级阻力和所述道路坡度对应的道路坡度阻力确定目标阻力；
    根据获取的视线距离、阻力距离和所述目标阻力确定所述车道上的阻力基准车速。
  6. 根据权利要求5所述的方法，其特征在于，所述根据获取的视线距离、阻力距离和所述目标阻力确定所述车道上的阻力基准车速的步骤，包括：
    计算所述视线距离与所述阻力距离之间的差值与预设距离之间的比值；
    若所述比值的余数等于零，则将所述目标阻力的阻力值确定为所述当前车辆行驶车道上的阻力基准车速；
    若所述比值的余数等于一，则确定所述当前车辆行驶车道上的阻力基准车速为零。
  7. 根据权利要求1所述的方法，其特征在于，所述根据所述当前车辆在车道上的基准车速对应的换挡决策因子确定自适应换挡规律对应的换挡车速的步骤，包括：
    融合所述行驶车道上的基准车速、所述行驶车道左侧的左车道上的基准车速、所述行驶车道右侧的右车道上的基准车速各自对应的换挡决策因子，得到换挡决策融合因子；
    根据油门开度和所述换挡决策融合因子确定所述自适应换挡规律对应的换挡车速。
  8. 根据权利要求7所述的方法，其特征在于，所述根据油门开度和所述换挡决策融合因子确定所述自适应换挡规律对应的换挡车速的步骤，包括：
    根据所述油门开度获取对应的最低换挡车速和最高换挡车速；
    计算所述最高换挡车速与所述最低换挡车速的差值与所述换挡融合因子之间的第一乘积；
    计算所述最低换挡车速与所述第一乘积之间的和，将所述和作为所述自适应换挡规律对应的换挡车速。
  9. 根据权利要求7所述的方法，其特征在于，所述融合所述行驶车道上的基准车速、所述行驶车道左侧的左车道上的基准车速、所述行驶车道右侧的右车道上的基准车速各自对应的换挡决策因子，得到换挡决策融合因子的步骤，包括：
    计算所述行驶车道上的基准车速、所述左车道上的基准车速、所述右车道上的基准车速各自的换挡决策因子与对应系数之间的第二乘积，得到多个第二乘积；
    选取各换挡决策因子中的最大换挡决策因子；
    将所述多个第二乘积之和与所述最大换挡决策因子之间的比值确定为所述换挡决策融合因子。
  10. 根据权利要求1所述的方法，其特征在于，所述根据所述当前车辆在当前时刻的档位车速、所述当前车辆在前一时刻的档位车速以及所述自适应换挡规律对应的换挡车速确定目标档位的步骤，包括：
    若所述当前车辆在前一时刻的档位车速小于所述自适应换挡规律对应的换挡车速，且所述当前车辆在当前时刻的档位车速大于等于所述自适应换挡规律对应的换挡车速，则确定车辆中档位盘的最高档位为所述目标档位；
    若所述当前车辆在前一时刻的档位车速大于所述自适应换挡规律对应的换挡车速，且所述当前车辆在当前时刻的档位车速小于等于所述自适应换挡规律对应的换挡车速，则确定车辆中档位盘的最低档位为所述目标档位。
  11. 根据权利要求1所述的方法，其特征在于，在所述根据所述车道上的基准车速对应的换挡决策因子确定自适应换挡规律对应的换挡车速的步骤之前，所述方法还包括：
    按照预设距离分别将视线距离内的当前车道、左车道和右车道进行划分，得到各车道中的多个车道段；
    计算所述当前车道中相邻车道段的第一车道段对应的基准车速和第二车道段对应的基准车速之间的第一基准车速差值；
    根据所述第一基准车速差值、所述当前车道中第一车道段在所述视线距离中的第一视线位置占比确定所述当前车道的基准车速对应的换挡决策因子。
  12. 根据权利要求11所述的方法，其特征在于，所述根据所述第一基准车速差值、所述当前车道中第一车道段在所述视线距离中的第一视线位置占比确定所述当前车道的基准车速对应的换挡决策因子的步骤，包括：
    根据所述当前车道中相邻车道段的第一车道段对应的车道段距离和所述视线距离之间的比值与预设数值确定第一视线位置占比；
    将所述当前车道段中各相邻车道段对应的第一基准车速差值与对应的第一视线位置占比之间的乘积和作为所述当前车道的基准车速对应的换挡决策因子。
  13. 根据权利要求11所述的方法，其特征在于，在所述按照预设距离分别将视线距离内的当前车道、左侧车道和右侧车道进行划分，得到各车道中的多个车道段的步骤之后，所述方法还包括：
    计算所述左车道中相邻车道段的第一车道段对应的基准车速与所述当前车道中对应车道段的基准车速之间的第二基准车速差值；
    计算所述左车道中所述相邻车道段的第二车道段对应的基准车速与所述当前车道中对应车道段的基准车速之间的第三基准车速差值；
    根据所述第二基准车速差值、所述第三基准车速差值以及所述左车道中相邻车道段的第一车道段在所述视线距离中的第二视线位置占比确定所述左车道的基准车速对应的换挡决策因子。
  14. 根据权利要求13所述的方法，其特征在于，所述根据所述第二基准车速差值、所述第三基准车速差值以及所述左车道中相邻车道段的第一车道段在所述视线距离中的第二视线位置占比确定所述左车道的基准车速对应的换挡决策因子的步骤，包括：
    计算所述第二基准车速差值和所述第三基准车速差值之间的第四基准车速差值；
    根据所述左车道中相邻车道段的第一车道段对应的车道段距离和所述视线距离之间的比值与预设数值确定第二视线位置占比；
    将所述左车道中各相邻车道段对应的第四基准车速差值与对应的第二视线位置占比之间的乘积和作为所述左车道的基准车速对应的换挡决策因子。
  15. 根据权利要求11所述的方法，其特征在于，在所述按照预设距离分别将视线距离内的当前车道、左侧车道和右侧车道进行划分，得到各车道中的多个车道段的步骤之后，所述方法还包括：
    计算所述右车道中相邻车道段的第一车道段对应的基准车速与所述当前车道中对应车道段的基准车速之间的第五基准车速差值；
    计算所述右车道中所述相邻车道段的第二车道段对应的基准车速与所述当前车道中对应车道段的基准车速之间的第六基准车速差值；
    根据所述第五基准车速差值、所述第六基准车速差值以及所述右车道中相邻车道段的第一车道段在所述视线距离中的第三视线位置占比确定所述右车道的基准车速对应的换挡决策因子。
  16. 根据权利要求15所述的方法，其特征在于，所述根据所述第五基准车速差值、所述第六基准车速差值以及所述右车道中相邻车道段的第一车道段在所述视线距离中的第三视线位置占比确定所述右车道的基准车速对应的换挡决策因子的步骤，包括：
    计算所述第五基准车速差值和所述第六基准车速差值之间的第七基准车速差值；
    根据所述右车道中相邻车道段的第一车道段对应的车道段距离和所述视线距离之间的比值与预设数值确定第三视线位置占比；
    将所述右车道中各相邻车道段对应的第七基准车速差值与对应的第三视线位置占比之间的乘积和作为所述右车道的基准车速对应的换挡决策因子。
  17. 一种基于场景的预测性换挡规律自适应装置，其特征在于，所述装置包括：
    基准车速确定模块，配置为根据当前车辆行驶过程中获取的场景信息确定所述当前车辆行驶车道上的基准车速；
    换挡车速确定模块，配置为根据所述车道上的基准车速对应的换挡决策因子确定自适应换挡规律对应的换挡车速；
    执行模块，配置为根据所述当前车辆在当前时刻的档位车速、所述当前车辆在前一时刻的档位车速以及所述自适应换挡规律对应的换挡车速确定目标档位，并基于所述目标档位进行执行操作。
  18. 一种电子设备，其特征在于，包括：
    存储器，存储有计算机可读指令；
    处理器，读取存储器存储的计算机可读指令，以执行权利要求1-16中的任一项所述的方法。
  19. 一种计算机可读存储介质，其特征在于，其上存储有计算机可读指令，当所述计算机可读指令被计算机的处理器执行时，使计算机执行权利要求1-16中的任一项所述的方法。
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