WO2023082086A1 - 自动车辆控制的方法和装置 - Google Patents

自动车辆控制的方法和装置 Download PDF

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Publication number
WO2023082086A1
WO2023082086A1 PCT/CN2021/129753 CN2021129753W WO2023082086A1 WO 2023082086 A1 WO2023082086 A1 WO 2023082086A1 CN 2021129753 W CN2021129753 W CN 2021129753W WO 2023082086 A1 WO2023082086 A1 WO 2023082086A1
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WIPO (PCT)
Prior art keywords
vehicle
braking torque
torque
current
target
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PCT/CN2021/129753
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English (en)
French (fr)
Inventor
邹良
杨晓东
王前
Original Assignee
华为技术有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Publication date
Application filed by 华为技术有限公司 filed Critical 华为技术有限公司
Priority to CN202180020861.4A priority Critical patent/CN116419862A/zh
Priority to PCT/CN2021/129753 priority patent/WO2023082086A1/zh
Publication of WO2023082086A1 publication Critical patent/WO2023082086A1/zh

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L15/00—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles
    • B60L15/20—Methods, circuits, or devices for controlling the traction-motor speed of electrically-propelled vehicles for control of the vehicle or its driving motor to achieve a desired performance, e.g. speed, torque, programmed variation of speed
    • 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
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
    • B60W40/06—Road conditions
    • B60W40/076—Slope angle of the road

Definitions

  • the present application relates to the field of automatic driving of vehicles, and more particularly, relates to a method and device for automatic vehicle control.
  • HAC hill-start assist control
  • the present application provides a method and device for automatic vehicle control, which can ensure the real-time performance of slope angle estimation and improve the accuracy of slope angle estimation, thereby shortening the time required for starting and stopping the vehicle and reducing the vibration during the starting and stopping process of the vehicle , to prevent the vehicle from slipping, thereby improving the user's driving experience.
  • a method for automatic vehicle control is provided, and the method can be executed by the vehicle; or, it can also be executed by a chip or circuit for the vehicle; or, it can also be executed by an advanced driving assistance system (advanced driving assistance system, ADAS) to execute, this application is not limited to this.
  • advanced driving assistance system advanced driving assistance system, ADAS
  • the implementation by the ADAS on the vehicle is taken as an example below.
  • the method may include: acquiring a first acceleration signal of the vehicle and a second acceleration signal of the vehicle; inputting the first acceleration signal into a first filter to generate a third acceleration signal, and inputting the second acceleration signal into a second filter A fourth acceleration signal is generated, the third acceleration signal and the fourth acceleration signal have the same phase delay characteristic; and a slope angle is determined according to the third acceleration signal and the fourth acceleration signal.
  • the first acceleration signal is a vehicle speed differential signal
  • the second acceleration signal is a vehicle longitudinal acceleration signal.
  • the angle of the current slope can be obtained by making a difference and transformation of the two acceleration signals with the same phase delay characteristics after filtering.
  • the method for automatic vehicle control determines the slope angle by using two acceleration signals with the same phase delay characteristics, which can eliminate the problem of different phase delay characteristics of the two acceleration signals caused by filtering, thereby improving the slope angle. Timeliness and accuracy of estimates.
  • the first filter and the second filter are optimized filters based on phase delay characteristics of the first acceleration signal and the second acceleration signal.
  • the first acceleration signal and the second acceleration signal can be subjected to a frequency sweep test to obtain Bode diagrams of the two signals, and the phase-frequency characteristic curves in the Bode diagrams of the two signals are respectively phase-frequency characteristic curves A and B ; Or the phase-frequency characteristic curves A and B of the vehicle speed differential first acceleration signal and the second acceleration signal can also be obtained in other ways.
  • phase delay difference between B is recorded as the third phase delay.
  • the parameters of the first filter and the second filter are optimized, so that the first acceleration signal and the second acceleration signal pass through the optimized After the first filter and the second filter, the obtained third acceleration signal and the fourth acceleration signal have the same phase delay characteristics.
  • the first filter and the second filter are filters optimized for offline processing.
  • the process of optimizing the filter parameters based on the phase delay characteristics of the first acceleration signal and the second acceleration signal is off-line processing.
  • the first filter and the second filter can select commonly used digital filters, such as Butterworth filter, Chebyshev Type I/Type II filter and elliptic filter, etc. Not limited.
  • the first acceleration signal is obtained by differentiating and filtering the speed of the vehicle
  • the second acceleration signal is obtained by filtering the longitudinal acceleration of the vehicle signal of.
  • the method further includes: determining the mass of the vehicle based on a recursive least squares method according to the slope angle.
  • the automatic vehicle control method of the embodiment of the present application uses the recursive least squares method to estimate the vehicle mass based on the accurately estimated slope angle, which can accurately estimate the vehicle mass, thereby providing more accurate vehicle mass information for controlling the start and stop of the vehicle.
  • a method for automatic vehicle control comprising: determining first slope angle information according to first data collected by a first sensor, where the first sensor includes a gyroscope sensor; The second data determines the second slope angle information, and the second sensor includes at least one of GPS, laser radar and camera; based on the optimal estimation method according to the first slope angle information and the second slope angle information Determine the ramp angle.
  • the first ramp angle information is determined by integrating the gyroscope angular velocity information obtained from the gyroscope sensor; the second ramp angle information is determined according to the environment information acquired by the laser radar, GPS, camera device and the like. In some possible implementation manners, the second slope angle information is determined according to one or more of point cloud data, GPS data, and image data.
  • the second slope angle information may be a slope angle determined according to sensor information such as laser radar, GPS, and camera; or, the second slope angle information may also be a slope angle determined according to laser radar Multiple slope angles determined by sensor information such as , GPS, and camera devices.
  • first slope angle information as the predicted value and the second slope angle information as the observed value
  • more accurate slope angle information is determined according to optimal estimation methods such as Kalman filter fusion.
  • the data used in the embodiment of the present application to determine the slope angle comes from sensors different from those used in the method in the first aspect. Therefore, when the sensor used in the method in the first aspect fails, the vehicle can Dynamically switch to using the method of the embodiment of the present application to estimate the slope angle.
  • the method for automatic vehicle control in the embodiment of the present application can ensure redundant reliability of slope estimation by determining the slope angle through data obtained from various sensors.
  • the slope estimation scheme can be dynamically switched according to the accuracy of the input signal and the failure of the sensor to ensure the reliability and accuracy of the slope estimation results.
  • the method further includes: determining the mass of the vehicle based on a recursive least squares method according to the slope angle.
  • the recursive least squares method is used to estimate the vehicle's mass, which can accurately estimate the vehicle's mass, thereby providing accurate vehicle mass information for controlling the start and stop of the vehicle.
  • a method for automatic vehicle control which can be specifically executed by the start-stop control module in the ADAS, and the method includes: obtaining the ramp angle and the quality of the vehicle; determining the vehicle according to the quality and the ramp angle The first braking torque; obtain the current braking torque and the current driving torque of the vehicle; at the first moment, determine the target braking torque according to the first braking torque and the current braking torque, and determine the target braking torque according to the current driving torque The target driving torque; the first moment is the moment when the vehicle starts or stops.
  • the current driving torque may be the actual driving torque T m of the vehicle
  • the current braking torque may be the actual braking torque T b of the vehicle.
  • the above-mentioned first braking torque may be the second requested braking torque T bReq2 calculated according to the slope angle and the vehicle mass.
  • the slope angle obtained in the embodiment of the present application may be the slope angle estimated by using the method of the first aspect or the method of the second aspect; or, it may also be the current road stored in the memory of the vehicle ramp angle information.
  • the mass of the vehicle acquired in the embodiment of the present application may be the mass of the vehicle estimated by using the method of the first aspect or the method of the second aspect; or, it may also be the current vehicle mass stored in the memory of the vehicle the quality of.
  • the automatic vehicle control method provided by the embodiment of the present application, based on the accurately estimated vehicle mass and road gradient, cooperatively controls the target driving torque and the target braking torque to ensure that the target braking torque and the target driving torque can simultaneously increase to the actual required value of the vehicle.
  • the fast and smooth transition between the braking torque and the driving torque can shorten the time required for the vehicle to start and stop, and at the same time ensure the stability of the vehicle during the start and stop process, thereby improving the driving experience of the user.
  • determining the first braking torque according to the mass and the slope angle may specifically be: obtaining a second braking torque, the second braking torque is The torque determined according to the mass and the slope angle; the first coefficient is determined according to the total mass of the vehicle when it is fully loaded, the second coefficient is determined according to the estimation error of the slope angle, and according to the first coefficient, the second coefficient, the The mass and the ramp angle determine a third braking torque; the first braking torque is determined based on the second braking torque and the third braking torque.
  • the above second braking torque may be the requested braking torque T bReq determined by the PID control module according to the mass of the vehicle, the angle of the slope, the acceleration of the front vehicle, the current speed of the vehicle and other information.
  • the above-mentioned third braking torque may specifically be the initial braking torque T ini ; or, during the process of stopping the vehicle, the above-mentioned third braking torque may also be the desired braking torque T des .
  • the third braking torque determined by the start-stop control module is used to correct the required braking torque required for starting and stopping the vehicle, and then the target braking torque is determined according to the corrected first braking torque
  • the torque can prevent the vehicle from slipping during the vehicle starting process, and can unload the braking torque faster during the vehicle parking process.
  • the method further includes: before determining the target braking torque according to the first braking torque and the current braking torque, according to the third braking torque and the current braking torque, The current driving torque determines the fourth braking torque; the determining the target braking torque according to the first braking torque and the current braking torque is specifically: determining the fifth braking torque according to the first braking torque and the current braking torque braking torque; determining a target braking torque according to the fourth braking torque and the fifth braking torque.
  • the above fourth braking torque may be the difference ⁇ T between the initial braking torque T ini and the current driving torque T m , or may also be the minimum braking torque T blo ; the above fifth system
  • the dynamic torque may be the first target braking torque T bCmd3 , or may be the fourth target braking torque T bCmd3 .
  • the automatic vehicle control method of the embodiment of the present application determines the fifth braking torque according to the first braking torque and the current braking torque, which can control the target braking torque to be loaded or unloaded smoothly, and reduce the vibration when the vehicle starts or stops . Furthermore, taking the larger of the fourth braking torque and the fifth braking torque as the target braking torque can prevent the vehicle from slipping during starting or stopping, and improve driving safety.
  • the method further includes: when the first moment is a moment in the process of starting the vehicle, when the slope angle is less than zero, or the current driving torque When the difference between the third braking torque and the third braking torque is greater than or equal to the first threshold, the fifth braking torque is determined to be the target braking torque.
  • the difference between the current driving torque and the third braking torque is greater than or equal to the first threshold during the starting process of the vehicle, it means that the vehicle has started.
  • No additional braking compensation is required for the vehicle on a slope (the slope angle is greater than zero) or a downhill road (the slope angle is less than zero); or, if the vehicle starts downhill, the vehicle needs to generate a speed along the downhill direction And/or acceleration, at this time, it is only necessary to gradually unload the braking torque, without worrying about the problem of rolling on a hill caused by insufficient braking torque, and there is no need to perform additional braking compensation on the vehicle. Therefore, it is only necessary to determine the fifth braking torque as the target braking torque.
  • the method further includes: when the first moment is a moment during the start of the vehicle, when the absolute value of the slope angle is less than or equal to the second threshold , or, when the first braking torque is less than or equal to the second threshold, it is determined that the target braking torque is zero.
  • the target braking torque can be set to zero in order to drive the vehicle to a quick start.
  • the method includes: when the first moment is a moment during the vehicle start process, acquiring a first driving torque, the first driving torque is based on the mass and the torque determined by the slope angle; and the target driving torque is determined according to the first driving torque and the current driving torque.
  • the first driving torque may be the requested driving torque T mReq determined by the PID control module according to information such as the mass of the vehicle, the slope angle, the acceleration of the front vehicle, and the current speed of the vehicle.
  • the target driving torque can be controlled to increase steadily, and the vibration during the starting process of the vehicle can be reduced.
  • the method further includes: before determining the target driving torque according to the first driving torque and the current driving torque, acquiring the current speed of the vehicle; when the current When the speed is less than zero, the compensation torque is determined according to the current speed; the target driving torque is determined according to the first driving torque, the current driving torque and the compensation torque.
  • the compensation torque when the vehicle is in the process of starting, it is determined whether to increase the compensation torque according to the current speed of the vehicle.
  • the compensation torque is increased to prevent the vehicle from continuing to roll.
  • the method further includes: when the first moment is a moment during the vehicle parking process, according to the first braking torque and the current braking torque Before determining the fifth braking torque, obtain the current speed and current acceleration of the vehicle; when the current speed is less than zero, or, when the current speed is greater than or equal to zero, and the current acceleration is greater than or equal to zero, determine according to the current speed compensation torque; determining the fifth braking torque according to the first braking torque, the compensation torque and the current braking torque.
  • the compensation torque when the vehicle is in the parking process, it is determined whether to increase the compensation torque according to the current speed and/or current acceleration of the vehicle.
  • the compensation torque is increased to prevent the vehicle from continuing to roll.
  • the method further includes: when the first moment is the moment during the parking of the vehicle, determining a first duration, the first duration being the current time of the vehicle The duration for which the speed is zero; when the first duration is greater than or equal to a fourth threshold, the third braking torque is determined to be the target braking torque.
  • the vehicle when the vehicle is in the parking process, when the first duration of the vehicle speed is greater than or equal to the preset value, it is considered that the vehicle has stopped.
  • the third braking torque calculated from the road angle is assigned to the target braking torque, so that the vehicle is controlled to start according to the third braking torque when the vehicle starts next time.
  • the method further includes: before acquiring the slope angle and the mass of the vehicle, determining the first distance between the vehicle and the vehicle immediately in front; Controlling the vehicle to start or stop with the target braking torque and the target driving torque includes: when the first distance is less than or equal to a fifth threshold, controlling the vehicle to stop according to the target braking torque and the target driving torque.
  • the method further includes: before acquiring the slope angle and the mass of the vehicle, determining a second distance between the vehicle and the destination;
  • the braking torque and the target driving torque to control the vehicle to start or stop include: when the second distance is less than or equal to a sixth threshold, controlling the vehicle to stop according to the target braking torque and the target driving torque.
  • the method further includes: before acquiring the slope angle and the mass of the vehicle, determining the acceleration of the vehicle closest to the front; according to the target braking torque and the The target driving torque to control the starting or stopping of the vehicle includes: when the acceleration of the closest preceding vehicle is greater than or equal to a seventh threshold, controlling the vehicle to start according to the target braking torque and the target driving torque.
  • an automatic vehicle control device comprising: an acquisition unit, configured to acquire a first acceleration signal of the vehicle and a second acceleration signal of the vehicle; a processing unit, configured to obtain the first acceleration signal Inputting the first filter to generate a third acceleration signal, and inputting the second acceleration signal to the second filter to generate a fourth acceleration signal, the phase delay characteristics of the third acceleration signal and the fourth acceleration signal are the same; the processing unit It is also used for determining the slope angle according to the third acceleration signal and the fourth acceleration signal.
  • the first filter and the second filter in the device are optimized based on the phase delay characteristics of the first acceleration signal and the second acceleration signal filter.
  • the first filter and the second filter in the device are filters optimized for offline processing.
  • the processing unit is further configured to: differentiate the speed of the vehicle and filter to obtain the first acceleration signal; filter the longitudinal acceleration of the vehicle to obtain the first acceleration signal Two acceleration signals.
  • the processing unit is further configured to: determine the mass of the vehicle based on a recursive least square method according to the slope angle.
  • an automatic vehicle control device which includes: a processing unit configured to determine first slope angle information according to first data collected by a first sensor, where the first sensor includes a gyroscope sensor; the The processing unit is also used to determine the second slope angle information according to the second data collected by the second sensor, and the second sensor includes at least one of GPS, laser radar and camera device; The ramp angle information and the second ramp angle information determine the ramp angle based on an optimal estimation method.
  • the processing unit is further configured to: determine the mass of the vehicle based on a recursive least square method according to the slope angle.
  • an automatic vehicle control device comprising: an acquisition unit, configured to acquire a ramp angle and a mass of the vehicle; a processing unit, configured to determine the first brake according to the mass and the ramp angle torque; the acquiring unit is also used to acquire the current braking torque and the current driving torque of the vehicle; the processing unit is also used to determine the target braking torque according to the first braking torque and the current braking torque at the first moment , and the target driving torque is determined according to the current driving torque; the first moment is the moment when the vehicle starts or stops.
  • the acquiring unit is further configured to: acquire a second braking torque, where the second braking torque is a torque determined according to the mass and the slope angle; the The processing unit is further configured to: determine a first coefficient according to the total mass of the vehicle when it is fully loaded, determine a second coefficient according to the estimation error of the slope angle, and determine according to the first coefficient, the second coefficient, the mass and the slope angle determining a third braking torque; determining the first braking torque according to the second braking torque and the third braking torque.
  • the processing unit is further configured to: before determining the target braking torque according to the first braking torque and the current braking torque, according to the third braking torque determining the fourth braking torque based on the dynamic torque and the current driving torque; determining the target braking torque according to the first braking torque and the current braking torque includes: determining according to the first braking torque and the current braking torque fifth braking torque; determining a target braking torque according to the fourth braking torque and the fifth braking torque.
  • the processing unit is further configured to: when the slope angle is less than zero, or the difference between the current driving torque and the third braking torque is greater than or equal to the first threshold, determine the fifth braking torque as the target braking torque.
  • the processing unit is further configured to: when the absolute value of the slope angle is less than or equal to a second threshold, or, when the first braking torque is less than or When equal to the second threshold, it is determined that the target braking torque is zero.
  • the acquiring unit is further configured to: acquire a first driving torque, where the first driving torque is a torque determined according to the mass and the slope angle; the processing unit Also used for: determining the target driving torque according to the first driving torque and the current driving torque.
  • the processing unit is further configured to: before determining the target driving torque according to the first driving torque and the current driving torque, acquire the current speed of the vehicle; When the current speed is less than zero, determining the compensation torque according to the current speed; determining the target driving torque according to the first driving torque and the current driving torque includes: according to the first driving torque, the current driving torque and the compensation torque determines the target drive torque.
  • the processing unit is further configured to: before determining the fifth braking torque according to the first braking torque and the current braking torque, obtain the vehicle's Current speed and current acceleration; when the current speed is less than zero, or, when the current speed is greater than or equal to zero and the current acceleration is greater than or equal to zero, the compensation torque is determined according to the current speed; the compensation torque is determined according to the first braking torque and Determining the fifth braking torque with the current braking torque includes: determining the fifth braking torque according to the first braking torque, the compensation torque and the current braking torque.
  • the processing unit is further configured to: determine a first duration, the first duration being the duration during which the current speed of the vehicle is zero; when the first duration When greater than or equal to the fourth threshold, determine the third braking torque as the target braking torque.
  • the processing unit is further configured to: before acquiring the slope angle and the mass of the vehicle, determine the first distance between the vehicle and the closest preceding vehicle;
  • the controlling the vehicle to start or stop according to the target braking torque and the target driving torque includes: when the first distance is less than or equal to a fifth threshold, controlling the vehicle to stop according to the target braking torque and the target driving torque.
  • the processing unit is further configured to: determine the second distance between the vehicle and the destination before acquiring the slope angle and the mass of the vehicle; Controlling the vehicle to start or stop with the target braking torque and the target driving torque includes: when the second distance is less than or equal to a sixth threshold, controlling the vehicle to stop according to the target braking torque and the target driving torque.
  • the processing unit is further configured to: before acquiring the slope angle and the mass of the vehicle, determine the acceleration of the vehicle closest to the front; and determine the acceleration according to the target braking torque Controlling the vehicle to start or stop with the target driving torque includes: when the acceleration of the closest preceding vehicle is greater than or equal to a seventh threshold, controlling the vehicle to start according to the target braking torque and the target driving torque.
  • an automatic vehicle control device which includes: a memory for storing programs; a processor for executing the programs stored in the memory, and when the programs stored in the memory are executed, the processor is used for executing the above-mentioned The method in any possible implementation manner of the first aspect to the third aspect.
  • an automatic driving vehicle is provided, and the vehicle includes the device in any possible implementation manner of the third aspect to the seventh aspect above.
  • a computer program product includes: computer program code, when the computer program code is run on a computer, it causes the computer to execute any possible implementation manner of the above first aspect to the third aspect method in .
  • a computer-readable storage medium stores program codes.
  • the computer program codes run on a computer, the computer executes any one of the above-mentioned first to third aspects. Methods in Possible Implementations.
  • a chip system in an eleventh aspect, includes a processor, configured to call a computer program or a computer instruction stored in a memory, so that the processor executes any one of the above-mentioned first to third aspects. method in the implementation.
  • the processor is coupled to the memory through an interface.
  • the chip system further includes a memory, where computer programs or computer instructions are stored.
  • Fig. 1 is a schematic structural diagram of an automatic vehicle control device provided by an embodiment of the present application
  • FIG. 2 is a schematic diagram of a system architecture for the application of an automatic vehicle control method provided in an embodiment of the present application
  • Fig. 3 is a schematic flowchart of a method for automatic vehicle control provided by an embodiment of the present application
  • Fig. 4 is a schematic diagram of the technical effect of a method for automatic vehicle control provided by an embodiment of the present application.
  • Fig. 5 is a schematic diagram of the technical effect of a method for automatic vehicle control provided by an embodiment of the present application.
  • Fig. 6 is a schematic flowchart of another automatic vehicle control method provided by the embodiment of the present application.
  • Fig. 7 is a schematic flowchart of another automatic vehicle control method provided by the embodiment of the present application.
  • Fig. 8 is a schematic flowchart of another automatic vehicle control method provided by the embodiment of the present application.
  • Fig. 9 is a schematic flowchart of another automatic vehicle control method provided by the embodiment of the present application.
  • Fig. 10 is a schematic diagram of the technical effect of a method for automatic vehicle control provided by an embodiment of the present application.
  • Fig. 11 is a schematic flowchart of a method for automatic vehicle control provided by an embodiment of the present application.
  • Fig. 12 is a schematic flowchart of a method for automatic vehicle control provided by an embodiment of the present application.
  • Fig. 13 is a schematic flowchart of a method for automatic vehicle control provided by an embodiment of the present application.
  • Fig. 14 is a schematic block diagram of an automatic vehicle control device provided by an embodiment of the present application.
  • Fig. 15 is a schematic block diagram of an automatic vehicle control device provided by an embodiment of the present application.
  • Fig. 1 is a schematic structural diagram of an automatic vehicle control device provided by an embodiment of the present application.
  • the vehicle 100 can be configured in a fully or partially automatic driving mode.
  • the vehicle 100 can obtain its surrounding environment information through the perception system 120, and obtain an automatic driving strategy based on the analysis of the surrounding environment information to realize fully automatic driving, or present the analysis results to the user to realize partially automatic driving.
  • the vehicle 100 is configured in a fully or partially autonomous driving mode.
  • Vehicle 100 may include various subsystems such as travel system 110 , perception system 120 , and control system 130 .
  • vehicle 100 may include more or fewer subsystems, and each subsystem may include multiple elements.
  • each subsystem and element of the vehicle 100 may be interconnected by wire or wirelessly.
  • the perception system 120 may include several kinds of sensors that sense information about the environment around the vehicle 100 .
  • the perception system 120 may include a global positioning system 121 (the global positioning system may be a GPS system, or a Beidou system or other positioning systems), an inertial measurement unit (inertial measurement unit, IMU) 122, a laser radar 123, a millimeter wave radar 124 , one or more of ultrasonic radar 125 and camera device 126 .
  • a global positioning system 121 the global positioning system may be a GPS system, or a Beidou system or other positioning systems
  • IMU inertial measurement unit
  • Propulsion system 110 may include components that provide powered motion for vehicle 100 .
  • propulsion system 110 may include engine 111 , transmission 112 and wheels/tires 113 .
  • the engine 111 converts the energy source into mechanical energy, and the transmission 112 may transmit the mechanical power from the engine 111 to the wheels 113 .
  • the control system 130 controls the operation of the vehicle 100 and its components.
  • the control system 130 may include a sensor fusion algorithm unit 131 , a cooperative control unit 132 , a rolling compensation unit 133 and a driving/braking unit 134 .
  • the sensor fusion algorithm unit 131 in the control system 130 can dynamically estimate the slope angle and vehicle mass according to the environmental information sensed by the perception system 120 .
  • the cooperative control unit 132 can calculate the target driving torque/braking torque according to the actual driving torque and actual braking torque of the vehicle, combined with the estimated slope angle and vehicle mass, and input the result to the driving/braking control unit 134 to realize The smooth loading and unloading of the driving/braking torque can complete the smooth transition of the torque when the vehicle starts or stops.
  • the rolling compensation unit 133 can increase the additional braking/driving torque according to the real-time speed and acceleration of the vehicle, so as to prevent the vehicle from rolling during starting or stopping.
  • the driving/braking control unit 134 is used to implement the target driving/braking torque, and feed back the actual driving/braking torque to the cooperative control unit 132 and the rolling compensation unit 133 .
  • the driving/braking control unit may include components for controlling the driving motor and the hydraulic system, controlling the driving motor to output driving torque according to the target driving torque, and controlling the hydraulic system to output braking torque according to the target braking torque.
  • the driving/braking control unit may further include other control components, which is not limited in this embodiment of the present application.
  • Computing platform 150 may include at least one processor 151 that may execute instructions 153 stored in a non-transitory computer-readable medium such as memory 152 .
  • computing platform 150 may also be a plurality of computing devices that control individual components or subsystems of vehicle 100 in a distributed manner.
  • the processor 151 may be any conventional processor, such as a central processing unit (central processing unit, CPU). Alternatively, the processor 151 may also include, for example, an image processor (graphic process unit, GPU), a field programmable gate array (field programmable gate array, FPGA), a system on chip (system on chip, SOC), an ASIC ( application specific integrated circuit, ASIC) or their combination.
  • a central processing unit central processing unit, CPU
  • the processor 151 may also include, for example, an image processor (graphic process unit, GPU), a field programmable gate array (field programmable gate array, FPGA), a system on chip (system on chip, SOC), an ASIC ( application specific integrated circuit, ASIC) or their combination.
  • the memory 152 can also store data, such as road maps, route information, vehicle position, direction, speed and other data. These data may be used by vehicle 100 and computing platform 150 during operation of vehicle 100 in autonomous, semi-autonomous, and/or manual modes.
  • the computing platform 150 may control functions of the vehicle 100 based on input received from various subsystems (eg, the perception system 120 ). For example, the computing platform 150 can utilize the vehicle speed and acceleration information determined from the global positioning system 121 in the perception system 120 to calculate the mass of the vehicle and the gradient of the road in real time.
  • various subsystems eg, the perception system 120
  • the computing platform 150 can utilize the vehicle speed and acceleration information determined from the global positioning system 121 in the perception system 120 to calculate the mass of the vehicle and the gradient of the road in real time.
  • one or more of these components described above may be installed separately or associated with the vehicle 100 .
  • memory 152 may exist partially or completely separate from vehicle 100 .
  • the components described above may be communicatively coupled together in a wired and/or wireless manner.
  • the above-mentioned components are just examples, and in actual applications, components in the above-mentioned modules may be added or deleted according to actual needs.
  • the above vehicle 100 may include one or more different types of vehicles, and may also include one or more different types of vehicles on land (for example, roads, roads, railways, etc.), water (for example: waterways, rivers, oceans, etc.) or means of transport or movable objects that operate or move in space.
  • a vehicle may include a car, a bicycle, a motorcycle, a train, a subway, an airplane, a ship, an aircraft, a robot, or other types of transportation means or movable objects, which are not limited in this embodiment of the present application.
  • Fig. 2 shows a schematic diagram of a system architecture of the method for automatic vehicle control according to the embodiment of the present application. As shown in Fig. 2, it includes a perception module, a data module and a control module. The system shown in Fig. 2 can be applied to intelligent driving vehicles, etc. Supported start and stop control scenarios.
  • the perception module may be one or more of the plurality of sensors included in the perception system 120 in FIG. wait.
  • the data module and the control module can be one or more of the computing platforms 150 in FIG. 1, the data module can also be the sensor fusion algorithm unit 134 included in the control system 130 in FIG.
  • the system 130 includes a cooperative control unit 132 , a rolling compensation unit 133 and a driving/braking control unit 134 .
  • the perception module can input the environmental information acquired by the global positioning system 121 such as GPS, laser radar 123, and camera 126 into the data module, and the sensor fusion algorithm unit 134 in the data module can determine according to the above environmental information Ramp angle information for the current road.
  • the global positioning system 121 such as GPS, laser radar 123, and camera 126
  • the sensor fusion algorithm unit 134 in the data module can determine according to the above environmental information Ramp angle information for the current road.
  • the perception module can input the acquired vehicle speed signal, acceleration information, gyroscope angular velocity information, and the actual driving/braking torque fed back by the vehicle into the data module and the control module.
  • the data module analyzes and processes the vehicle's speed, acceleration and angular velocity information to obtain real-time slope angle information and vehicle quality information. Further, the data module inputs the above slope angle information and vehicle quality information into the control module.
  • the PID control unit in the control module is based on the environmental information obtained from the perception module, such as the current speed and acceleration of the vehicle, the acceleration of the closest preceding vehicle, the distance to the closest preceding vehicle, and the distance to the destination. etc., and the estimated slope angle and vehicle mass obtained from the data module, calculate the requested driving/braking torque and input it into the start-stop control unit.
  • the start-stop control unit combines slope angle information and vehicle mass information to calculate target driving/braking torque, controls the target driving torque to gradually unload or increase to the requested driving torque, or controls the target braking torque to unload or increase to the requested braking torque.
  • control module can also carry out cooperative control on the target driving/braking torque to ensure the smooth transition of the torque during the starting or stopping process of the vehicle, reduce the vibration of the vehicle during the starting and stopping process, and realize the non-inductive start of the vehicle. stop.
  • control module may also combine the actual speed and/or acceleration information of the vehicle to control the magnitude of the additional driving/braking torque, so as to prevent the vehicle from slipping on a road with a non-zero gradient.
  • the factors that affect the stability of the vehicle during starting and stopping mainly include the accuracy of the slope angle estimation, the accuracy of the vehicle mass estimation, and the control of the motor torque during the starting and stopping process.
  • the current commonly used slope angle estimation scheme is to use real-time vehicle speed signals and IMU acceleration signals for processing.
  • the vehicle longitudinal motion acceleration a x can be obtained by differentiating the real-time vehicle speed signal;
  • the IMU acceleration at is the superposition of the vehicle longitudinal motion acceleration a x and the longitudinal component of the gravitational acceleration g affected by the slope .
  • the component g x of the gravitational acceleration along the longitudinal direction of the vehicle on the ramp can be obtained.
  • the acceleration signal obtained by the differentiation of the vehicle speed must have a delay in the time domain. It is difficult to ensure that the delay characteristic is consistent with the delay characteristic of the IMU acceleration signal that has also been filtered, so when the two make a difference, it will bring a large slope estimation error. The above errors may also affect the accuracy of vehicle mass estimation.
  • the embodiments of the present application provide a method and device for automatic vehicle control, which can accurately estimate the slope angle and vehicle mass, based on the accurately estimated slope and mass, combined with the current actual driving torque and braking torque of the vehicle, cooperatively Adjust the target driving/braking torque to achieve a fast and smooth transition from the actual output torque to the vehicle's calculated start or stop torque during the vehicle start or stop process, while reducing the vibration during the vehicle start and stop process, it can also Shorten the time required for the vehicle to start and stop, and improve the user's driving experience.
  • sensor failure may occur during the driving process of the vehicle.
  • this application also provides a redundant backup strategy for slope angle estimation, so that when the sensor signal is abnormal When the slope signal is switched online, it can ensure the accuracy of the slope angle estimation, thereby ensuring the smooth transition of the torque when the vehicle starts or stops, and improves the driving experience of the user.
  • Fig. 3 shows a schematic flowchart of a method 300 for automatic vehicle control provided by an embodiment of the present application.
  • Fig. 3 shows a process of estimating the slope angle in real time based on the phase delay characteristic optimization method, the method shown in the process can be executed by the device shown in Fig. 1, and can also be applied to the system shown in Fig. 2, this Application examples are not limited thereto.
  • the steps or operations of the automatic vehicle control method shown in FIG. 3 are only examples, and other operations or variations of the operations in FIG. 3 may also be performed in the embodiment of the present application.
  • the method 300 includes:
  • the real-time vehicle speed signal of the vehicle is obtained, and the vehicle speed is differentiated to obtain the longitudinal motion acceleration signal of the vehicle, that is, the acceleration signal excluding the longitudinal component of the acceleration of gravity along the vehicle.
  • the real-time vehicle speed signal can be calculated from the wheel speed obtained by the wheel speed sensor; or the real-time vehicle speed signal can be obtained from the information fed back by the relevant vehicle speed sensor of the vehicle chassis, which is not limited in the embodiment of the present application.
  • the real-time vehicle speed signal fluctuates greatly, that is, the curve of the real-time vehicle speed versus time is not smooth, therefore, in the process of deriving the real-time vehicle speed signal, high-frequency glitch noise will inevitably be generated, so it is necessary to analyze the above-mentioned vehicle longitudinal motion acceleration signal Filter processing is performed to filter out high-frequency burr noise. Further, Fourier transform is performed on the filtered vehicle speed differential signal, that is, the filtered vehicle longitudinal motion acceleration signal, to obtain the phase-frequency characteristic curve A and the amplitude-frequency characteristic curve A' of the vehicle speed differential signal.
  • the vehicle longitudinal acceleration signal is filtered to filter out high-frequency spur noise. Further, Fourier transform is performed on the filtered vehicle longitudinal acceleration to obtain the phase-frequency characteristic curve B and the amplitude-frequency characteristic curve B' of the vehicle longitudinal acceleration signal.
  • the Bode plots of the two signals can be obtained by performing a frequency sweep test on the vehicle speed differential signal and the vehicle longitudinal acceleration signal, and the phase-frequency characteristic curves in the Bode diagrams of the two signals are respectively phase-frequency characteristic curves A and B;
  • the phase-frequency characteristic curves A and B of the vehicle speed differential signal and the vehicle longitudinal acceleration signal can be obtained in other ways, which are not limited in the comparison of the embodiment of the present application.
  • the vehicle longitudinal acceleration is the superposition of the vehicle longitudinal motion acceleration and the gravitational acceleration affected by the slope along the vehicle longitudinal component.
  • the vehicle longitudinal acceleration signal may be obtained through an IMU acceleration sensor, or may be obtained through other acceleration sensors, which is not limited in this embodiment of the present application.
  • phase delay difference between B is recorded as the third phase delay.
  • ⁇ A is the frequency
  • ⁇ ( ⁇ A ) is the phase-frequency response, that is, the phase change of the frequency component after passing through the filter
  • P( ⁇ A ) represents the delay when the frequency component passes through the filter.
  • the parameters of filters A and B are optimized based on the phase delay characteristics of the two signals, so that the phase delay characteristics of the above two signals after passing through filter A and filter B respectively can be kept consistent, that is, After the two signals are filtered by filter A and filter B respectively, the lag characteristics of the phase angle in time are the same.
  • the parameters of filter A are optimized according to the first phase delay and the third phase delay
  • the parameters of filter B are optimized according to the second phase delay and the third phase delay.
  • intelligent optimization algorithms such as particle swarm optimization (PSO), genetic algorithm (genetic algorithm, GA) and other intelligent optimization algorithms can be used. limited.
  • the vehicle speed differential signal passes through the filter A to obtain the acceleration signal a.
  • the longitudinal acceleration signal of the vehicle passes through the filter B to obtain an acceleration signal b.
  • c a1-b1.
  • the acceleration signal b1 is the superposition of the vehicle longitudinal motion acceleration (ie, the vehicle speed differential signal) a1 and the gravitational acceleration affected by the slope along the vehicle longitudinal component gx .
  • vehicle longitudinal motion acceleration ie, the vehicle speed differential signal
  • a1 the vehicle longitudinal motion acceleration
  • c -g x at this time
  • b1 a1-g x
  • c g x at this time.
  • the estimated road angle s arcsin(c/g), where g is the acceleration due to gravity. That is, when the vehicle is going downhill, the estimated angle is a negative value; when the vehicle is going uphill, the estimated angle is a positive value.
  • S301a, S301b and S302 are offline processing (off-line processing), that is, filter A and filter B are not optimized in real time during vehicle driving, but are based on the stored vehicle differential
  • the signals and vehicle longitudinal acceleration signals are used for slope estimation during vehicle driving.
  • S303a, S303b and S304 are on-line processing (on-line processing). Specifically, when the vehicle is running, the vehicle speed differential signal and the vehicle longitudinal acceleration signal pass through the optimized filters A and B respectively in real time to obtain Acceleration signals a1 and b1, and then estimate the slope angle in real time according to the acceleration a1 and b1.
  • the filters involved in the embodiments of the present application may be commonly used digital filters, such as Butterworth filters, Chebyshev Type I/Type II filters, and elliptic filters, which are not limited in the embodiments of the present application.
  • the slope angle information may be stored in historical information, so that the vehicle can use it when starting and/or parking on this road next time.
  • filter parameter optimization is performed based on the phase delay characteristics of the vehicle differential signal and the vehicle longitudinal acceleration signal, so that the phase delay of the above two signals passes through the optimized filter respectively. This can be kept consistent, which in turn improves the accuracy of the estimated ramp angle.
  • (a) in Figure 4 is the Bode diagram of the unoptimized two-way signal
  • (b) in Figure 4 is the two-way filter that has been optimized based on the phase delay characteristics of the two-way signal
  • the Bode diagram of the two-way signal shows that the consistency of the phase delay characteristics of the two-way signal is significantly improved.
  • Figure 5 is the result verified by the actual drive test data, as shown in Figure 5, the delay of the slope estimation result after filter optimization can be increased by about 500ms at most.
  • FIG. 6 shows a schematic flowchart of a method 600 for automatic vehicle control provided by an embodiment of the present application. Specifically, FIG. 6 shows a flow of slope angle estimation as a redundant strategy. The method shown in the flow can be executed by the device shown in FIG. 1, and can also be applied to the system shown in FIG. 2. The present application Embodiments are not limited thereto.
  • the method 600 includes:
  • the angular velocity information of the gyroscope comes from the IMU gyroscope sensor, or from other gyroscope sensors, which is not limited in this embodiment of the present application.
  • S601b Determine the second slope angle information by using laser radar, GPS, camera device, etc.
  • the vehicle determines the second slope angle information according to the environment information acquired by the laser radar, GPS, camera device and the like.
  • the second slope angle information is determined according to one or more of point cloud data, GPS data, and image data.
  • the second slope angle information may be a slope angle determined according to sensor information such as laser radar, GPS, and camera; or, the second slope angle information may also be a slope angle determined according to laser radar Multiple slope angles determined by sensor information such as , GPS, and camera devices.
  • the first slope angle information is used as the predicted value
  • the second slope angle information is used as the observed value
  • the bias bias of the gyroscope sensor is considered, the following angle integral calculation model equation is constructed:
  • Angle t is the slope angle estimated at time t
  • bias t is the zero bias of the gyroscope at time t
  • Gyro is the angular velocity measured by the gyroscope
  • z is the slope angle measured or estimated by other sensors, such as through laser radar, GPS and A camera device or the like acquires the slope angle.
  • the estimated slope angle can be obtained by applying the Kalman filter recurrence equation for fusion calculation. It should be understood that in this embodiment of the present application, other optimal estimation methods, such as the recursive least squares method, can be used to determine a more accurate value by using the first slope angle information as the predicted value and the second slope angle information as the observed value.
  • the current slope angle is not limited in this embodiment of the present application.
  • the slope angle information may be stored in historical information, so that the vehicle can use it when starting and/or parking on this road next time.
  • the slope estimation scheme can be dynamically switched according to the accuracy of the input signal and the failure of the sensor to ensure the reliability and accuracy of the slope estimation result.
  • FIG. 7 shows a schematic flowchart of a method for automatic vehicle control provided by an embodiment of the present application.
  • FIG. 7 shows a process for estimating vehicle mass in real time.
  • the method shown in the process can be applied to the application scenario shown in FIG. 1 or the system shown in FIG. 2 , and the embodiment of the present application is not limited thereto.
  • the steps or operations of the method for automatic vehicle control shown in FIG. 7 are only examples, and other operations or variations of the operations in FIG. 7 may also be performed in the embodiment of the present application.
  • the method is specifically:
  • vehicle longitudinal dynamics model is constructed as follows:
  • F x is the longitudinal driving force of the vehicle
  • m is the mass of the vehicle to be estimated
  • a x is the longitudinal acceleration of the vehicle
  • C d is the drag coefficient
  • A is the frontal area
  • v x is the longitudinal speed of the vehicle
  • g is the acceleration of gravity
  • ⁇ is the slope of the road surface
  • f is the rolling resistance coefficient of the road surface.
  • the above-mentioned ratios are calculated using the method of recursive least squares to obtain the estimated vehicle mass.
  • the vehicle may store the mass information for use when the vehicle starts and/or stops next time.
  • the automatic vehicle control method of the embodiment of the present application uses the recursive least squares method to estimate the vehicle mass based on the accurately estimated slope angle, which can accurately estimate the vehicle mass, thereby providing a more accurate vehicle mass signal for controlling the start and stop of the vehicle.
  • Fig. 8 shows a schematic flowchart of a method 800 for automatic vehicle control provided by an embodiment of the present application.
  • Fig. 8 shows the flow of the cooperative control of driving and braking torque during the starting process of the vehicle.
  • the method shown in the flow can be executed by the device shown in Fig. 1.
  • the compensation module can correspond to the cooperative control unit 132 and the rolling compensation unit 133 in FIG. 1 respectively; the method shown in this process can also be applied to the system shown in FIG. 2 , specifically, it can be controlled by the start-stop control in FIG. unit execution.
  • the steps or operations of the automatic vehicle control method shown in FIG. 8 are only examples, and other operations or variations of the operations in FIG. 8 may also be performed in the embodiment of the present application.
  • the method 800 includes:
  • the estimated slope angle s may be the result obtained according to the method 300 or the method 600 ; the estimated vehicle mass m may be the result obtained according to the method 700 .
  • the above estimated vehicle mass m and slope angle s can also be obtained by methods other than the above methods, for example, after the vehicle drives to the road, the vehicle perception system recognizes the road according to the surrounding environment information After the road saved in the vehicle history information, the slope angle of the road saved in the history information can be called; or, when the vehicle starts, the current slope angle can be determined according to the slope angle information saved in the history record when the vehicle was last stopped s.
  • the requested braking torque T bReq is calculated.
  • This step can be shown in Figure 2
  • the PID control unit in is executed; it should be understood that the requested braking torque T bReq is the braking torque required for the vehicle to start under the current state.
  • the calculated actual driving torque T m is the actual output torque of the vehicle's drive system at the current moment fed back by the torque sensor, and the actual braking torque T b is the actual output torque of the vehicle's braking system at the current moment fed back by the vehicle sensor.
  • the start-stop control unit may start to execute S811 after receiving the instruction.
  • the above-mentioned instruction may be a starting instruction input by the user interface of the vehicle; or, the above-mentioned instruction may be an instruction related to the acceleration of the closest preceding vehicle recognized by the vehicle perception system, for example, when the acceleration of the closest preceding vehicle is greater than or equal to the acceleration obtained by the system
  • the threshold is preset, the start command is sent to the start-stop control unit.
  • the above instructions may also be other instructions for controlling the start of the vehicle, which is not limited in this embodiment of the present application.
  • T ini mg*a*(b+sin(
  • the above-mentioned initial braking torque T ini is the braking torque required to overcome the vehicle sliding caused by the downward component of the vehicle's own gravity along the slope when the vehicle is in a stationary state before starting.
  • the above T ini may also be the expected braking torque T des when the vehicle stops the last time stored in the history record of the vehicle (that is, the actual driving torque T b when the vehicle stops).
  • magnification factor a is determined according to the ratio of the total mass of the vehicle when it is fully loaded to the curb mass of the vehicle, where the total mass of the vehicle refers to the mass of the vehicle when it is fully equipped and fully loaded with passengers (including the driver) and goods.
  • Vehicle curb weight refers to the empty weight of the vehicle when it is ready to drive under normal conditions and has no passengers (including the driver) and no cargo.
  • the total mass of the vehicle when it is fully loaded is m 1
  • the curb mass of the vehicle is m 2
  • a m 1 /m 2
  • a is a constant greater than 1.
  • the slope deviation coefficient b is determined according to the systematic error of the slope angle estimation. For example, if the slope angle estimation error is 0.5-0.8%, then b can take any value in the range of 1.005-1.008.
  • the above-mentioned mass amplification factor a can also be determined according to the number of passengers in the vehicle.
  • m 0 is the default weight of the user of the vehicle, which may specifically be 80kg, which is not limited in this embodiment of the present application.
  • the first target braking torque is calculated according to the second requested braking torque T bReq2 :
  • T bCmd1 T bReq2 *c+(1-c)*T b , where c is an exponential decay coefficient.
  • the exponential decay coefficient c is a constant less than or equal to 1.
  • the larger c is, the faster the transition from the target braking torque to the requested braking torque is, and the vehicle is more likely to shake; the smaller c is, the faster the target braking torque is to the requested braking torque.
  • the slower the transition the longer it takes to start and the lower the efficiency. Therefore, it is necessary to reasonably set the value of c in combination with the actual situation.
  • the above-mentioned coefficients a, b, and c are all calibration constants, which can be set according to actual road conditions, vehicle types, etc., and the specific values of the above-mentioned coefficients are not limited in this embodiment of the present application.
  • T gap is a first preset value, representing the minimum driving torque required for the vehicle to start.
  • T m -T ini ⁇ T gap it means that the vehicle has started, no matter whether the vehicle is on an uphill road (s>0) or a downhill road (s ⁇ 0), there is no need to perform additional braking on the vehicle, and then continue to execute S815 ; or, if s ⁇ 0, it means that the vehicle is starting downhill, that is, the vehicle needs to generate speed and/or acceleration along the downhill direction. At this time, it is only necessary to gradually unload the braking torque without worrying about the slope caused by insufficient braking torque. Road slipping problem, so S815 can be continued.
  • T m ⁇ T ini ⁇ T gap it may only be judged whether T m ⁇ T ini ⁇ T gap is established, and if it is established, continue to execute S815 , and if not, continue to execute S816 . That is to say, whether the vehicle starts on an uphill road (s>0) or a downhill road (s ⁇ 0), as long as the difference between the actual driving torque T m and the torque T ini required to overcome the vehicle's own gravity is greater than or equal to the first preset value, that is, the minimum driving torque T gap required for the vehicle to start, there is no need to brake the vehicle; when the above difference is less than T gap , the difference between T ini and T m is calculated .
  • T bCmd1 and ⁇ T are taken as T bCmd2 .
  • s min is the second preset value, that is, the minimum angle of the slope at which the vehicle will not roll when the braking torque of the vehicle is 0; T min is the third preset value, in order to ensure that the vehicle will not roll Minimum safe braking torque.
  • the slope angle of the vehicle is less than or equal to the second preset value or the second requested braking torque is less than or equal to the third preset value, it means that no braking torque is applied at this time, and the vehicle will not roll, so it can be Set the second target braking torque to zero.
  • the second target braking torque T bCmd2 is assigned to the target braking torque T bCmd .
  • this step can be executed by the PID control unit in Figure 2;
  • the vehicle speed V s is For the longitudinal speed of the vehicle fed back by the speed sensor, V s >0 means that the vehicle is moving forward, and V s ⁇ 0 means that the vehicle has moved backward, that is, the vehicle has slipped.
  • T mCmd1 T mReq *c+(1-c)*T m .
  • V s ⁇ 0 If V s ⁇ 0 is established, continue to execute S824; if not, continue to execute S826.
  • T add T add +T 0 +T s *V s
  • T add in the first item on the right side of the formula represents the compensation driving torque increased in the last cycle
  • the initial value of T add is 0
  • T 0 is the driving torque constant, that is, the fixed driving torque increased in each cycle
  • T s is the speed proportional coefficient, the faster the rolling speed, the greater the value of the third item on the right side of the above formula.
  • T 0 and T s are system preset values, which can be set according to actual road conditions, vehicle types, etc.
  • the compensation driving torque T add is added to the first target driving torque T mCmd1 .
  • T mCmd and T bCmd should be values greater than or equal to zero.
  • T mCmd and T bCmd change in real time until the vehicle completes starting.
  • the above S811-S830 is only one cycle.
  • the drive/brake unit of the vehicle executes T mCmd and T bCmd , and the torque sensor will obtain the drive torque T actually output by the drive/brake unit.
  • m and braking torque T b information The T m and T b will be used as input values for the next calculation of the target driving/braking torque until the target driving torque is equal to the requested driving torque.
  • S811-S820 and S821-S826 may be executed simultaneously or successively, which is not limited in this embodiment of the present application.
  • S811-S822, S826 and S830 may be executed, that is, the vehicle roll compensation method involved in S823-S825 is not executed.
  • S818 may be executed first, and if the condition
  • first and second target braking torques are only for the purpose of clearly distinguishing the target braking torques involved in each step of the process, which are essentially target braking torques. Intermediate quantity in the torque calculation process. The same is true for the "first" target drive torque, which will still be expressed in this manner hereinafter.
  • the automatic vehicle control method of the embodiment of the present application by combining the estimated vehicle mass and the road gradient, cooperatively controls the driving torque and the braking torque, so as to ensure that the resultant force generated by the two can balance the slope resistance, and can control the smooth loading and braking of the driving torque.
  • the braking torque is smoothly unloaded at the same time, so as to ensure the smooth start of the vehicle and shorten the time required for the vehicle to start. From the actual vehicle test results shown in Figure 10, on a road with a slope of 15%, the general vehicle takes 2.5 seconds to start, but it only takes 1.5 seconds to start using the automatic vehicle control method of the embodiment of the present application.
  • the method of the embodiment of the present application can significantly reduce the time required for start-up, and can better meet the needs of ADS for quick start-up.
  • the vehicle rolling compensation mechanism the vehicle can be prevented from rolling during the starting process, which can improve the safety of the driving process and the driving experience of the user.
  • Fig. 9 shows a schematic flowchart of a method 900 for automatic vehicle control provided by an embodiment of the present application.
  • Fig. 9 shows the flow of cooperative control of driving and braking torque during vehicle parking, the method shown in the flow can be executed by the device shown in Fig. 1, and Fig. 9 shows the cooperative control module and the vehicle slip
  • the compensation modules may respectively correspond to the coordinated control unit 132 and the rolling compensation unit 133 in FIG. 1 ; the method shown in the flow chart may also be applied to the system shown in FIG. 2 , which is not limited in this embodiment of the present application.
  • the steps or operations of the automatic vehicle control method shown in FIG. 9 are only examples, and other operations or variations of the operations in FIG. 9 may also be performed in the embodiment of the present application.
  • the method 900 includes:
  • the start-stop control unit may start to execute S911 after receiving the instruction.
  • the above instruction may be a parking instruction input by the user interface of the vehicle; or, when the vehicle perception system recognizes that the distance to the nearest preceding vehicle is less than or equal to the preset distance, start to execute S911; or, the vehicle perception system recognizes that the vehicle is When the distance between the destinations is less than or equal to the preset distance, S911 is executed.
  • the desired braking torque T des is the maximum target braking torque that only considers the gravity that needs to be overcome when the vehicle stops on a slope.
  • the minimum braking torque T blo is the minimum braking torque that the braking system needs to output at the current moment in order to stop the vehicle under the premise of considering the influence of the slope. Specifically, the calculation formula is:
  • T blo T des -max(mg*sin(s)*R,0)+min(0,T m );
  • the driving system can output both driving torque and braking torque. If the driving system outputs braking torque, the actual driving torque T m fed back by the torque sensor is a negative value. In addition, when the vehicle needs to stop during the uphill process, the slope resistance will contribute a part of the braking force when the vehicle goes uphill. If the torque output by the drive system is actually the braking torque, the braking force required to overcome the gravity needs to be considered.
  • T bCmd3 T bReq2 *c+(1-c)*T b , wherein, c is an exponential decay coefficient, so that the target braking torque transitions smoothly to T des .
  • T bCmd4 max(T bCmd3 , T blo ), that is, the larger value of T bCmd3 and T blo is assigned to the fourth target braking torque, so as to prevent the vehicle from being unable to brake due to too small braking torque.
  • the first duration t is the duration during which the vehicle's moving speed is 0.
  • the duration is greater than the system preset threshold t 0 , the vehicle is considered to have stopped.
  • T des to T bCmd forcibly, so as to ensure that the vehicle does not slip on the slope.
  • T gap2 is the fourth preset value.
  • T des -T b ⁇ T gap2 it means that the actual braking torque has not reached a certain value, then continue to execute S922; otherwise, if T des -T b ⁇ T gap2 , it means that the actual braking torque has increased to a certain value, then The drive torque can be unloaded, that is, continue to execute S923.
  • T min2 is a fourth preset value, and when T mCmd2 is less than or equal to the preset value, it can be considered that the vehicle does not need driving torque. Therefore, if
  • the embodiment of the present application also provides a vehicle rolling compensation method, which specifically includes:
  • the vehicle speed V s is the longitudinal velocity of the vehicle fed back by the speed sensor
  • the vehicle motion acceleration a s is the vehicle motion acceleration obtained by differentiating the vehicle speed V s , that is, the component of the acceleration of gravity along the longitudinal direction of the vehicle is not included.
  • V s >0 indicates that the vehicle is moving forward at the current moment
  • V s ⁇ 0 indicates that the vehicle is moving backward at the current moment
  • V s >0 it means that the vehicle has slipped, and it is necessary to add additional compensation braking torque to prevent the vehicle from continuing to roll
  • V s ⁇ 0 and a s ⁇ 0 it means that the vehicle has not decelerated, or the vehicle has not decelerated. Forward slippage occurs, and additional compensating braking torque is also required at this time. Therefore, if "V s ⁇ 0" or "V s ⁇ 0 and a s ⁇ 0" is true, continue to execute S933; if not, continue to execute S934.
  • the vehicle is decelerating, or has come to a stop without rolling, so there is no need to increase the compensating drive torque.
  • the compensation driving torque is added to the actual driving torque, and input to S913 to calculate the target driving torque.
  • S915 may be executed first, and if the condition first duration t ⁇ t 0 in S915 is not established, then continue to execute S913-S914 and S930 in sequence; if the condition first duration t ⁇ t in S915 If t 0 is established, continue to execute S916 and S930 in sequence.
  • the automatic vehicle control method of the embodiment of the present application by combining the estimated vehicle mass and the road gradient, cooperatively controls the driving torque and the braking torque to ensure that the resultant force generated by the two can balance the slope resistance, and can control the steady increase of the driving torque and the braking torque.
  • the braking torque is smoothly unloaded at the same time, so as to ensure the stability of the vehicle during parking.
  • the vehicle can be prevented from rolling during parking, which can improve the safety of the driving process and the driving experience of the user.
  • FIG. 11 shows a schematic flowchart of a method 1100 for automatic vehicle control provided by an embodiment of the present application.
  • FIG. 11 shows the flow of the method for estimating the slope angle during vehicle driving.
  • the method shown in the flow can be executed by the device shown in FIG. 1, and can also be applied to the system shown in FIG. 2.
  • the embodiment of the present application Not limited to this.
  • the steps or operations of the automatic vehicle control method shown in FIG. 11 are only examples, and other operations or variations of the operations in FIG. 11 may also be performed in the embodiment of the present application.
  • the method 1100 includes:
  • the first acceleration signal in the embodiment of the present application may be the vehicle speed differential signal in the above embodiments, and the second acceleration signal may be the vehicle longitudinal acceleration signal.
  • the third acceleration signal may be the acceleration signal a1 in the above embodiment
  • the fourth acceleration signal may be the acceleration signal b1 in the above embodiment
  • the first filter may be the filter A in the above embodiment
  • the second filter may be the filter B in the above embodiment.
  • the automatic vehicle control method of the embodiment of the present application optimizes the filter parameters based on the phase delay characteristic between the vehicle differential signal and the vehicle longitudinal acceleration signal, so that the above two signals pass through the optimized filter respectively, and the phase The time delay can be kept consistent, so as to ensure the accuracy of the estimated slope angle, thereby reducing the vibration that occurs during the starting and stopping of the vehicle, and improving the user experience.
  • FIG. 12 shows a schematic flowchart of a method 1200 for automatic vehicle control provided by an embodiment of the present application.
  • FIG. 12 shows the flow of the method for estimating the slope angle during the driving of the vehicle.
  • the method shown in the flow can be executed by the device shown in FIG. 1 , and can also be applied to the system shown in FIG. 2 . Not limited to this.
  • the steps or operations of the automatic vehicle control method shown in FIG. 12 are only examples, and other operations or variations of the operations in FIG. 12 may also be performed in the embodiment of the present application.
  • the method 1200 includes:
  • S1210 Determine first slope angle information according to first data collected by a first sensor, where the first sensor includes a gyroscope sensor.
  • the first data may be the angular velocity of the gyroscope in the above embodiment, and the angular velocity of the gyroscope is integrated to determine the first slope angle information.
  • S1220 Determine second slope angle information from the second data collected by the second sensor, where the second sensor includes at least one of GPS, laser radar, and camera device.
  • the second data may be one or more of GPS data, laser point cloud data, and image data
  • the method for determining the second slope angle information according to the second data may refer to the above-mentioned embodiments, which are not described herein. Let me repeat.
  • the slope angle is determined by using data acquired by different sensors than in method 1200, which can ensure redundant reliability of slope estimation.
  • the slope estimation scheme can be dynamically switched according to the accuracy of the input signal and the failure of the sensor to ensure the reliability and accuracy of the slope estimation result.
  • FIG. 13 shows a schematic flowchart of a method 1300 for automatic vehicle control provided by an embodiment of the present application.
  • FIG. 13 shows the flow of coordinated control of driving and braking torque during the process of starting and stopping the vehicle.
  • the method shown in the flow can be executed by the device shown in FIG. 1, and can also be applied to the system shown in FIG. 2. Application examples are not limited thereto.
  • the steps or operations of the automatic vehicle control method shown in FIG. 13 are only examples, and other operations or variations of the operations in FIG. 13 may also be performed in the embodiment of the present application.
  • the method 1300 includes:
  • the first braking torque in the embodiments of the present application may be the second requested braking torque T bReq2 in the above embodiments.
  • the current braking torque in the embodiments of the present application may be the actual braking torque in the above embodiments
  • the current driving torque may be the actual driving torque in the above embodiments.
  • the first moment determines a target braking torque according to the first braking torque and the current braking torque, and determine a target driving torque according to the current driving torque, the first moment is when the vehicle starts or moments during parking.
  • the method for determining the target braking torque according to the first braking torque and the current braking torque and the method for determining the target driving torque according to the current driving torque can refer to the above-mentioned embodiments, which will not be repeated here.
  • the automatic vehicle control method provided by the embodiment of the present application, based on the accurately estimated vehicle mass and road gradient, cooperatively controls the target driving torque and the target braking torque to ensure that the target braking torque and the target driving torque can simultaneously increase to the actual required value of the vehicle.
  • the fast and smooth transition between the braking torque and the driving torque can shorten the time required for the vehicle to start and stop, and at the same time ensure the stability of the vehicle during the start and stop process, thereby improving the driving experience of the user.
  • the method provided by the embodiment of the present application is described in detail above with reference to FIG. 3 to FIG. 13 .
  • the device provided by the embodiment of the present application will be described in detail below with reference to FIG. 14 and FIG. 15 .
  • the descriptions of the device embodiments correspond to the descriptions of the method embodiments. Therefore, for details not described in detail, reference may be made to the method embodiments above. For brevity, details are not repeated here.
  • Fig. 14 is a schematic block diagram of an automatic vehicle control device provided by an embodiment of the present application.
  • the apparatus 1400 includes an acquisition unit 1410 and a processing unit 1420 .
  • the acquisition unit 1410 can implement a corresponding communication function, and the processing unit 1420 is used for data processing.
  • the device 1400 may further include a storage unit, which may be used to store instructions and/or data, and the processing unit 1420 may read the instructions and/or data in the storage unit, so that the device implements the aforementioned method embodiments .
  • a storage unit which may be used to store instructions and/or data
  • the processing unit 1420 may read the instructions and/or data in the storage unit, so that the device implements the aforementioned method embodiments .
  • the apparatus 1400 may include units for performing the methods in FIG. 3 to FIG. 13 .
  • each unit in the device 1400 and other operations and/or functions described above are for realizing the corresponding processes of the method embodiments in FIG. 3 to FIG. 13 .
  • the acquiring unit 1410 can be used to execute S1110 in the method 1100
  • the processing unit 1420 can be used to execute S1120 and S1130 in the method 1100 .
  • the device 1400 includes: an acquisition unit 1410, configured to acquire a first acceleration signal of the vehicle and a second acceleration signal of the vehicle; a processing unit 1420, configured to input the first acceleration signal into the first filter to generate a third acceleration signal. acceleration signal, and input the second acceleration signal into the second filter to generate the fourth acceleration signal, the phase delay characteristics of the third acceleration signal and the fourth acceleration signal are the same; the processing unit 1420 is also used to The acceleration signal and the fourth acceleration signal determine a ramp angle.
  • the first filter and the second filter in the device are filters optimized based on phase delay characteristics of the first acceleration signal and the second acceleration signal.
  • the first filter and the second filter in the device are filters optimized for offline processing.
  • the processing unit 1420 is further configured to: differentiate the velocity of the vehicle and filter to obtain the first acceleration signal; filter the longitudinal acceleration of the vehicle to obtain the second acceleration signal.
  • the processing unit 1420 is further configured to: determine the mass of the vehicle based on a recursive least square method according to the slope angle.
  • the apparatus can also be used to execute the method in FIG. 12 .
  • the processing unit 1420 can be used to execute S1210-S1230 in the method 1200 .
  • the device 1400 includes: a processing unit 1420, configured to determine first slope angle information according to first data collected by a first sensor, where the first sensor includes a gyro sensor; The second data collected by the sensor determines the second slope angle information, and the second sensor includes at least one of GPS, laser radar and camera device; the processing unit 1420 is also configured to The second ramp angle information determines the ramp angle based on an optimal estimation method.
  • a processing unit 1420 configured to determine first slope angle information according to first data collected by a first sensor, where the first sensor includes a gyro sensor; The second data collected by the sensor determines the second slope angle information, and the second sensor includes at least one of GPS, laser radar and camera device; the processing unit 1420 is also configured to The second ramp angle information determines the ramp angle based on an optimal estimation method.
  • the processing unit 1420 is further configured to: determine the mass of the vehicle based on a recursive least square method according to the slope angle.
  • the device can also be used to execute the method in FIG. 13.
  • the device 1400 is used to execute the method 1300 in FIG. S1320, S1340 and S1350 in the method 1300 are executed.
  • the device 1400 includes: an acquisition unit 1410, configured to acquire the slope angle and the mass of the vehicle; a processing unit 1420, configured to determine the first braking torque according to the mass and the slope angle; the acquisition unit 1410 also uses to obtain the current braking torque and the current driving torque of the vehicle; the processing unit 1420 is also used to determine the target braking torque according to the first braking torque and the current braking torque at the first moment, and to determine the target braking torque according to the current driving torque Torque determines the target driving torque; the first moment is a moment during the process of starting or stopping the vehicle.
  • the acquiring unit 1410 is further configured to: acquire a second braking torque, where the second braking torque is a torque determined according to the mass and the slope angle; the processing unit 1420 is also configured to: A first coefficient is determined from the gross mass of the vehicle when fully loaded, a second coefficient is determined from the estimation error of the ramp angle, a third braking torque is determined from the first coefficient, the second coefficient, the mass and the ramp angle ; determining the first braking torque according to the second braking torque and the third braking torque.
  • the processing unit 1420 is further configured to: before determining the target braking torque according to the first braking torque and the current braking torque, according to the third braking torque and the current driving torque determining a fourth braking torque; determining a target braking torque according to the first braking torque and the current braking torque includes: determining a fifth braking torque according to the first braking torque and the current braking torque; The fourth braking torque and the fifth braking torque determine a target braking torque.
  • the processing unit 1420 is further configured to: when the slope angle is less than zero, or when the difference between the current driving torque and the third braking torque is greater than or equal to a first threshold, The fifth braking torque is determined as the target braking torque.
  • the processing unit 1420 is further configured to: when the absolute value of the slope angle is less than or equal to a second threshold, or, when the first braking torque is less than or equal to a second threshold, determine The target braking torque is zero.
  • the acquiring unit 1410 is further configured to: acquire a first driving torque, where the first driving torque is a torque determined according to the mass and the slope angle; the processing unit 1420 is further configured to: according to the The first driving torque and the current driving torque determine the target driving torque.
  • the processing unit 1420 is further configured to: before determining the target driving torque according to the first driving torque and the current driving torque, obtain the current speed of the vehicle; when the current speed is less than zero , determining the compensation torque according to the current speed; determining the target driving torque according to the first driving torque and the current driving torque includes: determining the target driving torque according to the first driving torque, the current driving torque and the compensation torque.
  • the processing unit 1420 is further configured to: before determining the fifth braking torque according to the first braking torque and the current braking torque, obtain the current speed and the current acceleration of the vehicle; When the current speed is less than zero, or, when the current speed is greater than or equal to zero, and the current acceleration is greater than or equal to zero, the compensation torque is determined according to the current speed; the second braking torque is determined according to the first braking torque and the current braking torque.
  • the fifth braking torque includes: determining the fifth braking torque according to the first braking torque, the compensation torque and the current braking torque.
  • the processing unit 1420 is further configured to: determine a first duration, the first duration being the duration during which the vehicle's current speed is zero; when the first duration is greater than or equal to the fourth threshold , determining the third braking torque as the target braking torque.
  • the processing unit 1420 is further configured to: before acquiring the slope angle and the mass of the vehicle, determine the first distance between the vehicle and the vehicle immediately in front; Controlling the vehicle to start or stop with the target driving torque includes: when the first distance is less than or equal to a fifth threshold, controlling the vehicle to stop according to the target braking torque and the target driving torque.
  • the processing unit 1420 is further configured to: before acquiring the slope angle and the mass of the vehicle, determine the second distance between the vehicle and the destination; according to the target braking torque and the The target driving torque to control the vehicle to start or stop includes: when the second distance is less than or equal to a sixth threshold, controlling the vehicle to stop according to the target braking torque and the target driving torque.
  • the processing unit 1420 is also used for: before acquiring the slope angle and the mass of the vehicle, determine the acceleration of the vehicle closest to the front; control the vehicle according to the target braking torque and the target driving torque Starting or stopping the vehicle includes: controlling the vehicle to start according to the target braking torque and the target driving torque when the acceleration of the closest preceding vehicle is greater than or equal to the seventh threshold.
  • the processing unit 1420 in FIG. 14 may be realized by at least one processor or a processor-related circuit
  • the acquiring unit 1410 may be realized by a transceiver or a transceiver-related circuit
  • the storage unit may be realized by at least one memory.
  • Fig. 15 is a schematic block diagram of an automatic vehicle control device according to an embodiment of the present application.
  • the parking device 1500 shown in FIG. 15 may include: a processor 1510 , a transceiver 1520 and a memory 1530 .
  • the processor 1510, the transceiver 1520 and the memory 1530 are connected through an internal connection path, the memory 1530 is used to store instructions, the processor 1510 is used to execute the instructions stored in the memory 1530, and the transceiver 1530 receives/sends some parameters.
  • the memory 1530 may be coupled to the processor 1510 through an interface, or may be integrated with the processor 1510 .
  • transceiver 1520 may include but not limited to a transceiver device such as an input/output interface (input/output interface), so as to realize communication between the communication device 1500 and other devices or communication networks.
  • a transceiver device such as an input/output interface (input/output interface), so as to realize communication between the communication device 1500 and other devices or communication networks.
  • each step of the above method may be implemented by an integrated logic circuit of hardware in the processor 1510 or instructions in the form of software.
  • the methods disclosed in the embodiments of the present application may be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in the processor.
  • the software module can be located in a mature storage medium in the field such as random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, register.
  • the storage medium is located in the memory 1530, and the processor 1510 reads the information in the memory 1530, and completes the steps of the above method in combination with its hardware. To avoid repetition, no detailed description is given here.
  • the memory may include a read-only memory and a random access memory, and provide instructions and data to the processor.
  • a portion of the processor may also include non-volatile random access memory.
  • the processor may also store device type information.
  • An embodiment of the present application also provides a computer-readable medium, the computer-readable medium stores program codes, and when the computer program codes are run on a computer, the computer executes the above-mentioned Figure 3, Figure 6 to Figure 9 Or any method in Figure 11 to Figure 13.
  • An embodiment of the present application also provides a chip, including: at least one processor and a memory, the at least one processor is coupled to the memory, and is used to read and execute instructions in the memory, so as to execute the above-mentioned Figure 3, Any method in Figures 6 to 9 or Figures 11 to 13.
  • An embodiment of the present application also provides an automatic driving vehicle, including: at least one processor and a memory, the at least one processor is coupled to the memory, and is used to read and execute instructions in the memory to execute the above-mentioned 3. Any method in Fig. 6 to Fig. 9 or Fig. 11 to Fig. 13 .
  • sequence numbers of the above-mentioned processes do not mean the order of execution, and the execution order of the processes should be determined by their functions and internal logic, and should not be used in the embodiments of the present application.
  • the implementation process constitutes any limitation.
  • a component may be, but is not limited to being, a process running on a processor, a processor, an object, an executable, a thread of execution, a program, and/or a computer.
  • an application running on a computing device and the computing device can be components.
  • One or more components can reside within a process and/or thread of execution and a component can be localized on one computer and/or distributed between two or more computers.
  • these components can execute from various computer readable media having various data structures stored thereon.
  • a component may, for example, be based on a signal having one or more packets of data, such as data from two components interacting with another component between a local system, a distributed system, and/or a network, such as the Internet through a signal interacting with other systems. Communicate through local and/or remote processes.
  • the disclosed systems, devices and methods may be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • the division of the units is only a logical function division. In actual implementation, there may be other division methods.
  • multiple units or components can be combined or May be integrated into another system, or some features may be ignored, or not implemented.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms.
  • the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
  • each functional unit in each embodiment of the present application may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit.
  • the functions described above are realized in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium.
  • the technical solution of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including Several instructions are used to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the methods described in the various embodiments of the present application.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disc and other media that can store program codes. .

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Abstract

一种自动车辆控制的方法和装置，自动车辆控制的方法包括：获取车辆的第一加速度信号和车辆的第二加速度信号；将第一加速度信号输入第一滤波器生成第三加速度信号，且将第二加速度信号输入第二滤波器生成第四加速度信号，第三加速度信号和第四加速度信号的相位延时特性相同；根据第三加速度信号和第四加速度信号确定坡道角度。通过相位延时特性相同的两路加速度信号确定坡道角度，能够消除相位延时特性不同带来的坡道估计误差的问题，从而提高坡道角度估计的实时性和准确性。进而结合目标扭矩的协同控制方法，减小车辆启停过程中的抖动，缩短车辆启停所需时长，提升用户的驾乘体验。

Description

自动车辆控制的方法和装置 技术领域
本申请涉及车辆的自动驾驶领域，更具体地，涉及一种自动车辆控制的方法和装置。
背景技术
随着车辆控制技术的进步，车辆在前进挡行驶过程中，不再需要换挡/踩离合等多余动作，通过驱动和制动的联合控制，即可以实现车辆的起步和停车。在现有技术中，一般通过坡道辅助系统(hill-start assist control，HAC)辅助控制车辆的起停。但是，在智能驾驶领域，HAC尚未与自动驾驶系统深度结合，此外，道路坡度(坡道角度)实时估计的准确性、车辆质量实时估计的准确性、起停过程电机扭矩的准确控制不能得到保证，导致在实际行驶过程中仍然存在溜车或刹车过猛等问题。
因此，如何防止车辆在自动驾驶系统控制下的起停抖动和溜车，是一个亟待解决的问题。
发明内容
本申请提供一种自动车辆控制的方法和装置，能够保证坡道角度估计的实时性，提高坡道角度估计的准确性，从而缩短车辆起停所需时长，减小车辆起停过程中的抖动，避免车辆溜车，进而提升用户的驾乘体验。
第一方面，提供了一种自动车辆控制的方法，该方法可以由车辆执行；或者，也可以由用于车辆的芯片或电路执行；或者，也可以由高级驾驶辅助系统(advanced driving assistance system，ADAS)来执行，本申请对此不作限定。为了便于描述，下面以由车辆上的ADAS执行为例进行说明。
该方法可以包括：获取车辆的第一加速度信号和该车辆的第二加速度信号；将该第一加速度信号输入第一滤波器生成第三加速度信号，且将该第二加速度信号输入第二滤波器生成第四加速度信号，该第三加速度信号和该第四加速度信号的相位延时特性相同；根据该第三加速度信号和该第四加速度信号确定坡道角度。
在一些可能的实现方式中，该第一加速度信号为车速微分信号，该第二加速度信号为车辆纵向加速度信号。对经过滤波处理的两路相位延时特性相同的加速度信号作差及变换，可以获得当前坡道的角度。
本申请实施例提供的自动车辆控制的方法，通过相位延时特性相同的两路加速度信号确定坡道角度，能够消除滤波导致的两路加速度信号相位延时特性不同的问题，进而提高坡道角度估计的实时性和准确性。
结合第一方面，在第一方面的某些实现方式中，该第一滤波器和该第二滤波器为基于该第一加速度信号和该第二加速度信号的相位延时特性优化的滤波器。
具体地，可以分别对第一加速度信号和第二加速度信号进行扫频测试获得两路信号的 伯德图，取两路信号伯德图中的相频特性曲线分别为相频特性曲线A、B；或者也可以通过其他方式获取车速微分第一加速度信号和第二加速度信号的相频特性曲线A和B。
进一步地，分别确定相频特性曲线A的第一相位延时和相频特性曲线B的第二相位延时，根据第一相位延时和第二相位延时确定两个相频特性曲线A和B之间的相位延时差，记为第三相位延时。基于上述第一相位延时、第二相位延时和第三相位延时对第一滤波器和第二滤波器的参数进行优化，以使第一加速度信号和第二加速度信号分别通过优化后的第一滤波器和第二滤波器后，获得的第三加速度信号和第四加速度信号的相位延时特性相同。
结合第一方面，在第一方面的某些实现方式中，该第一滤波器和该第二滤波器为离线处理优化的滤波器。
具体地，基于第一加速度信号和第二加速度信号的相位延时特性对滤波器参数进行优化的过程为离线处理(off-line processing)。
可选地，第一滤波器和第二滤波器可选择常用的数字滤波器，比如巴特沃斯滤波器、切比雪夫I型/II型滤波器和椭圆滤波器等，本申请实施例对此不作限定。
结合第一方面，在第一方面的某些实现方式中，该第一加速度信号为对该车辆的速度进行微分并滤波获得的信号，该第二加速度信号为对该车辆的纵向加速度进行滤波获得的信号。
结合第一方面，在第一方面的某些实现方式中，该方法还包括：根据该坡道角度，基于递推最小二乘法确定该车辆的该质量。
本申请实施例的自动车辆控制的方法，基于准确估计的坡道角度，利用递推最小二乘法估算车辆的质量，能够准确估计车辆质量，从而为控制车辆起停提供更加准确的车辆质量信息。
第二方面，提供了一种自动车辆控制的方法，该方法包括：根据第一传感器采集的第一数据确定第一坡道角度信息，该第一传感器包括陀螺仪传感器；根据第二传感器采集的第二数据确定第二坡道角度信息，该第二传感器包括GPS、激光雷达和摄像装置中的至少一种；根据该第一坡道角度信息和该第二坡道角度信息基于最优估计方法确定坡道角度。
在一些可能的实现方式中，对从陀螺仪传感器获取的陀螺仪角速度信息进行积分确定第一坡道角度信息；根据激光雷达、GPS以及摄像装置等获取的环境信息确定第二坡道角度信息。在一些可能的实现方式中，根据点云数据、GPS数据以及图像数据中的一种或多种确定第二坡道角度信息。
在一些可能的实现方式中，该第二坡道角度信息可以为根据激光雷达、GPS以及摄像装置等传感器信息确定的一个坡道角度；或者，该第二坡道角度信息也可以为根据激光雷达、GPS以及摄像装置等传感器信息分别确定的多个坡道角度。
进一步地，以第一坡道角度信息为预测值，以第二坡道角度信息为观测值，根据卡尔曼滤波融合等最优估计方法确定更为准确的坡道角度信息。
需要说明的是，本申请实施例确定坡道角度所使用的数据来源于与第一方面中的方法使用的传感器不同的传感器，因此，当第一方面中的方法使用的传感器失效时，车辆可以动态切换到使用本申请实施例的方法进行坡道角度估计。
本申请实施例的自动车辆控制的方法，通过从多种传感器获取的数据确定坡道角度，能够保证坡道估计的冗余可靠性。实际使用中，可以根据输入信号的准确性、传感器失效 情况，动态切换坡道估计方案，保证坡道估计结果的可靠性和准确性。
结合第二方面，在第二方面的某些实现方式中，该方法还包括：根据该坡道角度，基于递推最小二乘法确定该车辆的该质量。
本申请实施例的自动车辆控制的方法，当个别传感器失效时，通过剩余的正常工作的传感器仍然能准确估计坡道角度。基于准确估计的坡道角度，利用递推最小二乘法估算车辆的质量，能够准确估计车辆质量，从而为控制车辆起停提供准确的车辆质量信息。
第三方面，提供了一种自动车辆控制的方法，该方法具体可以由ADAS中的起停控制模块执行，该方法包括：获取坡道角度和车辆的质量；根据该质量和该坡道角度确定第一制动扭矩；获取该车辆的当前制动扭矩和当前驱动扭矩；在第一时刻，根据该第一制动扭矩和该当前制动扭矩确定目标制动扭矩，且根据该当前驱动扭矩确定该目标驱动扭矩；该第一时刻为该车辆起步或停车过程中的时刻。
在一些可能的实现方式中，该当前驱动扭矩可以为车辆的实际驱动扭矩T m，该当前制动扭矩可以为车辆的实际制动扭矩T b。
在一些可能的实现方式中，上述第一制动扭矩可以为根据坡道角度和车辆质量计算的第二请求制动扭矩T bReq2。
在一些可能的实现方式中，本申请实施例获取的坡道角度可以为使用第一方面的方法或使用第二方面的方法估计的坡道角度；或者，也可以为车辆的存储器存储的当前道路的坡道角度信息。
在一些可能的实现方式中，本申请实施例获取的车辆的质量可以为使用第一方面的方法或使用第二方面的方法估计的车辆的质量；或者，也可以为车辆的存储器存储的当前车辆的质量。
本申请实施例提供的自动车辆控制的方法，基于准确估计的车辆质量和道路坡度，协同控制目标驱动扭矩和目标制动扭矩，保证目标制动扭矩和目标驱动扭矩能够同时向车辆实际所需的制动扭矩和驱动扭矩快速、平稳过渡，从而在缩短车辆起停所需时长的同时，能够保证车辆起停过程中的平稳性，进而提升用户的驾乘体验。
结合第三方面，在第三方面的某些实现方式中，该根据该质量和该坡道角度确定第一制动扭矩，具体可以为：获取第二制动扭矩，该第二制动扭矩是根据该质量和该坡道角度确定的扭矩；根据该车辆满载时的总质量确定第一系数，根据该坡道角度的估计误差确定第二系数，根据该第一系数、该第二系数、该质量和该坡道角度确定第三制动扭矩；根据该第二制动扭矩和第三制动扭矩确定该第一制动扭矩。
在一些可能的实现方式中，上述第二制动扭矩可以为由PID控制模块根据车辆的质量、坡道角度以及前车加速度、车辆当前速度等信息确定的请求制动扭矩T bReq。在车辆起步过程中，上述第三制动扭矩具体可以为初始制动扭矩T ini；或者，在车辆停车过程中，上述第三制动扭矩也可以为期望制动扭矩T des。
本申请实施例提供的自动车辆控制的方法，通过起停控制模块确定的第三制动扭矩校正车辆起停所需的请求制动扭矩，进而根据校正后得到第一制动扭矩确定目标制动扭矩，在车辆起步过程中能够防止车辆溜车，在车辆停车过程中能够更快的卸载制动扭矩。
结合第三方面，在第三方面的某些实现方式中，该方法还包括：在根据该第一制动扭矩和该当前制动扭矩确定目标制动扭矩之前，根据该第三制动扭矩和该当前驱动扭矩确定第四制动扭矩；该根据该第一制动扭矩和该当前制动扭矩确定目标制动扭矩，具体为：根 据该第一制动扭矩和该当前制动扭矩确定第五制动扭矩；根据该第四制动扭矩和该第五制动扭矩确定目标制动扭矩。
在一些可能的实现方式中，上述第四制动扭矩可以为初始制动扭矩T ini与当前驱动扭矩T m之间的差值δT，或者也可以为最小制动扭矩T blo；上述第五制动扭矩可以为第一目标制动扭矩T bCmd3，或者也可以为第四目标制动扭矩T bCmd3。
本申请实施例的自动车辆控制的方法，根据该第一制动扭矩和该当前制动扭矩确定第五制动扭矩，能够控制目标制动扭矩平稳加载或卸载，减少车辆起步或停车过程中抖动。进一步地，取第四制动扭矩和第五制动扭矩中较大的值为目标制动扭矩，能够防止车辆起步或停车过程中发生溜车，提高行车安全性。
结合第三方面，在第三方面的某些实现方式中，该方法还包括：当该第一时刻为该车辆起步过程中的时刻时，当该坡道角度小于零，或者，该当前驱动扭矩与该第三制动扭矩之间的差值大于或等于第一阈值时，确定该第五制动扭矩为该目标制动扭矩。
本申请实施例的自动车辆控制的方法，在车辆起步过程中，当前驱动扭矩与该第三制动扭矩之间的差值大于或等于第一阈值时，说明车辆已经起步，则无论车辆在上坡道路(坡道角度大于零)还是下坡道路(坡道角度小于零)，均无需对车辆进行额外的制动补偿；或者，若车辆在下坡起步，即需要车辆产生沿下坡方向的速度和/或加速度，此时只需逐步卸载制动扭矩，而无需担心因制动扭矩不足导致的坡道溜车问题，也无需对车辆进行额外的制动补偿。因此，确定第五制动扭矩为目标制动扭矩即可。
结合第三方面，在第三方面的某些实现方式中，该方法还包括：当该第一时刻为该车辆起步过程中的时刻时，当该坡道角度的绝对值小于或等于第二阈值时，或，当该第一制动扭矩小于或等于第二阈值时，确定该目标制动扭矩为零。
本申请实施例的自动车辆控制的方法，在起步过程中，若车辆所处坡道角度小于或等于预设值，或者请求制动扭矩小于或等于预设值，说明此时不施加制动扭矩，车辆也不会发生溜车。因此可以将目标制动扭矩设置为零，以便驱动车辆快速起步。
结合第三方面，在第三方面的某些实现方式中，该方法包括：当该第一时刻为该车辆起步过程中的时刻时，获取第一驱动扭矩，该第一驱动扭矩为根据该质量和该坡道角度确定的扭矩；根据该第一驱动扭矩和该当前驱动扭矩确定该目标驱动扭矩。
具体地，该第一驱动扭矩可以为由PID控制模块根据车辆的质量、坡道角度以及前车加速度、车辆当前速度等信息确定的请求驱动扭矩T mReq。
本申请实施例的自动车辆控制的方法，通过根据该第一驱动扭矩和当前驱动扭矩确定目标驱动扭矩，能够控制目标驱动扭矩平稳增加，减少车辆起步过程中的抖动。
结合第三方面，在第三方面的某些实现方式中，该方法还包括：在根据该第一驱动扭矩和该当前驱动扭矩确定该目标驱动扭矩之前，获取该车辆的当前速度；当该当前速度小于零时，根据该当前速度确定补偿扭矩；根据该第一驱动扭矩、该当前驱动扭矩和该补偿扭矩确定该目标驱动扭矩。
本申请实施例的自动车辆控制的方法，当车辆在起步过程中时，根据车辆当前速度确定是否增加补偿扭矩。当车辆发生背离车头方向的运动时，即当前速度小于零时，增加补偿扭矩，以防止车辆继续溜车。
结合第三方面，在第三方面的某些实现方式中，该方法还包括：当该第一时刻为该车辆停车过程中的时刻时，在根据该第一制动扭矩和该当前制动扭矩确定第五制动扭矩之前， 获取该车辆的当前速度和当前加速度；当该当前速度小于零时，或，当该当前速度大于或等于零，并且该当前加速度大于或等于零时，根据该当前速度确定补偿扭矩；根据该第一制动扭矩、该补偿扭矩和该当前制动扭矩确定该第五制动扭矩。
本申请实施例的自动车辆控制的方法，当车辆在停车过程中时，根据车辆当前速度和/或当前加速度确定是否增加补偿扭矩。当车辆发生背离车头方向的运动时，即当前速度小于零时；或者，车辆朝向车辆方向的运动的加速度仍大于或等于零时，增加补偿扭矩，以防止车辆继续溜车。
结合第三方面，在第三方面的某些实现方式中，该方法还包括：当该第一时刻为该车辆停车过程中的时刻时，确定第一时长，该第一时长为该车辆的当前速度为零所持续的时长；当该第一时长大于或等于第四阈值时，确定该第三制动扭矩为该目标制动扭矩。
本申请实施例的自动车辆控制的方法，当车辆在停车过程中时，当车辆速度为零的第一时长大于或等于预设值时，认为车辆已经停稳，此时将根据车辆质量和坡道角度计算出的第三制动扭矩赋值给目标制动扭矩，以便车辆在下次起步时根据该第三制动扭矩控制车辆起步。
结合第三方面，在第三方面的某些实现方式中，该方法还包括：在获取坡道角度和车辆的质量之前，确定该车辆与最紧邻前车之间的第一距离；该根据该目标制动扭矩和该目标驱动扭矩控制该车辆起步或停车，包括：当该第一距离小于或等于第五阈值时，根据该目标制动扭矩和该目标驱动扭矩控制该车辆停车。
结合第三方面，在第三方面的某些实现方式中，该方法还包括：在该获取坡道角度和车的质量之前，确定该车辆与目的地之间的第二距离；该根据该目标制动扭矩和该目标驱动扭矩控制该车辆起步或停车，包括：当该第二距离小于或等于第六阈值时，根据该目标制动扭矩和该目标驱动扭矩控制该车辆停车。
结合第三方面，在第三方面的某些实现方式中，该方法还包括：在该获取坡道角度和车辆的质量之前，确定最紧邻前车的加速度；该根据该目标制动扭矩和该目标驱动扭矩控制该车辆起步或停车，包括：当该最紧邻前车的加速度大于或等于第七阈值时，根据该目标制动扭矩和该目标驱动扭矩控制该车辆起步。
第四方面，提供了一种自动车辆控制的装置，该装置包括：获取单元，用于获取车辆的第一加速度信号和该车辆的第二加速度信号；处理单元，用于将该第一加速度信号输入第一滤波器生成第三加速度信号，且将该第二加速度信号输入第二滤波器生成第四加速度信号，该第三加速度信号和该第四加速度信号的相位延时特性相同；该处理单元还用于根据该第三加速度信号和该第四加速度信号确定坡道角度。
结合第四方面，在第四方面的某些实现方式中，该装置中的该第一滤波器和该第二滤波器为基于该第一加速度信号和该第二加速度信号的相位延时特性优化的滤波器。
结合第四方面，在第四方面的某些实现方式中，该装置中的该第一滤波器和该第二滤波器为离线处理优化的滤波器。
结合第四方面，在第四方面的某些实现方式中，该处理单元还用于：对该车辆的速度进行微分并滤波获得该第一加速度信号；对该车辆的纵向加速度进行滤波获得该第二加速度信号。
结合第四方面，在第四方面的某些实现方式中，该处理单元还用于：根据该坡道角度，基于递推最小二乘法确定该车辆的该质量。
第五方面，提供了一种自动车辆控制的装置，该装置包括：处理单元，用于根据第一传感器采集的第一数据确定第一坡道角度信息，该第一传感器包括陀螺仪传感器；该处理单元还用于根据第二传感器采集的第二数据确定第二坡道角度信息，该第二传感器包括GPS、激光雷达和摄像装置中的至少一种；该处理单元还用于根据该第一坡道角度信息和该第二坡道角度信息基于最优估计方法确定坡道角度。
在一些可能的实现方式中，该处理单元还用于：根据该坡道角度，基于递推最小二乘法确定该车辆的该质量。
第六方面，提供了一种自动车辆控制的装置，该装置包括：获取单元，用于获取坡道角度和车辆的质量；处理单元，用于根据该质量和该坡道角度确定第一制动扭矩；该获取单元还用于获取该车辆的当前制动扭矩和当前驱动扭矩；该处理单元还用于在第一时刻，根据该第一制动扭矩和该当前制动扭矩确定目标制动扭矩，且根据该当前驱动扭矩确定该目标驱动扭矩；该第一时刻为该车辆起步或停车过程中的时刻。
结合第六方面，在第六方面的某些实现方式中，该获取单元还用于：获取第二制动扭矩，该第二制动扭矩是根据该质量和该坡道角度确定的扭矩；该处理单元还用于：根据该车辆满载时的总质量确定第一系数，根据该坡道角度的估计误差确定第二系数，根据该第一系数、该第二系数、该质量和该坡道角度确定第三制动扭矩；根据该第二制动扭矩和第三制动扭矩确定该第一制动扭矩。
结合第六方面，在第六方面的某些实现方式中，该处理单元还用于：在该根据该第一制动扭矩和该当前制动扭矩确定目标制动扭矩之前，根据该第三制动扭矩和该当前驱动扭矩确定第四制动扭矩；该根据该第一制动扭矩和该当前制动扭矩确定目标制动扭矩，包括：根据该第一制动扭矩和该当前制动扭矩确定第五制动扭矩；根据该第四制动扭矩和该第五制动扭矩确定目标制动扭矩。
结合第六方面，在第六方面的某些实现方式中，该处理单元还用于：当该坡道角度小于零，或者，该当前驱动扭矩与该第三制动扭矩之间的差值大于或等于第一阈值时，确定所述第五制动扭矩为所述目标制动扭矩。
结合第六方面，在第六方面的某些实现方式中，该处理单元还用于：当该坡道角度的绝对值小于或等于第二阈值时，或，当该第一制动扭矩小于或等于第二阈值时，确定该目标制动扭矩为零。
结合第六方面，在第六方面的某些实现方式中，该获取单元还用于：获取第一驱动扭矩，该第一驱动扭矩为根据该质量和该坡道角度确定的扭矩；该处理单元还用于：根据该第一驱动扭矩和该当前驱动扭矩确定该目标驱动扭矩。
结合第六方面，在第六方面的某些实现方式中，该处理单元还用于：在该根据该第一驱动扭矩和该当前驱动扭矩确定该目标驱动扭矩之前，获取该车辆的当前速度；当该当前速度小于零时，根据该当前速度确定补偿扭矩；该根据该第一驱动扭矩和该当前驱动扭矩确定该目标驱动扭矩，包括：根据该第一驱动扭矩、该当前驱动扭矩和该补偿扭矩确定该目标驱动扭矩。
结合第六方面，在第六方面的某些实现方式中，该处理单元还用于：在该根据该第一制动扭矩和该当前制动扭矩确定第五制动扭矩之前，获取该车辆的当前速度和当前加速度；当该当前速度小于零时，或，当该当前速度大于或等于零，并且该当前加速度大于或等于零时，根据该当前速度确定补偿扭矩；该根据该第一制动扭矩和该当前制动扭矩确定第五 制动扭矩，包括：根据该第一制动扭矩、该补偿扭矩和该当前制动扭矩确定该第五制动扭矩。
结合第六方面，在第六方面的某些实现方式中，该处理单元还用于：确定第一时长，该第一时长为该车辆的当前速度为零所持续的时长；当该第一时长大于或等于第四阈值时，确定该第三制动扭矩为该目标制动扭矩。
结合第六方面，在第六方面的某些实现方式中，该处理单元还用于：在该获取坡道角度和车辆的质量之前，确定该车辆与最紧邻前车之间的第一距离；该根据该目标制动扭矩和该目标驱动扭矩控制该车辆起步或停车，包括：当该第一距离小于或等于第五阈值时，根据该目标制动扭矩和该目标驱动扭矩控制该车辆停车。
结合第六方面，在第六方面的某些实现方式中，该处理单元还用于：在该获取坡道角度和车辆的质量之前，确定该车辆与目的地之间的第二距离；该根据该目标制动扭矩和该目标驱动扭矩控制该车辆起步或停车，包括：当该第二距离小于或等于第六阈值时，根据该目标制动扭矩和该目标驱动扭矩控制该车辆停车。
结合第六方面，在第六方面的某些实现方式中，该处理单元还用于：在该获取坡道角度和车辆的质量之前，确定最紧邻前车的加速度；该根据该目标制动扭矩和该目标驱动扭矩控制该车辆起步或停车，包括：当该最紧邻前车的加速度大于或等于第七阈值时，根据该目标制动扭矩和该目标驱动扭矩控制该车辆起步。
第七方面，提供了一种自动车辆控制的装置，该装置包括：存储器，用于存储程序；处理器，用于执行存储器存储的程序，当存储器存储的程序被执行时，处理器用于执行上述第一方面至第三方面任一种可能实现方式中的方法。
第八方面，提供了一种自动驾驶车辆，该车辆包括上述第三方面至第七方面任一种可能实现方式中的装置。
第九方面，提供了一种计算机程序产品，上述计算机程序产品包括：计算机程序代码，当上述计算机程序代码在计算机上运行时，使得计算机执行上述第一方面至第三方面任一种可能实现方式中的方法。
需要说明的是，上述计算机程序代码可以全部或部分存储在第一存储介质上，其中第一存储介质可以与处理器封装在一起的，也可以与处理器单独封装，本申请实施例对此不作具体限定。
第十方面，提供了一种计算机可读存储介质，上述计算机可读存储介质存储有程序代码，当上述计算机程序代码在计算机上运行时，使得计算机执行上述第一方面至第三方面任一种可能实现方式中的方法。
第十一方面，提供了一种芯片系统，该芯片系统包括处理器，用于调用存储器中存储的计算机程序或计算机指令，以使得该处理器执行上述第一方面至第三方面任一种可能实现方式中的方法。
结合第十一方面，在一种可能的实现方式中，该处理器通过接口与存储器耦合。
结合第十一方面，在一种可能的实现方式中，该芯片系统还包括存储器，该存储器中存储有计算机程序或计算机指令。
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图1是本申请实施例提供的一种自动车辆控制的装置的示意性结构图；
图2是本申请实施例提供的一种自动车辆控制的方法应用的一种系统架构示意图；
图3是本申请实施例提供的一种自动车辆控制的方法的示意性流程图；
图4是本申请实施例提供的一种自动车辆控制的方法的技术效果示意图；
图5是本申请实施例提供的一种自动车辆控制的方法的技术效果示意图；
图6是本申请实施例提供的又一种自动车辆控制的方法的示意性流程图；
图7是本申请实施例提供的再一种自动车辆控制的方法的示意性流程图；
图8是本申请实施例提供的再一种自动车辆控制的方法的示意性流程图；
图9是本申请实施例提供的再一种自动车辆控制的方法的示意性流程图；
图10是本申请实施例提供的一种自动车辆控制的方法的技术效果示意图；
图11是本申请实施例提供的一种自动车辆控制的方法的示意性流程图；
图12是本申请实施例提供的一种自动车辆控制的方法的示意性流程图；
图13是本申请实施例提供的一种自动车辆控制的方法的示意性流程图；
图14是本申请实施例提供的一种自动车辆控制的装置的示意性框图；
图15是本申请实施例提供的一种自动车辆控制的装置的示意性框图。
具体实施方式
下面将结合附图，对本申请中的技术方案进行描述。为了便于理解，下文结合图1，以智能驾驶的场景为例，介绍本申请实施例适用的场景。
图1是本申请实施例提供的一种自动车辆控制的装置的示意性结构图。
在一种可能的实施方式中，可以将车辆100配置为完全或部分自动驾驶模式。例如：车辆100可以通过感知系统120获取其周围的环境信息，并基于对周边环境信息的分析得到自动驾驶策略以实现完全自动驾驶，或者将分析结果呈现给用户以实现部分自动驾驶。将车辆100配置为完全或部分地自动驾驶模式。
车辆100可包括各种子系统，例如行进系统110、感知系统120和控制系统130。可选地，车辆100可包括更多或更少的子系统，并且每个子系统可包括多个元件。另外，车辆100的每个子系统和元件可以通过有线或者无线互连。
感知系统120可包括感测关于车辆100周边的环境的信息的若干种传感器。例如，感知系统120可包括全球定位系统121(全球定位系统可以是GPS系统，也可以是北斗系统或者其他定位系统)、惯性测量单元(inertial measurement unit，IMU)122、激光雷达123、毫米波雷达124、超声雷达125以及摄像装置126中的一种或者多种。
行进系统110可包括为车辆100提供动力运动的组件。在一个实施例中，行进系统110可包括引擎111、传动装置112和车轮/轮胎113。引擎111将能量源转换成机械能量，传动装置112可以将来自引擎111的机械动力传送到车轮113。
控制系统130为控制车辆100及其组件的操作。控制系统130可包括传感器融合算法单元131、协同控制单元132、溜车补偿单元133和驱/制动单元134。在本申请实施例中，控制系统130中的传感器融合算法单元131可以根据感知系统120感测的环境信息，动态估计坡道角度和车辆质量。协同控制单元132可以根据车辆的实际驱动扭矩和实际制动扭矩，结合估计的坡道角度及车辆质量，计算目标驱动扭矩/制动扭矩，并将结果输入驱/制动控制单元134，以实现驱动/制动扭矩的平稳加载和卸载，完成车辆在起步或停车过程中扭矩的平稳过渡。溜车补偿单元133可以根据车辆的实时速度及加速度，增加附加制动/ 驱动扭矩，以防止车辆在起步或停车过程中发生溜车。驱/制动控制单元134用于执行目标驱动/制动扭矩，并将实际驱动/制动扭矩反馈给协同控制单元132和溜车补偿单元133。具体地，驱/制动控制单元可以包括控制驱动电机和液压系统的部件，控制驱动电机根据目标驱动扭矩输出驱动扭矩，控制液压系统根据目标制动扭矩输出制动扭矩。在一些可能的实现方式中，驱/制动控制单元还可以包括其他控制部件，本申请实施例对此不作限定。
车辆100的部分或所有功能受计算平台150控制。计算平台150可包括至少一个处理器151，处理器151可以执行存储在例如存储器152这样的非暂态计算机可读介质中的指令153。在一些实施例中，计算平台150还可以是采用分布式方式控制车辆100的个体组件或子系统的多个计算设备。
处理器151可以是任何常规的处理器，诸如中央处理单元(central processing unit，CPU)。替选地，处理器151还可以包括诸如图像处理器(graphic process unit，GPU)，现场可编程门阵列(field programmable gate array，FPGA)、片上系统(system on chip，SOC)、专用集成芯片(application specific integrated circuit，ASIC)或它们的组合。
除了指令153以外，存储器152还可存储数据，例如道路地图、路线信息，车辆的位置、方向、速度等数据。这些数据可在车辆100在自主、半自主和/或手动模式中操作期间被车辆100和计算平台150使用。
计算平台150可基于从各种子系统(例如，感知系统120)接收的输入来控制车辆100的功能。例如，计算平台150可利用来自感知系统120中的全球定位系统121确定的车辆速度和加速度信息，实时计算车辆的质量和道路的坡度。
在一些可能的实现方式中，上述这些组件中的一个或多个可与车辆100分开安装或关联。例如，存储器152可以部分或完全地与车辆100分开存在。上述组件可以按有线和/或无线方式来通信地耦合在一起。
在一些可能的实现方式中，上述组件只是一个示例，实际应用中，上述各个模块中的组件有可能根据实际需要增添或者删除。
在一些可能的实现方式中，上述车辆100可以包括一种或多种不同类型的交通工具，也可以包括一种或多种不同类型的在陆地(例如，公路，道路，铁路等)，水面(例如：水路，江河，海洋等)或者空间上操作或移动的运输工具或者可移动物体。例如，车辆可以包括汽车，自行车，摩托车，火车，地铁，飞机，船，飞行器，机器人或其它类型的运输工具或可移动物体等，本申请实施例对此不作限定。
图2示出了本申请实施例的自动车辆控制的方法的一种系统架构示意图，如图2所示包括感知模块、数据模块和控制模块，图2所示的系统可以应用于智能驾驶车辆等支持的起步和停车控制场景中。
感知模块可以是图1中的感知系统120所包括的多个传感器中的一个或多个，具体可以包括全球定位系统121、IMU122、激光雷达123、毫米波雷达124、超声雷达125以及摄像装置126等。数据模块和控制模块可以是图1中的计算平台150中的一个或多个，数据模块也可以是图1中控制系统130所包含的传感器融合算法单元134，控制模块也可以是图1中控制系统130所包括协同控制单元132、溜车补偿单元133和驱/制动控制单元134。
在一些可能的实现方式中，感知模块可以将全球定位系统121如GPS、激光雷达123及摄像装置126等获取的环境信息输入数据模块，数据模块中的传感器融合算法单元134 可以根据上述环境信息确定当前道路的坡道角度信息。
在一些可能的实现方式中，感知模块可以将获取的车辆的速度信号、加速度信息和陀螺仪角速度信息以及车辆反馈的实际驱动/制动扭矩等输入数据模块和控制模块。数据模块对车辆的速度、加速度和角速度信息进行分析和处理，得到实时的坡道角度信息和车辆质量信息。进一步地，数据模块将上述坡道角度信息和车辆质量信息输入控制模块。
在车辆起步或停车过程中，控制模块中的PID控制单元根据从感知模块获取的环境信息如车辆当前的速度和加速度、最紧邻前车加速度、与最紧邻前车的距离、距离目的地的距离等，以及从数据模块获取的估计的坡道角度和车辆质量，计算出请求驱动/制动力矩，并将其输入起停控制单元。起停控制单元结合坡道角度信息和车辆质量信息计算目标驱动/制动扭矩，控制目标驱动扭矩逐步卸载或增加到请求驱动扭矩，或者控制目标制动扭矩卸载或增加到请求制动扭矩。在上述过程中，控制模块还可以对目标驱动/制动扭矩进行协同控制，以保证车辆在起步或停车过程中扭矩的平稳过渡，减少车辆在起停过程中的抖动，实现车辆的无感起停。在一些可能的实现方式中，控制模块还可以结合车辆的实际速度和/或加速度信息，控制附加驱动/制动扭矩的大小，以防止车辆在坡度不为零的道路上发生溜车。
如前所述，影响车辆起步和停车过程中平稳性的因素主要包括坡道角度估计的准确性、车辆质量估计的准确性以及起停过程中电机扭矩的控制情况。
目前常用的坡道角度估计方案是利用实时车速信号和IMU加速度信号进行处理。一方面，通过对实时车速信号进行微分可以得到车辆纵向的运动加速度a x；另一方面，IMU加速度a t是车辆纵向的运动加速度a x和受坡道影响的重力加速度g的纵向分量的叠加。将上述两个加速度信号作差，可以获得车辆在坡道上重力加速度沿车纵向的分量g x，结合受力分析，将该差值作反正弦变换即可得到坡道角度s，即s＝arcsin(g x/g)。在上述方法中，涉及对车速进行微分得到加速度的操作，由于对实际车速信号做微分将不可避免将产生高频毛刺噪声，所以需要对其进行滤波处理，而一旦采用滤波器将会对结果带来一定的延时，因此车速微分得到的加速度信号必然存在时域的延时。该延时特性和也进行了滤波处理的IMU加速度信号的延时特性难以保证一致，所以当二者作差时，将带来较大的坡道估计误差。上述误差还可能影响车辆质量估计的准确性。
在保证坡道估计和质量估计准确性的情况下，如何控制车辆的驱动/制动扭矩快速、平稳的加载和卸载，以防止车辆起停过程中抖动和溜车，也是亟待解决的问题。现有技术中，控制车辆起步时，一般先保持制动扭矩恒定不变，逐渐施加驱动扭矩，当实际驱动扭矩达到目标值，再卸载驱动扭矩；或者，先将制动扭矩减小至0，再逐渐施加驱动扭矩，这样在调节扭矩的过程耗时较长，无法满足高阶自动驾驶(autonomous driving solution，ADS)系统快速起步的需求。
鉴于此，本申请实施例提供了一种自动车辆控制的方法和装置，能够准确估计坡道角度和车辆质量，基于准确估计的坡度和质量，结合车辆当前的实际驱动扭矩和制动扭矩，协同调节目标驱动/制动扭矩，以实现车辆起步或停车过程中实际输出扭矩快速、平稳地过渡到车辆计算的起步或停车所需扭矩，在减小车辆起停过程中的抖动的同时，还能够缩短车辆起停所需时长，提升用户的驾乘体验。此外，车辆行驶过程中，可能会出现传感器失效故障的情况，为提升坡道估计系统的可靠性和稳定性，本申请还提供一种坡道角度估计的冗余备用策略，以在传感器信号异常时，能够进行坡度信号的在线切换，保证坡道角 度估计的准确性，进而保证车辆起步或停车过程中扭矩的平稳过渡，提升用户的驾乘体验。
图3示出了本申请实施例提供的一种自动车辆控制的方法300的示意性流程图。具体地，图3示出了基于相位延时特性优化方法实时估计坡道角度的流程，该流程所示方法可以由图1所示的装置执行，也可以应用于图2所示的系统，本申请实施例不限于此。图3示出的自动车辆控制的方法的步骤或操作仅是示例，本申请实施例还可以执行其他操作或者图3中的各个操作的变形。该方法300包括：
S301a，获取车速微分信号的相频特性曲线A。
具体地，获取车辆的实时车速信号，对车速进行微分获得车辆纵向的运动加速度信号，即不含重力加速度沿车辆纵向分量的加速度信号。在一些可能的实现方式中，可以通过轮速传感器获取的车轮转速计算上述实时车速信号；或者可以通过车辆底盘的相关车速传感器反馈的信息获取实时车速信号，本申请实施例对此不作限定。
由于实时车速信号波动较大，即实时车速随时间变化曲线不平滑，因此，对实时车速信号求导的过程中，将不可避免地产生高频毛刺噪声，所以需要对上述车辆纵向的运动加速度信号进行滤波处理，以滤掉高频毛刺噪声。进一步地，对滤波处理后的车速微分信号，即滤波处理后的车辆纵向的运动加速度信号进行傅里叶变换，以获得车速微分信号的相频特性曲线A和幅频特性曲线A’。
S301b，获取车辆纵向加速度信号的相频特性曲线B。
在一些可能的实现方式中，对车辆纵向加速度信号进行滤波处理，以滤掉高频毛刺噪声。进而对滤波处理后的车辆纵向加速度进行傅里叶变换，以获得车辆纵向加速度信号的相频特性曲线B和幅频特性曲线B’。
具体地，可以分别对车速微分信号和车辆纵向加速度信号进行扫频测试获得两路信号的伯德图，取两路信号伯德图中的相频特性曲线分别为相频特性曲线A、B；或者通过其他方式获取车速微分信号和车辆纵向加速度信号的相频特性曲线A和B，本申请实施例对比不作限定。
应理解，车辆纵向加速度为车辆纵向的运动加速度和受坡道影响的重力加速度沿车辆纵向分量的叠加。在一些可能的实现方式中，可以通过IMU加速度传感器获取上述车辆纵向加速度信号，也可以通过其他加速度传感器获取上述车辆纵向加速度信号，本申请实施例对此不作限定。
S302，确定相频特性曲线A和B的相位延时特性，基于相位延时特性分别优化滤波器A和B。
具体地，分别确定相频特性曲线A的第一相位延时和相频特性曲线B的第二相位延时，根据第一相位延时和第二相位延时确定两个相频特性曲线A和B之间的相位延时差，记为第三相位延时。
应理解，相频特性曲线A的相位延时可以表示为：
Figure PCTCN2021129753-appb-000001
其中，ω A为频率，θ(ω A)为相频响应，即频率分量经过滤波器后的相位变化，P(ω A)代表频率分量经过滤波器时的延时。
进一步地，基于两路信号的相位延时特性对滤波器A和B的参数进行优化，以使上 述两路信号在分别经过滤波器A和滤波器B后的相位延时特性能够保持一致，即两路信号在分别经过滤波器A和滤波器B滤波后，相位角在时间上的滞后特性相同。在一些可能的实现方式中，根据第一相位延时和第三相位延时对滤波器A的参数进行优化，根据第二相位延时和第三相位延时对滤波器B的参数进行优化。在一些可能的实现方式中，在优化滤波器参数过程中，可以采用粒子群优化算法(particle swarm optimization，PSO)、遗传算法(genetic algorithm，GA)等智能优化算法，本申请实施例对此不作限定。
S303a，车速微分信号通过滤波器A得到加速度信号a。
S303b，车辆纵向加速度信号通过滤波器B得到加速度信号b。
S304，加速度信号a1与b1作差得到车辆在坡道上重力加速度沿车辆纵向的分量c。
具体地，c＝a1-b1。
应理解，加速度信号b1为车辆纵向的运动加速度(即车速微分信号)a1与受坡道影响的重力加速度沿车辆纵向分量g x的叠加。当车辆在下坡时，b1＝a1+g x，此时c＝-g x；当车辆在爬坡(上坡)时，b1＝a1-g x，此时c＝g x。
S305，对加速度信号c作反正弦函数变换得到估计的坡道角度信息。
具体地，估计的道路的角度s＝arcsin(c/g)，其中，g为重力加速度。即，车辆下坡时，估算出的角度为负值；车辆上坡时，估算出的角度为正值。
需要说明的是，本申请实施例中S301a、S301b和S302为离线处理(off-line processing)，即并非在车辆行驶过程中对滤波器A和滤波器B实时优化，而是根据存储的车辆微分信号和车辆纵向加速度信号对滤波器A和B的参数进行优化后，用于车辆行驶过程的坡道估计。本申请实施例中S303a、S303b和S304为在线处理(on-line processing)，具体地，车辆行驶时，车速微分信号和车辆纵向加速度信号分别、实时地通过优化过的滤波器A和B，获得加速度信号a1和b1，进而根据加速度a1和b1实时估计坡道角度。
本申请实施例涉及的滤波器可选择常用的数字滤波器，比如巴特沃斯滤波器、切比雪夫I型/II型滤波器和椭圆滤波器等，本申请实施例对此不作限定。
在一些可能的实现方式中，车辆估算出当前所处道路的坡道角度后，可以将该坡道角度信息存储在历史信息中，以便车辆下次在此道路起步和/或停车时使用。
本申请实施例的自动车辆控制的方法，通过基于车辆微分信号和车辆纵向加速度信号的相位延时特性，进行滤波器参数优化，使得上述两路信号分别通过优化后的滤波器后，相位延时能够保持一致，进而提高估计的坡道角度的准确性。如图4中所示，图4中的(a)为未经优化的两路信号的伯德图，图4中的(b)为经过基于两路信号相位延时特性优化的滤波器的两路信号的伯德图，可见两路信号的相位延时特性的一致性明显提升。图5为通过实际路测数据验证的结果，如图5所示，滤波器优化之后的坡道估计结果延时最大可提高大约500ms。
图6示出了本申请实施例提供的一种自动车辆控制的方法600的示意性流程图。具体地，图6示出了一种作为冗余策略的坡道角度估计的流程，该流程所示方法可以由图1所示的装置执行，也可以应用于图2所示的系统，本申请实施例不限于此。该方法600包括：
S601a，对陀螺仪角速度积分得到第一坡道角度信息。
在一些可能的实现方式，陀螺仪角速度信息来源于IMU陀螺仪传感器，也可以来源其他陀螺仪传感器，本申请实施例对此不作限定。
S601b，通过激光雷达、GPS以及摄像装置等确定第二坡道角度信息。
具体地，车辆根据激光雷达、GPS以及摄像装置等获取的环境信息确定第二坡道角度信息。在一些可能的实现方式中，根据点云数据、GPS数据以及图像数据中的一种或多种确定第二坡道角度信息。
在一些可能的实现方式中，该第二坡道角度信息可以为根据激光雷达、GPS以及摄像装置等传感器信息确定的一个坡道角度；或者，该第二坡道角度信息也可以为根据激光雷达、GPS以及摄像装置等传感器信息分别确定的多个坡道角度。
S602，基于卡尔曼滤波融合得到估计的坡道角度信息。
具体地，将第一坡道角度信息作为预测值，将第二坡道角度信息作为观测值，考虑陀螺仪传感器的bias偏置，构造如下角度积分计算模型方程：
Figure PCTCN2021129753-appb-000002
Figure PCTCN2021129753-appb-000003
其中，Angle t为t时刻估计的坡道角度，bias t为t时刻陀螺仪零偏bias，Gyro为陀螺仪测量角速度，z为其他传感器测量或估计的坡道角度，比如通过激光雷达、GPS以及摄像装置等获取坡道角度。
基于上述角度模型方程，应用卡尔曼滤波递推方程进行融合计算即可得到估算的坡道角度。应理解，本申请实施例也可以通过其他最优估计方法，如递推最小二乘法，以第一坡道角度信息为预测值，以第二坡道角度信息为观测值，确定更为准确的当前坡道角度，本申请实施例对此不作限定。
在一些可能的实现方式中，车辆估算出当前所处道路的坡道角度后，可以将该坡道角度信息存储在历史信息中，以便车辆下次在此道路起步和/或停车时使用。
本申请实施例的自动车辆控制的方法，通过陀螺仪和激光视觉等传感器获取的信息确定坡道角度信息，与方法300中确定坡道角度信息所需信息的来源(车速传感器和加速度传感器)不同，即方法300和方法400估计坡道角度依赖不同传感器源，因此可保证坡道估计的冗余可靠性。实际使用中，可以根据输入信号的准确性、传感器失效情况，动态切换坡道估计方案，保证坡道估计结果的可靠性和准确性。
图7示出了本申请实施例提供的一种自动车辆控制的方法示意性流程图。具体地，图7示出了实时估计车辆质量的流程，该流程所示方法可以应用于图1所示的应用场景，也可以应用于图2所示的系统，本申请实施例不限于此。图7示出的自动车辆控制的方法的步骤或操作仅是示例，本申请实施例还可以执行其他操作或者图7中的各个操作的变形。该方法具体为：
获取车辆纵向加速度、估计的坡道角度，以及车辆当前时刻的实际制动力和/或驱动力，根据上述信息，利用递推最小二乘法估计车辆质量。
具体地，构建车辆纵向动力学模型为：
F x＝ma x+0.5C dA v x 2+mg(sinθ+fcosθ)
其中，F x为车辆的纵向驱动力，m为待估计的车辆质量，a x为车辆纵向加速度，C d为风阻系数，A为迎风面积，v x为车辆纵向速度，g为重力加速度，θ为路面坡度，f为路 面滚阻系数。应理解，上述物理量中除了待估计的车辆质量m以外，其他都为已知量。
记有效驱动力F fx＝F x-0.5C dA v x 2-mg(sinθ+fcosθ)，则F fx＝ma x，即有效驱动力F fx和车辆纵向加速度ma x的比值即为车辆质量。考虑到实际信号存在噪声波动，利用递推最小二乘的方法对上述比值进行计算，以获得估计的车辆质量。
在一些可能的实现方式中，估算出车辆的质量后，车辆可以存储该质量信息，以便车辆下次起步和/或停车时使用。
本申请实施例的自动车辆控制的方法，基于准确估计的坡道角度，利用递推最小二乘法估算车辆的质量，能够准确估计车辆质量，从而为控制车辆起停提供更加准确的车辆质量信号。
图8示出了本申请实施例提供的一种自动车辆控制的方法800的示意性流程图。具体地，图8示出了车辆起步过程中驱动和制动扭矩协同控制的流程，该流程所示方法可以由图1所示的装置执行，图8中分别示出了协同控制模块和溜车补偿模块，可以分别对应于图1中的协同控制单元132和溜车补偿单元133；该流程所示方法也可以应用于图2所示的系统，具体地，可以由图2中的起停控制单元执行。图8示出的自动车辆控制的方法的步骤或操作仅是示例，本申请实施例还可以执行其他操作或者图8中的各个操作的变形。该方法800包括：
S811，获取请求制动扭矩T bReq、实际驱动扭矩T m、实际制动扭矩T b和估计的车辆质量m及坡道角度s。
具体地，估计的坡道角度s可以为根据方法300得到的结果，也可以为根据方法600得到的结果；估计的车辆质量m可以为根据方法700得到的结果。在一些可能的实现方式中，上述估计的车辆质量m及坡道角度s也可以是通过上述方法以外其他方法获得的，例如，车辆行驶至道路后，车辆感知系统根据周围环境信息识别出该道路为车辆历史信息中保存的道路后，可以调用历史信息中保存的该道路的坡道角度；或者，车辆起步时，根据最近一次停车时在历史记录中保存的坡道角度信息确定当前坡道角度s。进一步地，根据车辆估计出的车辆质量m及坡道角度s，结合车辆当前时刻的速度和/或加速度、以及最紧邻前车加速度等信息计算请求制动扭矩T bReq，该步骤可以由图2中的PID控制单元执行；应理解，请求制动扭矩T bReq为车辆在当前状态下起步所需的制动扭矩。计算出的实际驱动扭矩T m为扭矩传感器反馈的当前时刻车辆的驱动系统实际输出的扭矩，实际制动扭矩T b为车辆传感器反馈的当前时刻车辆的制动系统实际输出的扭矩。
在一些可能的实现方式中，起停控制单元可以在接收到指令后开始执行S811。具体地，上述指令可以为车辆的用户接口输入的起步指令；或者，上述指令可以为与车辆感知系统识别到的最紧邻前车加速度相关的指令，例如当最紧邻前车的加速度大于获得等于系统预设阈值时，向起停控制单元发送的起步指令。上述指令也可以为其他控制车辆起步的指令，本申请实施例对此不作限定。
S812，计算初始制动扭矩T ini，确定第二请求制动扭矩T bReq2。
具体地，T ini＝mg*a*(b+sin(|s|))*R，其中，m、s为分别为估计的车辆质量和坡道角度，R为轮胎半径，a为质量放大系数，b为坡度偏离系数。上述初始制动扭矩T ini为车辆处于起步前的静止状态时，为了克服车辆自身重力沿坡道向下分量导致的溜车所需的制动扭矩。
在一些可能的实现方式中，上述T ini也可以为车辆的历史记录中存储的车辆最近一次停车时期望制动扭矩T des(即车辆停稳时的实际驱动扭矩T b)。
需要说明的是，根据车辆满载时的总质量与车辆整备质量的比值确定放大系数a，其中，车辆的总质量是指车辆装备齐全，并按规定装满客(包括驾驶员)、货物时的重量，车辆整备质量是指车辆在正常条件下准备行驶时，尚未载人(包括驾驶员)、载物时的空车质量。例如，车辆满载时的总质量为m 1，车辆整备质量为m 2，则a＝m 1/m 2。应理解，a为大于1的常数。根据坡道角度估计的系统误差确定坡道偏离系数b，例如，坡道角度估计误差为0.5～0.8％，则b可取1.005～1.008中的任一值。
在一些可能的实现方式中，上述质量放大系数a还可以根据车内乘客数量确定，具体方法可以为：车辆的感知系统(具体可以为摄像装置)识别到车辆内部用户数量为n，则a＝m 1/(m 2+n·m 0)。其中，m 0为车辆默认的用户体重，该值具体可为80kg，本申请实施例对此不作限定。
应理解，车辆起步过程中时，若在上坡道路，随着制动扭矩的逐步卸载，驱动扭矩逐步增加，在制动扭矩卸载到0时，保证驱动力能平衡坡道阻力；若在下坡起步，根据请求加速度的大小，判断是否完全卸载制动扭矩，以及是否增加驱动扭矩，以保证平稳起步。
因此，进一步确定第二请求制动扭矩为T bReq2＝min(T bReq，T ini)，即，取T bReq和T ini中较小的赋值给T bReq2，若车辆为坡道起步，则通过T bReq2＝min(T bReq，T ini)逐步卸载制动扭矩；若车辆为平路起步，则请求制动扭矩为0，即，不需要给车辆施加制动扭矩。
S813，计算第一目标制动扭矩T bCmd1。
具体地，根据第二请求制动扭矩T bReq2计算第一目标制动扭矩：
T bCmd1＝T bReq2*c+(1-c)*T b，其中，c为指数衰减系数。
指数衰减系数c为小于或等于1的常数，c越大，目标制动扭矩向请求制动扭矩的过渡越快，车辆越容易发生抖动；c越小，则目标制动扭矩向请求制动扭矩的过渡越慢，起步所需时长过长，效率较低。因此，需要结合实际情况合理设定c的值。
在一些可能的实现方式中，上述系数a、b和c均为标定常数，可以根据实际路况、车辆类型等进行设定，本申请实施例对上述系数具体数值不作限定。
S814，判断T m-T ini≥T gap或s＜0是否成立。
具体地，T gap为第一预设值，表示车辆起步所需的最小驱动扭矩。
若T m-T ini≥T gap成立，说明车辆已经起步，无论车辆在上坡道路(s＞0)还是下坡道路(s＜0)，均无需对车辆进行额外制动，则继续执行S815；或者，若s＜0，说明车辆在下坡起步，即需要车辆产生沿下坡方向的速度和/或加速度，此时只需逐步卸载制动扭矩，而无需担心因制动扭矩不足导致的坡道溜车问题，因此可以继续执行S815。只有当s≥0且T m-T ini＜T gap，说明在上坡起步的情况下，实际驱动扭矩T m还不足以驱动车辆起步。此时，为了防止车辆自身重力导致的溜车，需要保证制动扭矩足以平衡驱动扭矩与车辆自身重力产生的扭矩之间的差值，因此需继续执行S816。
在一些可能的实现方式中，S814中可以只判断T m-T ini≥T gap是否成立，若成立，则继续执行S815，若不成立，则继续执行S816。也就是说，无论车辆在上坡道路(s＞0)还是下坡道路(s＜0)起步，只要实际驱动扭矩T m与为克服车辆自身重力所需的扭矩T ini之间的差值大于或等于第一预设值，即车辆起步所需的最小驱动扭矩T gap时，便无需对车辆进行制动；当上述差值小于T gap时，则计算T ini与T m之间的差值。
S815，令δT＝0。
S816，令δT＝T ini-T m。
S817，确定第二目标制动扭矩T bCmd2＝max(T bCmd1，δT)。
具体地，为降低车辆起步过程中的抖动，以及保证行车安全，取T bCmd1和δT中较大的值为T bCmd2。
S818，判断|s|≤s min或T bReq≤T min是否成立。
具体地，s min为第二预设值，即车辆制动扭矩为0时也不会发生溜车的坡道最小角度；T min为第三预设值，为保证车辆不会发生溜车的最小安全制动扭矩。
若|s|≤s min或T bReq≤T min成立，则继续执行S819；若不成立，则继续执行S820。
S819，令T bCmd2＝0。
若车辆所处坡道角度小于或等于第二预设值或第二请求制动扭矩小于或等于第三预设值，说明此时不施加制动扭矩，车辆也不会发生溜车，因此可以将第二目标制动扭矩设置为0。
S820，令T bCmd＝T bCmd2。
将第二目标制动扭矩T bCmd2赋值给目标制动扭矩T bCmd。
S821，获取请求驱动扭矩T mReq、实际驱动扭矩T m和车速V s。
其中，根据车辆估计出的车辆质量m及坡道角度s，结合车辆当前时刻的速度和/或加速度计算请求驱动扭矩T mReq，该步骤可以由图2中的PID控制单元执行；车速V s为速度传感器反馈的车辆纵向速度，V s＞0代表车辆向前行驶，V s＜0代表车辆发生了向后移动，即发生了溜车。
S822，计算第一目标驱动扭矩T mCmd1。
具体地，T mCmd1＝T mReq*c+(1-c)*T m。
S823，判断车速V s＜0是否成立。
若V s＜0成立，则继续执行S824；若不成立，则继续执行S826。
S824，计算补偿驱动扭矩T add。
车辆起步过程中发生了溜车，则需要增加补偿驱动扭矩，以防止车辆继续溜车。
具体地，T add＝T add+T 0+T s*V s，其中，式子右侧第一项的T add代表上一次循环增加的补偿驱动扭矩，应理解，T add初始值为0；T 0为驱动扭矩常数，即每次循环增加的固定的驱动扭矩；T s为速度比例系数，溜车速度越快，则上述式子右侧第三项的数值越大。T 0和T s均为系统预设值，可以根据实际路况、车辆类型等进行设定。
S825，令T mCmd1＝T mCmd1+T add。
为了防止车辆继续溜车，在第一目标驱动扭矩T mCmd1中增加补偿驱动扭矩T add。
S826，令T mCmd＝T mCmd1。
若S823中判断V s＜0，则将S825中的第一目标驱动扭矩T mCmd1的值赋给目标驱动扭矩T mCmd；若S823中判断V s≥0，则将S822中的第一目标驱动扭矩T mCmd1的值赋给目标驱动扭矩T mCmd。
S830，输出目标驱动扭矩T mCmd和/或目标制动扭矩T bCmd。
应理解，T mCmd和T bCmd应为大于或者等于0的值。车辆起步过程中，T mCmd和T bCmd为实时变化的，直至车辆完成起步。此外，上述S811-S830仅为一个循环，S830输出T mCmd和T bCmd后，车辆的驱/制动单元执行T mCmd和T bCmd，扭矩传感器将获取到驱/制动单元实际输出的驱动扭矩T m和制动扭矩T b的信息。该T m和T b将作为下一次目标驱动/制动扭矩计算的输入值，直至目标驱动扭矩等于请求驱动扭矩。
需要说明的是，图8中的各个步骤可以按照与图8呈现的不同的顺序来执行，并且有可能并非要执行图8中的全部操作。例如，S811-S820与S821-S826可以同时执行，也可以先后执行，本申请实施例对此不作限制。在一些可能的实现方式中，车辆在起步过程中，也可以仅执行S811-S822、S826和S830，即不执行S823-S825涉及的溜车补偿方法。
在一些可能的实现方式中，执行S812后可以先执行S818，若S818中的条件|s|＜s min或T bReq＜T min不成立，则继续依次执行S813-S817和S820；若S818中的条件成立，则直接依次执行S819和S830。
还需说明的是，本申请实施例中，“第一”、“第二”目标制动扭矩的表述方式仅是为了将过程各步骤涉及的目标制动扭矩区分清楚，其本质为目标制动扭矩计算过程中的中间量。“第一”目标驱动扭矩亦是如此，下文中仍将采用此方式进行表述。
本申请实施例的自动车辆控制的方法，通过结合估计的车辆质量和道路坡度，协同控制驱动扭矩和制动扭矩，保证二者产生的合力能够平衡坡道阻力，并且能够控制驱动扭矩平稳加载和制动扭矩平稳卸载同时进行，从而保证车辆平稳起步，缩短车辆起步所需时长。从图10所示的实车测试结果看，在坡度为15％的道路上，一般车辆起步所需时长为2.5s，采用本申请实施例自动车辆控制的方法起步只需要1.5s。在平路上，一般车辆起步所需时长为1.5s左右，采用本申请实施例自动车辆控制的方法起步只需要0.5s。也就是说，本申请实施例的方法能够明显减少起步所需时长，更能满足ADS快速起步的需求。此外，通过采用溜车补偿机制，防止车辆起步过程中发生溜车，能够提升驾驶过程中安全性和用户的驾乘体验。
图9示出了本申请实施例提供的一种自动车辆控制的方法900的示意性流程图。具体地，图9示出了车辆停车过程中驱动和制动扭矩协同控制的流程，该流程所示方法可以由图1所示的装置执行，图9中分别示出了协同控制模块和溜车补偿模块，可以分别对应于图1中的协同控制单元132和溜车补偿单元133；该流程所示方法也可以应用于图2所示的系统，本申请实施例对此不作限定。图9示出的自动车辆控制的方法的步骤或操作仅是示例，本申请实施例还可以执行其他操作或者图9中的各个操作的变形。该方法900包括：
S911，获取实际驱动/制动扭矩T m、T b、请求制动扭矩T bReq和估计的车辆质量m及坡道角度s。
具体地，上述数据获取的详细方法可以参照S811，在此不再赘述。
在一些可能的实现方式中，起停控制单元可以在接收到指令后开始执行S911。具体地，上述指令可以为车辆的用户接口输入的停车指令；或者，车辆感知系统识别到与最紧邻前车距离小于或等于预设距离时，开始执行S911；或者，车辆感知系统识别到车辆与目的地之间的距离小于或等于预设距离时，开始执行S911。
S912，计算期望制动扭矩T des和最小制动扭矩T blo，确定第二请求制动扭矩T bReq2。
期望制动扭矩T des为仅考虑车辆在坡道上停稳需要克服的重力所需的最大目标制动扭矩。具体地，计算公式为：T des＝mg*a*(b+sin(|s|))*R，其中，m、s为分别为估计的车辆质量和坡道角度，R为轮胎半径，a为质量放大系数，b为坡度偏离系数。
最小制动扭矩T blo为在考虑坡度影响的前提下，为使车辆停下，当前时刻制动系统需要输出的最小制动扭矩。具体地，计算公式为：
T blo＝T des–max(mg*sin(s)*R，0)+min(0，T m)；
应理解，车辆停车过程中，驱动系统即可以输出驱动扭矩，也可以输出制动扭矩，若 驱动系统输出制动扭矩，则扭矩传感器反馈的实际驱动扭矩T m为负值。此外，当车辆需要在上坡过程中停车时，车辆上坡时坡道阻力将贡献一部分制动力，若驱动系统输出的扭矩实际上为制动扭矩，则在考虑需要克服的重力所需的制动扭矩的前提下，液压系统实际需要输出的最小制动扭矩，需要减掉坡道阻力和驱动系统贡献的制动扭矩，即T blo＝T des–mg*sin(s)*R+T m；若车辆上坡时，驱动系统输出的驱动扭矩为正值，则液压系统实际需要输出的最小制动扭矩为T blo＝T des–mg*sin(s)*R。同理，当车辆需要在下坡过程中停车时，上式则变为T blo＝T des+T m或T blo＝T des。
进一步确定第二请求制动扭矩为T bReq2＝max(T bReq，T des)，即，取T bReq和T des中较大的赋值给T bReq2。
S913，计算第三目标制动扭矩T bCmd3。
具体地，T bCmd3＝T bReq2*c+(1-c)*T b，其中，c为指数衰减系数，使目标制动扭矩平稳的过渡到T des。
S914，确定第四目标制动扭矩T bCmd4。
具体地，T bCmd4＝max(T bCmd3，T blo)，即取T bCmd3和T blo中较大的值赋给第四目标制动扭矩，以防止制动扭矩过小导致车辆无法制动。
S915，判断第一时长t≥t 0是否成立。
第一时长t为车辆运动速度为0所持续的时长，当该时长大于系统预设阈值t 0时，认为车辆已经停稳。
若t≥t 0成立，则继续执行S916；若不成立则继续执行S917。
S916，令T bCmd＝T des。
若车辆已经停稳，将T des强制赋值给T bCmd，从而保证车辆在坡道上不发生溜车。
S917，令T bCmd＝T bCmd2。
若车辆还未停稳，则将计算出的T bCmd2赋值给T bCmd，直至第一时长t大于或等于t 0。
S921，判断T des-T b≥T gap2是否成立。
具体地，T gap2为第四预设值。当T des-T b≥T gap2，说明实际制动扭矩还未达到一定值，则继续执行S922；反之，若T des-T b＜T gap2，说明实际制动扭矩已经增加到一定值，则可以开始卸载驱动扭矩，即继续执行S923。
S922，令T mCmd2＝T m。
S923，令T mCmd2＝T m*c。
S924，判断|T mCmd2|≤T min2是否成立。
具体地，T min2为第四预设值，当T mCmd2小于或等于该预设值时，即可认为车辆不需要驱动扭矩。因此，若|T mCmd2|≤T min2成立，则继续执行S925；若不成立，则继续执行S926。
S925，令T mCmd2＝0。
S926，令T mCmd＝T mCmd2。
S930，输出目标驱动扭矩T mCmd和/或目标制动扭矩T bCmd。
在一些可能的实现方式中，为了防止停车过程中发生溜车，本申请实施例还提供一种溜车补偿方法，具体包括：
S931，获取实际制动扭矩T m、车速V s和加速度a s。
其中车速V s为速度传感器反馈的车辆纵向速度，车辆运动加速度a s为对车速V s进行微分得到的车辆运动加速度，即不包含重力加速度沿车辆纵向的分量。
S932，判断“V s＜0”或“V s≥0且a s≥0”是否成立。
V s＞0代表当前时刻车辆向前行驶，V s＜0代表当前时刻车辆发生了向后移动，V s＝0代表当前时刻车辆速度为0。当V s＞0时，说明发生了溜车，此时需要增加额外的补偿制动扭矩，以阻止继续溜车；当V s≥0且a s≥0时，说明车辆仍未减速，或车辆向前发生了溜车，此时也需要增加额外的补偿制动扭矩。因此，若“V s＜0”或“V s≥0且a s≥0”成立，则继续执行S933；若不成立，则继续执行S934。
S933，计算补偿驱动扭矩T add。
T add的具体计算方法请见方法800中的S824，在此不再赘述。
S934，令T add＝0。
此时车辆正在减速，或者已经停稳且未发生溜车，因此无需增加补偿驱动扭矩。
S935，令T b＝T b+T add。
具体地，将补偿驱动扭矩附加到实际驱动扭矩中，并输入S913计算目标驱动扭矩。
需要说明的是，图9中的各个步骤可以按照与图9呈现的不同的顺序来执行，并且有可能并非要执行图9中的全部操作。在一些可能的实现方式中，车辆在停车过程中，也可以仅执行S911-S930，即不执行S931-S935涉及的溜车补偿方法。
在一些可能的实现方式中，执行S912后可以先执行S915，若S915中的条件第一时长t≥t 0不成立，则继续依次执行S913-S914和S930；若S915中的条件第一时长t≥t 0成立，则继续依次执行S916和S930。
本申请实施例的自动车辆控制的方法，通过结合估计的车辆质量和道路坡度，协同控制驱动扭矩和制动扭矩，保证二者产生的合力能够平衡坡道阻力，并且能够控制驱动扭矩平稳增加和制动扭矩平稳卸载同时进行，从而保证车辆停车过程中的平稳性。此外，结合溜车补偿机制，防止车辆停车过程中发生溜车，能够提升驾驶过程中安全性和用户的驾乘体验。
图11示出了本申请实施例提供的一种自动车辆控制的方法1100的示意性流程图。具体地，图11示出了车辆行驶过程中坡道角度估算方法的流程，该流程所示方法可以由图1所示的装置执行，也可以应用于图2所示的系统，本申请实施例不限于此。图11示出的自动车辆控制的方法的步骤或操作仅是示例，本申请实施例还可以执行其他操作或者图11中的各个操作的变形。该方法1100包括：
S1110，获取车辆的第一加速度信号和所述车辆的第二加速度信号。
示例性地，本申请实施例中的第一加速度信号可以为上述实施例中的车速微分信号，第二加速度信号可以为车辆纵向加速度信号。
S1120，将第一加速度信号输入第一滤波器生成第三加速度信号，且将所述第二加速度信号输入第二滤波器生成第四加速度信号，所述第三加速度信号和所述第四加速度信号的相位延时特性相同。
具体地，第三加速度信号可以为上述实施例中的加速度信号a1，第四加速度信号可以为上述实施例中的加速度信号b1。第一滤波器可以为上述实施例中的滤波器A，第二滤波器可以为上述实施例中的滤波器B。
应理解，滤波器A和B为基于两路信号的相位延时特性优化的滤波器，具体优化过程及方法可以参考上述实施例中的描述，在此不再赘述。
S1130，根据所述第三加速度信号和所述第四加速度信号确定坡道角度。
具体确定坡道角度的方法可以参考上述方法300中的S304和S305，在此不再赘述。
本申请实施例的自动车辆控制的方法，通过基于车辆微分信号和车辆纵向加速度信号之间的相位延时特性，进行滤波器参数优化，使得上述两路信号分别通过优化后的滤波器后，相位延时能够保持一致，从而保证估计的坡道角度的准确性，进而减小车辆起停过程中发生的抖动，提高用户体验。
图12示出了本申请实施例提供的一种自动车辆控制的方法1200的示意性流程图。具体地，图12示出了车辆行驶过程中坡道角度估算方法的流程，该流程所示方法可以由图1所示的装置执行，也可以应用于图2所示的系统，本申请实施例不限于此。图12示出的自动车辆控制的方法的步骤或操作仅是示例，本申请实施例还可以执行其他操作或者图12中的各个操作的变形。该方法1200包括：
S1210，根据第一传感器采集的第一数据确定第一坡道角度信息，所述第一传感器包括陀螺仪传感器。
具体地，该第一数据可以为上述实施例中的陀螺仪角速度，对陀螺仪角速度进行积分确定上述第一坡道角度信息。
S1220，第二传感器采集的第二数据确定第二坡道角度信息，所述第二传感器包括GPS、激光雷达和摄像装置中的至少一种。
具体地，该第二数据具体可以为GPS数据、激光点云数据和图像数据中的一种或多种，根据第二数据确定第二坡道角度信息的方法可以参考上述实施例，在此不再赘述。
S1230，根据所述第一坡道角度信息和所述第二坡道角度信息基于最优估计方法确定坡道角度。
具体地，基于最优估计方法确定坡道角度的方法可以参考上述实施例，在此不再赘述。
本申请实施例的自动车辆控制的方法，通过与方法1200中不同的传感器获取的数据确定坡道角度，能够保证坡道估计的冗余可靠性。实际使用中，可以根据输入信号的准确性、传感器失效情况，动态切换坡道估计方案，保证坡道估计结果的可靠性和准确性。
图13示出了本申请实施例提供的一种自动车辆控制的方法1300的示意性流程图。具体地，图13示出了车辆起停过程中驱动和制动扭矩协同控制的流程，该流程所示方法可以由图1所示的装置执行，也可以应用于图2所示的系统，本申请实施例不限于此。图13示出的自动车辆控制的方法的步骤或操作仅是示例，本申请实施例还可以执行其他操作或者图13中的各个操作的变形。该方法1300包括：
S1310，获取坡道角度和车辆的质量。
需要说明的是，坡道角度和车辆的质量的获取方式可以参考上述实施例中的描述，此处不再赘述。
S1320，根据所述质量和所述坡道角度确定第一制动扭矩。
示例性地，本申请实施例中的第一制动扭矩可以为上述实施例中的第二请求制动扭矩T bReq2。
需要说明的是，根据所述质量和所述坡道角度确定第一制动扭矩的方法可以参考上述实施例中的描述，此处不再赘述。
S1330，获取所述车辆的当前制动扭矩和当前驱动扭矩。
示例性地，本申请实施例中的当前制动扭矩可以为上述实施例中的实际制动扭矩，当前驱动扭矩可以为上述实施例中的实际驱动扭矩。
S1340，在第一时刻，根据所述第一制动扭矩和所述当前制动扭矩确定目标制动扭矩，且根据所述当前驱动扭矩确定目标驱动扭矩，所述第一时刻为所述车辆起步或停车过程中的时刻。
需要说明的是，根据第一制动扭矩和当前制动扭矩确定目标制动扭矩的方法，以及根据当前驱动扭矩确定目标驱动扭矩的方法可以参考上述实施例，此处不再赘述。
本申请实施例提供的自动车辆控制的方法，基于准确估计的车辆质量和道路坡度，协同控制目标驱动扭矩和目标制动扭矩，保证目标制动扭矩和目标驱动扭矩能够同时向车辆实际所需的制动扭矩和驱动扭矩快速、平稳过渡，从而在缩短车辆起停所需时长的同时，能够保证车辆起停过程中的平稳性，进而提升用户的驾乘体验。
上文中结合图3至图13详细说明了本申请实施例提供的方法。下面将结合图14和图15详细说明本申请实施例提供的装置。装置实施例的描述与方法实施例的描述相互对应，因此，未详细描述的内容可以参见上文方法实施例，为了简洁，这里不再赘述。
图14是本申请实施例提供的自动车辆控制的装置的示意性框图。该装置1400包括获取单元1410和处理单元1420。获取单元1410可以实现相应的通信功能，处理单元1420用于进行数据处理。
可选地，该装置1400还可以包括存储单元，该存储单元可以用于存储指令和/或数据，处理单元1420可以读取存储单元中的指令和/或数据，以使得装置实现前述方法实施例。
该装置1400可以包括用于执行图3至图13中的方法的单元。并且，该装置1400中的各单元和上述其他操作和/或功能分别为了实现图3至图13的方法实施例的相应流程。
其中，当该装置1400用于执行图11中的方法1100时，获取单元1410可用于执行方法1100中的S1110，处理单元1420可用于执行方法1100中的S1120和S1130。
具体地，该装置1400包括：获取单元1410，用于获取车辆的第一加速度信号和该车辆的第二加速度信号；处理单元1420，用于将该第一加速度信号输入第一滤波器生成第三加速度信号，且将该第二加速度信号输入第二滤波器生成第四加速度信号，该第三加速度信号和该第四加速度信号的相位延时特性相同；该处理单元1420还用于根据该第三加速度信号和该第四加速度信号确定坡道角度。
在一些可能的实现方式中，该装置中的该第一滤波器和该第二滤波器为基于该第一加速度信号和该第二加速度信号的相位延时特性优化的滤波器。
在一些可能的实现方式中，该装置中的该第一滤波器和该第二滤波器为离线处理优化的滤波器。
在一些可能的实现方式中，该处理单元1420还用于：对该车辆的速度进行微分并滤波获得该第一加速度信号；对该车辆的纵向加速度进行滤波获得该第二加速度信号。
在一些可能的实现方式中，该处理单元1420还用于：根据该坡道角度，基于递推最小二乘法确定该车辆的该质量。
该装置还可以用于执行图12中的方法，当该装置1400用于执行图12中的方法1200时，处理单元1420可用于执行方法1200中的S1210-S1230。
具体地，该装置1400包括：处理单元1420，用于根据第一传感器采集的第一数据确定第一坡道角度信息，该第一传感器包括陀螺仪传感器；该处理单元1420还用于根据第二传感器采集的第二数据确定第二坡道角度信息，该第二传感器包括GPS、激光雷达和摄像装置中的至少一种；该处理单元1420还用于根据该第一坡道角度信息和该第二坡道角 度信息基于最优估计方法确定坡道角度。
在一些可能的实现方式中，该处理单元1420还用于：根据该坡道角度，基于递推最小二乘法确定该车辆的该质量。
该装置还可以用于执行图13中的方法，当该装置1400用于执行图13中的方法1300时，法1100时，获取单元1410可用于执行方法1300中的S1310和S1330，处理单元1420可用于执行方法1300中的S1320、S1340和S1350。
具体地，该装置1400包括：获取单元1410，用于获取坡道角度和车辆的质量；处理单元1420，用于根据该质量和该坡道角度确定第一制动扭矩；该获取单元1410还用于获取该车辆的当前制动扭矩和当前驱动扭矩；该处理单元1420还用于在第一时刻，根据该第一制动扭矩和该当前制动扭矩确定目标制动扭矩，且根据该当前驱动扭矩确定该目标驱动扭矩；该第一时刻为该车辆起步或停车过程中的时刻。
在一些可能的实现方式中，该获取单元1410还用于：获取第二制动扭矩，该第二制动扭矩是根据该质量和该坡道角度确定的扭矩；该处理单元1420还用于：根据该车辆满载时的总质量确定第一系数，根据该坡道角度的估计误差确定第二系数，根据该第一系数、该第二系数、该质量和该坡道角度确定第三制动扭矩；根据该第二制动扭矩和第三制动扭矩确定该第一制动扭矩。
在一些可能的实现方式中，该处理单元1420还用于：在该根据该第一制动扭矩和该当前制动扭矩确定目标制动扭矩之前，根据该第三制动扭矩和该当前驱动扭矩确定第四制动扭矩；该根据该第一制动扭矩和该当前制动扭矩确定目标制动扭矩，包括：根据该第一制动扭矩和该当前制动扭矩确定第五制动扭矩；根据该第四制动扭矩和该第五制动扭矩确定目标制动扭矩。
在一些可能的实现方式中，该处理单元1420还用于：当该坡道角度小于零，或者，该当前驱动扭矩与该第三制动扭矩之间的差值大于或等于第一阈值时，确定所述第五制动扭矩为所述目标制动扭矩。
在一些可能的实现方式中，该处理单元1420还用于：当该坡道角度的绝对值小于或等于第二阈值时，或，当该第一制动扭矩小于或等于第二阈值时，确定该目标制动扭矩为零。
在一些可能的实现方式中，该获取单元1410还用于：获取第一驱动扭矩，该第一驱动扭矩为根据该质量和该坡道角度确定的扭矩；该处理单元1420还用于：根据该第一驱动扭矩和该当前驱动扭矩确定该目标驱动扭矩。
在一些可能的实现方式中，该处理单元1420还用于：在该根据该第一驱动扭矩和该当前驱动扭矩确定该目标驱动扭矩之前，获取该车辆的当前速度；当该当前速度小于零时，根据该当前速度确定补偿扭矩；该根据该第一驱动扭矩和该当前驱动扭矩确定该目标驱动扭矩，包括：根据该第一驱动扭矩、该当前驱动扭矩和该补偿扭矩确定该目标驱动扭矩。
在一些可能的实现方式中，该处理单元1420还用于：在该根据该第一制动扭矩和该当前制动扭矩确定第五制动扭矩之前，获取该车辆的当前速度和当前加速度；当该当前速度小于零时，或，当该当前速度大于或等于零，并且该当前加速度大于或等于零时，根据该当前速度确定补偿扭矩；该根据该第一制动扭矩和该当前制动扭矩确定第五制动扭矩，包括：根据该第一制动扭矩、该补偿扭矩和该当前制动扭矩确定该第五制动扭矩。
在一些可能的实现方式中，该处理单元1420还用于：确定第一时长，该第一时长为 该车辆的当前速度为零所持续的时长；当该第一时长大于或等于第四阈值时，确定该第三制动扭矩为该目标制动扭矩。
在一些可能的实现方式中，该处理单元1420还用于：在该获取坡道角度和车辆的质量之前，确定该车辆与最紧邻前车之间的第一距离；该根据该目标制动扭矩和该目标驱动扭矩控制该车辆起步或停车，包括：当该第一距离小于或等于第五阈值时，根据该目标制动扭矩和该目标驱动扭矩控制该车辆停车。
在一些可能的实现方式中，该处理单元1420还用于：在该获取坡道角度和车辆的质量之前，确定该车辆与目的地之间的第二距离；该根据该目标制动扭矩和该目标驱动扭矩控制该车辆起步或停车，包括：当该第二距离小于或等于第六阈值时，根据该目标制动扭矩和该目标驱动扭矩控制该车辆停车。
在一些可能的实现方式中，该处理单元1420还用于：在该获取坡道角度和车辆的质量之前，确定最紧邻前车的加速度；该根据该目标制动扭矩和该目标驱动扭矩控制该车辆起步或停车，包括：当该最紧邻前车的加速度大于或等于第七阈值时，根据该目标制动扭矩和该目标驱动扭矩控制该车辆起步。
图14中的处理单元1420可以由至少一个处理器或处理器相关电路实现，获取单元1410可以由收发器或收发器相关电路实现，存储单元可以通过至少一个存储器实现。
图15是本申请实施例的自动车辆控制装置的示意性框图。图15所示的泊车设备1500可以包括：处理器1510、收发器1520以及存储器1530。其中，处理器1510、收发器1520以及存储器1530通过内部连接通路相连，该存储器1530用于存储指令，该处理器1510用于执行该存储器1530存储的指令，以收发器1530接收/发送部分参数。可选地，存储器1530既可以和处理器1510通过接口耦合，也可以和处理器1510集成在一起。
需要说明的是，上述收发器1520可以包括但不限于输入/输出接口(input/output interface)一类的收发装置，来实现通信设备1500与其他设备或通信网络之间的通信。
在实现过程中，上述方法的各步骤可以通过处理器1510中的硬件的集成逻辑电路或者软件形式的指令完成。结合本申请实施例所公开的方法可以直接体现为硬件处理器执行完成，或者用处理器中的硬件及软件模块组合执行完成。软件模块可以位于随机存储器，闪存、只读存储器，可编程只读存储器或者电可擦写可编程存储器、寄存器等本领域成熟的存储介质中。该存储介质位于存储器1530，处理器1510读取存储器1530中的信息，结合其硬件完成上述方法的步骤。为避免重复，这里不再详细描述。
还应理解，本申请实施例中，该存储器可以包括只读存储器和随机存取存储器，并向处理器提供指令和数据。处理器的一部分还可以包括非易失性随机存取存储器。例如，处理器还可以存储设备类型的信息。
本申请实施例还提供一种计算机可读介质，所述计算机可读介质存储有程序代码，当所述计算机程序代码在计算机上运行时，使得所述计算机执行上述图3、图6至图9或图11至图13中的任一种方法。
本申请实施例还提供一种芯片，包括：至少一个处理器和存储器，所述至少一个处理器与所述存储器耦合，用于读取并执行所述存储器中的指令，以执行上述图3、图6至图9或图11至图13中的任一种方法。
本申请实施例还提供一种自动驾驶车辆，包括：至少一个处理器和存储器，所述至少一个处理器与所述存储器耦合，用于读取并执行所述存储器中的指令，以执行上述图3、 图6至图9或图11至图13中的任一种方法。
应理解，本文中术语“和/或”，仅仅是一种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。另外，本文中字符“/”，一般表示前后关联对象是一种“或”的关系。
应理解，在本申请的各种实施例中，上述各过程的序号的大小并不意味着执行顺序的先后，各过程的执行顺序应以其功能和内在逻辑确定，而不应对本申请实施例的实施过程构成任何限定。
在本说明书中使用的术语“部件”、“模块”、“系统”等用于表示计算机相关的实体、硬件、固件、硬件和软件的组合、软件、或执行中的软件。例如，部件可以是但不限于，在处理器上运行的进程、处理器、对象、可执行文件、执行线程、程序和/或计算机。通过图示，在计算设备上运行的应用和计算设备都可以是部件。一个或多个部件可驻留在进程和/或执行线程中，部件可位于一个计算机上和/或分布在2个或更多个计算机之间。此外，这些部件可从在上面存储有各种数据结构的各种计算机可读介质执行。部件可例如根据具有一个或多个数据分组(例如来自与本地系统、分布式系统和/或网络间的另一部件交互的二个部件的数据，例如通过信号与其它系统交互的互联网)的信号通过本地和/或远程进程来通信。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统、装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
在本申请所提供的几个实施例中，应该理解到，所揭露的系统、装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。
所述功能如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(Read-Only Memory，ROM)、随 机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以所述权利要求的保护范围为准。

Claims (42)

  1. 一种自动车辆控制的方法，其特征在于，包括：
    获取车辆的第一加速度信号和所述车辆的第二加速度信号；
    将所述第一加速度信号输入第一滤波器生成第三加速度信号，且将所述第二加速度信号输入第二滤波器生成第四加速度信号，所述第三加速度信号和所述第四加速度信号的相位延时特性相同；
    根据所述第三加速度信号和所述第四加速度信号确定坡道角度。
  2. 如权利要求1所述的方法，其特征在于，所述第一滤波器和所述第二滤波器为基于所述第一加速度信号和所述第二加速度信号的相位延时特性优化的滤波器。
  3. 如权利要求1或2所述的方法，其特征在于，所述第一滤波器和所述第二滤波器为离线处理优化的滤波器。
  4. 如权利要求1至3中任一项所述的方法，其特征在于，所述第一加速度信号为对所述车辆的速度进行微分并滤波获得的信号，所述第二加速度信号为对所述车辆的纵向加速度进行滤波获得的信号。
  5. 如权利要求1至4中任一项所述的方法，其特征在于，所述方法还包括：
    根据所述坡道角度，基于递推最小二乘法确定所述车辆的所述质量。
  6. 一种自动车辆控制的方法，其特征在于，包括：
    根据第一传感器采集的第一数据确定第一坡道角度信息，所述第一传感器包括陀螺仪传感器；
    根据第二传感器采集的第二数据确定第二坡道角度信息，所述第二传感器包括GPS、激光雷达和摄像装置中的至少一种；
    根据所述第一坡道角度信息和所述第二坡道角度信息基于最优估计方法确定坡道角度。
  7. 如权利要求6所述的方法，其特征在于，所述方法还包括：
    根据所述坡道角度，基于递推最小二乘法确定所述车辆的所述质量。
  8. 一种自动车辆控制的方法，其特征在于，包括：
    获取坡道角度和车辆的质量；
    根据所述质量和所述坡道角度确定第一制动扭矩；
    获取所述车辆的当前制动扭矩和当前驱动扭矩；
    在第一时刻，根据所述第一制动扭矩和所述当前制动扭矩确定目标制动扭矩，且根据所述当前驱动扭矩确定所述目标驱动扭矩；
    所述第一时刻为所述车辆起步或停车过程中的时刻。
  9. 如权利要求8所述的方法，其特征在于，所述根据所述质量和所述坡道角度确定第一制动扭矩，包括：
    获取第二制动扭矩，所述第二制动扭矩是根据所述质量和所述坡道角度确定的扭矩；
    根据所述车辆满载时的总质量确定第一系数，根据所述坡道角度的估计误差确定第二系数，根据所述第一系数、所述第二系数、所述质量和所述坡道角度确定第三制动扭矩；
    根据所述第二制动扭矩和第三制动扭矩确定所述第一制动扭矩。
  10. 如权利要求8或9所述的方法，其特征在于，所述根据所述第一制动扭矩和所述当前制动扭矩确定目标制动扭矩之前，所述方法还包括：
    根据所述第三制动扭矩和所述当前驱动扭矩确定第四制动扭矩；
    所述根据所述第一制动扭矩和所述当前制动扭矩确定目标制动扭矩，包括：
    根据所述第一制动扭矩和所述当前制动扭矩确定第五制动扭矩；
    根据所述第四制动扭矩和所述第五制动扭矩确定目标制动扭矩。
  11. 如权利要求10所述的方法，其特征在于，当所述第一时刻为所述车辆起步过程中的时刻时，所述根据所述第四制动扭矩和所述第五制动扭矩确定目标制动扭矩，包括：
    当所述坡道角度小于零，或者，所述当前驱动扭矩与所述第三制动扭矩之间的差值大于或等于第一阈值时，确定所述第五制动扭矩为所述目标制动扭矩。
  12. 如权利要求10中所述的方法，其特征在于，当所述第一时刻为所述车辆起步过程中的时刻时，所述方法还包括：
    当所述坡道角度的绝对值小于或等于第二阈值时，或，当所述第一制动扭矩小于或等于第二阈值时，确定所述目标制动扭矩为零。
  13. 如权利要求8至12中任一项所述的方法，其特征在于，当所述第一时刻为所述车辆起步过程中的时刻时，所述根据所述当前驱动扭矩确定所述目标驱动扭矩，包括：
    获取第一驱动扭矩，所述第一驱动扭矩为根据所述质量和所述坡道角度确定的扭矩；
    根据所述第一驱动扭矩和所述当前驱动扭矩确定所述目标驱动扭矩。
  14. 如权利要求13中所述的方法，其特征在于，所述根据所述第一驱动扭矩和所述当前驱动扭矩确定所述目标驱动扭矩之前，所述方法还包括：
    获取所述车辆的当前速度；
    当所述当前速度小于零时，根据所述当前速度确定补偿扭矩；
    所述根据所述第一驱动扭矩和所述当前驱动扭矩确定所述目标驱动扭矩，包括：
    根据所述第一驱动扭矩、所述当前驱动扭矩和所述补偿扭矩确定所述目标驱动扭矩。
  15. 如权利要求10所述的方法，其特征在于，当所述第一时刻为所述车辆停车过程中的时刻时，所述根据所述第一制动扭矩和所述当前制动扭矩确定第五制动扭矩之前，所述方法还包括：
    获取所述车辆的当前速度和当前加速度；
    当所述当前速度小于零时，或，当所述当前速度大于或等于零，并且所述当前加速度大于或等于零时，根据所述当前速度确定补偿扭矩；
    所述根据所述第一制动扭矩和所述当前制动扭矩确定第五制动扭矩，包括：
    根据所述第一制动扭矩、所述补偿扭矩和所述当前制动扭矩确定所述第五制动扭矩。
  16. 如权利要求15所述的方法，其特征在于，当所述第一时刻为所述车辆停车过程中的时刻时，所述方法还包括：
    确定第一时长，所述第一时长为所述车辆的当前速度为零所持续的时长；
    当所述第一时长大于或等于第四阈值时，确定所述第三制动扭矩为所述目标制动扭矩。
  17. 如权利要求8至16中任一项所述的方法，其特征在于，所述获取坡道角度和车辆的质量之前，所述方法还包括：
    确定所述车辆与最紧邻前车之间的第一距离；
    所述根据所述目标制动扭矩和所述目标驱动扭矩控制所述车辆起步或停车，包括：
    当所述第一距离小于或等于第五阈值时，根据所述目标制动扭矩和所述目标驱动扭矩控制所述车辆停车。
  18. 如权利要求8至17中任一项所述的方法，其特征在于，所述获取坡道角度和车的质量之前，所述方法还包括：
    确定所述车辆与目的地之间的第二距离；
    所述根据所述目标制动扭矩和所述目标驱动扭矩控制所述车辆起步或停车，包括：
    当所述第二距离小于或等于第六阈值时，根据所述目标制动扭矩和所述目标驱动扭矩控制所述车辆停车。
  19. 如权利要求8至16中任一项所述的方法，其特征在于，所述获取坡道角度和车辆的质量之前，所述方法还包括：
    确定最紧邻前车的加速度；
    所述根据所述目标制动扭矩和所述目标驱动扭矩控制所述车辆起步或停车，包括：
    当所述最紧邻前车的加速度大于或等于第七阈值时，根据所述目标制动扭矩和所述目标驱动扭矩控制所述车辆起步。
  20. 一种自动车辆控制的装置，其特征在于，包括：
    获取单元，用于获取车辆的第一加速度信号和所述车辆的第二加速度信号；
    处理单元，用于将所述第一加速度信号输入第一滤波器生成第三加速度信号，且将所述第二加速度信号输入第二滤波器生成第四加速度信号，所述第三加速度信号和所述第四加速度信号的相位延时特性相同；
    所述处理单元还用于根据所述第三加速度信号和所述第四加速度信号确定坡道角度。
  21. 如权利要求20所述的装置，其特征在于，所述第一滤波器和所述第二滤波器为基于所述第一加速度信号和所述第二加速度信号的相位延时特性优化的滤波器。
  22. 如权利要求20或21所述的装置，其特征在于，所述第一滤波器和所述第二滤波器为离线处理优化的滤波器。
  23. 如权利要求20至22所述的装置，其特征在于，所述处理单元还用于：
    对所述车辆的速度进行微分并滤波获得所述第一加速度信号；
    对所述车辆的纵向加速度进行滤波获得所述第二加速度信号。
  24. 如权利要求20至23所述的装置，其特征在于，所述处理单元还用于：
    根据所述坡道角度，基于递推最小二乘法确定所述车辆的所述质量。
  25. 一种自动车辆控制的装置，其特征在于，包括：
    处理单元，用于根据第一传感器采集的第一数据确定第一坡道角度信息，所述第一传感器包括陀螺仪传感器；
    所述处理单元还用于根据第二传感器采集的第二数据确定第二坡道角度信息，所述第二传感器包括GPS、激光雷达和摄像装置中的至少一种；
    所述处理单元还用于根据所述第一坡道角度信息和所述第二坡道角度信息基于最优估计方法确定坡道角度。
  26. 如权利要求25所述的装置，其特征在于，所述处理单元还用于：
    根据所述坡道角度，基于递推最小二乘法确定所述车辆的所述质量。
  27. 一种自动车辆控制的装置，其特征在于，包括：
    获取单元，用于获取坡道角度和车辆的质量；
    处理单元，用于根据所述质量和所述坡道角度确定第一制动扭矩；
    所述获取单元还用于获取所述车辆的当前制动扭矩和当前驱动扭矩；
    所述处理单元还用于在第一时刻，根据所述第一制动扭矩和所述当前制动扭矩确定目标制动扭矩，且根据所述当前驱动扭矩确定所述目标驱动扭矩；
    所述第一时刻为所述车辆起步或停车过程中的时刻。
  28. 如权利要求27所述的装置，其特征在于，所述获取单元还用于：获取第二制动扭矩，所述第二制动扭矩是根据所述质量和所述坡道角度确定的扭矩；
    所述处理单元还用于：
    根据所述车辆满载时的总质量确定第一系数，根据所述坡道角度的估计误差确定第二系数，根据所述第一系数、所述第二系数、所述质量和所述坡道角度确定第三制动扭矩；
    根据所述第二制动扭矩和第三制动扭矩确定所述第一制动扭矩。
  29. 如权利要求27或28所述的装置，其特征在于，所述处理单元还用于：
    在所述根据所述第一制动扭矩和所述当前制动扭矩确定目标制动扭矩之前，根据所述第三制动扭矩和所述当前驱动扭矩确定第四制动扭矩；
    所述根据所述第一制动扭矩和所述当前制动扭矩确定目标制动扭矩，包括：
    根据所述第一制动扭矩和所述当前制动扭矩确定第五制动扭矩；
    根据所述第四制动扭矩和所述第五制动扭矩确定目标制动扭矩。
  30. 如权利要求29所述的装置，其特征在于，当所述第一时刻为所述车辆起步过程中的时刻时，所述处理单元还用于：
    当所述坡道角度小于零，或者，所述当前驱动扭矩与所述第三制动扭矩之间的差值大于或等于第一阈值时，确定所述第五制动扭矩为所述目标制动扭矩。
  31. 如权利要求29所述的装置，其特征在于，当所述第一时刻为所述车辆起步过程中的时刻时，所述处理单元还用于：
    当所述坡道角度的绝对值小于或等于第二阈值时，或，当所述第一制动扭矩小于或等于第二阈值时，确定所述目标制动扭矩为零。
  32. 如权利要求27至31中任一项所述的装置，其特征在于，当所述第一时刻为所述车辆起步过程中的时刻时，所述获取单元还用于：
    获取第一驱动扭矩，所述第一驱动扭矩为根据所述质量和所述坡道角度确定的扭矩；
    所述处理单元还用于：
    根据所述第一驱动扭矩和所述当前驱动扭矩确定所述目标驱动扭矩。
  33. 如权利要求32所述的装置，其特征在于，所述处理单元还用于：
    在所述根据所述第一驱动扭矩和所述当前驱动扭矩确定所述目标驱动扭矩之前，获取所述车辆的当前速度；
    当所述当前速度小于零时，根据所述当前速度确定补偿扭矩；
    所述根据所述第一驱动扭矩和所述当前驱动扭矩确定所述目标驱动扭矩，包括：
    根据所述第一驱动扭矩、所述当前驱动扭矩和所述补偿扭矩确定所述目标驱动扭矩。
  34. 如权利要求29所述的装置，其特征在于，当所述第一时刻为所述车辆停车过程中的时刻时，所述处理单元还用于：
    在所述根据所述第一制动扭矩和所述当前制动扭矩确定第五制动扭矩之前，获取所述车辆的当前速度和当前加速度；
    当所述当前速度小于零时，或，当所述当前速度大于或等于零，并且所述当前加速度大于或等于零时，根据所述当前速度确定补偿扭矩；
    所述根据所述第一制动扭矩和所述当前制动扭矩确定第五制动扭矩，包括：
    根据所述第一制动扭矩、所述补偿扭矩和所述当前制动扭矩确定所述第五制动扭矩。
  35. 如权利要求34所述的装置，其特征在于，当所述第一时刻为所述车辆停车过程中的时刻时，所述处理单元还用于：
    确定第一时长，所述第一时长为所述车辆的当前速度为零所持续的时长；
    当所述第一时长大于或等于第四阈值时，确定所述第三制动扭矩为所述目标制动扭矩。
  36. 如权利要求27至35中任一项所述的装置，其特征在于，所述处理单元还用于：
    在所述获取坡道角度和车辆的质量之前，确定所述车辆与最紧邻前车之间的第一距离；
    所述根据所述目标制动扭矩和所述目标驱动扭矩控制所述车辆起步或停车，包括：
    当所述第一距离小于或等于第五阈值时，根据所述目标制动扭矩和所述目标驱动扭矩控制所述车辆停车。
  37. 如权利要求27至36中任一项所述的装置，其特征在于，所述处理单元还用于：
    在所述获取坡道角度和车辆的质量之前，确定所述车辆与目的地之间的第二距离；
    所述根据所述目标制动扭矩和所述目标驱动扭矩控制所述车辆起步或停车，包括：
    当所述第二距离小于或等于第六阈值时，根据所述目标制动扭矩和所述目标驱动扭矩控制所述车辆停车。
  38. 如权利要求27至35中任一项所述的装置，其特征在于，所述处理单元还用于：
    在所述获取坡道角度和车辆的质量之前，确定最紧邻前车的加速度；
    所述根据所述目标制动扭矩和所述目标驱动扭矩控制所述车辆起步或停车，包括：
    当所述最紧邻前车的加速度大于或等于第七阈值时，根据所述目标制动扭矩和所述目标驱动扭矩控制所述车辆起步。
  39. 一种自动车辆控制的装置，其特征在于，包括：
    收发器，用于接收和发送消息；
    存储器，用于存储计算机程序；
    处理器，用于执行所述存储器中存储的计算机程序，以使得所述装置执行如权利要求1至19中任一项所述的方法；所述处理器与存储器耦合。
  40. 一种自动驾驶车辆，其特征在于，包括权利要求20至38中任一项所述的装置。
  41. 一种计算机可读存储介质，其特征在于，其上存储有计算机程序，所述计算机程序被计算机执行时，以使得实现如权利要求1至19中任一项所述的方法。
  42. 一种芯片，其特征在于，所述芯片包括处理器与数据接口，所述处理器通过所述数据接口读取存储器上存储的指令，以执行如权利要求1至19中任一项所述的方法。
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CN1743988A (zh) * 2004-09-01 2006-03-08 株式会社东芝 铁道车辆信息控制系统
CN110095635A (zh) * 2019-05-08 2019-08-06 吉林大学 一种全轮驱动车辆的纵向车速估计方法
CN110103976A (zh) * 2019-04-17 2019-08-09 国机智骏科技有限公司 路面坡度计算方法和装置
CN112061106A (zh) * 2020-09-15 2020-12-11 中国第一汽车股份有限公司 自动驾驶控制方法、装置、车辆和存储介质

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Publication number Priority date Publication date Assignee Title
CN1743988A (zh) * 2004-09-01 2006-03-08 株式会社东芝 铁道车辆信息控制系统
CN110103976A (zh) * 2019-04-17 2019-08-09 国机智骏科技有限公司 路面坡度计算方法和装置
CN110095635A (zh) * 2019-05-08 2019-08-06 吉林大学 一种全轮驱动车辆的纵向车速估计方法
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