WO2023005156A1 - Mise à jour de paramètre - Google Patents

Mise à jour de paramètre Download PDF

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Publication number
WO2023005156A1
WO2023005156A1 PCT/CN2022/070568 CN2022070568W WO2023005156A1 WO 2023005156 A1 WO2023005156 A1 WO 2023005156A1 CN 2022070568 W CN2022070568 W CN 2022070568W WO 2023005156 A1 WO2023005156 A1 WO 2023005156A1
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WO
WIPO (PCT)
Prior art keywords
target vehicle
data
vehicle
historical
control
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Application number
PCT/CN2022/070568
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English (en)
Chinese (zh)
Inventor
黄超
姚亦玮
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上海仙途智能科技有限公司
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Publication of WO2023005156A1 publication Critical patent/WO2023005156A1/fr

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • 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
    • 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
    • B60W40/10—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 vehicle motion
    • B60W40/107—Longitudinal acceleration
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/23—Updating
    • 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
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0043—Signal treatments, identification of variables or parameters, parameter estimation or state estimation
    • 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
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/10—Longitudinal speed
    • B60W2520/105—Longitudinal acceleration
    • 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
    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/15—Road slope, i.e. the inclination of a road segment in the longitudinal direction

Definitions

  • the present application relates to the technical field of vehicles, in particular to a method, device, device and computer-readable storage medium for updating parameters.
  • control module of the vehicle is responsible for receiving information such as upstream planning and positioning, and generates control commands such as accelerator, brake, and steering wheel according to the planned driving trajectory and required speed, as well as the current position, attitude and speed of the vehicle. .
  • the underlying hardware system has a large delay, the driving speed is small, the quality of the vehicle is reduced during driving, and the vehicle control model changes, which requires real-time update of the vehicle control parameters.
  • Existing methods for updating control parameters include but are not limited to methods for updating control parameters based on offline visual analysis of vehicle underlying hardware performance, that is, offline cleaning data, visual analysis of vehicle underlying hardware performance, and updating vehicle control parameters .
  • this method is simple and can guarantee the control effect of the vehicle within a certain period of time, but the parameter update cycle is long, the ability to resist noise is weak, and the parameters cannot be automatically corrected, requiring manual intervention, which increases the workload.
  • the present application provides a parameter update method, device, device and computer-readable storage medium, which can shorten the parameter update cycle, improve the ability to resist noise, and can automatically update parameters.
  • a method for updating parameters comprising: acquiring historical driving data of a target vehicle within a selected historical period; acquiring feed-forward data corresponding to the target vehicle at the current running moment, wherein the feed-forward data includes The vehicle acceleration brought by the slope information of the position and the calculated response delay time of the underlying hardware of the target vehicle; according to the historical driving data and the feed-forward data, the control parameters of the target vehicle are renew.
  • a parameter updating device comprising: a historical data acquisition unit, used to acquire historical driving data of a target vehicle within a selected historical period; a feedforward data acquisition unit, used to acquire the feedforward data corresponding to the target vehicle at the current running time data, wherein the feedforward data includes the vehicle acceleration based on the slope information of the target vehicle’s position and the calculated response delay time of the underlying hardware of the target vehicle; the control parameter update unit is used for The control parameters of the target vehicle are updated according to the historical driving data and the feed-forward data.
  • An electronic device comprising: a processor and a memory; the memory is used to store a computer program; the processor is used to execute the above parameter update method by invoking the computer program.
  • a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the above parameter update method is implemented.
  • the historical driving data of the target vehicle in the selected historical period is obtained, and the feed-forward data corresponding to the target vehicle at the current running time is obtained, wherein the feed-forward data includes information based on the location of the target vehicle
  • the acceleration of the vehicle brought by the slope information and the calculated response delay time of the underlying hardware of the target vehicle and then update the control parameters of the target vehicle according to the historical driving data and feed-forward data.
  • this application uses real-time feed-forward data as input, which can solve the problems of vehicle bottom performance changes and road terrain changes, and, combined with real-time data such as historical driving data during the driving process of the target vehicle, online update of vehicle control parameters can be achieved. Shorten the parameter update cycle, improve the ability to resist noise, and make the control system more reliable and accurate, so as to achieve better control effect.
  • FIG. 1 is a schematic flow diagram of a parameter updating method shown in the present application
  • Fig. 2 is a schematic diagram of parameter update based on the control system shown in the present application.
  • Fig. 3 is a schematic diagram of updating parameters based on the longitudinal speed control system shown in the present application.
  • FIG. 4 is a schematic diagram of the composition of a parameter updating device shown in the present application.
  • FIG. 5 is a schematic structural diagram of an electronic device shown in the present application.
  • first, second, third, etc. may be used in this application to describe various information, the information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of the present application, first information may also be called second information, and similarly, second information may also be called first information. Depending on the context, the word “if” as used herein may be interpreted as “at” or “when” or “in response to a determination.”
  • Model Predictive Control is a control method based on predicting the controlled object.
  • PID Abbreviation of Proportional (proportional), Integral (integral), and Differential (differential).
  • process control a controller that controls the proportional (P), integral (I) and differential (D) of the deviation.
  • FIG. 1 it is a schematic flowchart of a parameter update method provided by the embodiment of the present application, the method includes the following steps S101-S103:
  • S101 Obtain historical driving data of the target vehicle within a selected historical period.
  • the target vehicle can be any type of self-driving vehicle, which can specifically be a vehicle with a large delay in the underlying hardware system, a small driving speed, a decrease in quality during driving, or a change in the vehicle control model, such as a low-speed vehicle. commercial vehicle.
  • the parameter update method shown in Figure 1 can be implemented by a set of control systems suitable for online identification on the target vehicle, refer to the schematic diagram of parameter update based on the control system shown in Figure 2, in order to To automatically adjust the control parameters of the target vehicle, it is necessary to obtain the data of the target vehicle in the historical driving process first.
  • the input of the control system is the historical driving data of the target vehicle within the selected historical period (the selected historical period may include one or more selected periods before the current moment), that is, the input is a time series
  • the historical driving data, the output is a frame of future control of the target vehicle.
  • the historical driving data may include at least one of vehicle positioning data, path planning data, vehicle underlying data, and vehicle control data of the target vehicle in a period of time.
  • vehicle positioning data refers to the position data of the target vehicle during the historical driving process
  • underlying vehicle data refers to the braking, steering wheel, manual/automatic driving mode and other data of the target vehicle during the driving process
  • path planning data refers to the target vehicle’s Planning route and other data
  • vehicle control data refers to the data related to the control of the target vehicle during the driving process, including but not limited to steering wheel control volume, accelerator brake control volume, gear control volume, lighting control volume, etc.
  • the current driving data can be used as the historical driving data input to the control system.
  • the feedforward data includes, but is not limited to, the acceleration brought by the road gradient and the calculated response delay time of the underlying hardware, as shown in FIG. 2 .
  • the slope information is historical slope information of the target vehicle; or, the slope information is obtained by real-time positioning of the target vehicle based on a pre-established topographic map of the driving area.
  • the current slope information of the target vehicle can be replaced by a stable historical slope information; the topographic map of the vehicle driving area can also be established in advance, and the current slope information of the target vehicle can be obtained based on the topographic map by locating the target vehicle.
  • the slope information of the positioning is received, which is used as the feed-forward data in the control system shown in Fig. 2 .
  • S103 Update the control parameters of the target vehicle according to the historical driving data and the feed-forward data.
  • the control parameters of the target vehicle can be updated based on the historical driving data of the target vehicle in the selected historical period and the corresponding feed-forward data of the target vehicle at the current running time.
  • the control system can be divided into horizontal control strategy and vertical control strategy from the control content, and can also be divided into outer loop control strategy and inner loop control strategy from the control scope.
  • the horizontal control strategy includes and is not limited to LPR, MPC
  • the vertical control strategy includes and is not limited to PID, MPC, meter reading, bang-bang control
  • the outer loop control strategy includes but is not limited to LPR, MPC
  • the inner loop control strategy includes and Not limited to adaptive control.
  • Control system parameters are determined by the control strategy, such as MPC control corresponding parameter prediction range, control time domain, loss function, constraint function, etc.
  • control parameters of the control system can be updated in real time, and the control parameters include but are not limited to at least one of the steering wheel offset, the response delay time of the underlying hardware, and the position of the center of mass parameter.
  • the position of the center of mass of the target vehicle is obtained based on the water level information of the water tank of the target vehicle. Therefore, the position of the center of mass of the vehicle can be updated in real time in combination with the water level information of the water tank of the target vehicle.
  • "updating the control parameters of the target vehicle” in S103 may include: updating the control parameters of the target vehicle in combination with kinematics formulas. That is to say, the parameters of the control model can be updated in combination with the kinematic formula.
  • control quantities can be output based on the current updated control parameters.
  • These control quantities include but are not limited to steering wheel control quantities, accelerator and brake control quantities, and gear control quantities. , light control amount, etc. These control amounts will directly affect the speed and pose of the target vehicle during operation.
  • the positioning, vehicle and other information obtained by the target vehicle in response to these control quantities will enter the control system as the feedback quantity of the new cycle, that is, the response results of the target vehicle to the control quantities will be used to update the existing historical driving data, so that According to the historical driving data updated in real time, the control parameters of the target vehicle are updated in real time.
  • the planned speed is the input of the speed controller and also the target speed of the target vehicle;
  • the speed controller can be an MPC controller or a PID controller.
  • the target vehicle When performing speed control, the current speed and historical speed sequence of the target vehicle, and the pose information of the target vehicle can also be used as the input of the speed controller.
  • the feed-forward data is also input into the speed controller.
  • the feed-forward data includes but is not limited to the acceleration caused by the slope, the response delay time of the underlying hardware, etc., wherein the "acceleration caused by the slope" is obtained based on the real-time update of the slope information.
  • the “bottom hardware response delay time” is based on the subscribed "historical driving data of the target vehicle in the selected historical period” (ie step S101), calculated by displacement method, and used to update the delay in the speed controller online parameter.
  • the acceleration control amount in the control time domain can be obtained, and the final acceleration control amount is determined by the response delay time, and then combined with P (acc
  • cmd, velo) meter reading to get the final throttle, brake control, etc.
  • online speed, acceleration, and control data collection, cleaning, and machine learning can update the P(acc
  • the historical driving data of the target vehicle in the selected historical period is obtained, and the feed-forward data corresponding to the target vehicle at the current running moment is obtained, wherein the feed-forward data includes The vehicle acceleration brought by the slope information of the location and the calculated response delay time of the underlying hardware of the target vehicle, and then update the control parameters of the target vehicle according to the historical driving data and feed-forward data.
  • the embodiment of the present application uses real-time feed-forward data as input, which can solve the problems of vehicle bottom performance changes and road terrain changes, and, combined with real-time data such as historical driving data during the driving process of the target vehicle, update the control parameters of the vehicle online , can shorten the parameter update cycle, improve the ability to resist noise, and make the control system more reliable and accurate, so as to achieve better control effect.
  • the device includes: a historical data acquisition unit 410 for acquiring historical driving data of the target vehicle within a selected historical period; feedforward data acquisition Unit 420, configured to acquire feedforward data corresponding to the target vehicle at the current running moment, wherein the feedforward data includes vehicle acceleration brought about based on the slope information of the location of the target vehicle, and the calculated The underlying hardware response delay time of the target vehicle; the control parameter update unit 430, configured to update the control parameters of the target vehicle according to the historical driving data and the feed-forward data.
  • the historical driving data includes at least one of vehicle positioning data, route planning data, vehicle underlying data, and vehicle control data.
  • the slope information is the historical slope information of the target vehicle; or, the slope information is based on the pre-established topographic map of the driving area, by real-time positioning of the target vehicle vehicle gets.
  • control parameters include at least one parameter among steering wheel offset, underlying hardware response delay time, and center of mass position.
  • the centroid position is obtained based on water level information of a water tank of the target vehicle.
  • control parameter update unit 430 is specifically configured to update the control parameters of the target vehicle in combination with a kinematics formula.
  • the device embodiment since it basically corresponds to the method embodiment, for related parts, please refer to the part description of the method embodiment.
  • the device embodiments described above are only illustrative, and 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 it can be distributed to multiple network elements. Part or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this application. It can be understood and implemented by those skilled in the art without creative effort.
  • the embodiment of the present application also provides an electronic device, the structural diagram of which is shown in Figure 5, the electronic device 5000 includes at least one processor 5001, a memory 5002 and a bus 5003, at least one processor 5001 is connected to the memory 5002 Electrically connected; the memory 5002 is configured to store at least one computer-executable instruction, and the processor 5001 is configured to execute the at least one computer-executable instruction, thereby performing any one of the embodiments or any optional one in the present application. Steps of any parameter updating method provided in the implementation manner.
  • the processor 5001 can be FPGA (Field-Programmable Gate Array, Field Programmable Gate Array) or other devices with logic processing capabilities, such as MCU (Microcontroller Unit, micro control unit), CPU (Central Process Unit, central processing unit ).
  • MCU Microcontroller Unit, micro control unit
  • CPU Central Process Unit, central processing unit
  • the embodiment of the present application also provides another computer-readable storage medium, which stores a computer program, and the computer program is used to realize any of the functions provided by any embodiment or any optional implementation mode in the present application when executed by a processor. Steps of a parameter update method.
  • the computer-readable storage medium includes but is not limited to any type of disk (including floppy disk, hard disk, optical disk, CD-ROM, and magneto-optical disk), ROM (Read-Only Memory, read-only memory), RAM ( Random Access Memory, Random Access Memory), EPROM (Erasable Programmable Read-Only Memory, Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory, Electrically Erasable Programmable Read-Only Memory), flash memory, magnetic card or ray card. That is, a readable storage medium includes any medium that stores or transmits information in a form readable by a device (eg, a computer).
  • a device eg, a computer

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  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Mathematical Physics (AREA)
  • Human Computer Interaction (AREA)
  • Databases & Information Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
  • Steering Control In Accordance With Driving Conditions (AREA)

Abstract

Procédé de mise à jour de paramètre, consistant à : acquérir des données de conduite historiques d'un véhicule cible dans une période de temps historique sélectionnée, et acquérir des données d'action directe correspondant au véhicule cible au moment d'exécution actuel, les données d'action directe comprenant une accélération de véhicule provoquée par des informations de pente de l'emplacement du véhicule cible, et un délai de réponse de matériel sous-jacent calculé du véhicule cible ; et, mettre à jour un paramètre de commande du véhicule cible selon les données de conduite historiques et les données d'action directe. La présente demande peut résoudre les problèmes de variations de performances de véhicule et de changements de terrain de route sous-jacents. En outre, en association avec des données en temps réel à des fins de mise à jour en ligne d'un paramètre de commande du véhicule, une période de mise à jour de paramètre peut être raccourcie et la capacité de faible résistance au bruit peut être accrue, ce qui renforce la fiabilité et la précision d'un système de commande, et ce qui permet d'assurer des effets de commande améliorés. L'invention concerne également un appareil de mise à jour de paramètre, un dispositif et un support d'enregistrement lisible par ordinateur.
PCT/CN2022/070568 2021-07-29 2022-01-06 Mise à jour de paramètre WO2023005156A1 (fr)

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CN202110866659.5 2021-07-29
CN202110866659.5A CN115246410B (zh) 2021-07-29 2021-07-29 参数更新方法、装置、设备及计算机可读存储介质

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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107818377A (zh) * 2016-09-12 2018-03-20 法乐第(北京)网络科技有限公司 基于云计算平台的车辆全局优化控制方法、系统、车辆和云计算平台
CN111497765A (zh) * 2019-01-31 2020-08-07 驭势科技（北京）有限公司 自动驾驶车辆及控制方法、控制装置和计算机处理介质
CN111506024A (zh) * 2019-01-31 2020-08-07 驭势科技（北京）有限公司 自动驾驶车辆及控制方法、控制装置和计算机处理介质
KR20210089116A (ko) * 2020-06-29 2021-07-15 베이징 바이두 넷컴 사이언스 앤 테크놀로지 코., 엘티디. 종방향 동역학 모델의 트레이닝 방법, 장치 및 기기

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11738802B2 (en) * 2018-12-20 2023-08-29 Hl Mando Corporation Steering control system and control method thereof
CN110059095B (zh) * 2019-03-12 2021-06-25 北京小马慧行科技有限公司 一种数据更新方法及装置
US11194939B2 (en) * 2019-08-16 2021-12-07 Uatc, Llc Hardware in loop testing and generation of latency profiles for use in simulation
JP7169257B2 (ja) * 2019-09-20 2022-11-10 本田技研工業株式会社 車両制御装置、地図情報管理システム、車両制御方法、およびプログラム
CN111546902A (zh) * 2020-03-25 2020-08-18 张雪华 一种基于车联网的电动汽车坡道扭矩控制方法及其系统

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107818377A (zh) * 2016-09-12 2018-03-20 法乐第(北京)网络科技有限公司 基于云计算平台的车辆全局优化控制方法、系统、车辆和云计算平台
CN111497765A (zh) * 2019-01-31 2020-08-07 驭势科技（北京）有限公司 自动驾驶车辆及控制方法、控制装置和计算机处理介质
CN111506024A (zh) * 2019-01-31 2020-08-07 驭势科技（北京）有限公司 自动驾驶车辆及控制方法、控制装置和计算机处理介质
KR20210089116A (ko) * 2020-06-29 2021-07-15 베이징 바이두 넷컴 사이언스 앤 테크놀로지 코., 엘티디. 종방향 동역학 모델의 트레이닝 방법, 장치 및 기기

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