CN118124587A - Road feature processing method and road feature processing system - Google Patents

Road feature processing method and road feature processing system Download PDF

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Publication number
CN118124587A
CN118124587A CN202211528196.2A CN202211528196A CN118124587A CN 118124587 A CN118124587 A CN 118124587A CN 202211528196 A CN202211528196 A CN 202211528196A CN 118124587 A CN118124587 A CN 118124587A
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China
Prior art keywords
vehicle
road
acceleration
gradient
longitudinal
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CN202211528196.2A
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Chinese (zh)
Inventor
程昆朋
丁宁
马骁
陆倪阳
赵祥磊
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SAIC General Motors Corp Ltd
Pan Asia Technical Automotive Center Co Ltd
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SAIC General Motors Corp Ltd
Pan Asia Technical Automotive Center Co Ltd
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Application filed by SAIC General Motors Corp Ltd, Pan Asia Technical Automotive Center Co Ltd filed Critical SAIC General Motors Corp Ltd
Priority to CN202211528196.2A priority Critical patent/CN118124587A/en
Publication of CN118124587A publication Critical patent/CN118124587A/en
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    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT 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
    • B60W40/00Estimation 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
    • B60W40/02Estimation 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
    • B60W40/06Road conditions
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT 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
    • B60W40/00Estimation 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
    • B60W40/02Estimation 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
    • B60W40/06Road conditions
    • B60W40/076Slope angle of the road
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT 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
    • B60W40/00Estimation 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
    • B60W40/10Estimation 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
    • B60W40/107Longitudinal acceleration
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT 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
    • B60W40/00Estimation 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
    • B60W40/12Estimation 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 parameters of the vehicle itself, e.g. tyre models

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Mathematical Physics (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Control Of Driving Devices And Active Controlling Of Vehicle (AREA)

Abstract

The application provides a road characteristic processing method and a road characteristic processing system for a vehicle, wherein the method comprises the steps of calculating the transverse gradient and the longitudinal gradient acceleration of a road, calculating the steering wheel rotation angle compensation amount according to the transverse gradient, and calculating the wheel torque compensation amount according to the longitudinal gradient acceleration; calculating the bumping degree of the road, and setting a limiting amplitude of the steering wheel angle change rate according to the bumping degree; and judging whether the vehicle is running on the bridge or in the tunnel based on the height variation of the vehicle in the given time period. According to the technical scheme of the application, the active recognition and processing of the road characteristics are realized, the control effect of the vehicle is improved, and the running stability and safety of the vehicle are ensured.

Description

Road feature processing method and road feature processing system
Technical Field
The present application relates to the field of advanced driver assistance systems, in particular to a road feature processing method for a vehicle, and further to a road feature processing system.
Background
In recent years, automobiles are rapidly developing toward intelligence, and advanced driver assistance technology (ADVANCED DRIVER ASSIST SYSTEM, ADAS) is gradually rising. The ADAS can actively control the speed and the steering of the vehicle when necessary, can not only relieve the driver from the fatigue of driving, but also reduce or eliminate traffic accidents caused by human factors, and ensures that the automobile is safer. However, the operation of the ADAS is directly affected by the road characteristics, and the road has a transverse gradient, a longitudinal gradient, an up-and-down fluctuation (such as a deceleration strip), and the like, which can cause the vehicle to transversely or longitudinally deflect or vertically jolt, so that the dynamic parameters of the vehicle change, and the accurate control of the vehicle is affected, so that the real-time and accurate identification and processing of the road characteristics are required.
Disclosure of Invention
The present application aims to provide a road feature processing method for a vehicle and a road feature processing system to solve or alleviate at least part of the problems mentioned in the background art.
To achieve one of the foregoing objects, according to one aspect of the present application, there is provided a road feature processing method for a vehicle, the method comprising: calculating the transverse gradient and the longitudinal gradient acceleration of a road, calculating the steering wheel angle compensation amount according to the transverse gradient, and calculating the wheel torque compensation amount according to the longitudinal gradient acceleration; calculating the bumping degree of a road, and setting a limiting amplitude of the steering wheel angle change rate according to the bumping degree; whether the vehicle is traveling on a bridge or in a tunnel is determined based on the amount of change in the height of the vehicle in a given period of time.
In addition to, or as an alternative to, one or more of the above features, in further embodiments, the lateral gradient is calculated according to the following formula:
Transverse gradient
Wherein V is the longitudinal speed of the vehicle, R is the radius of curvature of the road,For the vertical acceleration of the vehicle,/>For the lateral acceleration of the vehicle,/>Gravitational acceleration.
In addition to, or as an alternative to, one or more of the above features, in a further embodiment, the steering wheel angle compensation amount is calculated according to the following formula:
steering wheel angle compensation
Where k is a calibrated quantity related to vehicle state parameters including vehicle speed, vehicle yaw rate, tire cornering stiffness, vehicle wheelbase.
In addition to, or as an alternative to, one or more of the above features, in a further embodiment, the longitudinal grade acceleration is calculated according to the following formula:
longitudinal gradient acceleration
Wherein,V is the longitudinal speed of the vehicle and t is time, which is the longitudinal acceleration of the vehicle.
In addition to, or as an alternative to, one or more of the above features, in a further embodiment, the wheel torque compensation amount is calculated according to the following formula:
wheel torque compensation amount
Where m is the mass of the vehicle and r is the tire radius of the vehicle.
In addition to one or more of the above features, or alternatively, in a further embodiment, the degree of jolt of the road is calculated based on an amount of change in vertical acceleration of the vehicle over a set time interval.
In addition to, or as an alternative to, one or more of the above features, in further embodiments, the height variation is calculated according to the following formula:
Height variation
Where t is time, t is the given time period, and β is the longitudinal gradient, which is calculated according to the following formula:
Longitudinal gradient
Wherein,Gravitational acceleration,/>Is a longitudinal gradient acceleration, which is calculated according to the following formula:
longitudinal gradient acceleration
Wherein,V is the longitudinal speed of the vehicle and t is time, which is the longitudinal acceleration of the vehicle.
In addition to or as an alternative to one or more of the above features, in a further embodiment the road feature processing method further comprises determining whether there is a bridge or tunnel within a set distance from the vehicle before calculating the altitude change, if so, calculating the altitude change.
To achieve one of the foregoing objects, according to another aspect of the present application, there is provided a road feature processing system including: the gradient information processing module is used for calculating the transverse gradient and the longitudinal gradient acceleration of the road, calculating the steering wheel angle compensation amount according to the transverse gradient and calculating the wheel torque compensation amount according to the longitudinal gradient acceleration; the jolt information processing module is used for calculating the jolt degree of a road and setting a limit amplitude of the steering wheel angle change rate according to the jolt degree; and a bridge tunnel identification module that determines whether the vehicle is traveling on a bridge or in a tunnel based on a height variation of the vehicle in a given period of time.
In addition to, or as an alternative to, one or more of the above features, in a further embodiment the grade information processing module calculates the longitudinal grade acceleration according to the following formula:
longitudinal gradient acceleration
Wherein,V is the longitudinal speed of the vehicle and t is time, which is the longitudinal acceleration of the vehicle.
In addition to, or as an alternative to, one or more of the above features, in a further embodiment the grade information processing module calculates the wheel torque compensation amount according to the following formula:
wheel torque compensation amount
Where m is the mass of the vehicle and r is the tire radius.
In addition to one or more of the above features, or alternatively, in a further embodiment, the jerk information processing module calculates the jerk of the road based on a variation in vertical acceleration of the vehicle over a set time interval.
In addition to, or as an alternative to, one or more of the above features, in further embodiments the bridge tunnel identification module calculates the altitude change according to the following formula:
Height variation
Wherein t is the time of the time,For the given period of time,/>For the longitudinal gradient, it is calculated according to the following formula:
Longitudinal gradient
Wherein,Gravitational acceleration,/>Is a longitudinal gradient acceleration, which is calculated according to the following formula:
longitudinal gradient acceleration
Wherein,V is the longitudinal speed of the vehicle and t is time, which is the longitudinal acceleration of the vehicle.
According to the road feature processing method and the road feature processing system for the vehicle, through the active recognition and processing of the road features, the accurate and timely adjustment of the vehicle control strategy is realized, the control effect of the vehicle is improved, effective assistance is provided for the operation of a driver, the driving fatigue of the driver is reduced, the running stability and safety of the vehicle are ensured, and the riding comfort of the vehicle is improved.
Drawings
The present disclosure will be more readily understood with reference to the accompanying drawings. It is to be understood that these drawings are solely for purposes of illustration and are not intended as a definition of the limits of the application. In the figure:
FIG. 1 is a block diagram of a road feature processing system according to one embodiment of the application;
FIG. 2 shows a schematic force diagram of a vehicle on a cross-slope road;
FIG. 3 shows a schematic diagram of the forces exerted by a vehicle on a cross-hill road;
FIG. 4 is a schematic view showing the change in vertical acceleration when the vehicle is driving over a deceleration strip;
FIG. 5 is a flowchart particularly illustrating sub-method B performed by the jounce information processing module according to one embodiment of the present application; and
Fig. 6 shows in particular a flow chart of a sub-method C performed by the bridge tunnel identification module according to an embodiment of the application.
Detailed Description
The application will be described in detail hereinafter with reference to exemplary embodiments in the accompanying drawings. It should be understood, however, that this application may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. These embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the application to those skilled in the art.
Furthermore, for any single technical feature described or implied in the embodiments mentioned herein, or any single technical feature shown or implied in the drawings, it is easy for a person skilled in the art to proceed with appropriate combination or deletion between these technical features (or equivalents thereof), thereby obtaining still further embodiments of the application that may not be directly mentioned herein, without departing from the technical scope of the application.
Fig. 1 is a block diagram of a road feature processing system 100 according to one embodiment of the application. The road feature processing system 100 may be communicatively coupled to an inertial measurement unit 200 (IMU, inertial Measurement Unit,), a map system 300 (or map and positioning system) of the vehicle, and a vehicle control system 400, and may include a grade information processing module 110, a jounce information processing module 120, and a bridge tunnel identification module 130. The road feature processing system 100 may receive vehicle dynamics parameter information (e.g., speed, acceleration, etc.) from the IMU and surrounding road feature information from the map system 300, process the information, then transmit the processed road feature information and vehicle control and/or regulation parameter signals to the vehicle control system 400 and feed back the processed road feature information to the map system 300, and the map system 300 may also transmit information such as vehicle position and road feature to the vehicle control system 400. The road characteristic processing system 100 of the application can actively identify and process road characteristic information and adjust the transverse and longitudinal control effects of the vehicle according to the road characteristics, thereby counteracting adverse effects of the road characteristics on vehicle control and ensuring the stability and safety of vehicle running.
In a more specific embodiment, the gradient information processing module 110 of the road feature processing system 100 may calculate the lateral gradient, the longitudinal gradient acceleration, etc. of the road, and further calculate the steering wheel angle compensation amount according to the lateral gradient, so as to counteract the influence of the lateral gradient on the vehicle control, and ensure that the vehicle runs centrally in the lane; and calculating the wheel torque compensation amount according to the longitudinal gradient acceleration so as to counteract the influence of the longitudinal gradient on the vehicle speed control and ensure the stable running of the vehicle.
The specific calculation method of each parameter in the gradient information processing module 110 is as follows, wherein the x, y and z directions are the directions of the vehicle coordinate system, that is, x represents the longitudinal direction of the vehicle and is also the direction of the vehicle running; y represents the lateral direction of the vehicle; z represents the height direction of the vehicle, and the x, y and z directions are perpendicular to each other.
(One) with respect to roads having lateral gradients
A schematic diagram of the forces exerted on a vehicle on a cross-slope road is shown in fig. 2. The method is characterized by comprising the following steps of:
in the horizontal direction:
(1)
Where V denotes the vehicle longitudinal speed, R denotes the road radius of curvature, and m denotes the vehicle mass. F z、Fy represents the force applied by the vehicle in the z and y directions, and G is the weight of the vehicle.
In the vertical direction:
(2)
The working principle of the IMU is as follows:
(3)
(4)
Wherein the method comprises the steps of Representing acceleration of the vehicle in the y-direction (lateral direction), which may be measured at the IMU,/>Representing acceleration in the z-direction (vertical) of the vehicle (which may be measured at the IMU),/>Indicating the gravitational acceleration.
The simultaneous equations (1) - (4) can give the lateral gradient of the road:
(5)
The lateral gradient may affect the lateral control effect of the vehicle, causing the vehicle to deviate to the left or right of the lane. The grade information processing module 110 may further calculate a steering wheel angle compensation amount based on the lateral grade:
(6)
Where k is a calibration quantity related to vehicle state parameters such as vehicle speed, vehicle yaw rate, tire cornering stiffness, vehicle wheelbase, etc.
The road feature processing system 100 may send this steering wheel angle compensation amount information to the vehicle control system 400, which is then used to superimpose the steering wheel angle to eliminate or mitigate the effect of the lateral gradient.
(II) with respect to roads having longitudinal gradients
Fig. 3 shows a schematic diagram of the load applied to a vehicle on a cross slope. The method is characterized by comprising the following steps of:
(7)
(8)
(9)
wherein F x is the resultant force applied to the running direction of the vehicle, m is the mass of the vehicle body, May be inertial acceleration measured by the IMU in the direction of travel of the vehicle,/>For longitudinal gradient acceleration,/>The vehicle acceleration is determined from the vehicle speed.
Longitudinal gradient acceleration can be calculated by simultaneous equations (7) (8) (9):
(10)
the compensation torque which the vehicle power system should send at the wheel end can be calculated according to the longitudinal gradient acceleration:
(11)
Where T s is the wheel torque compensation amount for the longitudinal slope and r is the tire radius. The wheel torque compensation amount is used to compensate for the effect of the longitudinal slope on vehicle control. The wheel torque compensation quantity can enable the torque output by the power system on the slope to be more accurate, and is beneficial to better controlling the longitudinal speed of the vehicle.
In addition, the longitudinal gradient of the road can also be found according to the following formula:
(12)
In a further embodiment, the bump information processing module 120 of the road feature processing system 100 is configured to calculate a bump degree of a road, and set a limiting magnitude of a steering wheel angle change rate according to the bump degree, so as to limit the steering wheel angle change rate and avoid severe shake of the steering wheel caused by bump of the leading road.
Fig. 4 shows a schematic view of the change in vertical acceleration when the vehicle passes over a deceleration strip. The jerk information processing module 120 may calculate the degree of jerk of the road based on the amount of change in the vertical acceleration of the vehicle during the set time interval. For example, the vertical acceleration is obtained within 0.1sMaximum value/>And minimum/>Then, the change of the vertical acceleration within 0.1s can be calculated:
(13)
According to The pitch information processing module 120 may transmit the pitch degree to the vehicle control system 400 while transmitting the limited magnitude of the steering wheel angle change rate to the vehicle control system 400 to avoid severe steering wheel sway.
In one embodiment, the bridge tunnel identification module 130 of the road feature processing system 100 determines whether the vehicle is traveling on a bridge or in a tunnel based on the amount of change in the height of the vehicle over a given period of time. When it is recognized that the vehicle is driving on the bridge or driving into the tunnel, a corresponding signal may be generated to the vehicle control system 400 to enable the vehicle to perform a corresponding control adjustment for such driving conditions, so as to ensure a smooth and safe driving of the vehicle on the bridge or in the tunnel.
In a more specific embodiment, the bridge tunnel recognition module 130 may first determine whether a bridge or a tunnel is present near the surrounding vehicle according to the road information provided by the map system 300, and if the bridge or the tunnel is not present near the surrounding vehicle, determine that the vehicle is not driving on the bridge or driving into the tunnel. If a bridge or a tunnel exists nearby, calculating the height variation h of the vehicle in a certain time interval father:
(14)
where β is the longitudinal grade of the road, which can be calculated according to equation (12). When h is greater than a first threshold h A (which is a positive value), determining that the vehicle is driving on the bridge or out of the tunnel, so that a corresponding signal can be sent to the vehicle control system 400 to trigger the bridge control mode of the vehicle or the tunnel control mode of exiting the vehicle; when h is less than the second threshold h B (which is a negative value), it is determined that the vehicle is driving down the bridge or into the tunnel, so that a corresponding signal may be sent to the vehicle control system 400 to exit the bridge mode or trigger the tunnel control mode. Between triggering and exiting the corresponding mode, the mode is maintained. Therefore, when the vehicle runs on the bridge or in the tunnel, the corresponding control mode can be switched, and the safe and stable running of the vehicle in the bridge or the tunnel is ensured. In an alternative embodiment, the bridge control mode or the tunnel control mode may be integrated into a bridge tunnel mode, and triggering or exiting of the mode is performed according to the value of h and the corresponding bridge or tunnel road condition.
Under such a structure, the road feature processing system 100 described herein realizes accurate adjustment of the vehicle control strategy by identifying and processing the road features, improves the control effect of the vehicle, ensures the stability and safety of the vehicle running, and improves the riding comfort of the vehicle.
With the aforementioned road feature processing system 100, there is also provided a road feature processing method including the following simultaneous or non-simultaneous sub-methods that can be performed by the above gradient information processing module 110, the bump information processing module 120, and the bridge tunnel recognition module 130, respectively:
Sub-method A: calculating the transverse gradient and the longitudinal gradient acceleration of the road, calculating the steering wheel angle compensation amount according to the transverse gradient, and calculating the wheel torque compensation amount according to the longitudinal gradient acceleration;
sub-method B: calculating the bumping degree of the road, and setting a limiting amplitude of the steering wheel angle change rate according to the bumping degree;
sub-method C: whether the vehicle is traveling on the bridge or in the tunnel is determined based on the amount of change in the height of the vehicle in a given period of time.
Fig. 5 specifically shows a flowchart of a sub-method B performed by the jounce information processing module 120 according to one embodiment of the present application, comprising the steps of:
s110: low-pass filtering is carried out on the vertical acceleration;
s120: calculating the variation of the vertical acceleration of the vehicle in a set time interval;
s130: determining the bumpy degree of the road based on the variation of the vertical acceleration;
s140: the limit amplitude of the steering wheel angle change rate is set based on the degree of jolt of the road.
Fig. 6 specifically illustrates a flowchart of sub-method C performed by the bridge tunnel identification module 130 according to one embodiment of the application, which may include the steps of:
s210: judging whether a bridge or a tunnel exists within a set distance range from the vehicle according to the information from the map system 300, if yes, executing step S220, if not, executing step S250;
S220: calculating the height variation h of the vehicle in a given time period;
S230: judging whether a bridge exists in a set distance range from the vehicle, if so, executing step S231, and if not, executing step S241;
s231: judging whether h is greater than a first threshold h A, if yes, executing step S232, if no, executing step S250;
s232: judging that the vehicle drives on the bridge;
s233: judging whether h is smaller than a second threshold h B, if yes, executing step S234, if no, returning to step 232;
s234: judging that the vehicle drives down the bridge;
S241: judging whether h is smaller than a second threshold h B, if yes, executing step S242, if no, executing step S250;
s242: judging that the vehicle is driven into a tunnel;
s243: judging whether h is greater than a first threshold h A, if yes, executing step S244, if no, returning to step 242;
S244: judging that the vehicle exits the tunnel;
S250: and judging that the vehicle does not run on the bridge or in the tunnel.
In other embodiments, step S232 may further include signaling the vehicle control system 400 to trigger a bridge control mode of the vehicle, step S234 may include signaling the vehicle control system 400 to exit the bridge control mode of the vehicle, step S242 may include signaling the vehicle control system 400 to trigger a tunnel control mode of the vehicle, and step S244 may include signaling the vehicle control system 400 to exit the tunnel control mode of the vehicle.
According to the road characteristic processing method, the road characteristic information can be accurately identified and processed in real time, and the vehicle control system is combined to perform real-time adjustment and optimization on the vehicle control, so that the adaptability of the vehicle control to different road conditions is obviously improved, the running stability and safety of the vehicle under various road conditions are improved, the driving fatigue of a driver is reduced, and the riding comfort of a passenger is improved.
The above examples mainly illustrate the road feature processing system and the road feature processing method of the present application. Although only a few embodiments of the present application have been described, those skilled in the art will appreciate that the present application can be embodied in many other forms without departing from the spirit or scope thereof. Accordingly, the illustrated examples and embodiments are to be considered as illustrative and not restrictive, and the application is intended to cover various modifications and substitutions without departing from the spirit and scope of the technical solutions of the application.

Claims (15)

1. A road feature processing method for a vehicle, the method comprising:
calculating the transverse gradient and the longitudinal gradient acceleration of a road, calculating the steering wheel angle compensation amount according to the transverse gradient, and calculating the wheel torque compensation amount according to the longitudinal gradient acceleration;
calculating the bumping degree of a road, and setting a limiting amplitude of the steering wheel angle change rate according to the bumping degree; and
Whether the vehicle is traveling on a bridge or in a tunnel is determined based on the amount of change in the height of the vehicle in a given period of time.
2. The method for processing road characteristics according to claim 1, wherein,
The lateral gradient is calculated according to the following formula:
Transverse gradient
Wherein V is the longitudinal speed of the vehicle, R is the radius of curvature of the road,For the vertical acceleration of the vehicle,/>For the lateral acceleration of the vehicle,/>Gravitational acceleration.
3. The method for processing road characteristics according to claim 2, wherein,
The steering wheel angle compensation amount is calculated according to the following formula:
steering wheel angle compensation
Where k is a calibrated quantity related to vehicle state parameters including vehicle speed, vehicle yaw rate, tire cornering stiffness, vehicle wheelbase.
4. The method for processing road characteristics according to claim 1, wherein,
Calculating the longitudinal gradient acceleration according to the following formula:
Longitudinal gradient acceleration
Wherein,V is the longitudinal speed of the vehicle and t is time, which is the longitudinal acceleration of the vehicle.
5. The road feature processing method according to claim 4, characterized in that the wheel torque compensation amount is calculated according to the following formula:
wheel torque compensation amount
Where m is the mass of the vehicle and r is the tire radius of the vehicle.
6. The road characteristic processing method according to claim 1, characterized in that the degree of jolt of the road is calculated based on a variation amount of vertical acceleration of the vehicle in a set time interval.
7. The method for processing road characteristics according to claim 1, wherein,
The height variation is calculated according to the following formula:
Height variation
Wherein t is the time of the time,For the given period of time,/>For the longitudinal gradient, it is calculated according to the following formula:
Longitudinal gradient
Wherein,Gravitational acceleration,/>Is a longitudinal gradient acceleration, which is calculated according to the following formula:
longitudinal gradient acceleration
Wherein,V is the longitudinal speed of the vehicle and t is time, which is the longitudinal acceleration of the vehicle.
8. The road feature processing method according to claim 7, characterized in that the road feature processing method further comprises determining whether there is a bridge or a tunnel within a set distance range from the vehicle before calculating the height variation, and if so, calculating the height variation.
9. A road feature processing system for a vehicle, the road feature processing system comprising:
the gradient information processing module is used for calculating the transverse gradient and the longitudinal gradient acceleration of the road, calculating the steering wheel angle compensation amount according to the transverse gradient and calculating the wheel torque compensation amount according to the longitudinal gradient acceleration;
The jolt information processing module is used for calculating the jolt degree of a road and setting a limit amplitude of the steering wheel angle change rate according to the jolt degree; and
And the bridge tunnel identification module is used for judging whether the vehicle runs on a bridge or in a tunnel or not based on the height variation of the vehicle in a given time period.
10. The road feature processing system of claim 9, wherein,
The gradient information processing module calculates the lateral gradient according to the following formula:
Transverse gradient
Wherein V is the longitudinal speed of the vehicle, R is the radius of curvature of the road,For the vertical acceleration of the vehicle,/>For the lateral acceleration of the vehicle,/>Gravitational acceleration.
11. The road feature processing system of claim 10, wherein,
The gradient information processing module calculates the steering wheel angle compensation amount according to the following formula:
steering wheel angle compensation
Where k is a calibrated quantity related to vehicle state parameters including vehicle speed, vehicle yaw rate, tire cornering stiffness, vehicle wheelbase.
12. The road feature processing system of claim 9, wherein,
The gradient information processing module calculates the longitudinal gradient acceleration according to the following formula:
longitudinal gradient acceleration
Wherein,V is the longitudinal speed of the vehicle and t is time, which is the longitudinal acceleration of the vehicle.
13. The road feature processing system of claim 12, wherein,
The gradient information processing module calculates the wheel torque compensation amount according to the following formula:
wheel torque compensation amount
Where m is the mass of the vehicle and r is the tire radius.
14. The road feature processing system according to claim 9, wherein the jerk information processing module calculates the jerk of the road based on a variation in vertical acceleration of the vehicle over a set time interval.
15. The road feature processing system of claim 9, wherein,
The bridge tunnel recognition module calculates the height variation according to the following formula:
Height variation
Wherein t is the time of the time,For the given period of time,/>For the longitudinal gradient, it is calculated according to the following formula:
Longitudinal gradient
Wherein,Gravitational acceleration,/>Is a longitudinal gradient acceleration, which is calculated according to the following formula:
longitudinal gradient acceleration
Wherein,V is the longitudinal speed of the vehicle and t is time, which is the longitudinal acceleration of the vehicle.
CN202211528196.2A 2022-12-01 2022-12-01 Road feature processing method and road feature processing system Pending CN118124587A (en)

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Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
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Publications (1)

Publication Number Publication Date
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