CN112114580B - ACC simulation test system and method - Google Patents
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Abstract
The application discloses an ACC simulation test system and method, relating to the technical field of simulation test; the system comprises a virtual scene model, a sensor model, a positioning model, a feedback module, an ACC algorithm carrier, an actuator model and a vehicle model; the method comprises the following steps: providing a vehicle model and a virtual scene model for generating virtual scene information, and generating a sensor target signal based on the virtual scene information and the vehicle model; collecting vehicle positioning parameters and feedback parameters of the vehicle model, and generating control parameters according to the sensor target signals, the vehicle positioning parameters and the feedback parameters; and driving the vehicle model based on the control parameters to generate vehicle pose information and execution state information. According to the method and the device, the vehicle pose information and the execution state information are updated according to the control parameters, a closed-loop simulation test is formed, and the reliability, the running efficiency and the algorithm iteration efficiency of the test are effectively improved.
Description
Technical Field
The application relates to the technical field of simulation testing, in particular to an ACC simulation testing system and method.
Background
An ACC (Adaptive Cruise Control) is an automobile Control system that controls braking and driving of a vehicle to keep the vehicle at a certain distance or at a certain speed, and with the gradual development of driving assistance functions, an L2-grade semi-automatic intelligent driving assistance system is gradually popularized, and at present, the ACC is continuously applied to general vehicles.
In the development process, the ACC function needs to be tested, and in the past, the test for the ACC function is usually implemented by a real vehicle test, for example, a patent with publication number CN107678418B and named as an adaptive cruise test method and device discloses a scheme for simulating real driving conditions to implement the ACC test. Because the real vehicle test needs to change the vehicle and load various complex scenes to simulate complex and various traffic conditions, and simultaneously needs to invest a large amount of testing personnel and equipment, the whole test period is long, the efficiency is low, the cost is high, and the requirement of rapid research and development rhythm is difficult to meet.
Disclosure of Invention
Aiming at the defects of the prior art, an ACC simulation test system and method are provided, and the problems of long test period, low efficiency and high cost of the ACC function applied to the automobile in the prior art are solved.
In order to achieve the above object, the present application provides the following technical solutions:
in one aspect, an ACC simulation test system is provided and comprises a virtual scene model, a sensor model, a positioning model, a feedback module, an ACC algorithm carrier, an actuator model and a vehicle model;
the virtual scene model is used for providing virtual scene information;
the input end of the sensor model is connected with the output ends of the vehicle model and the virtual scene model, and the output end of the sensor model is connected with the input end of the ACC algorithm carrier, so that a sensor target signal is generated based on the virtual scene information and the vehicle model;
the input end of the positioning model is connected with the output end of the vehicle model, and the output end of the positioning model is connected with the input end of the ACC algorithm carrier, so that vehicle positioning parameters are acquired based on the vehicle model;
the input end of the feedback module is connected with the output end of the vehicle model, and the output end of the feedback module is connected with the input end of the ACC algorithm carrier and used for collecting feedback parameters based on the vehicle model;
the output end of the ACC algorithm carrier is connected with the input end of the actuator model and used for generating control parameters based on the sensor target signals, the vehicle positioning parameters and the feedback parameters;
the output end of the actuator model is connected with the input end of the vehicle model and used for driving the vehicle model to generate vehicle pose information and execution state information based on the control parameters.
Optionally, the control parameter includes one or more of a deceleration parameter, a motor torque parameter, a gear parameter, and an electronic hand brake parameter.
Optionally, the actuator model includes:
the electronic control brake system is used for controlling the opening degree of a brake pedal of the vehicle model according to the deceleration parameter, the electronic control driving system is used for controlling the motor torque of the vehicle model according to the motor torque parameter, the electronic control gear is used for controlling the gear of the vehicle model according to the gear parameter, and/or the electronic control hand brake is used for controlling the hand brake state of the vehicle model according to the electronic hand brake parameter;
the execution state information includes:
one or more of pedal opening state information, motor torque state information, gear information and hand brake state information;
the feedback parameters include one or more of wheel speed parameters, wheel pulse parameters, and motor torque parameters.
Optionally, the ACC simulation test system further includes a vehicle state control module, an output end of the vehicle state control module is connected to an input end of the ACC algorithm carrier, and is configured to generate at least one abnormal state parameter and transmit the abnormal state parameter to the ACC algorithm carrier, where the abnormal state parameter is used to simulate an abnormal vehicle door state, an abnormal tire pressure state, an abnormal vehicle interior dome lamp state, or an abnormal vehicle window state;
and the ACC algorithm carrier is used for generating a stopping instruction and outputting the stopping instruction to the actuator model when at least one abnormal state parameter is received, so that the actuator model is suspended.
Optionally, the virtual scene model includes:
the lane line scene sub-model is used for generating lane line information, and the lane line information comprises lane line color information and lane line shape information;
and the obstacle scene submodel is used for generating obstacle information, wherein the obstacle information comprises dynamic obstacle information and static obstacle information.
In another aspect, an ACC simulation test method implemented based on the ACC simulation test system described above includes:
providing a vehicle model and a virtual scene model for generating virtual scene information, and generating a sensor target signal based on the virtual scene information and the vehicle model;
collecting vehicle positioning parameters and feedback parameters of the vehicle model, and generating control parameters according to the sensor target signals, the vehicle positioning parameters and the feedback parameters;
and driving the vehicle model based on the control parameters to generate vehicle pose information and execution state information.
Optionally, the control parameters include a deceleration parameter, a motor torque parameter, a gear parameter and/or an electronic hand brake parameter;
the execution state information includes:
one or more of pedal opening state information, motor torque state information, gear information and hand brake state information.
Optionally, the feedback parameter comprises one or more of a wheel speed parameter, a wheel impulse parameter and a motor torque parameter.
Optionally, the ACC simulation test method further includes:
generating at least one abnormal state parameter for simulating an abnormal vehicle door state, an abnormal tire pressure state, an abnormal vehicle interior dome lamp state or an abnormal vehicle window state;
suspending driving of the vehicle model in accordance with at least one abnormal-state parameter.
Optionally, the virtual scene information includes:
lane line information including lane line color information and lane line shape information;
and the obstacle information comprises dynamic obstacle information and static obstacle information.
Compared with the prior art, the method has the following beneficial effects:
the application provides an ACC simulation test system and method, which do not depend on real vehicle test, provide a simulated driving environment by using virtual scene information, finally generate control parameters by using vehicle pose information and execution state information of a vehicle in combination with the virtual scene information, and realize the update of the vehicle pose information and the execution state information according to the control parameters, thereby forming closed-loop simulation test, effectively improving the reliability and the operation efficiency of the test, and further improving the algorithm iteration efficiency in mass production.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
Fig. 1 is a block diagram of an ACC simulation test system provided in the present application;
fig. 2 is a block diagram of a virtual scene model in an ACC simulation test system according to the present application;
FIG. 3 is a block diagram illustrating an actuator model in an ACC simulation test system according to the present disclosure;
fig. 4 is a flowchart of an ACC simulation test method provided in the present application;
fig. 5 is another flowchart of an ACC simulation test method provided in the present application.
In the above figures: 11. an ACC algorithm vector; 12. an actuator model; 121. an electronically controlled braking system; 122. an electrically controlled drive system; 123. an electric control gear; 124. an electric control hand brake; 20. a vehicle model; 30. a virtual scene model; 31. a lane line scene sub-model; 32. an obstacle scene sub-model; 40. a sensor model; 50. positioning the model; 60. a feedback module; 70. a vehicle state control module.
Detailed Description
In order to make the objects, features and advantages of the present application more obvious and understandable, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the embodiments described below are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The technical scheme of the application is further explained by the specific implementation mode in combination with the attached drawings.
Referring to fig. 1, in one aspect, the present application provides an ACC simulation test system, which includes an ACC algorithm carrier 11, an actuator model 12, a vehicle model 20, a virtual scene model 30, a sensor model 40, a positioning model 50, and a feedback module 60.
The vehicle model 20 is used for simulating a vehicle to form a virtual vehicle, and generating vehicle pose information and execution state information based on the current pose and execution state calculation of the simulated virtual vehicle.
It is understood that the vehicle model 20 may be implemented based on a vehicle dynamics model in the prior art, such as a Carsim model, and the like, and is not limited herein. The execution state information includes one or more of brake pedal opening state information, motor torque state information, gear information, and handbrake state information calculated for the modeled vehicle model 20; furthermore, the execution state information is parameterized information.
Referring to fig. 2, the virtual scene model 30 includes a lane line scene sub-model 31 and an obstacle scene sub-model 32.
The lane line scene sub-model 31 is used to construct virtual lane line features to generate lane line information, where the generated lane line information includes lane line color information and lane line shape information, so as to simulate different types of lane lines in a road.
The obstacle scene submodel 32 is used to construct virtual obstacles, which may include signal lights, vehicles, pedestrians, buildings, or road signs, etc., to generate obstacle information; specifically, the obstacle information is divided into dynamic obstacle information and static obstacle information according to dynamic and static obstacles, so that the simulation of the driving environment is more practical.
The sensor model 40 includes a virtual sensor, an input end of which is connected to an output end of the vehicle model 20, and an output end of which is connected to an input end of the ACC algorithm carrier 11, and is configured to form sensor data for the virtual scene acquisition data constructed by the virtual scene model 30, and generate a sensor target signal based on the sensor data, which is used as a reference for driving the vehicle model 20 to perform a next action. In particular, the virtual sensor may include a laser radar sensor, a positioning sensor, and the like, and an image sensor, and the like, without being limited thereto.
For example, the sensor data generated by the sensor model 40 based on lane line information may include lane line parameters corresponding to different lane line colors, lane line shapes, and combinations thereof; the sensor data generated based on the obstacle information may include a longitudinal distance and a lateral distance from the target obstacle, and when the target obstacle is a dynamic obstacle, a longitudinal and/or lateral velocity, and a longitudinal and/or lateral velocity acceleration of the target obstacle may also be generated.
The input end of the positioning model 50 is connected with the output end of the vehicle model 20, and the output end of the positioning model is connected with the input end of the ACC algorithm carrier 11; the Positioning model 50 includes an Inertial Measurement Unit (IMU) Unit and a Global Positioning System (GPS) module, and is configured to generate vehicle Positioning parameters including data such as three-axis angular velocity, three-axis acceleration, and vehicle coordinates according to vehicle pose information.
Since the state of the vehicle model 20 changes from moment to moment during the test, and the relative position and distance between the vehicle model 20 and the target obstacle change, the sensor model 40 needs to process the sensor data in combination with the vehicle positioning parameters of the vehicle model 20 and finally generate the sensor target signal.
A feedback module 60, the input end of which is connected with the output end of the vehicle model 20, and the output end of which is connected with the input end of the ACC algorithm carrier 11; specifically, the feedback module 60 includes a virtual sensor, and is configured to acquire a feedback parameter for the vehicle pose information and the execution state information, and transmit the feedback parameter to the ACC algorithm carrier 11 to achieve the purpose of feedback, so as to improve the reliability of the simulation test.
The ACC algorithm carrier 11 is connected with the sensor model 40, the positioning model 50, the feedback module 60 and the vehicle model 20, and the output end of the ACC algorithm carrier is connected with the actuator model 12, so as to generate control parameters based on the vehicle positioning parameters, the sensor target signals and the feedback parameters, and output the control parameters to the actuator model 12 to drive the vehicle model 20 to perform virtualized driving actions, so that the vehicle model 20 calculates and updates the vehicle pose information and the execution state information.
In this embodiment, the ACC algorithm carrier 11 may be a hardware controller or a virtual storage medium.
Specifically, the control parameters generated by the ACC algorithm carrier 11 include one or more of deceleration parameters, motor torque parameters, gear parameters and electronic handbrake parameters.
Referring to fig. 3, the actuator model 12 includes:
the electronic control brake system 121 is used for controlling the opening degree of a brake pedal of the vehicle model according to the deceleration parameters, the electronic control driving system 122 is used for controlling the motor torque of the vehicle model according to the motor torque parameters, the electronic control gear 123 is used for controlling the gear of the vehicle model according to the gear parameters, and/or the electronic control hand brake 124 is used for controlling the hand brake state of the vehicle model according to the electronic hand brake parameters.
Further, the vehicle model 20 generates corresponding execution state information according to the control parameters, and updates the previously generated execution state information, thereby forming a test closed loop.
Based on the foregoing embodiment, further, the ACC simulation test system provided by the present embodiment further includes a vehicle state control module 70 for simulating an abnormal state. The vehicle state control module 70 is configured to generate at least one abnormal state parameter and transmit the abnormal state parameter to the ACC algorithm carrier 11, and when the ACC algorithm carrier 11 receives the at least one abnormal state parameter, generate a suspension instruction and output the suspension instruction to the actuator model 12, so that the actuator model 12 is suspended from operating, thereby testing the operating condition of the ACC simulation test system in the abnormal state.
In the embodiment, the abnormal state parameter is used for simulating an abnormal vehicle door state, an abnormal tire pressure state, an abnormal vehicle interior ceiling lamp state or an abnormal vehicle window state; it is understood that the abnormal state parameter can also be used to simulate an abnormal state other than the above-listed types that may create a safety hazard during driving of the vehicle, and is not limited herein.
When the vehicle state control module 70 generates two or more abnormal state parameters, the types of the respective abnormal state parameters are different.
If the ACC algorithm carrier 11 fails to control the system to pause or stop running when receiving at least one abnormal state parameter, the algorithm needs to be re-optimized to improve the ACC function, and the safety of the semi-automatic driving assistance system of the automobile is improved.
Referring to fig. 4, on the other hand, the present embodiment provides an ACC simulation test method, which is implemented based on the ACC simulation test system provided in the above embodiments, and includes the following steps:
and S11, providing a vehicle model and a virtual scene model for generating virtual scene information, and generating a sensor target signal based on the virtual scene information and the vehicle model.
And S12, collecting the vehicle positioning parameters and the feedback parameters of the vehicle model, and generating control parameters according to the sensor target signals, the vehicle positioning parameters and the feedback parameters.
And S13, driving the vehicle model based on the control parameters, and generating vehicle position and attitude information and execution state information.
In step S11, the virtual scene information includes lane line information and obstacle information.
The lane line information comprises lane line color information and lane line shape information; the combination of lane line color information and lane line shape information can constitute one type of lane line for each type of lane line to collect corresponding sensor data.
The obstacle information includes dynamic obstacle information and static obstacle information. Specifically, the dynamic obstacle information and the static obstacle information may include human, object, and vehicle types of obstacles, respectively, so that the simulation of the driving environment is more realistic.
Since the state of the vehicle model 20 changes from moment to moment during the test, and the relative position and distance between the vehicle model 20 and the target obstacle change, it is necessary to process the sensor data according to the vehicle positioning parameters and finally generate the sensor target signal.
In step S12, the feedback parameters include one or more of wheel speed parameters, wheel impulse parameters and motor torque parameters; it will be appreciated that the feedback parameters may also include other parameters generated during driving of the vehicle, and that several types of reference in which the generated control parameters can be referred to are herein chosen as references and do not constitute a limitation on the present embodiment.
In this embodiment, a feedback parameter may be acquired according to the vehicle pose information and the execution state information calculated and output by the vehicle model 20, a control parameter may be generated based on the feedback parameter in combination with the vehicle positioning parameter and the sensor target signal, and the vehicle model 20 may be driven to perform a virtualized driving action based on the control parameter, so that the vehicle model 20 may calculate and update the vehicle pose information and the execution state information, thereby improving the reliability of the simulation test.
The control parameters comprise one or more of deceleration parameters, motor torque parameters, gear parameters and electronic hand brake parameters.
It is to be understood that the execution state information is one or more of brake pedal opening state information, motor torque state information, gear information, and handbrake state information calculated for the modeled vehicle model 20; furthermore, the execution state information is parameterized information.
Referring to fig. 5, in order to test the operation condition of the ACC simulation test system in an abnormal state, the ACC simulation test method further includes the following steps:
and S21, generating at least one abnormal state parameter for simulating an abnormal vehicle door state, an abnormal tire pressure state, an abnormal vehicle interior ceiling lamp state or an abnormal vehicle window state.
In the embodiment, the abnormal state parameter is used for simulating an abnormal vehicle door state, an abnormal tire pressure state, an abnormal vehicle interior ceiling lamp state or an abnormal vehicle window state; it is understood that the abnormal state parameter can also be used to simulate an abnormal state other than the above-listed types that may create a safety hazard during driving of the vehicle, and is not limited herein.
When two or more abnormal state parameters are used, the types of the abnormal state parameters are different.
And S22, suspending driving of the vehicle model according to the at least one abnormal state parameter.
When at least one abnormal state parameter is generated, the system fails to suspend driving of the vehicle model, and then the algorithm needs to be re-optimized to improve the ACC function, so that the safety of the semi-automatic driving auxiliary system of the automobile is improved.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (7)
1. An ACC simulation test system is characterized by comprising a virtual scene model, a sensor model, a positioning model, a feedback module, an ACC algorithm carrier, an actuator model, a vehicle model and a vehicle state control module;
the virtual scene model is used for providing virtual scene information;
the input end of the sensor model is connected with the output ends of the vehicle model and the virtual scene model, and the output end of the sensor model is connected with the input end of the ACC algorithm carrier, so that a sensor target signal is generated based on the virtual scene information and the vehicle model;
the input end of the positioning model is connected with the output end of the vehicle model, and the output end of the positioning model is connected with the input end of the ACC algorithm carrier, so that vehicle positioning parameters are acquired based on the vehicle model;
the input end of the feedback module is connected with the output end of the vehicle model, and the output end of the feedback module is connected with the input end of the ACC algorithm carrier and used for collecting feedback parameters based on the vehicle model;
the output end of the ACC algorithm carrier is connected with the input end of the actuator model and used for generating control parameters based on the sensor target signals, the vehicle positioning parameters and the feedback parameters; the control parameters comprise one or more of deceleration parameters, motor torque parameters, gear parameters and electronic hand brake parameters;
the output end of the actuator model is connected with the input end of the vehicle model and is used for driving the vehicle model to generate vehicle pose information and execution state information based on the control parameters;
the virtual scene model includes:
the obstacle scene submodel is used for generating obstacle information, and the obstacle information comprises dynamic obstacle information and static obstacle information;
when the target obstacle is a dynamic obstacle, the sensor model generates longitudinal and/or lateral speed and longitudinal and/or lateral speed acceleration of the target obstacle;
the output end of the vehicle state control module is connected with the input end of the ACC algorithm carrier and is used for generating at least one abnormal state parameter and transmitting the abnormal state parameter to the ACC algorithm carrier, and the abnormal state parameter is used for simulating an abnormal vehicle door state, an abnormal tire pressure state, an abnormal vehicle interior ceiling lamp state or an abnormal vehicle window state;
and the ACC algorithm carrier is used for generating a stopping instruction and outputting the stopping instruction to the actuator model when at least one abnormal state parameter is received, so that the actuator model is suspended.
2. The ACC simulation test system of claim 1, wherein the actuator model comprises:
the electronic control brake system is used for controlling the opening degree of a brake pedal of the vehicle model according to the deceleration parameter, the electronic control driving system is used for controlling the motor torque of the vehicle model according to the motor torque parameter, the electronic control gear is used for controlling the gear of the vehicle model according to the gear parameter, and/or the electronic control hand brake is used for controlling the hand brake state of the vehicle model according to the electronic hand brake parameter;
the execution state information includes:
one or more of pedal opening state information, motor torque state information, gear information and hand brake state information;
the feedback parameters include one or more of wheel speed parameters, wheel pulse parameters, and motor torque parameters.
3. The ACC simulation test system of claim 1, wherein the virtual scene model further comprises:
and the lane line scene sub-model is used for generating lane line information, and the lane line information comprises lane line color information and lane line shape information.
4. An ACC simulation test method, comprising:
providing a vehicle model and a virtual scene model for generating virtual scene information, and generating a sensor target signal based on the virtual scene information and the vehicle model; the virtual scene information includes: obstacle information including dynamic obstacle information and static obstacle information; when the target obstacle is a dynamic obstacle, the sensor target signal comprises longitudinal and/or lateral velocity and longitudinal and/or lateral velocity acceleration of the target obstacle;
collecting vehicle positioning parameters and feedback parameters of the vehicle model, and generating control parameters according to the sensor target signals, the vehicle positioning parameters and the feedback parameters; the control parameters comprise one or more of deceleration parameters, motor torque parameters, gear parameters and electronic hand brake parameters;
driving the vehicle model based on the control parameters to generate vehicle pose information and execution state information;
generating at least one abnormal state parameter for simulating an abnormal vehicle door state, an abnormal tire pressure state, an abnormal vehicle interior dome lamp state or an abnormal vehicle window state; suspending driving of the vehicle model in accordance with at least one abnormal-state parameter.
5. The ACC simulation testing method of claim 4, wherein the execution state information comprises:
one or more of pedal opening state information, motor torque state information, gear information and hand brake state information.
6. The ACC simulation test method of claim 4, wherein the feedback parameters comprise one or more of wheel speed parameters, wheel impulse parameters, and motor torque parameters.
7. The ACC simulation testing method according to claim 4, wherein the virtual scenario information further includes:
the lane line information includes lane line color information and lane line shape information.
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