CN110647053A - Automatic driving simulation method and system - Google Patents
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Abstract
The embodiment of the invention relates to an automatic driving simulation method and system, wherein the method comprises the following steps: an environment modeling module in the automatic driving simulation system acquires environment modeling parameters and generates a simulation environment model according to the environment modeling parameters; an automatic driving module in the automatic driving simulation system monitors hardware signals; when the hardware signal is empty, acquiring a simulated environment model from an environment modeling module in the automatic driving simulation system through a data interaction module in the automatic driving simulation system; generating updating data of the simulation scene according to the simulation environment model and the simulation data; when the hardware signal is not empty, acquiring sensor data; generating updating data of the simulation scene according to the sensor data, feeding the simulation scene data back to the automatic driving software system through the data interaction module, and starting the next simulation; and the environment modeling module acquires the updating data of the simulation scene and updates the simulation environment model according to the updating data of the simulation scene so as to display the current simulation environment state.
Description
Technical Field
The invention relates to the field of automatic driving, in particular to an automatic driving simulation method and system.
Background
In recent years, algorithm research and scene application in the field of automatic driving are performed well, the safety and stability requirements of a system are increasingly specified, and a large amount of experiments are required for verification. The verification scene needs to cover common traffic scenes such as conventional urban expressway, traffic light road sections, intersections, roadside parking road sections and the like, the verification mode needs to include special traffic scenes such as dangerous scenes and accident scenes, and meanwhile, the verification scheme needs to be rapidly realized and repeatedly carried out. Therefore, a convenient and effective laboratory simulation verification method is needed for the automatic driving system to perform verification tests, so that the safety of the verification process is improved, the verifiable scene range is expanded, and the experimental verification cost is saved.
At present, the verification method of the automatic driving system mainly comprises: the method comprises verification self-test during software writing, real vehicle experiment after automatic driving system integration, and integrated simulation method for an end-to-end system based on deep learning and other methods. The self-test verification during software writing is generally carried out by a code writer, the verification test range is easy to limit, the problem of a code level is mainly covered, and the problem of an integrated system is not solved. The real-vehicle experiment after the integration of the automatic driving system is limited by the field, can not cover all traffic scenes, and can not carry out repeatability verification on special traffic scenes due to the consideration of safety; due to cost limitation, the accident scene cannot be completely reconstructed to carry out real vehicle experiments. The input and output interfaces of the integrated simulation method for the end-to-end system based on the methods such as deep learning are fixed, the integrated simulation method is mainly for the end-to-end integrated system and is not suitable for a self-defined algorithm system, meanwhile, the simulation system needs a large amount of real data to be trained to generate a simulation scene, the authenticity of the simulation scene needs to be continuously examined, and the scene is generally a complex scene and cannot be subjected to gradient verification from simple functions to the complex scene.
Disclosure of Invention
The invention aims to provide an automatic driving simulation method aiming at the defects of the prior art.
In order to achieve the above object, in a first aspect, an embodiment of the present invention provides an automatic driving simulation method, including:
an environment modeling module in the automatic driving simulation system acquires environment modeling parameters and generates a simulation environment model according to the environment modeling parameters;
an automatic driving module in the automatic driving simulation system monitors hardware signals;
when the hardware signal is empty, acquiring a simulated environment model from an environment modeling module in the automatic driving simulation system through a data interaction module in the automatic driving simulation system;
generating updating data of a simulation scene according to the simulation environment model and the simulation data;
when the hardware signal is not empty, acquiring sensor data;
generating updating data of a simulation scene according to the sensor data;
the environment modeling module acquires the updating data of the simulation scene and updates the simulation environment model according to the updating data of the simulation scene.
Preferably, before the environment modeling module obtains the environment modeling parameters and generates the simulation environment model according to the environment modeling parameters, the method further includes:
the environment modeling module acquires an environment scene type and determines whether the environment scene type is a first type;
and when the environment scene type is a first type, obtaining environment modeling parameters, and generating a simulation environment model according to the environment modeling parameters.
Further preferably, when the environmental scene type is not the first type, the method further includes:
the environment modeling module determines whether real scene data exists;
when the real scene data exist, generating a simulation environment model according to the real scene data;
and when the real scene data does not exist, generating a simulation environment model according to a preset environment model.
Preferably, the environment modeling parameters include: map information and traffic participant information.
Further preferably, the map information includes: static environment parameters and dynamic environment parameters;
the static environment parameters include: road geological parameters, road topographic parameters, road characteristic parameters and building parameters;
the dynamic environment parameters include: a weather parameter;
the traffic participant information includes: traffic participant type information, traffic participant location information, and traffic participant motion state information.
Preferably, after the environment modeling module obtains the update data of the simulation scene and updates the simulation environment model according to the update data of the simulation scene, the method further includes
And the data display module in the automatic driving simulation system outputs the updated simulation environment model.
Further preferably, before outputting the updated simulated environment model according to the data display module in the automatic driving simulation system, the method further comprises:
the environment modeling module acquires simulation object data and determines an interface function according to the simulation object data;
and determining a target communication mode according to the interface function.
Further preferably, the step of updating the simulated environment model according to the output of the data display module in the automatic driving simulation system specifically comprises:
and the data display module outputs the updated simulation environment model in the target communication mode.
In a second aspect, an embodiment of the present invention further provides an automatic driving simulation system, where the system includes: the system may further comprise an autopilot module, an environmental modeling module, a data interaction module, and a data display module as described above in relation to the first aspect.
The automatic driving simulation method provided by the embodiment of the invention does not depend on a large amount of actual traffic scene data, does not need to modify the interface of the automatic driving system, can perform gradient verification from a simple scene to a complex scene, can simultaneously realize the in-loop simulation verification process of software and hardware, meets the simulation verification requirement, saves manpower and material resources, has low time cost and high verification efficiency. In addition, the environment modeling module in the embodiment of the application can realize hierarchical and simple to complex gradient scene generation of the behaviors of the map and the traffic participants, and can generate the scenes without adopting a data-driven learning algorithm, so that the cost can be further saved.
Drawings
Fig. 1 is a schematic structural diagram of an automatic driving simulation system according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method of an automated driving simulation method according to an embodiment of the present invention;
fig. 3 is a flowchart of a method for modeling a simulation environment model according to an embodiment of the present invention.
Detailed Description
In order to better understand the technical solution of the present application, an application scenario of the software and hardware-in-the-loop simulation method provided by the present application is first introduced.
Simulation, as the name implies, refers to simulating real data. In the field of automatic driving, the method can be understood as a process of triggering simulation operation as a data source of an algorithm module and receiving a simulation operation result of the algorithm module through upper-layer input of the algorithm module in an environment modeling mode.
In the structural framework of the automatic driving simulation process, the automatic driving simulation system in the application is shown in fig. 1 and comprises an environment modeling module 1, a data interaction module 2, an automatic driving module 3 and a data display module 4. The environment modeling module 1 is mainly used for realizing a simulation processing process through a specific algorithm, the output result of the environment modeling module 1 is input as a simulation object of the automatic driving module 3 through the data interaction module 2, then the simulation objects are subjected to simulation operation in the algorithm module in the automatic driving module 3, the result of the simulation operation is fed back to the environment modeling module 1 through the data interaction module 2, and the environment modeling module 1 updates the environment model according to the fed-back simulation operation result so as to circulate, thereby realizing the hardware-in-the-loop simulation process. It can be understood that, for different simulation operations, different input and output interfaces need to be designed to implement a complete simulation process if the required input data is different. Meanwhile, an algorithm module in the automatic driving module can be replaced by an actuator module correspondingly so as to realize the process of the system simulation part of the hardware-in-loop.
In order to better understand the automatic driving simulation system in the present application, the following first describes in detail the technical solution of the automatic driving simulation method implemented in the automatic driving simulation system with reference to the accompanying drawings and embodiments.
The embodiment of the invention provides an automatic driving simulation method, a flow chart of which is shown in figure 2, and the method comprises the following steps:
specifically, an autopilot module in the autopilot simulation system monitors hardware signals output by upper sensor hardware or autopilot actuator hardware in real time.
specifically, when the hardware signal is empty, which means that the autopilot module cannot monitor the hardware signal output by the upper sensor hardware or the autopilot actuator hardware, that is, the sensor hardware or the autopilot actuator hardware is in an inactive state, the following step 130 is executed. When the hardware signal is not empty, which represents that the autopilot module can monitor the hardware signal output by the upper sensor hardware or the autopilot actuator hardware, that is, the sensor hardware or the autopilot actuator hardware is in an active state, the following step 131 is executed.
specifically, when the hardware signal is empty, it indicates that the autopilot module cannot monitor the hardware signal output by the upper sensor hardware or the autopilot actuator hardware, and the autopilot module needs to simulate the environment model from the environment modeling module in the autopilot simulation system through the data interaction module in the autopilot simulation system.
Before obtaining the simulation environment model, a modeling method of the simulation environment model in fig. 3 needs to be executed, where the method flow includes:
specifically, the environment modeling module firstly obtains environment scene types, wherein the environment scene types comprise a first type representing that a model needs to be built through preset input parameters and a second type representing that the model needs to be built through real environment parameters.
specifically, when the environment scene type is a first type representing that a model needs to be built through preset input parameters, the following step 230 is performed. When the environment scene type is not the first type representing that the model needs to be built by the preset input parameters, the following step 231 is performed.
specifically, when the environment scene type represents a first type requiring model construction through preset input parameters, the environment modeling module acquires environment modeling parameters. The environment modeling parameters can be understood as necessary constituent elements in the whole traffic scene except for the own vehicle.
More specifically, the environmental modeling parameters include, but are not limited to: map information and traffic participant information. The map information includes: the method comprises the steps of obtaining a static environment parameter which is only relevant to the position and is not relevant to the time in an experimental period, and obtaining a dynamic environment parameter which is variable along with the time. Static environmental parameters include, but are not limited to: road geological parameters, road topographic parameters, road characteristic parameters and building parameters; dynamic environment parameters include, but are not limited to: a weather parameter. The traffic participant information may be understood as parameters representing behavior decisions and current states of all traffic participants, such as pedestrians, vehicles, traffic lights, etc. participating in traffic behaviors except the own vehicle, including but not limited to: traffic participant type information, traffic participant location information, and traffic participant motion state information.
The road geological parameters may be understood as parameters representing information such as road positions and road widths represented by a geometric model obtained by extracting road shapes in a map. In some specific embodiments, the geometric model after being extracted by the road shape in the map mainly includes three types: the method comprises the following steps of representing a geometric model of a straight road by a straight line equation, representing a geometric model of road width change of a road at a lane changing part by a cubic polynomial, and representing a geometric model of road curvature change of a turning part by a constant speed spiral line. In the geometric models, the road position is represented by road point position coordinates, the road width is directly represented by geometric parameters, the coordinate SYSTEM is a global coordinate SYSTEM, a UNIVERSAL TRANSVERSE ink card grid SYSTEM (UNIVERSAL TRANSVERSE ink machine grid SYSTEM, UTM) geographic coordinate SYSTEM can be selected, and any suitable UNIVERSAL rectangular coordinate SYSTEM with a fixed origin can be selected. It is understood that when generating a simulation map using real geographic data, the conversion from the geographic coordinate system to the ordinary rectangular coordinate system is required, and when generating an autonomous driving available map using a simulation scene, the conversion from the ordinary rectangular coordinate system to the geographic coordinate system is required.
The road topography parameter may be understood as a parameter representing a logical relationship of a road structure of the map, including but not limited to a travelable direction of a road, a connection relationship between roads, a speed limit of a road, and the like, and a representation manner thereof is not limited by a coordinate system.
The road characteristic parameter can be understood as a parameter representing road characteristics, can be understood as road label information in a map, describes road surface physical characteristics such as road surface states, friction resistance and the like, and is not limited by a simulation scene and switching of use scenes of an automatic driving system.
Building parameters may be understood as representing building information on a map that may describe the perimeter of a road, expressed in corner coordinates of the outer enveloping polygons of an individual building or group of buildings, which parameters may serve as supplementary information to the map.
The weather parameter may be a parameter indicating a current weather condition, such as a current sunshine condition, a rain and snow condition, or the like, which affects an actual scene by the weather condition.
The traffic participant type information may be understood as information indicating basic information such as the type, shape, and the like of the traffic participant.
The traffic participant position information may be understood as information representing the current positions of all traffic participants, and may be represented by position coordinates of equivalent points or outline outer envelope point coordinates, and the coordinate system may adopt information of a global coordinate system or a vehicle coordinate system related to road information.
The traffic participant movement state information can be understood as information representing the movement amount of the traffic participant, such as speed, acceleration and the like.
specifically, when the environment scene type is not a first type representing that a model needs to be built through preset input parameters, the environment modeling module determines whether real scene data exists, and this process may be understood as a process of determining whether a real scene of the current vehicle exists. Step 241 is performed if real scene data exists, and step 242 is performed if real scene data does not exist.
241, generating a simulation environment model according to the real scene data;
specifically, when the real scene data exists, the environment modeling module selects the scene tag data according to the real scene data, and sets a scene according to the scene tag data combination to generate a simulated environment model.
specifically, when there is no real scene data, the environment modeling module obtains a preset environment model, and generates a simulated environment model according to the preset environment model.
It is understood that whether the above steps 230 or 241 or 242 are performed, the simulated environment model in step 130 can be obtained.
in particular, simulation data may be understood as an object to be simulated. After the automatic driving module acquires the simulated environment model from the environment modeling module, an algorithm module in the automatic driving module carries out simulation operation on simulation data according to the simulated environment model to generate updating data of a simulation scene. This process can be understood as software in loop emulation mode.
specifically, when the hardware signal is not empty, it represents that the autopilot module can monitor the hardware signal output by the upper sensor hardware or the autopilot actuator hardware, that is, the sensor hardware or the autopilot actuator hardware is in an active state, and the autopilot module obtains sensor data.
specifically, when the autopilot module detects an output signal of upper sensor hardware or autopilot actuator hardware, it is necessary to provide data input of an original scene, that is, sensor data, to the autopilot module, and generate update data of a simulated scene according to the sensor data.
specifically, after the update data of the simulation scene is obtained, the automatic driving module sends the update data of the simulation scene to the environment modeling module through the data interaction module, so that the environment modeling module updates the simulation environment model according to the update data of the simulation scene and outputs the simulation environment model through the data display module in the automatic driving simulation system.
And during output, the environment modeling module acquires the simulation object data, determines an interface function according to the simulation object data, determines a target communication mode according to the interface function, and is used for outputting the updated simulation environment model through the target communication mode by the data display module.
It is understood that the above steps 110-150 are only one-time in-loop simulation process, and as long as the system is online, the in-loop simulation process will be circulated all the time, and the simulation environment model will be updated in each loop.
The automatic driving simulation method provided by the embodiment of the invention does not depend on a large amount of actual traffic scene data, does not need to modify the interface of the automatic driving system, can perform gradient verification from a simple scene to a complex scene, can simultaneously realize the in-loop simulation verification process of software and hardware, meets the simulation verification requirement, saves manpower and material resources, has low time cost and high verification efficiency. In addition, the environment modeling module in the embodiment of the application can realize hierarchical and simple to complex gradient scene generation of the behaviors of the map and the traffic participants, and can generate the scenes without adopting a data-driven learning algorithm, so that the cost can be further saved.
Accordingly, an embodiment of the present invention further provides an automatic driving simulation system for implementing the automatic driving simulation method, and a schematic diagram of the automatic driving simulation system is further shown in fig. 1, where the automatic driving simulation system includes: the system comprises an environment modeling module 1, a data interaction module 2, an automatic driving module 3 and a data display module 4. The environment modeling module 1 is connected with the automatic driving module 3 through the data interaction module 2, and the data display module 4 is connected with the environment modeling module 1, the data interaction module 2 and the automatic driving module 3 and used for displaying data in the environment modeling module 1, the data interaction module 2 and the automatic driving module 3.
When the automatic driving simulation system works, the process is as follows:
the automatic driving module 3 monitors the hardware signal output by the upper sensor hardware or the automatic driving actuator hardware in real time and determines whether the hardware signal is empty. When the hardware signal is empty, the automatic driving module 3 simulates an environment model from the environment modeling module 1 through the data interaction module 2, and generates updating data of a simulation scene according to the simulated environment model and the simulation data; and when the hardware signal is not empty, the automatic driving module 3 generates the updating data of the simulation scene according to the sensor data. Then, the automatic driving module 3 sends the updated data of the simulation scene to the environment modeling module 1 through the data interaction module 2, so that the environment modeling module 1 updates the simulation environment model according to the updated data of the simulation scene, and sends the updated simulation environment model to the data display module 4, so that the updated simulation environment model is displayed by the data display module 4.
The automatic driving simulation system provided by the embodiment of the invention has a simple structure, is used for realizing gradient verification from a simple scene to a complex scene, can simultaneously realize the in-loop simulation verification process of software and hardware, meets the simulation verification requirement, saves manpower, material resources, time and cost, and has high verification efficiency. In addition, the environment modeling module in the embodiment of the application can realize hierarchical and simple to complex gradient scene generation of the behaviors of the map and the traffic participants, and can generate the scenes without adopting a data-driven learning algorithm, so that the cost can be further saved.
Those of skill would further appreciate that the various illustrative components and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied in hardware, a software module executed by a processor, or a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM powertrain control method, or any other form of storage medium known in the art.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (9)
1. An automated driving simulation method, the method comprising:
an environment modeling module in the automatic driving simulation system acquires environment modeling parameters and generates a simulation environment model according to the environment modeling parameters;
an automatic driving module in the automatic driving simulation system monitors hardware signals;
when the hardware signal is empty, acquiring a simulated environment model from an environment modeling module in the automatic driving simulation system through a data interaction module in the automatic driving simulation system;
generating updating data of a simulation scene according to the simulation environment model and the simulation data;
when the hardware signal is not empty, acquiring sensor data;
generating updating data of a simulation scene according to the sensor data;
the environment modeling module acquires the updating data of the simulation scene and updates the simulation environment model according to the updating data of the simulation scene.
2. The automated driving simulation method of claim 1, wherein before the environmental modeling module obtains environmental modeling parameters from which to generate the simulated environmental model, the method further comprises:
the environment modeling module acquires an environment scene type and determines whether the environment scene type is a first type;
and when the environment scene type is a first type, obtaining environment modeling parameters, and generating a simulation environment model according to the environment modeling parameters.
3. The automated driving simulation method of claim 2, wherein when the environmental scene type is not the first type, the method further comprises:
the environment modeling module determines whether real scene data exists;
when the real scene data exist, generating a simulation environment model according to the real scene data;
and when the real scene data does not exist, generating a simulation environment model according to a preset environment model.
4. The automated driving simulation method of claim 1, wherein:
the environment modeling parameters include: map information and traffic participant information.
5. The automated driving simulation method of claim 4, wherein:
the map information includes: static environment parameters and dynamic environment parameters;
the static environment parameters include: road geological parameters, road topographic parameters, road characteristic parameters and building parameters;
the dynamic environment parameters include: a weather parameter;
the traffic participant information includes: traffic participant type information, traffic participant location information, and traffic participant motion state information.
6. The autopilot simulation method of claim 1 wherein after the environmental modeling module obtains updated data for a simulation scenario and updates the simulated environmental model based on the updated data for the simulation scenario, the method further comprises
And the data display module in the automatic driving simulation system outputs the updated simulation environment model.
7. The autopilot simulation method of claim 6 wherein prior to outputting the updated simulated environmental model in accordance with a data display module in the autopilot simulation system, the method further comprises:
the environment modeling module acquires simulation object data and determines an interface function according to the simulation object data;
and determining a target communication mode according to the interface function.
8. The automatic driving simulation method according to claim 7, wherein the simulated environment model updated according to the output of the data display module in the automatic driving simulation system is specifically:
and the data display module outputs the updated simulation environment model in the target communication mode.
9. An autopilot simulation system comprising an autopilot module according to any one of claims 1 to 8, an environmental modeling module, a data interaction module and a data display module.
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