WO2020224434A1 - 一种驾驶仿真方法、装置、电子设备及计算机存储介质 - Google Patents

一种驾驶仿真方法、装置、电子设备及计算机存储介质 Download PDF

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Publication number
WO2020224434A1
WO2020224434A1 PCT/CN2020/086029 CN2020086029W WO2020224434A1 WO 2020224434 A1 WO2020224434 A1 WO 2020224434A1 CN 2020086029 W CN2020086029 W CN 2020086029W WO 2020224434 A1 WO2020224434 A1 WO 2020224434A1
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Prior art keywords
vehicle
target
background
traffic
speed
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PCT/CN2020/086029
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English (en)
French (fr)
Inventor
杜海宁
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腾讯科技（深圳）有限公司
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Priority to EP20802483.6A priority Critical patent/EP3901771A4/en
Publication of WO2020224434A1 publication Critical patent/WO2020224434A1/zh
Priority to US17/371,900 priority patent/US20210334420A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
    • G06F30/15—Vehicle, aircraft or watercraft design
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/0088—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0219—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory ensuring the processing of the whole working surface
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation

Definitions

  • This application relates to the field of automatic driving technology, and in particular to a driving simulation method, device, electronic equipment, and computer-readable storage medium.
  • Self-driving cars are smart cars that realize unmanned driving through computer systems. They can bring people many benefits, such as reducing traffic accidents, saving energy, and allowing people to have more free time. It is the future direction of automobile development.
  • the driving of an autonomous vehicle is controlled by a decision-making algorithm.
  • a simulated traffic environment needs to be built.
  • the test vehicle controlled by the decision-making algorithm runs in the simulated traffic environment.
  • the decision-making algorithm is determined by observing and recording the driving state of the test vehicle. to evaluate.
  • the simulated driving environment In order to make the simulated driving environment restore the real driving environment as much as possible, the simulated driving environment always needs several background vehicles, and the background vehicles need to have differentiated driving behaviors.
  • the embodiments of the present application provide a driving simulation method, device, electronic equipment, and computer-readable storage medium, which can effectively improve the efficiency and accuracy of building a simulated traffic environment.
  • the embodiment of the application provides a driving simulation method, the method is executed by an electronic device, and the electronic device includes one or more processors and a memory, and one or more programs, wherein the one or one The above program is stored in a memory, the program may include one or more units each corresponding to a set of instructions, and the one or more processors are configured to execute instructions; the method includes:
  • the target lane includes the lane where the test vehicle and the background vehicle are located;
  • driving each of the background vehicles is simulated in a simulated traffic environment.
  • the embodiment of the present application provides a driving simulation method, the method is executed by a server, the server includes one or more processors, a memory, and one or more programs, wherein the one or more The program is stored in the memory, the program may include one or more units each corresponding to a set of instructions, and the one or more processors are configured to execute the instructions; the method includes:
  • the target lane includes the lane where the test vehicle and the background vehicle are located;
  • driving each of the background vehicles is simulated in a simulated traffic environment.
  • the embodiment of the application provides a driving simulation device, including:
  • the first interaction module is configured to display a first configuration interface and receive parameters input through the first configuration interface
  • the parameter determination module is configured to determine the vehicle reference distance, the vehicle reference speed, and the number of background vehicles in the target lane based on the parameters; wherein the target lane includes the test vehicle and the lane where the background vehicle is located;
  • the background vehicle generation module is configured to determine the initial position of each background vehicle belonging to the target lane based on the location of the test vehicle, the vehicle reference distance, and the random distance deviation; based on the vehicle reference speed and the random speed deviation , Determine the initial speed of each of the background vehicles belonging to the target lane;
  • the simulation control module is configured to simulate driving each background vehicle in a simulated traffic environment based on the initial position and initial speed of each background vehicle and the number of the background vehicles.
  • An embodiment of the present application provides an electronic device, which includes a processor and a memory:
  • the memory is used to store computer programs
  • the processor is configured to execute the driving simulation method as described above according to the computer program.
  • An embodiment of the present application provides a computer-readable storage medium, and the computer-readable storage medium stores a computer program, and when the computer program is executed, the aforementioned driving simulation method is implemented.
  • the embodiment of the present application provides a computer program product including instructions, which when run on a computer, causes the computer to execute the above-mentioned driving simulation method.
  • the embodiment of the application provides a driving simulation method.
  • a user builds a simulated traffic environment based on this method, he only needs to configure a small amount of basic parameters through the first configuration interface at one time to complete the setting of each background vehicle in the simulated traffic environment. It can effectively reduce the manual operation required in the process of building a simulated traffic environment and improve the efficiency of building a simulated traffic environment.
  • the vehicle reference distance and vehicle reference speed will be adjusted according to the random distance deviation and the random speed deviation respectively, to ensure that the set background vehicle driving states are diverse and random, and effectively improve the accuracy of the simulated traffic environment. Meet the basic needs of traffic simulation.
  • FIGS. 1A-1C are schematic diagrams of application scenarios of the driving simulation method provided by the embodiments of this application.
  • FIG. 2 is a schematic flowchart of a driving simulation method provided by an embodiment of the application.
  • Figure 3 is a macro basic diagram of a target traffic flow provided by an embodiment of the application.
  • 4A is a schematic diagram of the principle of calculating a vehicle reference speed provided by an embodiment of the application.
  • FIG. 4B is a macro basic diagram of the target traffic flow provided by an embodiment of this application.
  • 4C is a schematic diagram of the principle of calculating the reference speed of a vehicle provided by an embodiment of the application.
  • 4D is a schematic diagram of a driving simulation interface provided by an embodiment of the application.
  • FIG. 5 is a schematic flowchart of a background vehicle setting method provided by an embodiment of the application.
  • 6A-6B are schematic flowcharts of the driving simulation process provided by the embodiments of this application.
  • FIG. 7 is a schematic structural diagram of a driving simulation device provided by an embodiment of the application.
  • FIG. 8 is a schematic structural diagram of a driving simulation device provided by an embodiment of the application.
  • FIG. 9 is a schematic structural diagram of a driving simulation device provided by an embodiment of the application.
  • FIG. 10 is a schematic structural diagram of a terminal device provided by an embodiment of the application.
  • the driving simulation method provided by the embodiments of the present application can be implemented by software, for example, simulation software for automatic driving simulation.
  • the simulation software can be deployed in a terminal device or a server, which will be described separately below.
  • FIG. 1A is a schematic diagram of an application scenario of a driving simulation method provided by an embodiment of the application; as shown in FIG. 1A, the application scenario includes a developer 110 and an electronic device 120; the electronic device 120 can run a simulation program.
  • the electronic device 120 sets the background vehicle (background traffic) that matches the set basic parameters in the simulation program, such as the front background vehicle and the rear background Vehicles and background vehicles drive on the road in accordance with predefined driving behaviors (initial position and initial speed) for subsequent verification and testing of decision-making algorithms for vehicles driving in traffic flows.
  • background traffic background traffic
  • predefined driving behaviors initial position and initial speed
  • the background vehicle When the background vehicle is driving on the road, by testing the perception system in the autopilot system of the vehicle, it can sense the environment information inside and outside the vehicle, including the position, speed, orientation and object classification of obstacles in the environment (such as vehicles, pedestrians, bicycles) ), and a high-precision map of the test vehicle's own state (including speed, acceleration and direction), and the real-time location of the test vehicle.
  • the environment information inside and outside the vehicle including the position, speed, orientation and object classification of obstacles in the environment (such as vehicles, pedestrians, bicycles)
  • a high-precision map of the test vehicle's own state including speed, acceleration and direction
  • the decision-making system determines the driving path and speed of the test vehicle according to the decision-making algorithm of the test vehicle.
  • the test vehicle uses its own decision-making algorithm during the driving process, based on the simulated traffic environment and objective physical laws.
  • the decision-making system determines the driving path and speed of the test vehicle, it sends the driving path and speed to the control system.
  • the control system receives the driving path and speed, it performs dynamic calculations based on the attributes of the vehicle body and external physical factors and converts it into a pair of tests
  • the vehicle control parameters such as the accelerator amount, brake amount, and steering wheel turning amount of the electronic control of the vehicle are executed and executed, thereby controlling the vehicle to realize the driving path.
  • the driving data of the test vehicle is recorded, and the driving data of the test vehicle is evaluated through the automatic driving evaluation system to obtain the evaluation data of the test vehicle ( Test report), where the driving data includes all the subtle performances of the test vehicle after starting from the starting point, such as whether it runs a red light, compaction line, whether it collides, whether it reaches the end point, throttle state, brake state, steering state, etc., according to the driving state of the test vehicle Data to evaluate the driving safety of the decision-making algorithm (vehicle driving decisions and behaviors on the road), for example, determine the driving safety of the decision-making algorithm based on fatal errors in the driving data, memory leaks, data delays, and traffic accidents Low; According to the driving data of the test vehicle, evaluate the driving comfort of the decision-making algorithm (the driving experience of the driver or occupant during the driving of the vehicle on the road), for example, evaluate the driving of the test vehicle according to the accelerator, brake
  • the electronic device 120 executes the driving simulation method provided by the embodiment of the present invention, as an example of the application scenario of the terminal device (electronic device 120) running simulation, see FIG. 1B, which is the driving simulation method provided by the embodiment of the application
  • FIG. 1B is the driving simulation method provided by the embodiment of the application
  • FIG. 1B A schematic diagram of the application scenario; as shown in Figure 1B, the application scenario includes a developer 110 and a terminal device 120-1; the terminal device 120-1 can run a simulation program.
  • the developer 110 can input the basic parameters of the developer to set the background vehicle in the simulated traffic environment through the first configuration interface 121 displayed on the terminal device 120-1; the terminal device 120-1 is used to execute the Driving simulation method, setting a background vehicle that matches the basic parameters set in a simulated traffic environment, and the background vehicle drives on the road according to predefined driving behaviors to verify the decision-making algorithm of the test vehicle driving in the traffic flow through the automatic driving system , Obtain the evaluation data of the test vehicle through the evaluation system to realize the simulation of the traffic environment of the test vehicle.
  • the developer 110 may call a simulation program running on the terminal device 120-1 to build a simulated traffic environment.
  • the terminal device 120-1 When building a simulated traffic environment, the terminal device 120-1 (for example, a simulation program run by the terminal device 120) will correspondingly display a first configuration interface 121, which carries a number of configurations for inputting basic parameters Controls, as shown in FIG. 1B, the first configuration interface 121 can carry a configuration control for inputting traffic state indication parameters and a configuration control for inputting background vehicle quantity indication parameters.
  • the developer 110 correspondingly inputs the basic parameters for setting the background vehicle through each configuration control displayed on the first configuration interface 121.
  • the terminal device 120-1 can determine the vehicle reference distance, vehicle reference speed, and target lane N (N takes a positive integer) target background vehicle speed according to these basic parameters. Furthermore, the terminal device 120-1 sequentially determines the initial position of the i-th background vehicle in the target lane according to the location of the test vehicle, the vehicle reference distance, and the random distance deviation, and sequentially determines the location of the target vehicle according to the vehicle reference speed and the random speed deviation.
  • the initial speed of the i-th background vehicle in the lane The value of i ranges from 1 to N.
  • the terminal device 120-1 can, according to the respective initial positions and initial speeds of each background vehicle, determine the background vehicles according to their respective initial positions and speeds.
  • the initial speed is driving on the road, and the test vehicle is started to test the decision-making algorithm of the test vehicle.
  • the autonomous driving simulation interface may be specifically as shown in the simulation interface 122 in FIG. 1B, where the vehicle surrounded by the rectangular frame in the simulation interface 122 is a test vehicle 1221, and the test vehicle 1221 runs on the decision algorithm to be tested in the simulation process
  • the other vehicles in the simulation interface 122 that are not surrounded by the rectangular frame in the simulation interface 122 are background vehicles generated based on the above method, such as background vehicles 1222. These background vehicles drive on the target road according to predefined driving behaviors. Certain driving behaviors of the test vehicle will affect the driving decision-making behavior of the test vehicle, so as to achieve the purpose of verifying the decision-making algorithm running on the test vehicle.
  • the terminal device 120-1 can fix the speed of the background vehicle at the front, and according to the car-following model (in the simulation process, the vehicle fleet composed of the test vehicle and each background vehicle will travel along the target road together.
  • the driving law can usually follow the car-following model) and update the speeds of other background vehicles accordingly. In this way, speed constraints are imposed on the background vehicles in the simulated traffic environment.
  • the application scenario shown in FIG. 1B is only an example. In actual applications, in addition to the automatic driving simulation based on the terminal device 120-1 shown in FIG. 1B, it may also be based on other types of terminal devices. Autonomous driving simulation.
  • the first configuration interface 121 and the simulation interface 122 shown in FIG. 1B are only examples. In actual applications, the first configuration interface and the simulation interface may also be expressed in other forms.
  • the application scenarios of the driving simulation method provided in the embodiments of the present application are not limited here.
  • FIG. 1C is a schematic diagram of an application scenario of the driving simulation method provided by an embodiment of the application; as shown in FIG. 1, the application scenario includes The user 110, the terminal 120-1, and the server 120-2; the server 120-2 can run a simulation program.
  • the user 110 can input the basic parameters for setting the background vehicle in the simulated traffic environment through the first configuration interface 121 displayed on the terminal 120-1, and the terminal 120-1 sends the basic parameters for setting the background vehicle and the decision algorithm to
  • the server 120-2 in the cloud the server 120-2 determines the vehicle reference distance, the vehicle reference speed, and the target lane N (the value of N is a positive integer) target background vehicle speed according to the basic parameters of the background vehicle. Furthermore, the server 120-2 determines the initial position of the background vehicle in the target lane according to the location of the test vehicle, the vehicle reference distance and the random distance deviation, and determines the initial position of the background vehicle in the target lane according to the vehicle reference speed and the random speed deviation.
  • the background vehicle drives on the road according to the predefined driving behavior (the initial speed and position of the background vehicle) to verify the decision-making algorithm of the test vehicle driving in the traffic flow through the automatic driving system, and obtain the evaluation of the test vehicle through the evaluation system data.
  • the server 120-2 can also synchronize the real-time driving data of the simulation environment to the terminal device.
  • the terminal device displays the driving process of the test vehicle operation decision-making algorithm on the simulation interface 122 according to the real-time driving data.
  • the embodiments of the present application provide a driving simulation method, which can effectively Simplify the manual operations that developers need to perform, and improve the efficiency of building a simulated traffic environment.
  • the basic parameters input by the developer through the first configuration interface are first received; then, according to the basic parameters input by the developer, the vehicle reference distance, vehicle reference speed, and target lane are determined.
  • the number of target background vehicles then, determine the initial position of each background vehicle in the target lane according to the location of the test vehicle, the vehicle reference distance and the random distance deviation, and determine the initial position of each background vehicle in the target lane according to the vehicle reference speed and the random speed deviation.
  • Speed In this way, after determining the respective initial speed and initial position of each background vehicle on the target lane, the autonomous driving simulation is carried out on this basis.
  • the method provided in the embodiment of this application Compared with the developer manually setting each background vehicle one by one in the simulated traffic environment, the method provided in the embodiment of this application only requires the developer to input a few basic parameters through the first configuration interface to complete the simulation of each background vehicle in the simulated traffic environment.
  • the setting greatly simplifies the operations that developers need to perform, and improves the efficiency of building a simulated traffic environment.
  • the method provided by the embodiments of the present application will also consider random speed deviations and random position deviations in the process of setting each background vehicle, thereby ensuring the diversity and randomness of the set background vehicle driving states, so as to simulate traffic The environment is more realistic.
  • the driving simulation method provided in the embodiments of the present application can be applied to an electronic device with a simulation function, and the electronic device may specifically be a terminal device, where the terminal device may specifically be a computer or a personal digital assistant (PDA) , Tablet computers, smart phones, etc.; the electronic device can be a server, a server cluster, etc.
  • the server can provide simulation services based on cloud technology for the developers of decision-making algorithms.
  • FIG. 2 is a schematic flowchart of a driving simulation method provided by an embodiment of the application.
  • the following embodiments are described with the terminal device as the execution subject.
  • the description is made by taking the simulation program running in the terminal device as the execution subject as an example.
  • the driving simulation method includes the following steps:
  • Step 201 Display a first configuration interface, and receive parameters input through the first configuration interface.
  • the user can call the simulation software carried on the terminal device for the simulated traffic environment.
  • the simulation software After the simulation software is called, the first configuration interface will be displayed to the user, and the user can accordingly input the basic parameters for setting the background vehicle in the simulated traffic environment through the first configuration interface according to the actual requirements of the simulation.
  • first configuration interface In order to facilitate the understanding of the above-mentioned first configuration interface and the basic parameters input through the first configuration interface, the following describes two exemplary manifestations of the first configuration interface, and correspondingly introduce the basic parameters received through each first configuration interface .
  • the first configuration interface can carry configuration controls for configuring traffic state indication parameters and configuration controls for configuring background vehicle quantity indication parameters; accordingly, the terminal device can use the first configuration On the interface, the target traffic state indication parameter and the target background vehicle quantity indication parameter input by the user are received.
  • the traffic state indicator parameters are parameters that can indicate the traffic state in the simulated traffic environment, for example, the capacity, traffic density, background vehicle driving speed in the simulated traffic environment, etc.; the terminal device is used to configure the traffic state indicator parameters on the first configuration interface After receiving the target traffic state indicator parameter input by the user, the configuration control of the, can set the target traffic state corresponding to the target traffic state indicator parameter in the simulated traffic environment according to the target traffic state indicator parameter.
  • the configuration control used to configure the traffic state indication parameter may be a configuration control used to configure the traffic density. Accordingly, the traffic density received by the terminal device through the configuration control is the target traffic density. Traffic density is a parameter used to characterize the density of vehicles on the road, which is usually in units of vehicles/km.
  • the aforementioned configuration controls for configuring traffic state indication parameters may include: a configuration control for configuring traffic capacity and a configuration control for configuring vehicle speed.
  • the terminal device is configured to configure traffic
  • the traffic capacity received by the capacity configuration control is the target traffic capacity
  • the vehicle speed received by the terminal device through the configuration control for configuring the vehicle speed is the target vehicle speed.
  • Traffic capacity is a parameter used to characterize the flow of vehicles on the road, which is usually united in vehicles/hour
  • vehicle speed is used to characterize the basic speed of each background vehicle on the road, and the initial speed of each background vehicle is the basic driving speed. Determined on the basis of speed, which is usually measured in kilometers per hour.
  • the traffic state indicator parameters can also be other reference data that can be used to set the traffic state in a simulated traffic environment.
  • the traffic state indicator parameters are not limited here.
  • the background vehicle quantity indicator parameter is basic data used to determine the number of background vehicles in the simulated traffic environment. After receiving the target background vehicle quantity indication parameter input by the user through the configuration control used to configure the background vehicle quantity indication parameter on the first configuration interface, the terminal device can determine the simulation process according to the target background vehicle quantity indication parameter. The number of background vehicles required.
  • the configuration control used to configure the background vehicle quantity indication parameter may be a configuration control used to configure the background vehicle quantity parameter. Accordingly, the number of background vehicles received by the terminal device through the configuration control is the target background The number of vehicles. The number of background vehicles can directly indicate the number of background vehicles that need to be set on the target lane in the simulated traffic environment.
  • the configuration control used to configure the number of background vehicles on the first configuration interface can be directly used to configure the number of background vehicles that need to be set on the target lane;
  • the configuration control for configuring the number of background vehicles on the first configuration interface can be used to configure the total number of background vehicles M and the target that need to be set in the simulated traffic environment The number of lanes S, and then, according to the value obtained by dividing M by S, the number of background vehicles that need to be set for each target lane is determined.
  • the aforementioned configuration control for configuring the background vehicle quantity indication parameter may be a configuration control for configuring the position range indication parameter.
  • the position range indication parameter received by the terminal device through the configuration control is the target.
  • the position range indicates the parameter.
  • the position range indication parameter can indicate the setting range of the background vehicle in the simulated traffic environment. Combining the position range and the vehicle spacing can determine the number of background vehicles that need to be set on the target lane in the simulated traffic environment.
  • the background vehicle quantity indicator parameter can also be other reference data that can determine the number of background vehicles in the simulated traffic environment. None is done here on the background vehicle quantity indicator parameter. limited.
  • the first configuration interface may carry configuration controls for configuring the reference distance of the vehicle, configuration controls for configuring the reference speed of the vehicle, and configuration controls for configuring the target number of background vehicles in the target lane.
  • the terminal device can receive the following basic parameters through the first configuration interface: vehicle reference distance, vehicle reference speed, and the target number of background vehicles in the target lane.
  • the vehicle reference distance is the distance between two adjacent vehicles on the same lane in the simulated traffic environment.
  • the vehicle reference speed is the same concept as the vehicle speed mentioned above, that is, it is used to characterize the basic driving speed of each background vehicle on the road, and the initial speed of each background vehicle is determined on the basis of the basic driving speed.
  • the terminal device can determine the background vehicles that need to be deployed in the simulated traffic environment according to the number of target background vehicles under the conditions of known vehicle reference distance, vehicle reference speed, and the number of target background vehicles. Set the corresponding initial position and initial speed of each background vehicle in the simulated traffic environment according to the vehicle reference distance and vehicle reference speed. In this way, determine the respective initial state data of each background vehicle in the simulated traffic environment to realize each background The deployment of vehicles.
  • the first configuration interface can be used to configure the vehicle reference distance, vehicle reference speed, and target number of background vehicles in the target lane, as well as other parameters that can determine the initial deployment status of each background vehicle in the simulated traffic environment. , There is no restriction on the types of parameters that can be configured on the first configuration interface.
  • the terminal device can obtain the types of background vehicles and the proportions of various types of background vehicles in all background vehicles through the first configuration interface.
  • the number of background vehicles directly obtained by the terminal device through the first configuration interface usually corresponds to the standard vehicle type; for example, suppose that a small passenger car As a standard model, the number of background vehicles acquired by the terminal device through the first configuration interface is 50, which means that if all background vehicles in the simulated traffic environment are small passenger cars, the simulated traffic environment includes 50 background vehicles.
  • the terminal device needs to combine the respective proportions of various types of background vehicles and vehicles set by the user when determining the number of background vehicles.
  • the conversion coefficients between various car models and standard car models further determine the corresponding numbers of various types of background vehicles in the simulated traffic environment, making the simulated traffic environment more realistic.
  • the terminal device determines that the number of background vehicles included in the simulated traffic environment is 100 according to the basic parameters received by the first configuration interface (that is, the background vehicles included in the simulated traffic environment are all small In the case of a passenger car, the number of background vehicles is 100), and the simulated traffic environment includes a small passenger car and a large passenger car with a ratio of 1:1.
  • the ratio of small passenger cars to large passenger cars it can be determined that 50 of the background vehicles need to be converted into small passenger cars, and the remaining 50 background vehicles are converted into large passenger cars. Since the small passenger car itself is a standard vehicle type, it can be directly determined that 50 small passenger cars need to be set in the simulated traffic environment.
  • the conversion coefficient table pre-stored in the terminal device if the conversion coefficient of large passenger cars to small passenger cars is determined to be 2 (that is, 1 large passenger car is equivalent to 2 small passenger cars), then 50 background vehicles can be converted into 25 large passenger cars , That is, it is determined that 25 large passenger cars need to be set up in the simulated traffic environment.
  • the target traffic density and target traffic capacity received by the terminal device through the first configuration interface usually correspond to the standard vehicle type.
  • Step 202 Determine the vehicle reference distance, vehicle reference speed, and the number of background vehicles in the target lane based on the parameters.
  • the terminal device After the terminal device receives the basic parameters input by the user through the first configuration interface, it can correspondingly determine the parameters for setting the background vehicle in the simulated traffic environment based on these basic parameters, including: vehicle reference distance, vehicle reference speed, and target lane The number of target background vehicles of N (the value of N is a positive integer).
  • the vehicle reference distance is the distance between two adjacent vehicles on the target lane in the simulated traffic environment (the distance between two vehicles before and after), and the vehicle reference distance can be the distance between the fronts of two adjacent vehicles.
  • the distance between the two adjacent vehicles can also be the distance between the rears of two adjacent vehicles; the initial distance between two adjacent vehicles on the target lane is determined on the basis of the vehicle reference distance.
  • the vehicle reference speed is used to characterize the basic driving speed of each background vehicle, and the initial speed of each background vehicle is determined on the basis of the vehicle reference speed.
  • the terminal device can determine the vehicle reference distance and the vehicle based on the macro basic map of the target traffic flow and the target traffic state indicator parameters. Reference speed; and determine the target background vehicle number in the target lane according to the target background vehicle number indicator parameter in the target lane.
  • the macro basic map of traffic flow can describe the relationship between the macro traffic capacity, traffic density and vehicle speed in the transportation network.
  • users can select the macro basic diagram of traffic flow suitable for this simulation from several macro basic diagrams of traffic flow provided by the simulation system according to the actual simulation requirements, as the macro basic diagram of the target traffic flow, and then According to the macro basic map of the target traffic flow and the target traffic state indicator parameters input by the user, the parameters required for setting the background vehicle in the simulated traffic environment are determined accordingly.
  • Fig. 3 is an exemplary macro basic diagram of target traffic flow provided by an embodiment of the application.
  • the macro basic map of the target traffic flow is usually set in a coordinate system with traffic density as the horizontal axis and capacity as the vertical axis.
  • the macro basic map of the target traffic flow may include two straight line segments, respectively The straight line segment 301 (the first straight line segment) and the straight line segment 302 (the second straight line segment), the straight line segment 301, the straight line segment 302 and the horizontal axis of the coordinate axis form a triangle.
  • Each point on the straight line 301 and the straight line 302 represents a traffic state, which can indicate the relationship between capacity, traffic density, and vehicle speed.
  • the ordinate of the intersection point of the straight line 301 and the straight line 302 is taken as the maximum capacity
  • the abscissa of the intersection point of the straight line 301 and the straight line 302 is taken as the critical traffic density
  • the intersection point of the straight line 302 and the horizontal axis The abscissa is used as the density of blocked traffic.
  • the straight line segment 301 is used to characterize the free running state of the vehicle, and the slope of the straight line segment 301 is the free-stream vehicle speed.
  • the vehicle in the simulated traffic environment can keep the free-stream vehicle speed unchanged. In this process, the capacity of the simulated traffic environment will gradually increase.
  • the capacity of the simulated traffic environment reaches the maximum capacity.
  • the straight line 302 is used to characterize the congested driving state of vehicles; as shown in the straight line 302, after the traffic density of the simulated traffic environment reaches the critical density and the capacity reaches the maximum capacity, the continuous increase of vehicles in the simulated traffic environment will lead to traffic The density gradually increases, the vehicle speed gradually slows down, and it enters a congested driving state, and accordingly, the traffic capacity also decreases. When the traffic density reaches the congestion density, the traffic flow enters a completely congested stop state, and the vehicle speed and capacity are reduced to zero.
  • the macro basic map of traffic flow shown in Figure 3 is only an example. In actual applications, when users build a simulated traffic environment, they can also select other shapes of traffic flow macro basic maps as the target traffic flow macro basics Figure; Or, the user can also select the macro basic map of traffic flow drawn according to other traffic flow parameters that can characterize the traffic state as the macro basic map of the target traffic flow. There is no limitation on the macro basic diagram of the target traffic flow used to set the background vehicle in the embodiment of the application.
  • the macro basic map of traffic flow provided by the simulation system may not meet the simulation needs of users; in order to ensure that users can build a simulated traffic environment that meets their simulation needs, the driving simulation provided in the embodiments of this application
  • the method can also support the user to customize the macro basic map of the target traffic flow.
  • the terminal device may display a second configuration interface to the user, and receive traffic flow quantitative parameters input by the user through the second configuration interface, the traffic flow quantitative parameters including free flow vehicle speed, congestion density, critical density, and maximum traffic capacity; further, The terminal device generates a macro basic map of the target traffic flow according to the traffic flow quantitative parameters input by the user.
  • the terminal device draws the macro basic map of traffic flow, it usually needs to know the traffic flow quantitative parameters such as free flow speed, congestion density, critical density, and maximum capacity;
  • the terminal device can determine the straight line segment used to characterize the free-running state of the vehicle according to the free-flow vehicle speed, critical density and maximum capacity, and determine the congested driving state of the vehicle according to the critical density, maximum capacity and congestion density In this way, the macro basic map of the target traffic flow that meets the user’s actual simulation needs is determined.
  • the terminal device can obtain it through the second configuration interface accordingly Other traffic flow quantitative parameters required when drawing the macro basic map of traffic flow, and use a specific method to draw the macro basic map of the target traffic flow based on the obtained traffic flow quantitative parameters.
  • the traffic flow quantitative parameters obtained in the second configuration interface are not used here. It does not make any restrictions, nor does it impose any restrictions on the way the terminal device draws the macro-basic diagram of the target traffic flow.
  • the terminal device when determining the vehicle reference distance and vehicle reference speed according to the macro basic map of the target traffic flow, can take specific processing methods to determine the vehicle reference distance according to the type of the target traffic state indicator parameter received by the first configuration interface. And the vehicle reference speed.
  • the terminal device can use the reciprocal of the target traffic density as the vehicle reference distance, and set it in the target traffic
  • the macro basic map determines the target traffic state corresponding to the target traffic density, determines the target capacity of the target traffic state in the target traffic macro basic map, and uses the ratio of the target capacity to the target traffic density as the vehicle reference speed.
  • the traffic state of the simulated traffic environment can be uniquely determined according to the traffic flow macro basic map, that is, the traffic capacity corresponding to the traffic density can be uniquely determined.
  • Vehicle speed because there is a reciprocal relationship between the vehicle distance and the traffic density, the vehicle distance can also be determined based on the traffic density in the case of a given traffic density.
  • the point where the abscissa is the target traffic density is taken as the target traffic state, and the ordinate of the target traffic state is taken as the target traffic capacity of the target traffic state in the target traffic macro basic map .
  • the terminal device when the terminal device receives the target traffic state indicator parameter input by the user through the first configuration interface as the target traffic density K, the terminal device can calculate the vehicle reference distance D by formula (1):
  • the vehicle reference distance D here can represent the distance between the fronts of two adjacent vehicles on the target lane, or the distance between the rears of two adjacent vehicles; the vehicle reference distance D It is equal to the sum of the body length of the standard background vehicle and the actual separation distance between two adjacent background vehicles.
  • the actual separation distance between two adjacent background vehicles refers to the rear and position of the background vehicle in front The distance between the front of the back background vehicle.
  • V V max (K ⁇ K cr ) (2)
  • V (KQ max /(K cr -K jam )+k jam Q max /(K jam -K cr ))/K(K>K cr ) (3)
  • K is the target traffic density input by the user
  • V max is the free flow speed in the macro basic map of the target traffic flow
  • Q max is the maximum capacity in the macro basic map of the target traffic flow
  • K cr is The critical density in the macro basic map of the target traffic flow
  • K jam is the congestion density in the macro basic map of the target traffic flow.
  • the terminal device may directly use the received target vehicle speed as the vehicle Baseline speed; and determine the target traffic state corresponding to the target capacity and target vehicle speed in the target traffic macro basic map, determine the target traffic density of the target traffic state in the target traffic macro basic map, and use the reciprocal of the target traffic density as Vehicle reference distance.
  • the traffic density corresponding to the combination of traffic capacity and target vehicle speed can be uniquely determined according to the macro basic map of traffic flow.
  • the vehicle spacing can be determined according to the traffic density.
  • the ordinate is determined as the target traffic capacity
  • the slope of the line connecting the coordinate origin is the target vehicle speed point, as the target traffic state
  • the abscissa of the target traffic state is The target traffic density of the target traffic state in the macro basic map of target traffic.
  • the terminal device when the terminal device receives the target traffic capacity Q and target vehicle speed V input by the user through the first configuration interface, the terminal device can calculate the target traffic density K by formula (4) and formula (5):
  • K K jam Q max /(Q max -V(K cr -K jam ))(V ⁇ V max ) (5)
  • V max is the free flow velocity in the macro basic map of the target traffic flow
  • Q max is the maximum capacity in the macro basic map of the target traffic flow
  • K cr is the critical density in the macro basic map of the target traffic flow
  • K jam is the congestion density in the macro basic map of the target traffic flow.
  • the terminal device can calculate the vehicle reference distance D according to the target traffic density K through the above formula (1).
  • the terminal device can obtain other basic parameters through the first configuration interface accordingly, and use other specific The calculation method determines the vehicle reference speed and vehicle reference distance based on the acquired basic parameters.
  • the terminal device when determining the number of target background vehicles in the target lane according to the target background vehicle number indicator parameter in the target lane, can take specific determinations according to the type of the target background vehicle number indicator parameter received through the first configuration interface. Way to determine the number of target background vehicles in the target lane.
  • the target background vehicle quantity indicator parameter received by the terminal device through the first configuration interface is the target background vehicle quantity parameter
  • the target background vehicle quantity parameter is used to indicate the target vehicle quantity on the target lane
  • the terminal device can directly use the target vehicle number indicated by the target background vehicle number parameter as the target background vehicle number on the target lane in the simulated traffic environment.
  • the terminal device may use the position range indicator parameter of the target background vehicle and the vehicle reference distance , To determine the number of target background vehicles in the target lane.
  • the position range indication parameter is used to indicate the position range of the generated background vehicle.
  • the position range is usually a range that can verify the decision algorithm of the test vehicle; when setting, the position can be set according to the parking sight distance of the test vehicle Range parameter, for example, the position of the test vehicle can be taken as the center, twice the parking sight distance of the test vehicle can be regarded as the length of the above-mentioned position range, that is, the parking sight distance of the test vehicle is taken as the radius, so that in the target lane
  • Range parameter for example, the position of the test vehicle can be taken as the center, twice the parking sight distance of the test vehicle can be regarded as the length of the above-mentioned position range, that is, the parking sight distance of the test vehicle is taken as the radius, so that in the target lane
  • the above determines the location range used to generate the background vehicle.
  • the terminal device can determine the number of target background vehicles in the target lane according to the position range indicated by the position range indicator parameter and the vehicle reference distance.
  • the position range indication parameter of the target background vehicle input by the user through the first configuration interface may include: a first distance parameter R1 and a second distance parameter R2, where R1 is used to indicate the test vehicle and the background vehicle in the forward direction of the test vehicle R2 is used to indicate the maximum distance between the test vehicle and the background vehicle in the reverse direction of the test vehicle.
  • the ratio of R1 to the vehicle reference distance can be determined, and the ratio of the R1 to the vehicle reference distance can be used as the number of background vehicles in front of the test vehicle on the target lane M1: Determine the ratio of R2 to the vehicle reference distance, and use the ratio of R2 to the vehicle reference distance as the target vehicle number M2 behind the test vehicle on the target lane.
  • the determination of the above-mentioned position range is usually implemented according to the Frenet coordinate system, that is, the center line of the target lane is used as the ordinate axis of the coordinate system, and the line perpendicular to the center line is used as the abscissa axis of the coordinate system.
  • first distance parameter R1 and the second distance parameter R2 may be equal or different. In practical applications, both the first distance parameter R1 and the second distance parameter R2 can be set to test the parking of the vehicle. Sight distance; the user can also set any value as the first distance parameter R1 and/or the second distance parameter R2 according to actual simulation requirements, and the first distance parameter R1 and the second distance parameter R2 are not limited here.
  • the terminal device can also obtain other forms of target background vehicle quantity indicator parameters through the first configuration interface. Accordingly, according to this form of target background vehicle quantity indicator parameters, the terminal device can determine the target lane target in a corresponding manner.
  • the number of background vehicles here is no restriction on the form of the target background vehicle quantity indication parameter, nor is there any restriction on the number of target background vehicles for the terminal device to determine the target lane.
  • the terminal device calculates the vehicle reference distance, the vehicle reference speed, and the number of target background vehicles in the target lane. , As the relevant parameters used to set the background vehicle in the simulated traffic environment, without additional calculation processing.
  • Step 203 Determine the initial position of each background vehicle belonging to the target lane based on the location of the test vehicle, the vehicle reference distance and the random distance deviation; determine the initial position of each background vehicle belonging to the target lane based on the vehicle reference speed and the random speed deviation speed.
  • the terminal device After the terminal device determines the vehicle reference distance, vehicle reference speed, and the number of target background vehicles in the target lane, it can determine the initial position of the i-th background vehicle in the target lane according to the location of the test vehicle, the vehicle reference distance, and the random distance deviation. And the initial speed of the i-th background vehicle in the target lane is determined one by one according to the vehicle reference speed and the random speed deviation.
  • the terminal device can determine the location of the test vehicle in the simulated traffic environment according to the parameters input by the user on the relevant configuration interface. For example, the user can set the location of the test vehicle in the simulated traffic environment through the relevant configuration interface. In the second lane, correspondingly, when the terminal device builds a simulated traffic environment, set the test vehicle in the second lane.
  • the terminal device can also automatically set the location of the test vehicle in the simulated traffic environment according to the actual simulation needs of the user, and there is no limitation on the setting method of the location of the test vehicle here.
  • both the random distance deviation and the random speed deviation are randomly determined for each background vehicle, so as to ensure that the random distance deviation and the random speed deviation corresponding to different background vehicles are as different as possible, thereby ensuring that the background vehicles are diverse in the simulation process. Sex. Specifically, when determining the random distance deviation and the random speed deviation for the background vehicle, it can be determined according to the normal distribution or the chi-square distribution. The method for determining the random distance deviation and the random speed deviation is not limited here. The following first introduces the method for determining the initial position of each background vehicle on the target lane.
  • the terminal device determines the initial position of the background vehicle in front of the test vehicle on the target lane, it can first superimpose the random distance deviation on the basis of the vehicle reference distance to obtain the first front distance, which is the position of the first front distance from the front of the test vehicle It can be used as the initial position of the first background vehicle in front of the test vehicle, that is, the terminal device can set the first background vehicle in front of the test vehicle at the position of the first front distance from the front of the test vehicle; then, The second front distance is obtained by superimposing the random distance deviation on the basis of the vehicle reference distance.
  • the second front distance can be regarded as the second front distance from the initial position of the first background vehicle in front of the test vehicle.
  • the initial position of the front background vehicle and so on, set the initial position of each background vehicle in front of the test vehicle one by one until the number of background vehicles in front of the test vehicle reaches the preset number of background vehicles in front of the test vehicle.
  • the terminal device when it determines the initial position of the background vehicle behind the test vehicle on the target lane, it can first superimpose the random distance deviation on the basis of the vehicle reference distance to obtain the first rear distance, which is the first distance from the rear of the test vehicle.
  • the position of the first rear distance can be used as the initial position of the first background vehicle behind the test vehicle, that is, the terminal device can set the first rear distance from the front of the test vehicle.
  • the background vehicle then, superimpose the random distance deviation on the basis of the vehicle reference distance to obtain the second rear distance.
  • the position that is separated from the initial position of the first background vehicle behind the test vehicle from the second rear distance can be used as the first The initial positions of two background vehicles behind the test vehicle; and so on, set the initial positions of each background vehicle behind the test vehicle one by one until the number of background vehicles behind the test vehicle reaches the preset background behind the test vehicle Until the number of vehicles.
  • the above random distance deviation can be positive or negative; because when determining the respective initial position of each background vehicle, different random distance deviations will be superimposed on the basis of the vehicle reference distance, and according to the superposition
  • the deviated vehicle distance determines the initial position of each background vehicle. Therefore, it can be ensured that the initial position of each background vehicle is random and diverse, which is closer to the real traffic scene.
  • the method for determining the initial speed of each background vehicle on the target lane is described below. Specifically, when setting the initial speed for a background vehicle, a random speed deviation can be superimposed on the vehicle reference speed, and then the vehicle speed obtained after superimposing the random speed deviation is set as the initial speed of the background vehicle; thus, the simulated traffic is determined The initial speed of each background vehicle in the environment.
  • the random distance deviation used when determining the initial position of the i-th background vehicle on the target lane, can be a normal random variable conforming to the first normal distribution.
  • the random speed deviation used may be a normal random variable conforming to the second normal distribution. That is, the initial position of each background vehicle can be determined according to the random distance deviation conforming to the normal distribution, and the initial speed of each background vehicle can be determined according to the random speed deviation conforming to the normal distribution.
  • the random distance deviation and the random speed deviation described above can also be determined in other ways, and the method for determining the random distance deviation and the method for determining the random speed deviation is not limited herein.
  • the terminal device needs to determine the number of target background vehicles on the S target lanes; for the jth ( The value of j is a positive integer not exceeding S) the target lane, the terminal device can determine the initial position of the i-th background vehicle in the j-th target lane according to the location of the test vehicle, the vehicle reference distance, and the random distance deviation. And according to the vehicle reference speed and the random speed deviation, the initial speed of the i-th background vehicle located in the j-th target lane is sequentially determined.
  • the terminal device when the terminal device sets the initial position and initial speed for each background vehicle on the target lane where the test vehicle is located, it can directly determine the respective initial position and initial speed of each background vehicle according to the above method; the terminal device targets other target lanes When setting the initial position and initial speed of each background vehicle, you can first translate the position of the test vehicle to the target lane along the direction perpendicular to the target lane, and use the translated position as the reference position. Then, according to the reference position, The above method is used to determine the respective initial position and initial speed of each background vehicle on the target lane.
  • Step 204 Based on the initial position and initial speed of each background vehicle and the number of background vehicles, simulate driving each background vehicle in a simulated traffic environment.
  • the autonomous driving simulation can be started in the simulated traffic environment; during the simulation process, the vehicle fleet consisting of the test vehicle and each background vehicle will move along the target road together
  • the driving pattern can usually follow the car-following model.
  • the car-following model is constructed based on the microscopic driving behavior of car following (CF), which is used to describe the interaction between two adjacent cars in a convoy driving on one-way roads that restrict overtaking; the car-following model uses The dynamic method is used to study the corresponding behavior of the car-following car caused by the change of the leading vehicle (Leading Vehicle, LV) motion state, and to understand the traffic flow characteristics of the single-lane by analyzing the way of each vehicle following the car.
  • CF microscopic driving behavior of car following
  • the types of background vehicles include pilot background vehicles (the frontmost vehicle among all background vehicles) and following background vehicles (background vehicles other than pilot background vehicles); fix the speed of pilot background vehicles and update the speed of the background vehicles Speed so that the following background vehicle can follow the pilot vehicle.
  • the simulation scene When the simulation scene is initially set, if the requirement of the surrounding traffic state of the scene to be tested is a non-free driving state, it is necessary to set the initial speed of the background vehicle to be lower than the speed of the free-stream vehicle.
  • the background vehicle at the forefront will gradually accelerate to the free-stream speed and drive out of the expected speed without other speed constraints.
  • the set position range that is, the test range valid for the test vehicle
  • other background vehicles following the background vehicle will gradually enter the free-running state and drive out of the preset position range.
  • the background vehicles around the test vehicle are gradually decreasing, and the decision algorithm of the test vehicle cannot be effectively verified.
  • the traffic state of the test vehicle will passively change to a free-running state and deviate
  • the surrounding traffic state is the initial setting of the non-free driving state.
  • the terminal device updates the speed and position of the background vehicle according to the car-following model during the simulation, it will fix the speed of the background vehicle at the front and control the background vehicle not to follow the car.
  • the model accelerates to free-stream speed so that it is always within the preset position range.
  • the above driving simulation method only requires the tester to input a few basic parameters through the first configuration interface to complete the setting of each background vehicle in the simulated traffic environment, which greatly simplifies the operations that the tester needs to perform and improves the construction of the simulated traffic environment effectiveness.
  • this method also considers random speed deviations and random position deviations in the process of setting each background vehicle, which ensures that the setting of each background vehicle driving state has diversity and randomness, making the simulated traffic environment more realistic.
  • the speed of the background vehicle at the front is fixed, and on this basis, the speed constraints of other background vehicles in the car-following model are realized, thereby preventing the background vehicles from being affected by the simulation traffic environment.
  • the lack of speed constraints causes the background vehicles to gradually drive out of the effective test range for the test vehicle, and the number of vehicles around the test vehicle gradually decreases, which makes it impossible to effectively test the decision algorithm of the test vehicle.
  • the user can first configure the free flow speed, congestion density, critical density, and maximum traffic capacity through the second configuration interface displayed on the terminal device. For example, suppose the user sets the free-flow vehicle speed to be 80 km/h, the congestion density is 140 vehicles/km, the critical density is 25 vehicles/km, and the maximum traffic capacity is 2000 vehicles/hour.
  • the terminal device After the terminal device receives the parameters input by the user through the second configuration interface, it will construct a macro basic diagram of the target traffic flow suitable for this simulation based on these parameters, as shown in Figure 4B.
  • the terminal device will display to the user a first configuration interface for configuring basic parameters.
  • the user can input the target traffic density and position range indication parameters through the first configuration interface.
  • the position range indication parameters may include the first distance parameter and the first distance parameter.
  • Two distance parameters For example, suppose that the target traffic density input by the user is 48 vehicles/km, and the first distance parameter and the second distance parameter are both 100 meters.
  • the terminal device calculates the reciprocal of the target traffic density of 48 vehicles/km as the vehicle reference distance, that is, by calculating 1000 (converting kilometers to meters) and dividing by 48, the vehicle reference distance is determined to be 20.83 meters, that is, between two adjacent background vehicles The distance is 20.83 meters.
  • the number of background vehicles that need to be set before the test vehicle can be determined according to the first distance parameter and the vehicle reference distance. For example, the terminal device calculates 100 divided by 20.83 to determine that 5 background vehicles need to be set before the test vehicle. Similarly, the terminal device determines that it is necessary to set up 5 background vehicles after the test vehicle.
  • the terminal device also needs to determine the target capacity of the simulation according to the macro basic map of the target traffic flow shown in Figure 4B and the target traffic density input by the user.
  • the target traffic density corresponding to a target traffic density of 48 vehicles/km corresponds to a target capacity of 1600 vehicles/hour; furthermore, the ratio of the target traffic capacity of 1600 vehicles/hour to the target traffic density of 48 vehicles/km is calculated as the vehicle reference speed for this simulation, namely Divide 1600 by 48 to get a reference speed of 33.33 km/h.
  • this simulation needs to set 5 background vehicles before and after the test vehicle, and the vehicle reference distance is 20.83 meters, and the vehicle reference speed is 33.33 km/h.
  • the terminal device can superimpose a random distance deviation on the basis of the vehicle reference distance, determine the initial position of each background vehicle, and superimpose the random speed deviation on the basis of the vehicle reference speed to determine The initial speed of each background vehicle, and then realize the automatic driving simulation, the simulation traffic environment built is shown in Figure 4D.
  • the method of setting a background vehicle in a simulated traffic environment by the terminal device and the method of driving simulation by the terminal device are introduced as a whole with reference to FIGS. 5 and 6A-6B. .
  • FIG. 5 is a schematic flowchart of a method for setting a background vehicle in a simulated traffic environment provided by an embodiment of the application. As shown in Figure 5, the method includes the following steps:
  • Step 501 The terminal device receives the target traffic density and location range indication parameters input by the user through the first configuration interface, so as to realize the simulation initialization setting.
  • Step 502 The terminal device determines the reciprocal of the target traffic density as the vehicle reference distance, and determines the number of background vehicles that need to be generated on each target lane according to the vehicle reference distance and the position range indication parameter input by the user; for example, it needs to determine The number of vehicles in front of the test vehicle in each target lane, and the number of vehicles behind the test vehicle.
  • the terminal device determines the target capacity corresponding to the target traffic density input by the user according to the macro basic map of the target traffic selected or customized by the user, and then calculates the ratio of the target capacity to the target traffic density as the vehicle reference speed of the background vehicle.
  • Step 503 Use the target lane where the background vehicle currently needs to be set as the current lane, and use the location of the test vehicle as the current location; it should be understood that if there is no test vehicle in the current lane, the test vehicle will be translated in the direction perpendicular to the lane. The current lane, and further, the position of the translated test vehicle on the current lane is taken as the current position.
  • Step 504 Determine whether the number of vehicles in front of the test vehicle meets the first preset number of vehicles; the first preset number of vehicles is the number of vehicles located in front of the test vehicle on the target lane determined in step 502. If it is satisfied, go to step 508, if not, go to step 505.
  • Step 505 Use the current position as a reference to move the vehicle forward by a distance corresponding to the reference distance, and superimpose a random distance deviation, and use the thus determined position as the new current position.
  • Step 506 Set a background vehicle at the current position determined in step 505, superimpose a random speed deviation on the basis of the vehicle reference speed determined in step 502, and use the determined speed as the set background vehicle speed Initial velocity.
  • Step 507 Add 1 to the number of background vehicles in front of the test vehicle to obtain the updated number of vehicles in front of the test vehicle, and return to step 504.
  • Step 508 Determine whether the number of vehicles behind the test vehicle meets the second preset number of vehicles; the second preset number of vehicles is the number of vehicles located behind the test vehicle in the target lane determined in step 502. If it is satisfied, go to step 512; if not, go to step 509.
  • Step 509 Using the current position determined in step 503 as a reference, move the vehicle back a distance corresponding to the reference distance, and superimpose a random distance deviation, and use the position thus determined as the new current position.
  • Step 510 Set a background vehicle at the current position determined in step 509, superimpose a random speed deviation on the basis of the vehicle reference speed determined in step 502, and use the determined speed as the set background vehicle speed Initial velocity.
  • Step 511 Add 1 to the number of background vehicles behind the test vehicle to obtain the updated number of vehicles behind the test vehicle, and return to step 508.
  • Step 512 Determine whether all target lanes have been traversed; that is, determine whether the setting of background vehicles on all target lanes has been completed; if yes, perform step 514; if not, perform step 513.
  • Step 513 Select the next target lane where no background vehicle is set as the current lane, and return to step 503.
  • Step 514 Confirm that the setting of all background vehicles in the simulated traffic environment is completed.
  • FIG. 6A is a schematic flowchart of a driving simulation process provided by an embodiment of this application. As shown in Figure 6A, the driving simulation process includes the following steps:
  • Step 601 After setting up each background vehicle in the simulated traffic environment, the terminal device can control the simulation to start running and start to traverse the background vehicles in the simulated traffic environment.
  • Step 602 Determine whether the current vehicle is the frontmost background vehicle; if yes, execute step 603, and if not, execute step 604.
  • Step 603 Fix the speed of the background vehicle.
  • Step 604 Update the speed of the background vehicle according to the car following model.
  • Step 605 Determine whether each background vehicle in the simulated traffic environment has been traversed; if yes, execute step 607; if not, execute step 606.
  • Step 606 Select the next background vehicle in the simulated traffic environment as the current vehicle, and return to step 602.
  • Step 607 Control each vehicle in the simulated traffic environment to make a lane change judgment, and update the lateral speed of each vehicle in the simulated traffic environment.
  • Step 608 Update the position of each vehicle in the simulated traffic environment.
  • Step 609 Determine whether the total simulation time of this simulation has reached the preset simulation time; if it reaches the preset simulation time, step 611 is executed, and if it is not reached, step 610 is executed.
  • Step 610 Control the simulation clock to advance at an equal distance, and prepare to traverse each background vehicle in the simulated traffic environment again.
  • Step 611 Determine the end of the simulation run.
  • FIG. 6B is a schematic flowchart of a driving simulation process provided by an embodiment of the application. As shown in Figure 6B, the driving simulation process includes the following steps:
  • Step 601 After setting up each background vehicle in the simulated traffic environment, the terminal device can control the simulation to start running and start to traverse the background vehicles in the simulated traffic environment.
  • Step 602 Determine whether the current vehicle is the frontmost background vehicle; if yes, execute step 603, and if not, execute step 604.
  • Step 603 Fix the speed of the background vehicle.
  • Step 604 Update the speed of the background vehicle according to the car following model.
  • Step 605 Record the driving data of the test vehicle.
  • Step 606 Determine whether each background vehicle in the simulated traffic environment has been traversed; if yes, execute step 608; if not, execute step 607.
  • Step 607 Select the next background vehicle in the simulated traffic environment as the current vehicle, and return to step 602.
  • Step 608 Control each vehicle in the simulated traffic environment to make a lane change judgment, and update the lateral speed of each vehicle in the simulated traffic environment.
  • Step 609 Update the position of each vehicle in the simulated traffic environment.
  • Step 610 Determine whether the total simulation time of this simulation has reached the preset simulation time; if it reaches the preset simulation time, step 612 is executed, if not, step 611 is executed.
  • Step 611 Control the simulation clock to advance equidistantly, and prepare to traverse each background vehicle in the simulated traffic environment again.
  • Step 612 Evaluate the decision algorithm based on the driving data of the test vehicle.
  • Step 613 Determine the end of the simulation run.
  • this application also provides a corresponding driving simulation device, so that the driving simulation method can be applied and realized in practice.
  • Fig. 7 is a schematic structural diagram of a driving simulation device 700 corresponding to the driving simulation method shown in Fig. 2 above, and the driving simulation device 700 includes:
  • the first interaction module 701 is configured to display a first configuration interface and receive parameters input through the first configuration interface;
  • the parameter determination module 702 is configured to determine the vehicle reference distance, the vehicle reference speed, and the number of background vehicles in the target lane based on the parameters; wherein the target lane includes the lane where the test vehicle and the background vehicle are located;
  • the background vehicle generation module 703 is configured to determine the initial position of each background vehicle belonging to the target lane based on the location of the test vehicle, the vehicle reference distance, and the random distance deviation; based on the vehicle reference speed and random speed Deviation, determining the initial speed of each of the background vehicles belonging to the target lane;
  • the simulation control module 704 is configured to simulate driving each background vehicle in a simulated traffic environment based on the initial position and initial speed of each background vehicle and the number of the background vehicles.
  • FIG. 8 is a schematic structural diagram of another driving simulation device 800 provided by an embodiment of the application.
  • the first configuration interface includes: configuration controls for configuring the traffic state indication parameters, and configuration controls for configuring the background vehicle quantity indication parameters
  • the first interaction module 701 is configured to: The target traffic state indication parameter and the target background vehicle quantity indication parameter input by the configuration control on the first configuration interface;
  • the parameter determination module 702 includes: a traffic state determination sub-module 801 configured to determine a vehicle reference distance and a vehicle reference speed based on the macro basic map of the target traffic flow and the target traffic state indication parameters; a background vehicle number determination sub-module 802, It is configured to determine the number of background vehicles in the target lane based on the target number of background vehicles in the target lane.
  • a traffic state determination sub-module 801 configured to determine a vehicle reference distance and a vehicle reference speed based on the macro basic map of the target traffic flow and the target traffic state indication parameters
  • a background vehicle number determination sub-module 802 It is configured to determine the number of background vehicles in the target lane based on the target number of background vehicles in the target lane.
  • the target traffic state indication parameter includes a target traffic density
  • the traffic state determination submodule 801 is configured as: the inverse of the target traffic density As the vehicle reference distance;
  • the macro basic map of the target traffic includes a first straight line segment and a second straight line segment located in a coordinate system; the horizontal axis of the coordinate system represents Traffic density, the vertical axis of the coordinate system represents the capacity, each point in the first straight line segment and the second straight line segment represents a traffic state, then the traffic state determining submodule 801 is configured to be specific Used for:
  • a point whose abscissa is the target traffic density is taken as a target traffic state
  • the ordinate of the target traffic state is taken as the target capacity of the target traffic state in the macro basic map of the target traffic.
  • the target traffic state indication parameters include target traffic capacity and target vehicle speed; then the traffic state determination submodule 801 is configured to: Determine the target traffic state corresponding to the target capacity and target vehicle speed in the traffic macro basic map, determine the target traffic density of the target traffic state in the target traffic macro basic map, and divide the target traffic density into The reciprocal is used as the vehicle reference distance; and,
  • the target vehicle speed is determined to be the vehicle reference speed.
  • the macro basic map of the target traffic includes a coordinate system and a first straight line segment and a second straight line segment located in the coordinate system; the coordinates The horizontal axis of the system represents traffic density, the vertical axis of the coordinate system represents capacity, and each point on the first straight line segment and the second straight line segment represents a traffic state; then the traffic state determiner Module 801 is configured as:
  • the ordinate is determined as the target traffic capacity, and the slope connecting the origin of the coordinate is the point of the target vehicle speed, as the target traffic status;
  • the abscissa of the target traffic state is taken as the target traffic density of the target traffic state in the target traffic macro basic map.
  • FIG. 9 is a schematic structural diagram of another driving simulation device 900 provided by an embodiment of the application.
  • the device further includes: a second interaction module 901, configured to display a second configuration interface, and receive traffic flow quantitative parameters input through the second configuration interface.
  • the traffic flow quantitative parameters include free flow vehicle speed, congestion density, critical density, and Maximum traffic capacity;
  • the basic map generation module 902 configured to generate a first straight line segment used to characterize the free running state of the vehicle according to the free-flow vehicle speed, the critical density, and the maximum traffic capacity;
  • the macro basic map of the target traffic flow is constructed.
  • the target background vehicle quantity indication parameter includes a background vehicle quantity parameter, which is used to indicate the number of background vehicles on the target lane.
  • the target background vehicle quantity indication parameter includes a position range indication parameter; then the background vehicle quantity determination submodule 802 is configured to: according to the target The position range indicator parameter of the background vehicle and the vehicle reference distance determine the number of background vehicles in the target lane.
  • the position range indication parameter of the target background vehicle includes a first distance parameter and a second distance parameter, wherein the first distance parameter is used for Indicates the maximum distance between the test vehicle and the background vehicle in the forward direction of the test vehicle; the second distance parameter is used to indicate the maximum distance between the test vehicle and the background vehicle in the backward direction of the test vehicle distance;
  • the background vehicle quantity determination submodule 802 is configured to: determine the ratio of the first distance parameter to the vehicle reference distance, and use the ratio as the number of background vehicles in front of the test vehicle on the target lane; The ratio of the second distance parameter to the vehicle reference distance, and the ratio is taken as the number of background vehicles behind the test vehicle on the target lane.
  • the first interaction module 701 is configured to: receive parameters input through configuration controls on the first configuration interface, and the parameters include vehicle The reference distance and vehicle reference speed and the number of background vehicles in the target lane.
  • the background vehicle generation module 703 is configured to determine the number of target background vehicles in each of the S target lanes, and the value of S is greater than 1. Positive integer; for the j-th target lane, the initial position of the i-th background vehicle in the j-th target lane is sequentially determined based on the location of the test vehicle, the vehicle reference distance, and the random distance deviation, and based on the vehicle reference speed The initial speed of the i-th background vehicle located in the j-th target lane is sequentially determined with the random speed deviation, and the value of j is a positive integer not exceeding S.
  • the types of the background vehicles include pilot background vehicles and following background vehicles; the simulation control module 704 is configured to: fix the pilot background vehicles And update the speed of the following background vehicle so that the following background vehicle can follow the pilot vehicle.
  • the random distance deviation is a normal random variable that conforms to the first normal distribution
  • the random speed deviation is a normal random variable conforming to the second normal distribution
  • the value range of i is 1 to N
  • N is The total number of background vehicles.
  • the above driving simulation device only needs the tester to input a few basic parameters through the first configuration interface to complete the setting of each background vehicle in the simulated traffic environment, which greatly simplifies the operations that the tester needs to perform and improves the construction of the simulated traffic environment effectiveness.
  • the device will further consider random speed deviations and random position deviations in the process of setting each background vehicle, ensuring that the setting of each background vehicle driving state has diversity and randomness, making the simulated traffic environment more realistic.
  • the speed of the background vehicle at the front is fixed, and on this basis, the speed constraints of other background vehicles in the car-following model are realized, thereby preventing the background vehicles from being affected by the simulation traffic environment.
  • the lack of speed constraints causes the background vehicles to gradually drive out of the effective test range for the test vehicle, and the number of vehicles around the test vehicle gradually decreases, which makes it impossible to effectively test the decision algorithm of the test vehicle.
  • the embodiment of the present application also provides a device for driving simulation.
  • the device may be a terminal.
  • the following describes the above-mentioned device provided by the embodiment of the present application from the perspective of hardware materialization.
  • the embodiment of the present application also provides a device. As shown in FIG. 10, for ease of description, only parts related to the embodiment of the present application are shown. For specific technical details that are not disclosed, please refer to the method part of the embodiment of the present application.
  • the terminal can be any terminal device including a mobile phone, a tablet computer, a personal digital assistant (PDA), a point of sales (POS), a vehicle-mounted computer, etc. Take the terminal as a mobile phone as an example:
  • FIG. 10 shows a block diagram of a part of the structure of a mobile phone related to a terminal provided in an embodiment of the present application.
  • the mobile phone includes: a radio frequency (RF) circuit 1010, a memory 1020, an input unit 1030, a display unit 1040, a sensor 1050, an audio circuit 1060, a wireless fidelity (WiFi) module 1070, and a processor 1080 , And power supply 1090 and other components.
  • RF radio frequency
  • the memory 1020 can be used to store software programs and modules.
  • the processor 1080 runs the software programs and modules stored in the memory 1020 to execute various functional applications and data processing of the mobile phone.
  • the memory 1020 may mainly include a program storage area and a data storage area.
  • the program storage area may store an operating system, an application program required by at least one function (such as a sound playback function, an image playback function, etc.), etc.; Data (such as audio data, phone book, etc.) created by the use of mobile phones.
  • the memory 1020 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices.
  • the processor 1080 is the control center of the mobile phone. It uses various interfaces and lines to connect the various parts of the entire mobile phone. It executes by running or executing software programs and/or modules stored in the memory 1020, and calling data stored in the memory 1020. Various functions and processing data of the mobile phone can be used to monitor the mobile phone as a whole.
  • the processor 1080 may include one or more processing units; the processor 1080 may integrate an application processor and a modem processor, where the application processor mainly processes the operating system, user interface, and application programs.
  • the device mainly deals with wireless communication. It can be understood that the foregoing modem processor may not be integrated into the processor 1080.
  • the processor 1080 included in the terminal also has the following functions:
  • the target lane includes the lane where the test vehicle and the background vehicle are located;
  • driving each of the background vehicles is simulated in a simulated traffic environment.
  • the processor 1080 is further configured to execute steps of any implementation manner of the driving simulation method provided in the embodiments of the present application.
  • the embodiments of the present application also provide a computer-readable storage medium for storing a computer program, and the computer program is used to execute any one of the driving simulation methods described in the foregoing embodiments.
  • the embodiments of the present application also provide a computer program product including instructions, which when run on a computer, cause the computer to execute any one of the driving simulation methods described in the foregoing embodiments.
  • the device in this embodiment of the application determines the vehicle reference distance, vehicle reference speed, and the number of background vehicles in the target lane based on the parameters input in the first configuration interface, and determines each background based on the location of the test vehicle, the vehicle reference distance, and the random distance deviation
  • the initial position of the vehicle determines the initial speed of each background vehicle based on the vehicle reference speed and the random speed deviation, and finally, based on the initial position, initial speed and number of background vehicles of each background vehicle, simulate driving each vehicle in a simulated traffic environment Background vehicles.
  • the method provided in the embodiment of the present application can effectively reduce the manual operation required in the process of building a simulated traffic environment, and improve the efficiency of building a simulated traffic environment.
  • the method provided by the embodiment of the present application determines the vehicle reference distance, vehicle reference speed, and the target number of background vehicles in the target lane according to the basic parameters input by the user, it will also compare the vehicle reference distance and the random distance deviation and the random speed deviation respectively.
  • the vehicle reference speed is adjusted, and then the respective initial positions and initial speeds of each background vehicle are set to ensure the diversity and randomness of the set background vehicle driving states to meet the basic needs of traffic simulation.

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Abstract

一种驾驶仿真方法、装置、设备及计算机可读存储介质，其中，该方法包括：显示第一配置界面，并接收通过第一配置界面输入的参数（201），基于参数确定车辆基准间距、车辆基准速度以及目标车道的背景车辆数量（202），基于测试车辆所在位置、车辆基准间距以及随机距离偏差，确定属于目标车道的每个背景车辆的初始位置；基于车辆基准速度以及随机速度偏差，确定属于目标车道的每个背景车辆的初始速度（203）；基于每个背景车辆的初始位置和初始速度以及背景车辆数量，在仿真的交通环境中模拟行驶每个背景车辆（204）。

Description

一种驾驶仿真方法、装置、电子设备及计算机存储介质
相关申请的交叉引用
本申请基于申请号为201910368409.1、申请日为2019年05月05日的中国专利申请提出，并要求该中国专利申请的优先权，该中国专利申请的全部内容在此引入本申请作为参考。
技术领域
本申请涉及自动驾驶技术领域，尤其涉及一种驾驶仿真方法、装置、电子设备及计算机可读存储介质。
背景技术
自动驾驶汽车是一种通过电脑系统实现无人驾驶的智能汽车，能够给人带来诸如减少交通事故、节省能源、让人拥有更多的自由时间等等很多好处，是未来汽车的发展方向。
自动驾驶汽车的行驶是受到决策算法控制的，为了测试决策算法，需要搭建仿真交通环境，由决策算法控制的测试车辆在仿真交通环境中行驶，通过观测、记录测试车辆的行驶状态来对决策算法进行评估。
为了使仿真驾驶环境尽量还原真实行驶环境，仿真驾驶环境总需要有若干辆背景车辆，且背景车辆需要有差异化的驾驶行为。
发明内容
本申请实施例提供了一种驾驶仿真方法、装置、电子设备及计算机可读存储介质，能够有效地提高仿真交通环境的搭建效率和准确率。
本申请实施例提供了一种驾驶仿真方法，所述方法由电子设备执行，所述电子设备包括有一个或多个处理器以及存储器，以及一个或一个以上 的程序，其中，所述一个或一个以上的程序存储于存储器中，所述程序可以包括一个或一个以上的每一个对应于一组指令的单元，所述一个或多个处理器被配置为执行指令；所述方法包括：
显示第一配置界面，并接收通过所述第一配置界面输入的参数；
基于所述参数确定车辆基准间距、车辆基准速度以及目标车道的背景车辆数量；其中，所述目标车道包括测试车辆以及背景车辆所在的车道；
基于测试车辆所在位置、所述车辆基准间距以及随机距离偏差，确定属于所述目标车道的每个所述背景车辆的初始位置；
基于所述车辆基准速度以及随机速度偏差，确定属于所述目标车道的每个所述背景车辆的初始速度；
基于每个所述背景车辆的初始位置和初始速度以及所述背景车辆数量，在仿真的交通环境中模拟行驶每个所述背景车辆。
本申请实施例提供了一种驾驶仿真方法，所述方法由服务器执行，所述服务器包括有一个或多个处理器以及存储器，以及一个或一个以上的程序，其中，所述一个或一个以上的程序存储于存储器中，所述程序可以包括一个或一个以上的每一个对应于一组指令的单元，所述一个或多个处理器被配置为执行指令；所述方法包括：
显示第一配置界面，并接收通过所述第一配置界面输入的参数；
基于所述参数确定车辆基准间距、车辆基准速度以及目标车道的背景车辆数量；其中，所述目标车道包括测试车辆以及背景车辆所在的车道；
基于测试车辆所在位置、所述车辆基准间距以及随机距离偏差，确定属于所述目标车道的每个所述背景车辆的初始位置；
基于所述车辆基准速度以及随机速度偏差，确定属于所述目标车道的每个所述背景车辆的初始速度；
基于每个所述背景车辆的初始位置和初始速度以及所述背景车辆数量，在仿真的交通环境中模拟行驶每个所述背景车辆。
本申请实施例提供了一种驾驶仿真装置，包括：
第一交互模块，配置为显示第一配置界面，并接收通过所述第一配置界面输入的参数；
参数确定模块，配置为基于所述参数确定车辆基准间距、车辆基准速度以及目标车道的背景车辆数量；其中，所述目标车道包括测试车辆以及背景车辆所在的车道；
背景车辆生成模块，配置为基于测试车辆所在位置、所述车辆基准间距以及随机距离偏差，确定属于所述目标车道的每个所述背景车辆的初始位置；基于所述车辆基准速度以及随机速度偏差，确定属于所述目标车道的每个所述背景车辆的初始速度；
仿真控制模块，配置为基于每个所述背景车辆的初始位置和初始速度以及所述背景车辆数量，在仿真的交通环境中模拟行驶每个所述背景车辆。
本申请实施例提供了一种电子设备，所述设备包括处理器以及存储器：
所述存储器用于存储计算机程序；
所述处理器用于根据所述计算机程序，执行如上述的驾驶仿真方法。
本申请实施例提供了一种计算机可读存储介质，所述计算机可读存储介质中存储计算机程序，所述计算机程序被执行时，实现上述的驾驶仿真方法。
本申请实施例提供了一种包括指令的计算机程序产品，当其在计算机上运行时，使得所述计算机执行上述的驾驶仿真方法。
从以上技术方案可以看出，本申请实施例具有以下优点：
本申请实施例提供了一种驾驶仿真方法，用户基于该方法搭建仿真交通环境时，仅需通过第一配置界面一次性配置少量的基本参数，即可完成仿真交通环境中各背景车辆的设置，能够有效地减少仿真交通环境搭建过程中所需的人工操作，提高仿真交通环境的搭建效率。并且，还会分别根据随机距离偏差和随机速度偏差对车辆基准间距和车辆基准速度进行调整， 保证所设置的各背景车辆行驶状态具有多样性和随机性，有效地提高仿真交通环境的准确率，满足交通仿真的基本需求。
附图说明
图1A-1C为本申请实施例提供的驾驶仿真方法的应用场景示意图；
图2为本申请实施例提供的驾驶仿真方法的流程示意图；
图3为本申请实施例提供的目标交通流宏观基本图；
图4A为本申请实施例提供的计算车辆基准速度的原理示意图；
图4B为本申请实施例提供的目标交通流宏观基本图；
图4C为本申请实施例提供的计算车辆基准速度的原理示意图；
图4D为本申请实施例提供的驾驶仿真界面的示意图；
图5为本申请实施例提供的背景车辆设置方法的流程示意图；
图6A-6B为本申请实施例提供的驾驶仿真过程的流程示意图；
图7为本申请实施例提供的驾驶仿真装置的结构示意图；
图8为本申请实施例提供的驾驶仿真装置的结构示意图；
图9为本申请实施例提供的驾驶仿真装置的结构示意图；
图10为本申请实施例提供的终端设备的结构示意图。
具体实施方式
为了使本技术领域的人员更好地理解本申请方案，下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
本申请的说明书和权利要求书及上述附图中的术语“第一”、“第二”等是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。应该理解 这样使用的数据在适当情况下可以互换，以便这里描述的本申请的实施例能够以除了在这里图示或描述的那些以外的顺序实施。此外，术语“包括”和“具有”以及他们的任何变形，意图在于覆盖不排他的包含，例如，包含了一系列步骤或单元的过程、方法、系统、产品或设备不必限于清楚地列出的那些步骤或单元，而是可包括没有清楚地列出的或对于这些过程、方法、产品或设备固有的其它步骤或单元。
为了便于理解本申请实施例提供的技术方案，下面先对本申请实施例提供的驾驶仿真方法的应用场景进行介绍。本申请实施例提供的驾驶仿真方法可以采用软件实施，例如，用于自动驾驶仿真的仿真软件，仿真软件可以部署在终端设备中，也可以部署在服务器中，下面分别进行说明。
参见图1A，图1A为本申请实施例提供的驾驶仿真方法的应用场景示意图；如图1A所示，该应用场景中包括开发者110和电子设备120；电子设备120可以运行仿真程序。
其中，开发者110输入用于在仿真交通环境中设置背景车辆的基本参数后，电子设备120在仿真程序中设置与设置的基本参数匹配的背景车辆(背景车流)，例如前方背景车辆、后方背景车辆，背景车辆按照预先定义好的驾驶行为(初始位置以及初始速度)在道路上行驶，以进行后续验证测试车辆在交通流中行驶的决策算法。在背景车辆在道路上行驶的过程中，通过测试车辆的自动驾驶系统中的感知系统，感知车内外环境信息，包括环境中障碍物的位置、速度、朝向以及物体分类(如车辆，行人，自行车)，以及测试车辆自身的状态(包括速度、加速度和方向)、测试车辆的实时位置的高精度地图。
在获得车内外环境信息，决策系统根据测试车辆的决策算法确定测试车辆的行车路径以及行车速度，其中，测试车辆在行驶的过程中通过自身的决策算法，依据模拟的交通环境、客观的物理规律以及积累的历史数据知识，对感知到的障碍物(包括背景车辆)做出预测以便做出宏观地决策， 预测背景车辆在将来一段时间内运动的方向以及在运动中的速度变化，还可以通过决策算法进行道路选择、车道选择、道路上是否正常跟随障碍物(例如人、车等)、是否绕过障碍物(例如人、车等)、是否停车、遇到交通灯和行人时是否等待避让、以及在路口和其他车辆的交互通过等，还可以根据环境感知信息，规划出理想的路径，包括选择路径途经的路径点，以及到达每个路径点时车辆的速度、朝向和加速度等，从而保证测试车辆能够安全行驶。
在决策系统确定出测试车辆的行车路径和速度后，将行车路径和速度发送至控制系统，控制系统接收到行车路径和速度后，结合车身属性和外界物理因素进行动力学计算，转换成对测试车辆电子化控制的油门量、刹车量、以及方向盘转向量等车辆控制参数并执行，从而控制车辆去实现行车路径。
通过上述自动驾驶系统验证测试车辆在交通流中行驶的决策算法的过程中，记录测试车辆的行车数据，并通过自动驾驶评价系统对该测试车辆的行车数据进行评价，获得测试车辆的评价数据(测试报告)，其中行车数据包括测试车辆从起点出发之后所有的细微表现，例如是否闯红灯、压实线、是否发生碰撞、是否达到终点、油门状态、刹车状态、转向状态等，根据测试车辆的行车数据，评价决策算法的驾驶安全性(车辆在道路上的行驶决策和行为)，例如根据行车数据中的致命错误、内存泄漏、数据延迟、发生交通事故等数据，确定该决策算法的驾驶安全性低；根据测试车辆的行车数据，评价决策算法的驾驶舒适性(车辆在道路上行驶期间驾驶员或乘员的驾乘体验)，例如根据行车数据中的油门、刹车、转向状态，评估测试车辆驾驶是否平稳、转弯是否平顺，从而确定驾驶舒适性；根据测试车辆的行车数据，评价决策算法的交通协调性(车辆在道路上行驶时相对其他背景车辆的交通移动表现)以及标准匹配性(按不同国家的法律法规，对自动驾驶行为作出评价)。将测试报告作为开发者不断改进决策算法的参 考，从而使决策算法被部署到自动驾驶车辆时，具有良好的性能。
在实施本申请实施例的过程中发现，在自动驾驶汽车的开发过程中，需要采用自动驾驶仿真测试系统对研发的决策算法进行测试验证，而测试验证时，如果人工搭建出仿真的交通环境，即在测试车辆的周边人工设置若干辆背景车辆，并设置背景车辆的驾驶行为，在仿真运行过程中，背景车辆按照预先定义好的驾驶行为在道路上行驶，以验证测试车辆在交通流中行驶的决策算法，则用户搭建仿真交通环境时，需要配置大量背景车辆参数，才能完成仿真交通环境中各背景车辆的设置，仿真交通环境的搭建效率低。
为了解决上述问题，电子设备120执行本发明实施例提供的驾驶仿真方法，作为终端设备(电子设备120)运行仿真的应用场景示例，参见图1B，图1B为本申请实施例提供的驾驶仿真方法的应用场景示意图；如图1B所示，该应用场景中包括开发者110和终端设备120-1；终端设备120-1可以运行仿真程序。其中，开发者110可以通过终端设备120-1上显示的第一配置界面121，输入开发者在仿真交通环境中设置背景车辆的基本参数；终端设备120-1用于执行本申请实施例提供的驾驶仿真方法，在仿真交通环境中设置与设置的基本参数匹配的背景车辆，背景车辆按照预先定义好的驾驶行为在道路上行驶，以通过自动驾驶系统验证测试车辆在交通流中行驶的决策算法，通过评价系统获得测试车辆的评价数据，以实现测试车辆的交通环境的仿真。当开发者110需要利用仿真交通环境对测试车辆的决策算法进行测试时，开发者110可以调用终端设备120-1上运行的仿真程序搭建仿真交通环境。搭建仿真交通环境时，终端设备120-1(例如，终端设备120运行的仿真程序)将相应地显示第一配置界面121，该第一配置界面121上承载有若干个用于输入基本参数的配置控件，如图1B所示，该第一配置界面121上可以承载用于输入交通状态指示参数的配置控件和用于输入背景车辆数量指示参数的配置控件。
开发者110通过第一配置界面121上显示的各配置控件，相应地输入用于设置背景车辆的基本参数。终端设备120-1接收到用户输入的基本参数后，即可根据这些基本参数确定车辆基准间距、车辆基准速度以及目标车道的N个(N的取值为正整数)目标背景车辆速度。进而，终端设备120-1根据测试车辆所在位置、车辆基准间距和随机距离偏差，依次确定位于目标车道的第i个背景车辆的初始位置，以及根据车辆基准速度和随机速度偏差，依次确定位于目标车道的第i个背景车辆的初始速度，i的取值范围为1至N。
如此，通过上述方式确定出N个背景车辆各自对应的初始位置和初始速度后，终端设备120-1即可根据各背景车辆各自对应的初始位置和初始速度，背景车辆按照各自对应的初始位置和初始速度在道路上行驶，测试车辆启动用于对测试车辆的决策算法进行测试。
该自动驾驶仿真界面具体可以如图1B中的仿真界面122所示，其中，仿真界面122中矩形框包围的车辆为测试车辆1221，该测试车辆1221上运行有此次仿真过程所要测试的决策算法，仿真界面122中其他未被仿真界面122中矩形框包围的车辆为基于上述方法生成的背景车辆，例如背景车辆1222，这些背景车辆按照预先定义的驾驶行为在目标道路上行驶，背景车辆所产生的某些驾驶行为会对测试车辆的驾驶决策行为产生影响，从而达到验证测试车辆上运行的决策算法的目的。
需要说明的是，为了防止因对背景车辆缺少速度约束，而导致各背景车辆逐渐驶出有效的测试范围，测试车辆周边的背景车辆数量减少，无法有效地对决策算法进行验证。终端设备120-1在进行仿真的过程中，可以固定位于最前方的背景车辆的速度，并根据跟驰模型(在仿真过程中，由测试车辆和各背景车辆组成的车队将一起沿目标道路的方向行驶，行驶规律通常可以遵循跟驰模型)相应地更新其他背景车辆的速度，如此，实现对仿真交通环境中的背景车辆施加速度约束。
应理解，上述图1B所示的应用场景仅为一种示例，在实际应用中，除了可以基于图1B所示的终端设备120-1进行自动驾驶仿真外，还可以基于其他类型的终端设备进行自动驾驶仿真。此外，图1B所示的第一配置界面121以及仿真界面122仅为示例，在实际应用中，第一配置界面以及仿真界面还可以表现为其他形式。在此不对本申请实施例提供的驾驶仿真方法的应用场景做任何限定。
作为服务器120-2(电子设备120)运行仿真程序的应用场景示例，参见图1C，图1C为本申请实施例提供的驾驶仿真方法的应用场景示意图；如图1所示，该应用场景中包括用户110、终端120-1以及服务器120-2；服务器120-2可以运行仿真程序。
其中，用户110可以通过终端120-1上显示的第一配置界面121，输入用于在仿真交通环境中设置背景车辆的基本参数，终端120-1将设置背景车辆的基本参数以及决策算法发送至云端的服务器120-2，服务器120-2根据背景车辆的基本参数，确定车辆基准间距、车辆基准速度以及目标车道的N个(N的取值为正整数)目标背景车辆速度。进而，服务器120-2根据测试车辆所在位置、车辆基准间距和随机距离偏差，确定位于目标车道的背景车辆的初始位置，以及根据车辆基准速度和随机速度偏差，确定位于目标车道的背景车辆的初始速度，背景车辆按照预先定义好的驾驶行为(背景车辆的初始速度以及位置)在道路上行驶，以通过自动驾驶系统验证测试车辆在交通流中行驶的决策算法，通过评价系统获得测试车辆的评价数据。服务器120-2在运行决策算法的过程中，还可以将仿真环境的实时行车数据同步到终端设备，终端设备根据实时行车数据，在仿真界面122显示测试车辆运行决策算法的驾驶过程。
综上，针对因需要开发者手动在仿真交通环境逐一设置背景车辆，而导致的仿真交通环境搭建效率低、操作繁琐等问题，本申请实施例提供了一种驾驶仿真方法，该方法能够有效地简化开发者所需执行的人工操作， 并且提高仿真交通环境的搭建效率。
例如，在本申请实施例提供的驾驶仿真方法中，先接收开发者通过第一配置界面输入的基本参数；然后，根据开发者输入的基本参数，确定车辆基准间距、车辆基准速度和目标车道的目标背景车辆数量；接着，根据测试车辆所在位置、车辆基准间距以及随机距离偏差依次确定目标车道上各背景车辆的初始位置，根据车辆基准速度和随机速度偏差依次确定目标车道上各背景车辆的初始速度；如此，确定出目标车道上各背景车辆各自的初始速度和初始位置后，以此为基础进行自动驾驶仿真。
相比于开发者在仿真交通环境中逐一手动设置各背景车辆，本申请实施例提供的方法仅需开发者通过第一配置界面输入少量的基本参数，即可完成仿真交通环境中各背景车辆的设置，大大简化了开发者所需执行的操作，提高了仿真交通环境的搭建效率。此外，本申请实施例提供的方法在设置各背景车辆的过程中，还会考虑随机速度偏差和随机位置偏差，从而保证了所设置的各背景车辆行驶状态具备多样性和随机性，使得仿真交通环境更加逼真。
应理解，本申请实施例提供的驾驶仿真方法可以应用于具备仿真功能的电子设备，该电子设备具体可以为终端设备，其中，终端设备具体可以为计算机、个人数字助理(Personal Digital Assitant，PDA)、平板电脑、智能手机等；该电子设备具体可以为服务器、服务器集群等，服务器可以提供基于云技术的仿真服务，供决策算法的开发者使用。
下面对本申请提供的驾驶仿真方法进行介绍。
参见图2，图2为本申请实施例提供的一种驾驶仿真方法的流程示意图。为了便于描述，下述实施例以终端设备作为执行主体进行描述，举例来说，是以终端设备中运行的仿真程序为执行主体为例进行描述。如图2所示，该驾驶仿真方法包括以下步骤：
步骤201：显示第一配置界面，并接收通过第一配置界面输入的参数。
当用户需要搭建仿真交通环境，并利用该仿真交通环境对测试车辆的决策算法进行验证时，用户可以调用终端设备上承载的用于仿真交通环境的仿真软件。该仿真软件被调用后，将向用户显示第一配置界面，用户可以相应地根据此次仿真的实际需求，通过该第一配置界面输入用于在仿真交通环境中设置背景车辆的基本参数。
为了便于理解上述第一配置界面以及通过第一配置界面输入的基本参数，下面介绍两种示例性的第一配置界面的表现形式，并相应地介绍通过各第一配置界面所接收到的基本参数。
在一种可能的实现方式中，第一配置界面上可以承载用于配置交通状态指示参数的配置控件和用于配置背景车辆数量指示参数的配置控件；相应地，终端设备可以通过该第一配置界面，接收到用户输入的目标交通状态指示参数和目标背景车辆数量指示参数。
交通状态指示参数为能够指示仿真交通环境中交通状态的参数，例如，仿真交通环境中的通行能力、交通密度、背景车辆行驶速度等；终端设备通过第一配置界面上用于配置交通状态指示参数的配置控件，接收到用户输入的目标交通状态指示参数后，即可根据该目标交通状态指示参数，在仿真交通环境中设置与该目标交通状态指示参数对应的目标交通状态。
在一些实施例中，上述用于配置交通状态指示参数的配置控件可以为用于配置交通密度的配置控件，相应地，终端设备通过该配置控件接收到的交通密度即为目标交通密度。交通密度是用于表征道路上车辆密度的参数，其通常以车/公里作为单位。
在一些实施例中，上述用于配置交通状态指示参数的配置控件可以包括：用于配置交通通行能力的配置控件和用于配置车辆速度的配置控件，相应地，终端设备通过用于配置交通通行能力的配置控件接收到的交通通行能力，即为目标交通通行能力，终端设备通过用于配置车辆速度的配置控件接收到的车辆速度，即为目标车辆速度。交通通行能力是用于表征道 路上车流量的参数，其通常以车/小时作为单位；车辆速度用于表征道路上各背景车辆的基本行驶速度，各背景车辆的初始速度均是在该基本行驶速度的基础上确定的，其通常以公里/小时作为单位。
应理解，交通状态指示参数除了可以为交通密度、交通通行能力和车辆速度以外，还可以为其他能够用于设置仿真交通环境中交通状态的参考数据，在此不对交通状态指示参数做任何限定。
背景车辆数量指示参数为用于确定仿真交通环境中背景车辆数量的基础数据。终端设备通过第一配置界面上用于配置背景车辆数量指示参数的配置控件，接收到用户输入的目标背景车辆数量指示参数后，即可根据该目标背景车辆数量指示参数，确定此次仿真过程所需的背景车辆的数量。
在一些实施例中，上述用于配置背景车辆数量指示参数的配置控件可以为用于配置背景车辆数量参数的配置控件，相应地，终端设备通过该配置控件接收到的背景车辆数量即为目标背景车辆数量。该背景车辆数量能够直接指示仿真交通环境中在目标车道上所需设置的背景车辆的数量。
例如，当所要搭建的仿真交通环境中仅有一条目标车道时，可以直接通过第一配置界面上用于配置背景车辆数量参数的配置控件，配置需要在该目标车道上设置的背景车辆的数量；当所要搭建的仿真交通环境中存在多条目标车道时，可以通过第一配置界面上用于配置背景车辆数量参数的配置控件，配置该仿真交通环境中总共需要设置的背景车辆的数量M以及目标车道的数目S，进而，根据M除以S得到的数值，确定每条目标车道需要设置的背景车辆的数量。
在一些实施例中，上述用于配置背景车辆数量指示参数的配置控件可以为用于配置位置范围指示参数的配置控件，相应地，终端设备通过该配置控件接收到的位置范围指示参数即为目标位置范围指示参数。位置范围指示参数能够指示仿真交通环境中背景车辆的设置范围，将该位置范围与车辆间距结合起来，即可确定仿真交通环境中在目标车道上所需设置的背 景车辆的数量。
应理解，背景车辆数量指示参数除了可以为背景车辆数量参数和位置范围指示参数以外，还可以为其他能够确定仿真交通环境中背景车辆数量的参考数据，在此不对该背景车辆数量指示参数做任何限定。
在另一种可能的实现方式中，第一配置界面上可以承载用于配置车辆基准间距的配置控件、用于配置车辆基准速度的配置控件以及用于配置目标车道的目标背景车辆数量的配置控件；相应地，终端设备可以通过该第一配置界面接收到以下基本参数：车辆基准间距、车辆基准速度以及目标车道的目标背景车辆数量。
其中，车辆基准间距为仿真交通环境中同一条车道上相邻的两辆车之间的距离。车辆基准速度与上文中所提及的车辆速度为同一概念，即用于表征道路上各背景车辆的基本行驶速度，各背景车辆的初始速度均是在该基本行驶速度的基础上确定的。
需要说明的是，通常情况下，终端设备在已知车辆基准间距、车辆基准速度以及目标背景车辆数量的条件下，即可相应地根据目标背景车辆数量，确定仿真交通环境中需要部署的背景车辆的数量，并根据车辆基准间距和车辆基准速度，设置仿真交通环境中各背景车辆各自对应的初始位置和初始速度，如此，确定仿真交通环境中各背景车辆各自对应的初始状态数据，实现各背景车辆的部署。应理解，第一配置界面除了可以用于配置车辆基准间距、车辆基准速度和目标车道的目标背景车辆数量外，还可以用于配置其他能够确定仿真交通环境中各背景车辆的初始部署状态的参数，在此不对第一配置界面所能配置的参数类型做任何限定。
在一些情况下，为了使得所搭建的仿真交通环境更加逼真，通常还可以根据用户的实际需求在仿真交通环境中设置多种不同类型的背景车辆，例如，可以在一个仿真交通环境中同时设置小型客车、大型客车、小型货车、大型货车等作为背景车辆。这种情况下，终端设备可以通过第一配置 界面获取背景车辆的类型，以及各种类型的背景车辆在所有背景车辆中所占的比例。需要说明的是，终端设备通过第一配置界面直接获取的背景车辆数量，或者根据位置范围指示参数和交通密度确定出的背景车辆数量，通常都是对应于标准车型的；例如，假设将小型客车作为标准车型，终端设备通过第一配置界面获取的背景车辆数量为50，则表明在仿真交通环境中的所有背景车辆均为小型客车的情况下，该仿真交通环境中包括50个背景车辆。针对上述需要在仿真交通环境中设置多种不同类型的背景车辆的应用场景，终端设备在确定出背景车辆数量的情况下，还需要结合用户设置的各种类型的背景车车辆各自对应的比例以及各种车型与标准车型之间的折算系数，进一步确定仿真交通环境中各种类型的背景车辆各自对应的数量，使得仿真交通环境更加逼真。
例如，假设标准车型为小型客车，终端设备根据第一配置界面接收到的基本参数，确定仿真交通环境中包括的背景车辆数量为100(即在该仿真交通环境中所包括的背景车辆均为小型客车的情况下，背景车辆的数量为100)，以及该仿真交通环境中包括比例为1:1的小型客车和大型客车。此时，根据小型客车和大型客车的比例，可以确定需要将其中50个背景车辆折算为小型客车，将剩余的50个背景车辆折算为大型客车。由于小型客车本身即为标准车型，因此，可以直接确定需要在该仿真交通环境中设置50个小型客车。根据终端设备中预先存储的折算系数表，确定大型客车相对于小型客车的折算系数为2(即1个大型客车相当于2个小型客车)，则可以将50个背景车辆折算为25个大型客车，即确定需要在该仿真交通环境中设置25个大型客车。
应理解，在实际应用中，除了可以将小型客车作为标准车型外，也可以将其他类型的车辆作为标准车型，在此不对标准车型做任何限定。并且，各种车型之间的折算系数可以根据实际需求设定，在此也不对各种车型之间的折算系数做任何限定。
需要说明的是，在实际应用中，终端设备通过第一配置界面接收的目标交通密度、目标交通通行能力等通常也均是对应于标准车型的。
步骤202：基于参数确定车辆基准间距、车辆基准速度以及目标车道的背景车辆数量。
终端设备通过第一配置界面接收到用户输入的基本参数后，即可根据这些基本参数相应地确定用于在仿真交通环境中设置背景车辆的参数，包括：车辆基准间距、车辆基准速度以及目标车道的N个(N的取值为正整数)目标背景车辆数量。
其中，车辆基准间距为仿真交通环境中目标车道上相邻的两辆车之间的距离(前后的两辆车之间的距离)，该车辆基准间距可以为相邻的两辆车的车头之间的距离，也可以为相邻的两辆车的车尾之间的距离；目标车道上相邻的两辆车之间的初始距离均是以该车辆基准间距为基础确定的。车辆基准速度用于表征各背景车辆的基本行驶速度，各背景车辆的初始速度均是以该车辆基准速度为基础确定的。
当终端设备通过第一配置界面接收到的基本参数包括目标交通状态指示参数和目标背景车辆指示参数时，终端设备可以根据目标交通流宏观基本图以及目标交通状态指示参数，确定车辆基准间距和车辆基准速度；以及根据目标车道的目标背景车辆数量指示参数，确定目标车道的目标背景车辆数量。
需要说明的是，交通流宏观基本图能够描述交通网络中宏观交通通行能力、交通密度和车辆速度之间的关系。搭建不同的仿真交通环境时，用户可以根据实际仿真需求，从仿真系统提供的若干个交通流宏观基本图中选择适用于此次仿真的交通流宏观基本图，作为目标交通流宏观基本图，进而，根据该目标交通流宏观基本图以及用户输入的目标交通状态指示参数，相应地确定用于在仿真交通环境中设置背景车辆所需的参数。
为了便于理解上述目标交通流宏观基本图，下面结合图3对本申请中 一种示例性的目标交通流宏观基本图进行介绍。
参见图3，图3为本申请实施例提供的一种示例性的目标交通流宏观基本图。如图3所示，该目标交通流宏观基本图通常设置在以交通密度作为横轴、以通行能力作为纵轴的坐标系中，该目标交通流宏观基本图可以包括两条直线段，分别为直线段301(第一直线段)和直线段302(第二直线段)，直线段301、直线段302与坐标轴的横轴组成了一个三角形。直线段301和直线段302上的每个点均代表一种交通状态，该交通状态能够指示通行能力、交通密度和车辆速度之间的关系。将直线段301与直线段302的相交点的纵坐标作为最大通行能力，将直线段301与直线段302的相交点的横坐标作为临界交通密度，并将直线段302与横轴的相交点的横坐标作为阻塞交通密度。
其中，直线段301用于表征车辆的自由行驶状态，直线段301的斜率是自由流车速，在交通密度从0增加至临界密度的过程中，仿真交通环境中的车辆可以保持自由流车速不变，在此过程中，仿真交通环境的通行能力会逐渐增大。在交通密度达到临界密度时，仿真交通环境的通行能力达到最大通行能力。
其中，直线段302用于表征车辆的拥堵行驶状态；如直线段302所示，仿真交通环境的交通密度达到临界密度、通行能力达到最大通行能力后，仿真交通环境中车辆的持续增多将导致交通密度逐渐增大，车速逐渐减慢，进入拥堵行驶状态，相应地，通行能力也随之下降。当交通密度达到阻塞密度时，车流进入完全拥堵的停止状态，车速和通行能力都降为0。
需要说明的是，图3所示的交通流宏观基本图仅为一种示例，在实际应用中，用户搭建仿真交通环境时，还可以选择其他形状的交通流宏观基本图作为目标交通流宏观基本图；或者，用户还可以选择根据其他能够表征交通状态的交通流参数绘制得到的交通流宏观基本图，作为目标交通流宏观基本图。在此不对本申请实施例中用于设置背景车辆的目标交通流宏 观基本图做任何限定。
需要说明的是，在一些情况下，仿真系统提供的交通流宏观基本图可能无法满足用户的仿真需求；为了保证用户可以构建出满足其仿真需求的仿真交通环境，本申请实施例提供的驾驶仿真方法还可以支持用户自定义目标交通流宏观基本图。
例如，终端设备可以向用户显示第二配置界面，接收用户通过该第二配置界面输入的交通流定量参数，该交通流定量参数包括自由流车速、阻塞密度、临界密度以及最大通行能力；进而，终端设备根据用户输入的交通流定量参数生成目标交通流宏观基本图。
基于上述对于图3所示的交通流宏观基本图的介绍可知，终端设备绘制交通流宏观基本图时，通常需要获知自由流车速、阻塞密度、临界密度以及最大通行能力等交通流定量参数；进而，终端设备可以根据自由流车速、临界密度以及最大通行能力，确定用于表征车辆的自由行驶状态的直线段，以及根据临界密度、最大通行能力以及阻塞密度，确定用于表征车辆的拥堵行驶状态的直线段，如此，确定出符合用户实际仿真需求的目标交通流宏观基本图。
应理解，在用户搭建仿真交通环境所需的目标交通流宏观基本图为其他形状，或者需要基于其他交通流定量参数搭建目标交通流宏观基本图时，终端设备可以通过第二配置界面相应地获取其他绘制交通流宏观基本图时所需的交通流定量参数，并采用特定的方式根据所获取的交通流定量参数绘制目标交通流宏观基本图，在此不对第二配置界面获取的交通流定量参数做任何限定，也不对终端设备绘制目标交通流宏观基本图的方式做任何限定。
例如，根据目标交通流宏观基本图确定车辆基准间距以及车辆基准速度时，终端设备可以根据第一配置界面接收到的目标交通状态指示参数的类型，相应地采取特定的处理方式，确定车辆基准间距和车辆基准速度。
在一种可能的实现方式中，若终端设备通过第一配置界面接收到的目标交通状态指示参数为目标交通密度，则终端设备可以将该目标交通密度的倒数作为车辆基准间距，并在目标交通宏观基本图中确定与目标交通密度对应的目标交通状态，确定目标交通状态在目标交通宏观基本图中具有的目标通行能力，并将目标通行能力与目标交通密度的比值作为车辆基准速度。
基于图3所示的交通流宏观基本图可知，在给定交通密度的情况下，根据交通流宏观基本图可以唯一确定仿真交通环境的交通状态，即唯一确定该交通密度对应的交通通行能力以及车辆速度。另外，由于车辆间距与交通密度之间成倒数关系，因此，在给定交通密度的情况下，根据该交通密度也可以确定出车辆间距。其中，在直线段301和直线段302中，将横坐标为目标交通密度的点作为目标交通状态，将目标交通状态的纵坐标，作为目标交通状态在目标交通宏观基本图中具有的目标通行能力。
基于上述原理，当终端设备通过第一配置界面接收到用户输入的目标交通状态指示参数为目标交通密度K时，终端设备可以通过公式(1)计算车辆基准间距D：
D＝1/K                           (1)
需要说明的是，此处的车辆基准间距D可以表征目标车道上相邻的两辆车的车头之间的距离，或者相邻的两辆车的车尾之间的距离；该车辆基准间距D等于标准背景车辆的车身长度与相邻的两个背景车辆之间的实际间隔距离之和，相邻的两个背景车辆之间的实际间隔距离是指位置靠前的背景车辆的车尾与位置靠后的背景车辆的车头之间的距离。根据上述原理计算车辆基准速度时，终端设备可以通过公式(2)和公式(3)计算车辆基准速度V：
V＝V max(K≤K cr)                     (2)
V＝(KQ max/(K cr-K jam)+k jamQ max/(K jam-K cr))/K(K＞K cr)         (3)
如图4A所示，其中，K为用户输入的目标交通密度，V max为目标交通流宏观基本图中的自由流速度，Q max为目标交通流宏观基本图中的最大通行能力，K cr为目标交通流宏观基本图中的临界密度，K jam为目标交通流宏观基本图中的阻塞密度。
在另一种可能的实现方式中，若终端设备通过第一配置界面接收到的目标交通状态指示参数为目标交通通行能力和目标车辆速度，则终端设备可以直接将所接收的目标车辆速度作为车辆基准速度；并且在目标交通宏观基本图中确定与目标通行能力和目标车辆速度对应的目标交通状态，确定目标交通状态在目标交通宏观基本图中具有的目标交通密度，将目标交通密度的倒数作为车辆基准间距。
根据图3所示的交通流宏观基本图可知，在给定交通通行能力和目标车辆速度的情况下，根据交通流宏观基本图可以唯一确定该交通通行能力与目标车辆速度的组合对应的交通密度。另外，由于车辆间距与交通密度之间成倒数关系，因此，在确定出交通密度的情况下，即可根据该交通密度确定车辆间距。其中，在直线段301和直线段302中，确定纵坐标为目标交通通行能力、且与坐标原点连线的斜率为目标车辆速度的点，以作为目标交通状态，将目标交通状态的横坐标作为目标交通状态在目标交通宏观基本图中具有的目标交通密度。
根据上述原理，当终端设备通过第一配置界面接收到用户输入的目标交通通行能力Q和目标车辆速度V时，终端设备可以通过公式(4)和公式(5)计算目标交通密度K：
K＝Q/V max(V＝V max)                     (4)
K＝K jamQ max/(Q max-V(K cr-K jam))(V＜V max)            (5)
如图4A所示，V max为目标交通流宏观基本图中的自由流速度，Q max为目标交通流宏观基本图中的最大通行能力，K cr为目标交通流宏观基本图中的临界密度，K jam为目标交通流宏观基本图中的阻塞密度。
计算得到目标交通密度K后，终端设备可以根据该目标交通密度K，通过上述公式(1)计算车辆基准间距D。
应理解，若目标交通流宏观基本图表现为其他形状，或者是根据其他能够表征交通状态的交通流参数绘制得到的，终端设备可以相应地通过第一配置界面获取其他基本参数，并采用其他特定的计算方式根据所获取的基本参数，确定车辆基准速度和车辆基准间距。
例如，根据目标车道的目标背景车辆数量指示参数确定目标车道的目标背景车辆数量时，终端设备可以根据自身通过第一配置界面接收到的目标背景车辆数量指示参数的类型，相应地采取特定的确定方式，确定目标车道的目标背景车辆数量。
在一种可能的实现方式中，若终端设备通过第一配置界面接收到的目标背景车辆数量指示参数为目标背景车辆数量参数，该目标背景车辆数量参数用于指示目标车道上目标车辆数量，则终端设备可以直接将该目标背景车辆数量参数所指示的目标车辆数量，作为仿真交通环境中目标车道上目标背景车辆的数量。
在另一种可能的实现方式中，若终端设备通过第一配置界面接收到的目标背景车辆数量指示参数为位置范围指示参数，则终端设备可以根据目标背景车辆的位置范围指示参数和车辆基准间距，确定目标车道的目标背景车辆数量。其中，位置范围指示参数用于指示生成背景车辆的位置范围，该位置范围通常为可以对测试车辆的决策算法产生验证作用的范围；在设定时，可以根据测试车辆的停车视距设定位置范围参数，例如，可以将测试车辆所处的位置作为中心，将该测试车辆的停车视距的二倍作为上述位置范围的长度，即以测试车辆的停车视距作为半径，如此，在目标车道上确定出用于生成背景车辆的位置范围。
在确定出车辆基准间距的条件下，终端设备可以根据位置范围指示参数所指示的位置范围以及该车辆基准间距，确定目标车道的目标背景车辆 的数量。
例如，用户通过第一配置界面输入的目标背景车辆的位置范围指示参数可以包括：第一距离参数R1和第二距离参数R2，其中，R1用于指示测试车辆与测试车辆的前进方向的背景车辆之间的最大距离，R2用于指示测试车辆与测试车辆的后退方向的背景车辆之间的最大距离。相应地，根据该位置范围参数确定目标车道的目标背景车辆数量时，可以确定R1与车辆基准间距的比值，并将该R1与车辆基准间距的比值作为目标车道上位于测试车辆前方的背景车辆数量M1；确定R2与车辆基准间距的比值，并将该R2与车辆基准间距的比值作为目标车道上位于测试车辆后方的目标车辆数量M2。
需要说明的是，上述位置范围的确定通常是根据Frenet坐标系实现的，即将目标车道的中心线作为坐标系的纵坐标轴，将与该中心线垂直的线作为坐标系的横坐标轴。
应理解，上述第一距离参数R1和第二距离参数R2可以相等，也可以不等，在实际应用中，通常可以将上述第一距离参数R1和第二距离参数R2均设置为测试车辆的停车视距；用户也可以根据实际仿真需求设置任意数值作为第一距离参数R1和/或第二距离参数R2，在此不对第一距离参数R1和第二距离参数R2做任何限定。
应理解，终端设备还可以通过第一配置界面获取其他形式的目标背景车辆数量指示参数，相应地，根据该种形式的目标背景车辆数量指示参数，终端设备可以采用对应的方式确定目标车道的目标背景车辆数量；在此不对目标背景车辆数量指示参数的形式做任何限定，也不对终端设备确定目标车道的目标背景车辆数量做任何限定。
当终端设备通过第一配置界面接收到的基本参数包括车辆基准间距、车辆基准速度以及目标车道的目标背景车辆数量时，终端设备将上述车辆基准间距、车辆基准速度以及目标车道的目标背景车辆数量，作为用于在 仿真交通环境中设置背景车辆的相关参数，无需对其做额外的计算处理。
步骤203：基于测试车辆所在位置、车辆基准间距以及随机距离偏差，确定属于目标车道的每个背景车辆的初始位置；基于车辆基准速度以及随机速度偏差，确定属于目标车道的每个背景车辆的初始速度。
终端设备确定出车辆基准间距、车辆基准速度以及目标车道的目标背景车辆数量后，即可根据测试车辆所在位置、车辆基准间距以及随机距离偏差逐一确定目标车道的第i个背景车辆的初始位置，以及根据车辆基准速度和随机速度偏差逐一确定目标车道的第i个背景车辆的初始速度。
应理解，在实际应用中，终端设备可以根据用户在相关配置界面输入的参数，确定测试车辆在仿真交通环境中所在的位置，例如，用户可以通过相关配置界面设置测试车辆位于仿真交通环境中的第二车道，相应地，终端设备搭建仿真交通环境时，将该测试车辆设置在第二车道。当然，终端设备也可以根据用户的实际仿真需求，自动在仿真交通环境中设置测试车辆所在位置，在此不对测试车辆所在位置的设置方式做任何限定。
应理解，随机距离偏差和随机速度偏差均是针对每个背景车辆随机确定的，如此保障不同的背景车辆所对应随机距离偏差和随机速度偏差尽可能的不同，从而保证仿真过程中背景车辆的多样性。具体的针对背景车辆确定随机距离偏差和随机速度偏差时，可以根据正态分布确定，也可以根据卡方分布确定，在此不对确定随机距离偏差和随机速度偏差的方式做任何限定。下面先介绍目标车道上各背景车辆的初始位置的确定方法。终端设备确定目标车道上位于测试车辆前方的背景车辆的初始位置时，可以先在车辆基准间距的基础上叠加随机距离偏差得到第一前间距，与测试车辆的车头相距该第一前间距的位置即可作为第一个位于测试车辆前方的背景车辆的初始位置，即终端设备可以在与测试车辆的车头相距第一前间距的位置处，设置第一个位于测试车辆前方的背景车辆；然后，在车辆基准间距的基础上叠加随机距离偏差得到第二前间距，在与第一个位于测试车辆 前方的背景车辆的初始位置相距该第二前间距的位置，即可作为第二个位于测试车辆前方的背景车辆的初始位置；以此类推，逐一设置各位于测试车辆前方的背景车辆的初始位置，直至位于测试车辆前方的背景车辆的数量达到预设的测试车辆前方的背景车辆数量为止。
相类似地，终端设备确定目标车道上位于测试车辆后方的背景车辆的初始位置时，可以先在车辆基准间距的基础上叠加随机距离偏差得到第一后间距，与测试车辆的车尾相距该第一后间距的位置即可作为第一个位于测试车辆后方的背景车辆的初始位置，即终端设备可以在与测试车辆的车头相距第一后间距的位置处，设置第一个位于测试车辆后方的背景车辆；然后，在车辆基准间距的基础上叠加随机距离偏差得到第二后间距，在与第一个位于测试车辆后方的背景车辆的初始位置相距该第二后间距的位置，即可作为第二个位于测试车辆后方的背景车辆的初始位置；以此类推，逐一设置各位于测试车辆后方的背景车辆的初始位置，直至位于测试车辆后方的背景车辆的数量达到预设的测试车辆后方的背景车辆数量为止。
应理解，上述随机距离偏差可以为正值，也可以为负值；由于在确定各背景车辆各自对应的初始位置时，均会在车辆基准间距的基础上叠加不同的随机距离偏差，并根据叠加偏差后的车辆间距确定各背景车辆的初始位置，因此，能够保证各背景车辆的初始位置随机多样，更接近真实交通场景。
下面介绍目标车道上各背景车辆的初始速度的确定方法。具体为某个背景车辆设置初始速度时，可以在车辆基准速度的基础上叠加随机速度偏差，进而将叠加随机速度偏差后得到的车辆速度，设置为该背景车辆的初始速度；如此确定出仿真交通环境中各背景车辆的初始速度。
由于在确定各背景车辆各自对应的初始速度时，均会在车辆基准速度的基础上叠加不同的随机速度偏差，因此，能够保证各背景车辆的初始速度随机多样，更符合真实交通场景中各车辆的行驶状态。
例如，确定目标车道上第i个背景车辆的初始位置时，所采用的随机距离偏差可以为符合第一正态分布的正态随机变量，确定目标车道上第i个背景车辆的初始速度时，所采用的随机速度偏差可以为符合第二正态分布的正态随机变量。即，可以根据符合正态分布的随机距离偏差确定各背景车辆的初始位置，以及可以根据符合正态分布的随机速度偏差确定各背景车辆的初始速度。
应理解，在实际应用中，也可以通过其他方式确定上述随机距离偏差和随机速度偏差，在此不对随机距离偏差的确定方法和随机速度偏差的确定方法做任何限定。
需要说明的是，在仿真交通环境中包括S条(S的取值为大于1的正整数)目标车道时，终端设备需要确定S条目标车道上各目标背景车辆的数量；针对第j条(j的取值为不超过S的正整数)目标车道，终端设备可以根据测试车辆所在位置、车辆基准间距以及随机距离偏差，依次确定位于第j条目标车道的第i个背景车辆的初始位置，并根据车辆基准速度和随机速度偏差，依次确定位于第j条目标车道的第i个背景车辆的初始速度。例如，终端设备针对测试车辆所在的目标车道上的各背景车辆设置初始位置和初始速度时，可以直接根据上述方式，确定各背景车辆各自对应的初始位置和初始速度；终端设备针对其他目标车道上的各背景车辆设置初始位置和初始速度时，可以先将测试车辆所处的位置沿与目标车道垂直的方向平移至该目标车道，将平移后的位置作为基准位置，进而，根据该基准位置，采用上述方式确定该目标车道上的各背景车辆各自对应的初始位置和初始速度。
步骤204：基于每个背景车辆的初始位置和初始速度以及背景车辆数量，在仿真的交通环境中模拟行驶每个背景车辆。
终端设备确定出N个背景车辆各自对应的初始位置和初始速度后，即可在仿真交通环境中启动自动驾驶仿真；在仿真过程中，由测试车辆和各 背景车辆组成的车队将一起沿目标道路的方向行驶，行驶规律通常可以遵循跟驰模型。
需要说明的是，在仿真过程中，终端设备需要固定所有背景车辆中最前方的背景车辆的速度，并根据跟驰模型更新其他背景车辆的速度。跟驰模型是根据车辆跟驰(Car Following，CF)这种微观驾驶行为构建的，其用于描述在限制超车的单行道上行驶车队中相邻两车之间的相互作用；跟驰模型是运用动力学的方法来研究前导车(Leading Vehicle，LV)运动状态变化所引起的跟驰车的相应行为，通过分析各车辆逐一跟驰的方式来理解单车道交通流特性。其中，背景车辆的类型包括领航背景车辆(所有背景车辆中最前方的车辆)和跟驰背景车辆(除领航背景车辆以外的背景车辆)；固定领航背景车辆的速度，并更新跟驰背景车辆的速度，以使跟驰背景车辆能够跟随领航车辆行驶。
初始设置仿真场景时，如果需要测试的场景对周边交通状态的要求为非自由驾驶状态，则需要设置背景车辆的初始速度小于自由流车速。在跟驰模型中，由于行驶在最前方的背景车辆没有前车需要跟随，因此，在没有其他速度约束的条件下，该位于最前方的背景车辆将逐渐加速至自由流速度，并驶出预设的位置范围(即为对于测试车辆有效的测试范围)；相应地，随着仿真时间的延长，跟随该背景车辆的其他背景车辆也将逐渐进入自由行驶状态，驶出预设的位置范围，测试车辆周边的背景车辆逐渐减少，无法对测试车辆的决策算法进行有效地验证。此外，在仿真时间足够长的情况下，随着测试车辆前方的背景车辆逐渐加速至自由流速度，并驶出预设的位置范围，测试车辆的交通状态将被动地变为自由行驶状态，偏离周边交通状态为非自由驾驶状态的初始设置。
为了防止上述情况的发生，终端设备在仿真进行的过程中，根据跟驰模型更新背景车辆的速度和位置时，会对位于最前方的背景车辆的速度进行固定，控制该背景车辆不按照跟驰模型加速至自由流车速，使其始终位 于预设的位置范围内。
上述驾驶仿真方法仅需测试人员通过第一配置界面输入少量的基本参数，即可完成仿真交通环境中各背景车辆的设置，大大简化了测试人员所需执行的操作，提高了仿真交通环境的搭建效率。此外，该方法在设置各背景车辆的过程中，还会考虑随机速度偏差和随机位置偏差，保证了所设置的各背景车辆行驶状态具备多样性和随机性，使得仿真交通环境更加逼真。并且，在仿真的过程中，会对位于最前方的背景车辆的速度进行固定，以此为基础实现对于跟驰模型中其他背景车辆的速度约束，由此防止因对仿真交通环境中的背景车辆缺少速度约束，而导致各背景车辆逐渐驶出对于测试车辆有效的测试范围，测试车辆周边的车辆数量逐渐变少，无法有效地对测试车辆的决策算法进行测试。
为了便于理解上述图2所示的驾驶仿真方法，下面结合具体示例，对上述驾驶仿真方法进行示例性说明。
当用户需要搭建仿真交通环境时，用户可以先通过终端设备显示的第二配置界面，配置自由流车速、阻塞密度、临界密度以及最大通行能力。例如，假设用户设置自由流车速为80公里/小时，阻塞密度为140车/公里，临界密度为25车/公里，最大通行能力为2000车/小时。终端设备接收到用户通过第二配置界面输入的参数后，将相应地根据这些参数构建适用于本次仿真的目标交通流宏观基本图，如图4B所示。
进而，终端设备将向用户显示用于配置基本参数的第一配置界面，用户可以通过该第一配置界面输入目标交通密度和位置范围指示参数，该位置范围指示参数可以包括第一距离参数和第二距离参数。例如，假设用户输入的目标交通密度为48车/公里，第一距离参数和第二距离参数均为100米。终端设备计算目标交通密度48车/公里的倒数作为车辆基准间距，即通过计算1000(将公里折算为米)除以48，确定车辆基准间距为20.83米，即相邻的两个背景车辆之间的距离为20.83米。进而，可以根据第一距离参 数和该车辆基准间距，确定需要在测试车辆之前设置的背景车辆的数量，例如，终端设备通过计算100除以20.83，确定需要在测试车辆之前设置5个背景车辆，相类似地，终端设备确定需要在测试车辆之后也设置5个背景车辆。
此外，终端设备还需要根据图4B所示的目标交通流宏观基本图和用户输入的目标交通密度，确定此次仿真的目标通行能力，如图4C所示，在目标交通流宏观基本图中，目标交通密度48车/公里对应的目标通行能力为1600车/小时；进而，计算该目标通行能力1600车/小时与目标交通密度48车/公里的比值，作为此次仿真的车辆基准速度，即利用1600除以48得到车辆基准速度为33.33公里/小时。
如此，确定出此次仿真需要在测试车辆的前后分别设置5个背景车辆，并且车辆基准间距为20.83米，车辆基准速度为33.33公里/小时。相应地，终端设备在仿真交通环境中设置背景车辆时，可以在车辆基准间距的基础上叠加随机距离偏差，确定每个背景车辆的初始位置，在车辆基准速度的基础上叠加随机速度偏差，确定每个背景车辆的初始速度，进而实现自动驾驶仿真，搭建的仿真交通环境如图4D所示。
为了便于理解本申请实施例提供的驾驶仿真方法，下面结合图5和图6A-6B，分别对终端设备在仿真交通环境中设置背景车辆的方法以及终端设备进行驾驶仿真的方法，做整体性介绍。
参见图5，图5为本申请实施例提供的在仿真交通环境中设置背景车辆的方法的流程示意图。如图5所示，该方法包括以下步骤：
步骤501：终端设备通过第一配置界面，接收用户输入的目标交通密度和位置范围指示参数，从而实现仿真初始化设置。
步骤502：终端设备确定目标交通密度的倒数作为车辆基准间距，并根据该车辆基准间距和用户输入的位置范围指示参数，确定每条目标车道上需要产生的背景车辆的数量；例如，需要确定每条目标车道上位于测试车 辆前方的车辆数量，以及位于测试车辆后方的车辆数量。
终端设备根据用户选择或自定义的目标交通宏观基本图，确定用户输入的目标交通密度所对应的目标通行能力，进而计算该目标通行能力与目标交通密度的比值作为背景车辆的车辆基准速度。
步骤503：将当前需要设置背景车辆的目标车道作为当前车道，将测试车辆所在的位置作为当前位置；应理解，若当前车道上不存在测试车辆，则将测试车辆沿与车道垂直的方向平移至该当前车道，进而，将平移后的测试车辆在当前车道上所在的位置作为当前位置。
步骤504：判断测试车辆前方的车辆数量是否满足第一预设车辆数量；该第一预设车辆数量即为步骤502中确定出的目标车道上位于测试车辆前方的车辆数量。若满足，则跳转至步骤508，若不满足，则执行步骤505。
步骤505：以当前位置为基准向前移动车辆基准间距对应的距离，并叠加一个随机距离偏差，将如此确定的位置作为新的当前位置。
步骤506：在步骤505确定出的当前位置处设置一辆背景车辆，并在步骤502确定出的车辆基准速度的基础上叠加一个随机速度偏差，将如此确定出的速度作为所设置的背景车辆的初始速度。
步骤507：将位于测试车辆前方的背景车辆数加1，得到更新后的测试车辆前方的车辆数量，返回执行步骤504。
步骤508：判断测试车辆后方的车辆数量是否满足第二预设车辆数量；该第二预设车辆数量即为步骤502中确定出的目标车道上位于测试车辆后方的车辆数量。若满足，则跳转至步骤512，若不满足，则执行步骤509。
步骤509：以步骤503中确定的当前位置为基准，向后移动车辆基准间距对应的距离，并叠加一个随机距离偏差，将如此确定的位置作为新的当前位置。
步骤510：在步骤509确定出的当前位置处设置一辆背景车辆，并在步骤502确定出的车辆基准速度的基础上叠加一个随机速度偏差，将如此确 定出的速度作为所设置的背景车辆的初始速度。
步骤511：将位于测试车辆后方的背景车辆数加1，得到更新后的测试车辆后方的车辆数量，返回执行步骤508。
步骤512：判断是否已遍历所有目标车道；即判断是否已完成对于所有目标车道上背景车辆的设置；若是，则执行步骤514，若否，则执行步骤513。
步骤513：选择下一条未设置背景车辆的目标车道作为当前车道，返回执行步骤503。
步骤514：确认完成在该仿真交通环境中所有背景车辆的设置。
参见图6A，图6A为本申请实施例提供的驾驶仿真过程的流程示意图。如图6A所示，该驾驶仿真过程包括以下步骤：
步骤601：终端设备在仿真交通环境中设置完各背景车辆后，即可控制仿真开始运行，开始遍历该仿真交通环境中各背景车辆。
步骤602：判断当前车辆是否为位于最前方的背景车辆；若是，则执行步骤603，若否，则执行步骤604。
步骤603：固定该背景车辆的车速。
步骤604：按照跟驰模型更新该背景车辆的车速。
步骤605：判断是否已遍历完该仿真交通环境中的各背景车辆；若是，则执行步骤607，若否，则执行步骤606。
步骤606：选取该仿真交通环境中的下一辆背景车辆作为当前车辆，返回执行步骤602。
步骤607：控制该仿真交通环境中的各车辆进行换道判断，并更新该仿真交通环境中各车辆的横向速度。
步骤608：更新该仿真交通环境中各车辆的位置。
步骤609：判断此次仿真的总仿真时间是否已达到预设仿真时间；若达 到，则执行步骤611，若未达到，则执行步骤610。
步骤610：控制仿真时钟等距推进，准备重新遍历该仿真交通环境中各背景车辆。
步骤611：确定此次仿真运行结束。
参见图6B，图6B为本申请实施例提供的驾驶仿真过程的流程示意图。如图6B所示，该驾驶仿真过程包括以下步骤：
步骤601：终端设备在仿真交通环境中设置完各背景车辆后，即可控制仿真开始运行，开始遍历该仿真交通环境中各背景车辆。
步骤602：判断当前车辆是否为位于最前方的背景车辆；若是，则执行步骤603，若否，则执行步骤604。
步骤603：固定该背景车辆的车速。
步骤604：按照跟驰模型更新该背景车辆的车速。
步骤605：记录测试车辆的行车数据。
步骤606：判断是否已遍历完该仿真交通环境中的各背景车辆；若是，则执行步骤608，若否，则执行步骤607。
步骤607：选取该仿真交通环境中的下一辆背景车辆作为当前车辆，返回执行步骤602。
步骤608：控制该仿真交通环境中的各车辆进行换道判断，并更新该仿真交通环境中各车辆的横向速度。
步骤609：更新该仿真交通环境中各车辆的位置。
步骤610：判断此次仿真的总仿真时间是否已达到预设仿真时间；若达到，则执行步骤612，若未达到，则执行步骤611。
步骤611：控制仿真时钟等距推进，准备重新遍历该仿真交通环境中各背景车辆。
步骤612：根据测试车辆的行车数据，对决策算法进行评价。
步骤613：确定此次仿真运行结束。
针对上文描述的驾驶仿真方法，本申请还提供了对应的驾驶仿真装置，以使上述驾驶仿真方法在实际中得以应用和实现。
参见图7，图7是与上文图2所示的驾驶仿真方法对应的一种驾驶仿真装置700的结构示意图，该驾驶仿真装置700包括：
第一交互模块701，配置为显示第一配置界面，并接收通过所述第一配置界面输入的参数；
参数确定模块702，配置为基于所述参数确定车辆基准间距、车辆基准速度以及目标车道的背景车辆数量；其中，所述目标车道包括测试车辆以及背景车辆所在的车道；
背景车辆生成模块703，配置为基于测试车辆所在位置、所述车辆基准间距以及随机距离偏差，确定属于所述目标车道的每个所述背景车辆的初始位置；基于所述车辆基准速度以及随机速度偏差，确定属于所述目标车道的每个所述背景车辆的初始速度；
仿真控制模块704，配置为基于每个所述背景车辆的初始位置和初始速度以及所述背景车辆数量，在仿真的交通环境中模拟行驶每个所述背景车辆。
在一些实施例中，在图7所示的驾驶仿真装置的基础上，参见图8，图8为本申请实施例提供的另一种驾驶仿真装置800的结构示意图。
在所述第一配置界面中包括：用于配置交通状态指示参数的配置控件、以及用于配置背景车辆数量指示参数的配置控件的情况下，所述第一交互模块701配置为：接收通过所述第一配置界面上的配置控件输入的目标交通状态指示参数和目标背景车辆数量指示参数；
所述参数确定模块702包括：交通状态确定子模块801，配置为基于目标交通流宏观基本图以及所述目标交通状态指示参数，确定车辆基准间距 和车辆基准速度；背景车辆数量确定子模块802，配置为基于所述目标车道的目标背景车辆数量指示参数，确定目标车道的背景车辆数量。
在一些实施例中，在图8所示的驾驶仿真装置的基础上，所述目标交通状态指示参数包括目标交通密度，则所述交通状态确定子模块801配置为：所述目标交通密度的倒数作为车辆基准间距；以及，
在目标交通宏观基本图中确定与所述目标交通密度对应的目标交通状态，确定所述目标交通状态在所述目标交通宏观基本图中具有的目标通行能力，并将所述目标通行能力与所述目标交通密度的比值作为车辆基准速度。
在一些实施例中，在图8所示的驾驶仿真装置的基础上，所述目标交通宏观基本图包括位于坐标系中的第一直线段和第二直线段；所述坐标系的横轴表示交通密度，所述坐标系的纵轴表示通行能力，所述第一直线段和所述第二直线段中的每个点代表一种交通状态，则所述交通状态确定子模块801配置为具体用于：
在目标交通宏观基本图中建立以下所述第一直线段和所述第二直线段的以下约束关系：
将所述第一直线段与所述第二直线段的相交点的纵坐标作为最大通行能力，将所述第一直线段与所述第二直线段的相交点的横坐标作为临界交通密度，并将所述第二直线段与横轴的相交点的横坐标作为阻塞交通密度；
在符合所述约束关系的所述第一直线段和所述第二直线段中，将横坐标为所述目标交通密度的点作为目标交通状态；
将所述目标交通状态的纵坐标，作为所述目标交通状态在所述目标交通宏观基本图中具有的目标通行能力。
在一些实施例中，在图8所示的驾驶仿真装置的基础上，所述目标交通状态指示参数包括目标交通通行能力和目标车辆速度；则所述交通状态确定子模块801配置为：在目标交通宏观基本图中确定与所述目标通行能 力和目标车辆速度对应的目标交通状态，确定所述目标交通状态在所述目标交通宏观基本图中具有的目标交通密度，将所述目标交通密度的倒数作为车辆基准间距；以及，
确定所述目标车辆速度为车辆基准速度。
在一些实施例中，在图8所示的驾驶仿真装置的基础上，所述目标交通宏观基本图包括坐标系以及位于所述坐标系中的第一直线段和第二直线段；所述坐标系的横轴表示交通密度，所述坐标系的纵轴表示通行能力，所述第一直线段和所述第二直线段上的每个点代表一种交通状态；则所述交通状态确定子模块801配置为：
在所述目标交通宏观基本图中建立所述第一直线段和所述第二直线段的以下约束关系：
将所述第一直线段与所述第二直线段的相交点的纵坐标作为最大通行能力，将所述第一直线段与所述第二直线段的相交点的横坐标作为临界交通密度，并将所述第二直线段与横轴的相交点的横坐标作为阻塞交通密度；
在符合所述约束关系的所述第一直线段和所述第二直线段中，确定纵坐标为目标交通通行能力、且与坐标原点连线的斜率为目标车辆速度的点，以作为目标交通状态；
将所述目标交通状态的横坐标作为所述目标交通状态在所述目标交通宏观基本图中具有的目标交通密度。
在一些实施例中，在图8所示的驾驶仿真装置的基础上，参见图9，图9为本申请实施例提供的另一种驾驶仿真装置900的结构示意图。所述装置还包括：第二交互模块901，配置为显示第二配置界面，接收通过第二配置界面输入的交通流定量参数，所述交通流定量参数包括自由流车速、阻塞密度、临界密度以及最大通行能力；基本图生成模块902，配置为根据所述自由流车速、所述临界密度以及所述最大通行能力，生成用于表征车辆的自由行驶状态的第一直线段；
根据所述临界密度、所述最大通行能力以及所述阻塞密度，生成用于表征车辆的拥堵行驶状态的第二直线段；
根据坐标系以及位于所述坐标系中的所述第一直线段和所述第二直线段，构建所述目标交通流宏观基本图。
在一些实施例中，在图8所示的驾驶仿真装置的基础上，所述目标背景车辆数量指示参数包括背景车辆数量参数，用于指示目标车道上的背景车辆数量。
在一些实施例中，在图8所示的驾驶仿真装置的基础上，所述目标背景车辆数量指示参数包括位置范围指示参数；则所述背景车辆数量确定子模块802配置为：根据所述目标背景车辆的位置范围指示参数和所述车辆基准间距，确定目标车道的背景车辆数量。
在一些实施例中，在图8所示的驾驶仿真装置的基础上，所述目标背景车辆的位置范围指示参数包括第一距离参数和第二距离参数，其中，所述第一距离参数用于指示所述测试车辆与所述测试车辆的前进方向的背景车辆之间的最大距离；所述第二距离参数用于指示所述测试车辆与所述测试车辆的后退方向的背景车辆之间的最大距离；
所述背景车辆数量确定子模块802配置为：确定所述第一距离参数与所述车辆基准间距的比值，并将所述比值作为目标车道上位于测试车辆前方的背景车辆数量；以及，确定所述第二距离参数与所述车辆基准间距的比值，并将所述比值作为目标车道上位于测试车辆后方的背景车辆数量。
在一些实施例中，在图7所示的驾驶仿真装置的基础上，所述第一交互模块701配置为：接收通过所述第一配置界面上的配置控件输入的参数，所述参数包括车辆基准间距和车辆基准速度以及目标车道的背景车辆数量。
在一些实施例中，在图7所示的驾驶仿真装置的基础上，所述背景车辆生成模块703配置为：确定S条目标车道各自的目标背景车辆数量，所述S取值为大于1的正整数；针对第j条目标车道，基于测试车辆所在位置、 所述车辆基准间距以及随机距离偏差依次确定位于第j条目标车道的第i个背景车辆的初始位置，并基于所述车辆基准速度和随机速度偏差依次确定位于第j条目标车道的第i个背景车辆的初始速度，所述j取值为不超过S的正整数。
在一些实施例中，在图7所示的驾驶仿真装置的基础上，所述背景车辆的类型包括领航背景车辆和跟驰背景车辆；所述仿真控制模块704配置为：固定所述领航背景车辆的速度，并更新所述跟驰背景车辆的速度，以使所述跟驰背景车辆能够跟随所述领航车辆行驶。
在一些实施例中，图7所示的驾驶仿真装置的基础上，在确定目标车道上第i个背景车辆的初始位置时，所述随机距离偏差为符合第一正态分布的正态随机变量；以及，在确定目标车道上第i个背景车辆的初始速度时，所述随机速度偏差为符合第二正态分布的正态随机变量，所述i的取值范围为1至N，N为背景车辆的总数量。
上述驾驶仿真装置仅需测试人员通过第一配置界面输入少量的基本参数，即可完成仿真交通环境中各背景车辆的设置，大大简化了测试人员所需执行的操作，提高了仿真交通环境的搭建效率。此外，该装置在设置各背景车辆的过程中，还会进一步考虑随机速度偏差和随机位置偏差，保证了所设置的各背景车辆行驶状态具备多样性和随机性，使得仿真交通环境更加逼真。并且，在仿真的过程中，会对位于最前方的背景车辆的速度进行固定，以此为基础实现对于跟驰模型中其他背景车辆的速度约束，由此防止因对仿真交通环境中的背景车辆缺少速度约束，而导致各背景车辆逐渐驶出对于测试车辆有效的测试范围，测试车辆周边的车辆数量逐渐变少，无法有效地对测试车辆的决策算法进行测试。
本申请实施例还提供了一种用于驾驶仿真的设备，该设备可以是终端，下面将从硬件实体化的角度对本申请实施例提供的上述设备进行介绍。
本申请实施例还提供了一种设备，如图10所示，为了便于说明，仅示出了与本申请实施例相关的部分，具体技术细节未揭示的，请参照本申请实施例方法部分。该终端可以为包括手机、平板电脑、个人数字助理(Personal Digital Assistant，PDA)、销售终端(Point of Sales，POS)、车载电脑等任意终端设备，以终端为手机为例：
图10示出的是与本申请实施例提供的终端相关的手机的部分结构的框图。参考图10，手机包括：射频(Radio Frequency，RF)电路1010、存储器1020、输入单元1030、显示单元1040、传感器1050、音频电路1060、无线保真(wireless fidelity，WiFi)模块1070、处理器1080、以及电源1090等部件。本领域技术人员可以理解，图10中示出的手机结构并不构成对手机的限定，可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。
存储器1020可用于存储软件程序以及模块，处理器1080通过运行存储在存储器1020的软件程序以及模块，从而执行手机的各种功能应用以及数据处理。存储器1020可主要包括存储程序区和存储数据区，其中，存储程序区可存储操作系统、至少一个功能所需的应用程序(比如声音播放功能、图像播放功能等)等；存储数据区可存储根据手机的使用所创建的数据(比如音频数据、电话本等)等。此外，存储器1020可以包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件、闪存器件、或其他易失性固态存储器件。
处理器1080是手机的控制中心，利用各种接口和线路连接整个手机的各个部分，通过运行或执行存储在存储器1020内的软件程序和/或模块，以及调用存储在存储器1020内的数据，执行手机的各种功能和处理数据，从而对手机进行整体监控。例如，处理器1080可包括一个或多个处理单元；处理器1080可集成应用处理器和调制解调处理器，其中，应用处理器主要处理操作系统、用户界面和应用程序等，调制解调处理器主要处理无线通 信。可以理解的是，上述调制解调处理器也可以不集成到处理器1080中。
在本申请实施例中，该终端所包括的处理器1080还具有以下功能：
显示第一配置界面，并接收通过所述第一配置界面输入的参数；
根据所述参数确定车辆基准间距、车辆基准速度以及目标车道的背景车辆数量；其中，所述目标车道包括测试车辆以及背景车辆所在的车道；
基于测试车辆所在位置、所述车辆基准间距以及随机距离偏差，确定属于所述目标车道的每个所述背景车辆的初始位置；
基于所述车辆基准速度以及随机速度偏差，确定属于所述目标车道的每个所述背景车辆的初始速度；
基于每个所述背景车辆的初始位置和初始速度以及所述背景车辆数量，在仿真的交通环境中模拟行驶每个所述背景车辆。
在一些实施例中，所述处理器1080还配置为执行本申请实施例提供的驾驶仿真方法的任意一种实现方式的步骤。
本申请实施例还提供一种计算机可读存储介质，用于存储计算机程序，该计算机程序用于执行前述各个实施例所述的一种驾驶仿真方法中的任意一种实施方式。
本申请实施例还提供一种包括指令的计算机程序产品，当其在计算机上运行时，使得计算机执行前述各个实施例所述的一种驾驶仿真方法中的任意一种实施方式。
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统，装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
以上所述，以上实施例仅用以说明本申请的技术方案，而非对其限制；尽管参照前述实施例对本申请进行了详细的说明，本领域的普通技术人员 应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本申请各实施例技术方案的精神和范围。
工业实用性
本申请实施例中设备基于第一配置界面输入的参数，确定车辆基准间距、车辆基准速度以及目标车道的背景车辆数量，并基于测试车辆所在位置、车辆基准间距以及随机距离偏差，确定每个背景车辆的初始位置；基于车辆基准速度以及随机速度偏差，确定每个背景车辆的初始速度，最后基于每个背景车辆的初始位置、初始速度以及背景车辆数量，在仿真的交通环境中模拟行驶每个背景车辆。从而，用户根据该方法搭建仿真交通环境时，仅需通过第一配置界面一次性配置少量的基本参数，即可完成仿真交通环境中各背景车辆的设置，相比相关技术中人工在仿真交通环境中逐一手动设置各背景车辆，本申请实施例提供的方法能够有效地减少仿真交通环境搭建过程中所需的人工操作，提高仿真交通环境的搭建效率。并且，本申请实施例提供的方法根据用户输入的基本参数确定出车辆基准间距、车辆基准速度和目标车道的目标背景车辆数量后，还会分别根据随机距离偏差和随机速度偏差对车辆基准间距和车辆基准速度进行调整，进而设置各背景车辆各自的初始位置和初始速度，保证所设置的各背景车辆行驶状态具有多样性和随机性，满足交通仿真的基本需求。

Claims (16)

  1. 一种驾驶仿真方法，所述方法由电子设备执行，所述电子设备包括有一个或多个处理器以及存储器，以及一个或一个以上的程序，其中，所述一个或一个以上的程序存储于存储器中，所述程序可以包括一个或一个以上的每一个对应于一组指令的单元，所述一个或多个处理器被配置为执行指令；所述方法包括：
    显示第一配置界面，并接收通过所述第一配置界面输入的参数；
    基于所述参数确定车辆基准间距、车辆基准速度以及目标车道的背景车辆数量；其中，所述目标车道包括测试车辆以及背景车辆所在的车道；
    基于所述测试车辆所在位置、所述车辆基准间距以及随机距离偏差，确定属于所述目标车道的每个背景车辆的初始位置；
    基于所述车辆基准速度以及随机速度偏差，确定属于所述目标车道的每个背景车辆的初始速度；
    基于每个所述背景车辆的初始位置和初始速度以及所述背景车辆数量，在仿真的交通环境中模拟行驶每个所述背景车辆。
  2. 根据权利要求1所述的方法，其中，
    所述第一配置界面中包括：用于配置交通状态指示参数的配置控件、以及用于配置背景车辆数量指示参数的配置控件；
    所述接收通过所述第一配置界面输入的参数，包括：
    接收通过所述第一配置界面上的配置控件输入的目标交通状态指示参数和目标背景车辆数量指示参数；
    所述基于所述参数确定车辆基准间距、车辆基准速度以及目标车道的背景车辆数量，包括：
    基于目标交通流宏观基本图以及所述目标交通状态指示参数，确定车辆基准间距和车辆基准速度；以及，
    基于所述目标车道的目标背景车辆数量指示参数，确定目标车道的背景车辆数量。
  3. 根据权利要求2所述的方法，其中，所述目标交通状态指示参数包括目标交通密度；
    所述基于目标交通流宏观基本图以及所述目标交通状态指示参数，确定车辆基准间距和车辆基准速度，包括：
    将所述目标交通密度的倒数作为车辆基准间距；以及，
    在目标交通宏观基本图中确定与所述目标交通密度对应的目标交通状态，确定所述目标交通状态在所述目标交通宏观基本图中具有的目标通行能力，并将所述目标通行能力与所述目标交通密度的比值作为车辆基准速度。
  4. 根据权利要求3所述的方法，其中，
    所述目标交通宏观基本图包括位于坐标系中的第一直线段和第二直线段；所述坐标系的横轴表示交通密度，所述坐标系的纵轴表示通行能力，所述第一直线段和所述第二直线段中的每个点代表一种交通状态；
    所述在目标交通宏观基本图中确定与所述目标交通密度对应的目标交通状态，包括：
    在目标交通宏观基本图中建立以下所述第一直线段和所述第二直线段的以下约束关系：
    将所述第一直线段与所述第二直线段的相交点的纵坐标作为最大通行能力，将所述第一直线段与所述第二直线段的相交点的横坐标作为临界交通密度，并将所述第二直线段与横轴的相交点的横坐标作为阻塞交通密度；
    在符合所述约束关系的所述第一直线段和所述第二直线段中，将横坐标为所述目标交通密度的点作为目标交通状态；
    所述确定所述目标交通状态在所述目标交通宏观基本图中具有的目标通行能力，包括：
    将所述目标交通状态的纵坐标，作为所述目标交通状态在所述目标交通宏观基本图中具有的目标通行能力。
  5. 根据权利要求2所述的方法，其中，所述目标交通状态指示参数包括目标通行能力和目标车辆速度；
    所述基于目标交通流宏观基本图以及所述目标交通状态指示参数，确定车辆基准间距和车辆基准速度，包括：
    在目标交通宏观基本图中确定与所述目标通行能力和目标车辆速度对应的目标交通状态，确定所述目标交通状态在所述目标交通宏观基本图中具有的目标交通密度，将所述目标交通密度的倒数作为车辆基准间距；以及，
    确定所述目标车辆速度为车辆基准速度。
  6. 根据权利要求5所述的方法，其中，
    所述目标交通宏观基本图包括坐标系以及位于所述坐标系中的第一直线段和第二直线段；所述坐标系的横轴表示交通密度，所述坐标系的纵轴表示通行能力，所述第一直线段和所述第二直线段上的每个点代表一种交通状态；
    所述在目标交通宏观基本图中确定与所述目标通行能力和目标车辆速度对应的目标交通状态，包括：
    在所述目标交通宏观基本图中建立所述第一直线段和所述第二直线段的以下约束关系：
    将所述第一直线段与所述第二直线段的相交点的纵坐标作为最大通行能力，将所述第一直线段与所述第二直线段的相交点的横坐标作为临界交通密度，并将所述第二直线段与横轴的相交点的横坐标作为阻塞交通密度；
    在符合所述约束关系的所述第一直线段和所述第二直线段中，确定纵坐标为目标交通通行能力、且与坐标原点连线的斜率为目标车辆速度的点，以作为目标交通状态；
    所述确定所述目标交通状态在所述目标交通宏观基本图中具有的目标交通密度，包括：
    将所述目标交通状态的横坐标作为所述目标交通状态在所述目标交通宏观基本图中具有的目标交通密度。
  7. 根据权利要求3至6任一项所述的方法，其中，所述方法还包括：显示第二配置界面，接收通过第二配置界面输入的交通流定量参数，所述交通流定量参数包括自由流车速、阻塞密度、临界密度以及最大通行能力；
    根据所述自由流车速、所述临界密度以及所述最大通行能力，生成用于表征车辆的自由行驶状态的第一直线段；
    根据所述临界密度、所述最大通行能力以及所述阻塞密度，生成用于表征车辆的拥堵行驶状态的第二直线段；
    根据坐标系以及位于所述坐标系中的所述第一直线段和所述第二直线段，构建所述目标交通流宏观基本图。
  8. 根据权利要求2至6任一项所述的方法，其中，所述目标背景车辆数量指示参数包括背景车辆数量参数，用于指示目标车道上的背景车辆数量。
  9. 根据权利要求2至6任一项所述的方法，其中，所述目标背景车辆数量指示参数包括位置范围指示参数；
    所述基于所述目标车道的目标背景车辆数量指示参数，确定目标车道的背景车辆数量，包括：
    根据所述目标背景车辆的位置范围指示参数和所述车辆基准间距，确定目标车道的背景车辆数量。
  10. 根据权利要求9所述的方法，其中，所述目标背景车辆的位置范围指示参数包括第一距离参数和第二距离参数，其中，所述第一距离参数用于指示所述测试车辆与所述测试车辆的前进方向的背景车辆之间的最大距离；所述第二距离参数用于指示所述测试车辆与所述测试车辆的后退方 向的背景车辆之间的最大距离；
    所述根据所述目标背景车辆的位置范围指示参数和所述车辆基准间距，确定目标车道的目标背景车辆数量，包括：
    确定所述第一距离参数与所述车辆基准间距的比值，并将所述比值作为目标车道上位于测试车辆前方的背景车辆数量；以及，
    确定所述第二距离参数与所述车辆基准间距的比值，并将所述比值作为目标车道上位于测试车辆后方的背景车辆数量。
  11. 根据权利要求1所述的方法，其中，所述第一配置界面中包括：用于配置车辆基准间距的配置控件、用于配置车辆基准速度的配置控件以及用于配置目标车道的背景车辆数量的配置控件；
    所述接收通过所述第一配置界面输入的参数，包括：
    接收通过所述第一配置界面上的配置控件输入的参数，所述参数包括车辆基准间距、车辆基准速度以及目标车道的背景车辆数量。
  12. 根据权利要求1至6以及10至11中任一项所述的方法，其中，
    所述背景车辆的类型包括领航背景车辆和跟驰背景车辆；
    所述在仿真的交通环境中模拟驾驶背景车辆，包括：
    固定所述领航背景车辆的速度，并更新所述跟驰背景车辆的速度，以使所述跟驰背景车辆能够跟随所述领航车辆行驶。
  13. 根据权利要求1至6以及10至11中任一项所述的方法，其中，在确定目标车道上第i个背景车辆的初始位置时，所述随机距离偏差为符合第一正态分布的正态随机变量；以及，在确定目标车道上第i个背景车辆的初始速度时，所述随机速度偏差为符合第二正态分布的正态随机变量，所述i的取值范围为1至N，N为背景车辆的总数量。
  14. 一种驾驶仿真装置，包括：
    第一交互模块，配置为显示第一配置界面，并接收通过所述第一配置界面输入的参数；
    参数确定模块，配置为基于所述基本参数确定车辆基准间距、车辆基准速度以及目标车道的目标背景车辆数量；其中，所述目标车道包括测试车辆以及背景车辆所在的车道；
    背景车辆生成模块，配置为基于所述测试车辆所在位置、所述车辆基准间距以及随机距离偏差，确定属于所述目标车道的每个背景车辆的初始位置；基于所述车辆基准速度以及随机速度偏差，确定属于所述目标车道的每个背景车辆的初始速度；
    仿真控制模块，配置为基于每个所述背景车辆的初始位置和初始速度以及所述背景车辆数量，在仿真的交通环境中模拟行驶每个所述背景车辆。
  15. 一种终端设备，所述终端设备包括处理器以及存储器：
    所述存储器用于存储计算机程序；
    所述处理器用于根据所述计算机程序执行权利要求1至13任一项所述的方法。
  16. 一种计算机可读存储介质，所述计算机可读存储介质中存储计算机程序，所述计算机程序被执行时，实现权利要求1至13任一项所述的方法。
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