Vehicle simulation test method and device, computer equipment, medium and program product

Abstract

The application relates to a vehicle simulation test method and device, computer equipment, a storage medium and a computer program product. A first simulation model of a target vehicle is acquired, a simulation scene library is established, input signals and output signals of an adaptive cruise algorithm are determined in combination with a preset cruise speed, a second simulation model of the target vehicle is established, and simulation test of the target vehicle is performed according to the second simulation model of the target vehicle and the simulation scene library. The problems of high test cost, long test period and low test efficiency of the existing test method can be solved, and efficient and convenient test of the adaptive cruise function of a tractor is realized.

Description

Technical Field

[0001] This application relates to the field of tractor-trailer autonomous driving simulation testing, and in particular to a vehicle simulation testing method, apparatus, computer equipment, storage medium, and computer program product. Background Technology

[0002] As autonomous driving technology continues to mature, adaptive cruise control has been applied to a certain extent in general passenger vehicles. However, the actual road testing of autonomous vehicles requires extensive testing to verify the reliability of the technology.

[0003] For existing adaptive cruise control functions of tractor vehicles, the common method for real-vehicle testing is to improve and update the algorithm based on the data processing results after a round of real-vehicle testing.

[0004] However, this testing method has a long testing time for a single scenario, and the data processing and algorithm update cycle is long, resulting in low testing efficiency and high testing cost per vehicle. Summary of the Invention

[0005] Therefore, it is necessary to provide a vehicle simulation testing method, device, computer equipment, computer-readable storage medium, and computer program product that can efficiently and conveniently test the adaptive cruise function of a tractor, addressing the aforementioned technical problems.

[0006] Firstly, this application provides a vehicle simulation testing method, which includes:

[0007] Obtain the first simulation model of the target vehicle;

[0008] Establish a simulation scenario library;

[0009] The input and output signals of the adaptive cruise algorithm are determined based on the first simulation model of the target vehicle, the simulation scenario library, and the preset cruise speed.

[0010] A second simulation model of the target vehicle is established based on the input and output signals of the adaptive cruise algorithm;

[0011] Simulation tests of the target vehicle are conducted based on the second simulation model of the target vehicle and the simulation scenario library.

[0012] In one embodiment, obtaining the first simulation model of the target vehicle includes:

[0013] Establish a dynamic simulation model of the target vehicle;

[0014] Add a target sensor;

[0015] The preset state and driving process of the target vehicle are determined based on the dynamic simulation model and target sensors;

[0016] The first simulation model of the target vehicle is obtained based on the dynamic simulation model, target sensors, and the preset state and driving process of the target vehicle.

[0017] In one embodiment, the above-mentioned establishment of the simulation scene library includes:

[0018] Obtain road information for the target scene;

[0019] Obtain traffic vehicle information in the target scene;

[0020] Determine the pre-driving route corresponding to the target vehicle and traffic vehicle information based on the road information of the target scene;

[0021] A simulation model of the target scene is obtained based on the pre-driving route corresponding to the road information, target vehicle, and traffic vehicle information of the target scene.

[0022] A simulation scenario library is established based on simulation models of multiple target scenarios.

[0023] In one embodiment, obtaining the road information of the target scene includes:

[0024] Obtain the road type and road signs of the target scene;

[0025] Determine the preset road parameters for the target scene based on the road type;

[0026] Identify fixed objects in the target scene based on road signs;

[0027] The road information of the target scene is determined based on preset road parameters and fixed objects.

[0028] In one embodiment, the determination of the input and output signals of the adaptive cruise algorithm based on the first simulation model of the target vehicle, the simulation scenario library, and the preset cruise speed includes:

[0029] The target vehicle's state signals and simulation scene signals are obtained based on the first simulation model of the target vehicle and the simulation scene library.

[0030] The target vehicle's status signal, the simulation scenario signal, and the preset cruise speed are used as the input signals for the adaptive cruise algorithm.

[0031] The output signal of the adaptive cruise algorithm is obtained based on the input signal of the adaptive cruise algorithm.

[0032] In one embodiment, the above-mentioned simulation test of the target vehicle based on the second simulation model of the target vehicle and the simulation scene library includes:

[0033] The first data of the target vehicle and the second data of the target sensor are obtained based on the second simulation model and the simulation scenario library.

[0034] The first cruising speed of the target vehicle is obtained based on the first data of the target vehicle and the second data of the target sensor.

[0035] If the first cruise speed does not reach the preset cruise speed, return to continue executing the steps of acquiring the first data of the target vehicle and the second data of the target sensor;

[0036] If the first cruise speed reaches the preset cruise speed, the simulation test is considered complete.

[0037] In one embodiment, the method further includes:

[0038] Based on the first data of the target vehicle and the second data of the target sensor, the vehicle speed adjustment time and the vehicle-to-vehicle distance are calculated; the vehicle speed adjustment time and the vehicle-to-vehicle distance are used to evaluate whether the adaptive cruise algorithm has achieved the target effect.

[0039] Secondly, this application also provides a vehicle simulation testing device, which includes:

[0040] The first model acquisition module is used to acquire the first simulation model of the target vehicle.

[0041] The simulation scenario creation module is used to create a simulation scenario library;

[0042] The target signal determination module is used to determine the input and output signals of the adaptive cruise algorithm based on the first simulation model of the target vehicle, the simulation scenario library, and the preset cruise speed.

[0043] The second model building module is used to build a second simulation model of the target vehicle based on the input and output signals of the adaptive cruise algorithm.

[0044] The simulation testing module is used to perform simulation tests on the target vehicle based on the second simulation model of the target vehicle and the simulation scenario library.

[0045] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method steps in any of the embodiments of the first aspect described above.

[0046] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the method steps of any of the embodiments in the first aspect described above.

[0047] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the method steps of any of the embodiments in the first aspect described above.

[0048] The aforementioned vehicle simulation testing method, apparatus, computer equipment, storage medium, and computer program products, by acquiring a first simulation model of the target vehicle, establishing a simulation scenario library, and determining the input and output signals of the adaptive cruise algorithm in conjunction with a preset cruise speed, thereby establishing a second simulation model of the target vehicle, and conducting simulation testing of the target vehicle based on the second simulation model and the simulation scenario library, can solve the problems of high testing cost, long testing cycle, and low testing efficiency of existing testing methods, and achieve efficient and convenient testing of the adaptive cruise function of tractor vehicles. Attached Figure Description

[0049] Figure 1 This is an application environment diagram of a vehicle simulation testing method in one embodiment;

[0050] Figure 2 This is a flowchart illustrating a vehicle simulation testing method in one embodiment;

[0051] Figure 3 for Figure 2 A flowchart illustrating step S201 in the illustrated embodiment;

[0052] Figure 4 for Figure 2 A flowchart illustrating step S202 in the illustrated embodiment;

[0053] Figure 5 for Figure 4 A flowchart illustrating step S401 in the illustrated embodiment;

[0054] Figure 6 for Figure 2 A flowchart illustrating step S203 in the illustrated embodiment;

[0055] Figure 7 for Figure 2 A flowchart illustrating step S205 in the illustrated embodiment;

[0056] Figure 8 This is a flowchart illustrating the vehicle simulation testing method in another embodiment;

[0057] Figure 9 This is a structural block diagram of a vehicle simulation testing device in one embodiment;

[0058] Figure 10 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0060] It is understood that the terms "first," "second," etc., used herein may be used to describe various data, but such data are not limited by these terms. These terms are only used to distinguish one data from another. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. The terminology used herein in the specification of this application is for the purpose of describing particular embodiments only and is not intended to limit the application. It should also be understood that the terms "comprising / including" or "having," etc., specify the presence of the stated features, integrals, steps, operations, or combinations thereof, but do not exclude the possibility of the presence or addition of one or more other features, integrals, steps, operations, or combinations thereof. Meanwhile, the term "and / or" as used in this specification includes any and all combinations of the associated listed items.

[0061] The vehicle simulation testing method provided in this application can be applied to computer equipment. This computer equipment can be any type of device, such as a terminal device, or various personal computers, laptops, tablets, wearable devices, servers, etc. This application does not limit the type of computer equipment. Figure 1 The diagram shows the internal structure of a computer device. Figure 1 The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and databases. The internal memory provides the environment for the operation of the operating system and computer programs in the non-volatile storage media. The database contains relevant data for the structural reliability assessment process. The network interface is used for communication with other external devices via a network connection. When the computer program is executed by the processor, it implements a vehicle simulation testing method.

[0062] In one embodiment, such as Figure 2 As shown, a vehicle simulation testing method is provided, including the following steps:

[0063] S201: Obtain the first simulation model of the target vehicle.

[0064] The first simulation model is a complete simulation model of the target vehicle, including the vehicle's dynamics simulation model and sensor models. The dynamics simulation model includes a body model, trailer model, suspension model, tire model, steering model, and braking model; the sensor model includes sensors with the target vehicle's current lane as the detection range and sensors with all lanes as the detection range.

[0065] S202: Establish a simulation scenario library.

[0066] The simulation scenario library contains multiple simulation scenarios used to simulate test conditions in real-world environments. Each simulation scenario consists of static content and dynamic traffic flow content. The static content includes basic roads, road-related parameters, road signs, and fixed objects in the scenario; the dynamic traffic flow includes the initial speed and position of vehicles, as well as their movement process.

[0067] S203: Determine the input and output signals of the adaptive cruise algorithm based on the first simulation model of the target vehicle, the simulation scenario library, and the preset cruise speed.

[0068] Adaptive cruise control is a function of the automated driving assistance system. When adaptive cruise control is activated, if there is no vehicle ahead, the vehicle will travel at the set cruise speed. If there is a vehicle ahead, the vehicle will adjust its distance and speed according to the set distance and cruise speed. The adaptive cruise control algorithm is used to realize the closed loop of the simulation test model. Its input signals include the real-time status signal of the simulated vehicle, relevant signals of the simulation scenario, and the cruise speed setpoint, etc., and the output signal is the desired acceleration of the simulated vehicle.

[0069] S204: Establish a second simulation model of the target vehicle based on the input and output signals of the adaptive cruise algorithm.

[0070] The second simulation model is a closed-loop model of the target vehicle, which is used to control the behavior of the simulated vehicle. The control signal is converted into a signal that the simulation software can recognize through the interface. When the expected acceleration output by the adaptive cruise algorithm is positive, the simulated vehicle will accelerate.

[0071] S205: Perform simulation tests on the target vehicle based on the second simulation model of the target vehicle and the simulation scenario library.

[0072] The second simulation model of the target vehicle is tested in each simulation scenario within a built simulation scenario library. Real-time changes in the target vehicle's state and sensor data are acquired and recorded. The real-time target vehicle state data includes current vehicle speed, current vehicle acceleration, and speed adjustment time due to scene changes. Real-time sensor data, provided by a built sensor model, includes the target vehicle's distance from the vehicle in front. Based on the acquired current vehicle speed and the set cruise speed in the adaptive cruise control algorithm's input signal, it is determined whether the adaptive cruise control algorithm achieves its intended function.

[0073] In the above-mentioned vehicle simulation testing method, by acquiring the first simulation model of the target vehicle, establishing a simulation scenario library, and determining the input and output signals of the adaptive cruise algorithm in combination with the preset cruise speed, a second simulation model of the target vehicle is established. The simulation test of the target vehicle is carried out based on the second simulation model of the target vehicle and the simulation scenario library. This method can solve the problems of high testing cost, long testing cycle and low testing efficiency of existing testing methods, and realize efficient and convenient testing of the adaptive cruise function of the tractor.

[0074] In one embodiment, such as Figure 3 As shown, obtaining the first simulation model of the target vehicle includes the following steps:

[0075] S301: Establish a dynamic simulation model of the target vehicle.

[0076] The dynamic simulation models include vehicle body models, trailer models, suspension models, tire models, steering models, and braking models, all of which are parametric simulation models.

[0077] S302: Add target sensor.

[0078] The target sensor includes a first sensor and a second sensor. The first sensor's detection range is the current lane, and its output signals include: whether there are other vehicles in the current lane, the acceleration of the nearest vehicle in the current lane, the relative speed and relative distance between other vehicles and the target vehicle, etc. The output signal of the first sensor will be used as part of the input signal for the adaptive cruise control algorithm during the test. The second sensor's detection range is all lanes, and its output signal will be used as a reference to assist in setting traffic vehicle behavior in some scenarios.

[0079] S303: Determine the preset state and driving process of the target vehicle based on the dynamic simulation model and target sensors.

[0080] The preset states of the target vehicle include its initial speed, initial position, and initial gear, such as an initial speed of 40 km / h, an initial position 10m from the starting point of the simulated road, and an initial gear of 4th gear. The cruise speed v is set in the specific parameters of the driving process. t This cruise speed value will be used as one of the input signals for the adaptive cruise algorithm during the test. The cruise speed needs to refer to the speed range that the algorithm can achieve. For example, if the range of cruise speed that the algorithm can achieve is 40km / h to 60km / h, then the range of cruise speed setting is also 40km / h to 60km / h.

[0081] S304: Obtain the first simulation model of the target vehicle based on the dynamic simulation model, target sensors, and the preset state and driving process of the target vehicle.

[0082] Specifically, preset states and driving processes are set for the dynamic simulation model of the target vehicle, and corresponding detection distances and detection angles are set for the target sensors to establish a complete simulation model of the target vehicle, namely the first simulation model.

[0083] In this embodiment, by establishing a dynamic simulation model of the target vehicle and adding target sensors, the preset state and driving process of the target vehicle are determined, and the first simulation model of the target vehicle can be obtained, which can realistically simulate the driving state of the tractor and realize the simulation test of the real vehicle.

[0084] In one embodiment, such as Figure 4 As shown, the above-mentioned establishment of the simulation scene library includes the following steps:

[0085] S401: Obtain road information for the target scene.

[0086] The road information for the target scene includes road types, road-related parameters, road signs, and fixed objects. Basic roads include different types such as main roads, curves, and intersections; road-related parameters include lane length, number of lanes, road type, lateral slope, longitudinal slope, and road material; road signs include lane lines, road signs, and traffic signs; and fixed objects include building models and vegetation.

[0087] S402: Obtain traffic vehicle information in the target scene.

[0088] The traffic vehicle information includes the initial speed and initial position of the traffic vehicle, such as an initial speed of 60 km / h and an initial position of 100 m from the target vehicle. The traffic vehicle information also includes the movement process, within which the lateral and longitudinal behaviors of the traffic vehicle can be set, such as a longitudinal acceleration of 2 m / s, an acceleration time of 5 s, and a lateral movement of 3.5 m to change lanes. The information also includes the end conditions of a process, such as setting the duration of the process or the trigger conditions for the process to end, such as ending the current process in 10 s, or ending the current process when the distance between the preceding vehicle and the current vehicle is 50 m.

[0089] S403: Determine the pre-driving route corresponding to the target vehicle and traffic vehicle information based on the road information of the target scene.

[0090] In this process, routes are added to target vehicles and other vehicles based on road information in the target scenario, serving as pre-driving routes for traffic participants in the simulation.

[0091] S404: Obtain the simulation model of the target scene based on the road information, target vehicle, and traffic vehicle information of the target scene and the corresponding pre-driving route.

[0092] The simulation model of the target scenario includes static content and dynamic traffic flow content. The static content is road information and target vehicles, while the dynamic traffic flow content is the pre-driving route corresponding to the traffic vehicle information.

[0093] S405: Establish a simulation scenario library based on simulation models of multiple target scenarios.

[0094] The simulation scenario library contains multiple target scenarios to simulate different test environments.

[0095] In this embodiment, by acquiring road information and traffic vehicle information of the target scene, the pre-driving route corresponding to the target vehicle and traffic vehicle information can be determined, thereby obtaining a simulation model of the target scene, establishing a simulation scene library, providing a large number of virtual scenes for simulation testing, and since the testing process has no risk factor, it can also construct extreme working condition scenarios that cannot be completed in real vehicle testing, thereby greatly improving the scenario coverage of the test.

[0096] In one embodiment, such as Figure 5 As shown, the above-mentioned method for obtaining road information for a target scene includes the following steps:

[0097] S501: Obtain the road type and road signs of the target scene.

[0098] The road types include different types of roads such as main roads, curves, and intersections; the road signs include lane lines, road signs, and traffic signs.

[0099] S502: Determine the preset road parameters for the target scene based on the road type.

[0100] The preset road parameters include lane length, number of lanes, road type, road lateral slope, road longitudinal slope, and road material.

[0101] S503: Obtain fixed objects in the target scene based on road signs.

[0102] The fixed objects include building models and vegetation.

[0103] S504: Determine the road information of the target scene based on preset road parameters and fixed objects.

[0104] In this embodiment, by acquiring the road type and road signs of the target scene, the preset road parameters of the target scene are determined. Combined with the fixed objects in the target scene, the road information of the target scene can be determined, and a simulation model of the target scene can be established to provide a test environment for the simulation test of the target vehicle.

[0105] In one embodiment, such as Figure 6 As shown, the above-mentioned determination of the input and output signals of the adaptive cruise algorithm based on the first simulation model of the target vehicle, the simulation scenario library, and the preset cruise speed includes the following steps:

[0106] S601: Obtain the target vehicle's state signal and simulation scene signal based on the target vehicle's first simulation model and simulation scene library.

[0107] The target vehicle's status signals include current vehicle speed, longitudinal acceleration, vehicle yaw angle, engine rotation speed, engine torque, and gearbox output shaft rotation speed; the simulation scenario signals include whether traffic in the current lane is valid, the acceleration of the nearest vehicle in the current lane, the speed of the nearest vehicle in the current lane relative to the target vehicle, and the distance of the nearest vehicle in the current lane relative to the target vehicle.

[0108] S602: The target vehicle's status signal, the simulation scene signal, and the preset cruise speed are used as input signals for the adaptive cruise algorithm.

[0109] S603: Obtain the output signal of the adaptive cruise algorithm based on the input signal of the adaptive cruise algorithm.

[0110] The output signal of the adaptive cruise algorithm is the desired acceleration of the target vehicle.

[0111] In this embodiment, the state signal of the target vehicle and the simulation scene signal are obtained through the first simulation model of the target vehicle and the simulation scene library. The state signal of the target vehicle, the simulation scene signal and the preset cruise speed are used as the input signal of the adaptive cruise algorithm to obtain the output signal of the adaptive cruise algorithm, that is, the expected acceleration of the target vehicle. This enables the control of the behavior of the target vehicle and completes the model closed loop of the simulation test.

[0112] In one embodiment, such as Figure 7 As shown, the above simulation test of the target vehicle based on the second simulation model of the target vehicle and the simulation scene library includes the following steps:

[0113] S701: Obtain the first data of the target vehicle and the second data of the target sensor based on the second simulation model and the simulation scenario library.

[0114] The first data for the target vehicle is real-time data on changes in the target vehicle's status, including current vehicle speed, current vehicle acceleration, and speed adjustment time due to changes in the scene; the second data for the target sensor is real-time data on changes in the sensor, including the target vehicle's distance from the vehicle in front.

[0115] S702: Obtain the first cruising speed of the target vehicle based on the first data of the target vehicle and the second data of the target sensor.

[0116] Among them, the current vehicle speed in the real-time change data of the target vehicle's status is used as the first cruising speed.

[0117] S703: If the first cruise speed does not reach the preset cruise speed, return to continue executing the steps of acquiring the first data of the target vehicle and the second data of the target sensor.

[0118] If the first cruise speed does not reach the preset cruise speed, meaning the adaptive cruise algorithm does not achieve the expected function, the test will continue.

[0119] S704: If the first cruise speed reaches the preset cruise speed, the simulation test is considered complete.

[0120] If the first cruise speed does not reach the preset cruise speed, the adaptive cruise algorithm has achieved its expected function, and the test is complete.

[0121] In this embodiment, the first data of the target vehicle and the second data of the target sensor are obtained through the second simulation model and the simulation scenario library, and then the first cruise speed of the target vehicle is obtained. By comparing the first cruise speed with the preset cruise speed, it can be determined whether the adaptive cruise algorithm has achieved the expected function, thus realizing efficient and convenient testing of the adaptive cruise function of the tractor.

[0122] In one embodiment, the vehicle simulation test method further includes: calculating the vehicle speed adjustment time and inter-vehicle time distance of the target vehicle based on the first data of the target vehicle and the second data of the target sensor.

[0123] Among them, the inter-vehicle time distance τ is calculated by the current vehicle speed v0 and the relative distance d between the target vehicle and the vehicle in front. x The calculation formula is: τ=d x / V0. The speed adjustment time and vehicle-to-vehicle distance are used to evaluate whether the adaptive cruise control algorithm has achieved its target effect. When the speed adjustment time and vehicle-to-vehicle distance reach the set values, the adaptive cruise control algorithm is judged to have achieved its target effect. The set values ​​refer to the values ​​that the algorithm under test can achieve at the beginning of its design. For example, an algorithm is designed such that when there is a vehicle decelerating 20 km / h ahead, the vehicle's speed adjustment time can be less than 10 seconds, and the final adjusted vehicle-to-vehicle distance is 3 seconds. When evaluating the algorithm, it is necessary to compare the obtained actual speed adjustment time with 10 seconds and the actual vehicle-to-vehicle distance with 3 seconds.

[0124] In this embodiment, by calculating the target vehicle's speed adjustment time and the time distance between vehicles, it is possible to evaluate whether the adaptive cruise control algorithm has achieved the target effect, improve the testing efficiency of the adaptive cruise control algorithm, and realize efficient and convenient testing of the adaptive cruise control function of the tractor.

[0125] In another embodiment, such as Figure 8 As shown, a vehicle simulation testing method is provided. Taking the application of this method in TruckMaker software and Simulink simulation tool as an example, it includes the following steps:

[0126] (1) Establish a vehicle dynamics simulation model of the tractor: Use TruckMaker software and Simulink tools to establish simulation models of each part of the tractor, including the vehicle dynamics model of the tractor body, trailer model, suspension model, tire model, steering model and braking model.

[0127] (2) Configure sensors for the simulation vehicle and set sensor parameters: Design the first sensor for the simulation vehicle in TruckMaker software, name it Radar_Path, select the current lane as the detection range, and set the sensor detection distance and detection angle; Design the second sensor for the simulation vehicle in TruckMaker software, name it Radar_All, select all lanes as the detection range, and set the sensor detection distance and detection angle; Assemble the sensors Radar_Path and Radar_All on the simulation vehicle and set the mounting position of the sensors on the simulation vehicle.

[0128] (3) Set the preset state and driving process of the simulation vehicle: Set the starting speed, starting position and starting gear of the simulation vehicle through TruckMaker software; add the driving process of the simulation vehicle, and set the cruise speed v in the specific parameters of the driving process. t This serves as one of the inputs to the adaptive cruise algorithm during the testing process.

[0129] (4) Build a test simulation scenario library in TruckMaker software: Build static content for test simulation scenarios in TruckMaker software; design traffic vehicle behavior and build dynamic traffic flow content for simulation scenarios.

[0130] (5) Embedding the adaptive cruise algorithm model: According to the test requirements, write an interface for the algorithm model to realize the closed loop of the simulation test model, including: establishing communication between TruckMaker software and Simulink tool, loading the adaptive cruise algorithm model into Simulink tool; providing input signals for the adaptive algorithm model test: loading the 'write' module interface in the model library provided by TruckMaker software into Simulink tool, designing and writing the TruckMaker software 'write' module interface in Simulink tool to provide some input and output signals for the adaptive cruise algorithm; the input signals provided by TruckMaker software for the algorithm include the real-time status signal of the simulated vehicle, the relevant signals of the simulation scene, and the cruise speed setpoint; the cruise speed setpoint signal is the cruise speed v set in step (3). t Provides: Based on testing needs, a custom Signal build module is designed in the Simulink tool to provide the input signal for the algorithm—the adaptive cruise algorithm spacing gear setting value signal; receives the output signal provided by the adaptive algorithm model: the 'read' module interface from the model library provided by the TruckMaker software is loaded into the Simulink tool, and the TruckMaker software 'read' module interface is designed and written in the Simulink tool; the TruckMaker software receives the output signal provided by the algorithm as the desired acceleration of the simulated vehicle.

[0131] (6) By calculating the vehicle dynamics model in step (1), the behavior of the simulated vehicle is controlled to complete the model closed loop of the simulation test.

[0132] (7) Adaptive cruise algorithm expected function test and verification: Run the simulation closed-loop model in step (6) in the simulation scenario built in step (4), and use TruckMaker software to acquire and record the real-time change data of the simulated vehicle's state and the real-time change data of the sensors. Among them, the real-time data of the simulated vehicle's state includes the current vehicle speed v0, the current vehicle acceleration a0, and the vehicle speed adjustment time t caused by scene changes.s The real-time sensor data is provided by Radar_Path in step (2), including the simulated vehicle's distance d relative to the vehicle in front. x The time interval τ between the vehicle and the simulated vehicle is indirectly calculated using the current vehicle speed and the distance between the simulated vehicle and the vehicle in front. The formula is: τ = dx / v0. Plot the simulation data in the same time coordinate system and record the speed adjustment time t. s Workshop time interval τ min Compare and analyze the values ​​of the two with the set values ​​of the two in the expected function of the adaptive cruise algorithm; record the adjusted cruise speed v0, and compare the speed v0 with the set cruise speed v in step (3). t Comparative analysis was conducted to evaluate whether the algorithm achieved the expected function. After the adaptive cruise algorithm was updated, step (6) was repeated until the adaptive cruise algorithm achieved the expected function standard. The test verification was then completed, and the entire process of the adaptive cruise algorithm model in-loop simulation test of the tractor was completed.

[0133] In this embodiment, the tractor-mounted adaptive cruise control model-in-the-loop testing method based on TruckMaker software, Simulink tools, and simulation scenarios enables efficient simulation testing, bringing forward the discovery of adaptive cruise control algorithm problems and solving the problems of high testing costs, long testing cycles, and low testing efficiency of existing testing methods. Furthermore, regarding the issue of test coverage, this method can provide a large number of virtual scenarios for simulation testing, and because the testing process has no inherent danger, it can also construct extreme operating conditions that cannot be achieved in real-vehicle testing, thereby significantly improving test coverage. Addressing the issue of the inability to reproduce the same traffic scenario, this method can accurately control variables in the scenario, monitor and replay simulation data in real time, effectively analyze test results, and locate algorithm problems.

[0134] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0135] Based on the same inventive concept, this application also provides a vehicle simulation testing device for implementing the vehicle simulation testing method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more vehicle simulation testing device embodiments provided below can be found in the limitations of the vehicle simulation testing method described above, and will not be repeated here.

[0136] In one embodiment, such as Figure 9 As shown, a vehicle simulation testing device is provided, comprising: a first model acquisition module 10, a simulation scene establishment module 20, a target signal determination module 30, a second model establishment module 40, and a simulation testing module 50, wherein:

[0137] The first model acquisition module 10 is used to acquire the first simulation model of the target vehicle;

[0138] Simulation scene creation module 20 is used to create a simulation scene library;

[0139] The target signal determination module 30 is used to determine the input and output signals of the adaptive cruise algorithm based on the first simulation model of the target vehicle, the simulation scenario library, and the preset cruise speed.

[0140] The second model building module 40 is used to build a second simulation model of the target vehicle based on the input and output signals of the adaptive cruise algorithm.

[0141] The simulation test module 50 is used to perform simulation tests on the target vehicle based on the second simulation model of the target vehicle and the simulation scenario library.

[0142] In one embodiment, the first model acquisition module includes: a simulation model building unit, a sensor adding unit, a driving state determination unit, and a first model acquisition unit, wherein:

[0143] The simulation model building unit is used to build a dynamic simulation model of the target vehicle.

[0144] Sensor adding unit, used to add target sensors;

[0145] The driving state determination unit is used to determine the preset state and driving process of the target vehicle based on the dynamic simulation model and target sensors.

[0146] The first model acquisition unit is used to acquire the first simulation model of the target vehicle based on the dynamic simulation model, the target sensor, and the preset state and driving process of the target vehicle.

[0147] In one embodiment, the simulation scenario establishment module includes: a road information acquisition unit, a vehicle information acquisition unit, a driving route determination unit, a simulation model acquisition unit, and a simulation scenario library establishment unit, wherein:

[0148] The road information acquisition unit is used to acquire road information of the target scene;

[0149] The vehicle information acquisition unit is used to acquire traffic vehicle information in the target scene;

[0150] The route determination unit is used to determine the pre-driving route corresponding to the target vehicle and traffic vehicle information based on the road information of the target scene.

[0151] The simulation model acquisition unit is used to acquire the simulation model of the target scene based on the road information, target vehicle, and traffic vehicle information of the target scene and the corresponding pre-driving route.

[0152] The simulation scenario library creation unit is used to create a simulation scenario library based on simulation models of multiple target scenarios.

[0153] In one embodiment, the road information acquisition unit includes: a road sign acquisition subunit, a road parameter determination subunit, a fixed object determination subunit, and a road information determination subunit, wherein:

[0154] The road sign acquisition subunit is used to acquire the road type and road signs of the target scene;

[0155] The road parameter determination subunit is used to determine the preset road parameters of the target scene based on the road type;

[0156] The fixed object determination subunit is used to obtain fixed objects in the target scene based on road signs;

[0157] The road information determination subunit is used to determine the road information of the target scene based on preset road parameters and fixed objects.

[0158] In one embodiment, the target signal determination module includes: a vehicle signal acquisition unit, an input signal determination unit, and an output signal determination unit, wherein:

[0159] The vehicle signal acquisition unit is used to acquire the state signal of the target vehicle and the simulation scene signal based on the first simulation model of the target vehicle and the simulation scene library.

[0160] The input signal determination unit is used to take the target vehicle's state signal, the simulation scene signal, and the preset cruise speed as the input signals for the adaptive cruise algorithm.

[0161] The output signal determination unit is used to obtain the output signal of the adaptive cruise algorithm based on the input signal of the adaptive cruise algorithm.

[0162] In one embodiment, the simulation test module includes: a data acquisition unit, a vehicle speed acquisition unit, and a vehicle speed determination module, wherein:

[0163] The data acquisition unit is used to acquire the first data of the target vehicle and the second data of the target sensor based on the second simulation model and the simulation scenario library.

[0164] The vehicle speed acquisition unit is used to acquire the first cruising speed of the target vehicle based on the first data of the target vehicle and the second data of the target sensor.

[0165] The vehicle speed determination module is used to return to the steps of acquiring the first data of the target vehicle and the second data of the target sensor when the first cruise speed has not reached the preset cruise speed; and to determine that the simulation test is completed when the first cruise speed reaches the preset cruise speed.

[0166] In one embodiment, the simulation test module is further configured to calculate the vehicle speed adjustment time and inter-vehicle distance of the target vehicle based on the first data of the target vehicle and the second data of the target sensor; the vehicle speed adjustment time and inter-vehicle distance are used to evaluate whether the adaptive cruise algorithm achieves the target effect.

[0167] Each module in the aforementioned vehicle simulation testing device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0168] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 10As shown, the computer device includes a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a vehicle simulation testing method. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0169] Those skilled in the art will understand that Figure 10 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0170] In one embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the following steps: acquiring a first simulation model of a target vehicle; establishing a simulation scenario library; determining the input and output signals of an adaptive cruise algorithm based on the first simulation model of the target vehicle, the simulation scenario library, and a preset cruise speed; establishing a second simulation model of the target vehicle based on the input and output signals of the adaptive cruise algorithm; and performing simulation testing of the target vehicle based on the second simulation model of the target vehicle and the simulation scenario library.

[0171] In one embodiment, the acquisition of a first simulation model of a target vehicle by the processor executing a computer program includes the following steps: establishing a dynamic simulation model of the target vehicle; adding target sensors; determining the preset state and driving process of the target vehicle based on the dynamic simulation model and the target sensors; and acquiring the first simulation model of the target vehicle based on the dynamic simulation model, the target sensors, and the preset state and driving process of the target vehicle.

[0172] In one embodiment, the process of establishing a simulation scenario library when the processor executes a computer program includes the following steps: acquiring road information of the target scenario; acquiring traffic vehicle information in the target scenario; determining the pre-driving route corresponding to the target vehicle and traffic vehicle information based on the road information of the target scenario; acquiring a simulation model of the target scenario based on the road information of the target scenario, the target vehicle and traffic vehicle information corresponding to the pre-driving route; and establishing a simulation scenario library based on the simulation models of multiple target scenarios.

[0173] In one embodiment, the acquisition of road information of a target scene by the processor executing a computer program includes the following steps: acquiring the road type and road signs of the target scene; determining preset road parameters of the target scene based on the road type; acquiring fixed objects in the target scene based on the road signs; and determining the road information of the target scene based on the preset road parameters and the fixed objects.

[0174] In one embodiment, the processor executing a computer program involves determining the input and output signals of an adaptive cruise algorithm based on a first simulation model of the target vehicle, a simulation scenario library, and a preset cruise speed. This includes the following steps: obtaining the target vehicle's state signal and simulation scenario signal based on the first simulation model of the target vehicle and the simulation scenario library; using the target vehicle's state signal, simulation scenario signal, and preset cruise speed as the input signals of the adaptive cruise algorithm; and obtaining the adaptive cruise algorithm's output signal based on the input signals of the adaptive cruise algorithm.

[0175] In one embodiment, the simulation test of the target vehicle based on a second simulation model of the target vehicle and a simulation scenario library when the processor executes the computer program includes the following steps: obtaining first data of the target vehicle and second data of the target sensor based on the second simulation model and the simulation scenario library; obtaining a first cruising speed of the target vehicle based on the first data of the target vehicle and the second data of the target sensor; if the first cruising speed does not reach the preset cruising speed, returning to continue executing the step of obtaining the first data of the target vehicle and the second data of the target sensor; if the first cruising speed reaches the preset cruising speed, determining that the simulation test is completed.

[0176] In one embodiment, when the processor executes the computer program, it further performs the following steps: calculating the vehicle speed adjustment time and the inter-vehicle distance based on the first data of the target vehicle and the second data of the target sensor; the vehicle speed adjustment time and the inter-vehicle distance are used to evaluate whether the adaptive cruise algorithm has achieved the target effect.

[0177] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, it performs the following steps: acquiring a first simulation model of a target vehicle; establishing a simulation scenario library; determining the input and output signals of an adaptive cruise algorithm based on the first simulation model of the target vehicle, the simulation scenario library, and a preset cruise speed; establishing a second simulation model of the target vehicle based on the input and output signals of the adaptive cruise algorithm; and performing simulation testing of the target vehicle based on the second simulation model of the target vehicle and the simulation scenario library.

[0178] In one embodiment, the acquisition of a first simulation model of a target vehicle by the execution of a computer program by a processor includes the following steps: establishing a dynamic simulation model of the target vehicle; adding target sensors; determining the preset state and driving process of the target vehicle based on the dynamic simulation model and the target sensors; and acquiring the first simulation model of the target vehicle based on the dynamic simulation model, the target sensors, and the preset state and driving process of the target vehicle.

[0179] In one embodiment, the process of establishing a simulation scenario library when a computer program is executed by a processor includes the following steps: acquiring road information of a target scenario; acquiring traffic vehicle information in the target scenario; determining the pre-driving route corresponding to the target vehicle and traffic vehicle information based on the road information of the target scenario; acquiring a simulation model of the target scenario based on the road information of the target scenario, the target vehicle and the pre-driving route corresponding to the traffic vehicle information; and establishing a simulation scenario library based on the simulation models of multiple target scenarios.

[0180] In one embodiment, the acquisition of road information of a target scene by a computer program executed by a processor includes the following steps: acquiring the road type and road signs of the target scene; determining preset road parameters of the target scene based on the road type; acquiring fixed objects in the target scene based on the road signs; and determining the road information of the target scene based on the preset road parameters and the fixed objects.

[0181] In one embodiment, when a computer program is executed by a processor, the process of determining the input and output signals of an adaptive cruise algorithm based on a first simulation model of the target vehicle, a simulation scenario library, and a preset cruise speed includes the following steps: obtaining the state signal and simulation scenario signal of the target vehicle based on the first simulation model of the target vehicle and the simulation scenario library; using the state signal, simulation scenario signal, and preset cruise speed of the target vehicle as the input signal of the adaptive cruise algorithm; and obtaining the output signal of the adaptive cruise algorithm based on the input signal of the adaptive cruise algorithm.

[0182] In one embodiment, when the computer program is executed by the processor, the simulation test of the target vehicle based on a second simulation model of the target vehicle and a simulation scenario library includes the following steps: obtaining first data of the target vehicle and second data of the target sensor based on the second simulation model and the simulation scenario library; obtaining a first cruising speed of the target vehicle based on the first data of the target vehicle and the second data of the target sensor; if the first cruising speed does not reach a preset cruising speed, returning to continue executing the step of obtaining the first data of the target vehicle and the second data of the target sensor; if the first cruising speed reaches the preset cruising speed, determining that the simulation test is completed.

[0183] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: calculating the vehicle speed adjustment time and the inter-vehicle distance based on the first data of the target vehicle and the second data of the target sensor; the vehicle speed adjustment time and the inter-vehicle distance are used to evaluate whether the adaptive cruise algorithm has achieved the target effect.

[0184] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps: acquiring a first simulation model of a target vehicle; establishing a simulation scenario library; determining the input and output signals of an adaptive cruise control algorithm based on the first simulation model of the target vehicle, the simulation scenario library, and a preset cruise speed; establishing a second simulation model of the target vehicle based on the input and output signals of the adaptive cruise control algorithm; and performing simulation testing of the target vehicle based on the second simulation model of the target vehicle and the simulation scenario library.

[0185] In one embodiment, the acquisition of a first simulation model of a target vehicle by the execution of a computer program by a processor includes the following steps: establishing a dynamic simulation model of the target vehicle; adding target sensors; determining the preset state and driving process of the target vehicle based on the dynamic simulation model and the target sensors; and acquiring the first simulation model of the target vehicle based on the dynamic simulation model, the target sensors, and the preset state and driving process of the target vehicle.

[0186] In one embodiment, the process of establishing a simulation scenario library when a computer program is executed by a processor includes the following steps: acquiring road information of a target scenario; acquiring traffic vehicle information in the target scenario; determining the pre-driving route corresponding to the target vehicle and traffic vehicle information based on the road information of the target scenario; acquiring a simulation model of the target scenario based on the road information of the target scenario, the target vehicle and the pre-driving route corresponding to the traffic vehicle information; and establishing a simulation scenario library based on the simulation models of multiple target scenarios.

[0187] In one embodiment, the acquisition of road information of a target scene by a computer program executed by a processor includes the following steps: acquiring the road type and road signs of the target scene; determining preset road parameters of the target scene based on the road type; acquiring fixed objects in the target scene based on the road signs; and determining the road information of the target scene based on the preset road parameters and the fixed objects.

[0188] In one embodiment, when a computer program is executed by a processor, the process of determining the input and output signals of an adaptive cruise algorithm based on a first simulation model of the target vehicle, a simulation scenario library, and a preset cruise speed includes the following steps: obtaining the state signal and simulation scenario signal of the target vehicle based on the first simulation model of the target vehicle and the simulation scenario library; using the state signal, simulation scenario signal, and preset cruise speed of the target vehicle as the input signal of the adaptive cruise algorithm; and obtaining the output signal of the adaptive cruise algorithm based on the input signal of the adaptive cruise algorithm.

[0189] In one embodiment, when the computer program is executed by the processor, the simulation test of the target vehicle based on a second simulation model of the target vehicle and a simulation scenario library includes the following steps: obtaining first data of the target vehicle and second data of the target sensor based on the second simulation model and the simulation scenario library; obtaining a first cruising speed of the target vehicle based on the first data of the target vehicle and the second data of the target sensor; if the first cruising speed does not reach a preset cruising speed, returning to continue executing the step of obtaining the first data of the target vehicle and the second data of the target sensor; if the first cruising speed reaches the preset cruising speed, determining that the simulation test is completed.

[0190] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: calculating the vehicle speed adjustment time and inter-vehicle distance of the target vehicle based on the first data of the target vehicle and the second data of the target sensor; the vehicle speed adjustment time and inter-vehicle distance are used to evaluate whether the adaptive cruise algorithm achieves the target effect.

[0191] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0192] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0193] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A vehicle simulation testing method, characterized in that, The method includes: Establish a dynamic simulation model of the target vehicle; Add a target sensor; The preset state and driving process of the target vehicle are determined based on the dynamic simulation model and the target sensor. The first simulation model of the target vehicle is obtained based on the dynamic simulation model, the target sensor, and the preset state and driving process of the target vehicle; Establish a simulation scenario library; The input and output signals of the adaptive cruise algorithm are determined based on the first simulation model of the target vehicle, the simulation scenario library, and the preset cruise speed; the input signals include the real-time status signal of the target vehicle, the simulation scenario signal, and the preset cruise speed; the output signal is the desired acceleration of the target vehicle. A second simulation model of the target vehicle is established based on the input and output signals of the adaptive cruise algorithm; the second simulation model is a closed-loop model of the target vehicle, used to control the behavior of the target vehicle; The target vehicle is simulated and tested using the second simulation model of the target vehicle and the simulation scenario library.

2. The method according to claim 1, characterized in that, The establishment of the simulation scenario library includes: Obtain road information for the target scene; Obtain traffic vehicle information in the target scenario; Determine the pre-driving route corresponding to the target vehicle and the traffic vehicle information based on the road information of the target scenario; A simulation model of the target scene is obtained based on the road information of the target scene, the target vehicle, and the pre-driving route corresponding to the traffic vehicle information. A simulation scenario library is established based on simulation models of multiple target scenarios.

3. The method according to claim 2, characterized in that, The acquisition of road information for the target scene includes: Obtain the road type and road signs of the target scene; Determine the preset road parameters for the target scene based on the road type; The fixed objects in the target scene are obtained based on the road signs; The road information of the target scene is determined based on the preset road parameters and the fixed object.

4. The method according to claim 1, characterized in that, The step of determining the input and output signals of the adaptive cruise algorithm based on the first simulation model of the target vehicle, the simulation scenario library, and the preset cruise speed includes: The state signal of the target vehicle and the simulation scene signal are obtained based on the first simulation model of the target vehicle and the simulation scene library. The target vehicle's status signal, the simulation scenario signal, and the preset cruise speed are used as the input signals for the adaptive cruise algorithm. The output signal of the adaptive cruise algorithm is obtained based on the input signal of the adaptive cruise algorithm.

5. The method according to claim 1, characterized in that, The step of performing simulation testing of the target vehicle based on the second simulation model of the target vehicle and the simulation scene library includes: The first data of the target vehicle and the second data of the target sensor are obtained according to the second simulation model and the simulation scenario library; The first cruising speed of the target vehicle is obtained based on the first data of the target vehicle and the second data of the target sensor. If the first cruise speed does not reach the preset cruise speed, return to continue executing the steps of acquiring the first data of the target vehicle and the second data of the target sensor; If the first cruise speed reaches the preset cruise speed, the simulation test is considered complete.

6. The method according to claim 5, characterized in that, The method further includes: Based on the first data of the target vehicle and the second data of the target sensor, the vehicle speed adjustment time and the inter-vehicle distance are calculated; the vehicle speed adjustment time and the inter-vehicle distance are used to evaluate whether the adaptive cruise algorithm has achieved the target effect.

7. A vehicle simulation testing device, characterized in that, The device includes: The first model acquisition module is used to establish a dynamic simulation model of the target vehicle; add target sensors; determine the preset state and driving process of the target vehicle based on the dynamic simulation model and the target sensors; and acquire the first simulation model of the target vehicle based on the dynamic simulation model, the target sensors, and the preset state and driving process of the target vehicle. The simulation scenario creation module is used to create a simulation scenario library; The target signal determination module is used to determine the input and output signals of the adaptive cruise algorithm based on the first simulation model of the target vehicle, the simulation scenario library, and the preset cruise speed; the input signals include the real-time status signal of the target vehicle, the simulation scenario signal, and the preset cruise speed; the output signal is the desired acceleration of the target vehicle. The second model building module is used to build a second simulation model of the target vehicle based on the input and output signals of the adaptive cruise algorithm; the second simulation model is a closed-loop model of the target vehicle, used to control the behavior of the target vehicle; The simulation testing module is used to perform simulation testing on the target vehicle based on the second simulation model of the target vehicle and the simulation scenario library.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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