Driving simulation test method and device, electronic equipment and storage medium

Abstract

The invention discloses a driving simulation test method and device, electronic equipment and a storage medium. The method comprises the following steps: in response to a power construction operation, constructing a vehicle power model corresponding to a to-be-tested vehicle, and in response to a perception construction operation, constructing a vehicle perception model corresponding to the to-be-tested vehicle; determining a driving decision rule in response to the rule selection operation; in response to the model integration operation, integrating the vehicle power model, the vehicle sensing model and the driving decision rule to obtain an integrated simulation model; in response to the scene building operation, determining a driving simulation scene; and in response to the driving test operation, determining a driving test result of the simulation vehicle model in the driving simulation scene. According to the technical scheme, complete simulation model construction, scene establishment and driving testing can be carried out through a highly integrated platform, the convenience and efficiency of driving simulation testing are improved, and the user experience feeling is improved.

Description

Technical Field

[0001] The present invention relates to the field of computer application technology, and in particular to a driving simulation test method, device, electronic equipment and storage medium. Background Art

[0002] At present, before vehicles are mass-produced, the driving performance of the vehicles is usually tested by conducting driving simulation tests on the vehicles to be produced to ensure the safety of the vehicles on the road.

[0003] In related technologies, it is usually necessary to first build a vehicle simulation model, then build a simulation test scenario, and finally conduct a simulation test. However, this process usually involves multiple platforms and requires compatibility processing between models, scenarios, and tests. However, the processing process is relatively complicated, resulting in a long driving simulation test cycle, low efficiency, and poor user experience. Summary of the invention

[0004] The present invention provides a driving simulation test method, device, electronic device and storage medium to solve the technical problems of the current driving simulation test process having a long cycle, low efficiency and poor user experience.

[0005] According to one aspect of the present invention, a driving simulation test method is provided, the method comprising:

[0006] In response to the power building operation, a vehicle power model corresponding to the vehicle to be tested is built, and in response to the perception building operation, a vehicle perception model corresponding to the vehicle to be tested is built;

[0007] In response to the rule selection operation, determining a driving decision rule;

[0008] In response to a model integration operation, the vehicle dynamics model, the vehicle perception model, and the driving decision rule are integrated to obtain an integrated simulation model;

[0009] In response to the scenario building operation, determining a driving simulation scenario;

[0010] In response to the driving test operation, a driving test result of the simulated vehicle model in the driving simulation scenario is determined, wherein the driving test result includes a test pass and / or a test fail.

[0011] According to another aspect of the present invention, a driving simulation test device is provided, the device comprising:

[0012] A power building module, configured to build a vehicle power model corresponding to the vehicle to be tested in response to a power building operation, and to build a vehicle perception model corresponding to the vehicle to be tested in response to a perception building operation;

[0013] A rule selection module for determining driving decision rules;

[0014] A model integration module, configured to integrate the vehicle dynamics model, the vehicle perception model and the driving decision rule in response to a model integration operation to obtain an integrated simulation model;

[0015] A scenario building module, for determining a driving simulation scenario in response to a scenario building operation;

[0016] The driving test module is used to determine the driving test result of the simulated vehicle model in the driving simulation scenario in response to the driving test operation, wherein the driving test result includes a test pass and / or a test fail.

[0017] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0018] at least one processor; and

[0019] a memory communicatively connected to the at least one processor; wherein,

[0020] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the driving simulation test method described in any embodiment of the present invention.

[0021] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to implement the driving simulation test method described in any embodiment of the present invention when executed by a processor.

[0022] The technical solution of the embodiment of the present invention is to construct a vehicle power model corresponding to the vehicle to be tested in response to a power construction operation, and to construct a vehicle perception model corresponding to the vehicle to be tested in response to a perception construction operation; to determine a driving decision rule in response to a rule selection operation; to integrate the vehicle power model, the vehicle perception model and the driving decision rule in response to a model integration operation to obtain an integrated simulation model; to determine a driving simulation scene in response to a scene construction operation; and to determine a driving test result of the simulated vehicle model in the driving simulation scene in response to a driving test operation, wherein the driving test result includes a test pass and / or a test fail. Based on the platform integrated by the present invention, a complete simulation model construction, scene construction and driving test are realized through a highly integrated platform, avoiding the problems of incompatibility and low efficiency existing in the traditional driving simulation test requiring multiple platforms, improving the convenience and efficiency of the driving simulation test, and enhancing the user experience.

[0023] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 is a flow chart of a driving simulation test method provided according to Embodiment 1 of the present invention;

[0026] Figure 2 is a flow chart of a driving simulation test method provided according to Embodiment 2 of the present invention;

[0027] Figure 3 is an overall flow chart of a driving simulation test method provided according to an embodiment of the present invention;

[0028] Figure 4 is a structural schematic diagram of a driving simulation test device provided according to Embodiment 3 of the present invention;

[0029] Figure 5 It is a structural schematic diagram of an electronic device for implementing the driving simulation test method of an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0032] Embodiment 1

[0033] Figure 1 A flowchart of a driving simulation test method is provided for the first embodiment of the present invention. This embodiment is applicable to the case of performing a simulation test on vehicle performance. The method can be performed by a driving simulation test device. The driving simulation test device can be implemented in the form of hardware and / or software. The driving simulation test device can be configured in a computer. Figure 1 As shown, the method includes:

[0034] S110. In response to a power building operation, a vehicle power model corresponding to the vehicle to be tested is built; and, in response to a perception building operation, a vehicle perception model corresponding to the vehicle to be tested is built.

[0035] Among them, the vehicle to be tested can be understood as a vehicle to be subjected to a driving simulation test. Optionally, the vehicle to be tested may include an autonomous driving vehicle and a manually driven vehicle. In an embodiment of the present invention, the vehicle to be tested may be preset according to scenario requirements, which is not specifically limited herein. For example, the vehicle to be tested may be a vehicle with A configuration, a vehicle with B configuration, or a vehicle with C configuration, etc.

[0036] The power building operation can be understood as an operation of building a power model corresponding to the vehicle to be tested. In an embodiment of the present invention, the power building operation can be preset according to the scene requirements and is not specifically limited here. Optionally, the power building operation may include one or more of the operations of dragging a power component model, setting parameters of a power component model, and combining multiple power component models.

[0037] The vehicle dynamics model can be understood as a simulation dynamics model corresponding to the vehicle to be tested. The vehicle dynamics model can receive a command signal and execute a corresponding driving action.

[0038] The perception construction operation can be understood as an operation of constructing a perception model corresponding to the vehicle to be tested. In an embodiment of the present invention, the perception construction operation can be preset according to the scenario requirements and is not specifically limited here. Optionally, the perception construction operation may include one or more of the operations of dragging a perception component model, setting parameters of a perception component model, and combining multiple perception component models.

[0039] The vehicle perception model can be understood as a simulation perception model corresponding to the vehicle to be tested. The vehicle perception model can obtain scene-related data in a driving simulation scene. In an embodiment of the present invention, the scene-related data may include one or more of pedestrian-related data, traffic light-related data, obstacle-related data, and road-related data.

[0040] Optionally, before building a vehicle power model corresponding to the vehicle to be tested in response to the power building operation, the method further includes:

[0041] In response to a power assembly selection operation, determining a power assembly model corresponding to the vehicle to be tested;

[0042] In response to the power component calibration operation, the power component model is attribute-calibrated according to the first attribute data to obtain the power component model after attribute calibration, wherein the first attribute data is attribute data of the power component entity on the vehicle to be tested obtained through the target database;

[0043] The step of constructing a vehicle dynamics model corresponding to the vehicle to be tested includes:

[0044] The vehicle power model corresponding to the vehicle to be tested is constructed based on the power component model after attribute calibration.

[0045] The power component selection operation may be understood as an operation of selecting a power component model. Optionally, in response to the power component selection operation, a selected power component model in a power component library is determined, wherein the power component library includes at least one candidate power model.

[0046] In the embodiment of the present invention, the power component selection operation can be preset according to the scene requirements and is not specifically limited here. Exemplarily, the power component selection operation may include single-clicking the candidate power model, double-clicking the candidate power model, or dragging the candidate power model to the target position.

[0047] The power component model can be understood as a simulation model corresponding to the power component of the vehicle to be tested. In an embodiment of the present invention, the power component model can be preset according to the scene requirements, and is not specifically limited here. Optionally, the power component model can include one or more of a spring model, a tire model, an engine model, and a frame model.

[0048] The power assembly entity can be understood as the entity of the power assembly of the vehicle to be tested. In an embodiment of the present invention, the power assembly entity and the power assembly model can correspond one to one. Optionally, the power assembly entity can include one or more of a spring entity, a tire entity, an engine entity, and a frame entity.

[0049] The first attribute data may be understood as the attribute data of the power component entity. Optionally, the first attribute data may include structural parameters and power performance parameters. The structural parameters may include size and posture, and the power performance parameters may include power, stiffness, power, and acceleration performance. Exemplarily, the first attribute data may include the size of the spring entity, the size of the tire entity, the power of the engine model, and the acceleration performance parameters of the engine model.

[0050] The power component calibration operation may be understood as an operation of calibrating the power component model based on the first attribute data corresponding to the power component entity.

[0051] Based on the above-mentioned embodiment scheme, a power component model having a structure consistent with the power component entity of the vehicle to be tested and having a power performance consistent with that of the vehicle to be tested can be obtained.

[0052] Optionally, before building the vehicle perception model corresponding to the vehicle to be tested in response to the perception building operation, the method further includes:

[0053] In response to the perception component selection operation, determining a perception component model corresponding to the vehicle to be tested;

[0054] In response to the perception component calibration operation, the perception component model is attribute-calibrated according to the second attribute data to obtain the perception component model after attribute calibration, wherein the second attribute data is attribute data of the perception component entity on the vehicle to be tested obtained through the target database;

[0055] The constructing of the vehicle perception model corresponding to the vehicle to be tested includes:

[0056] The vehicle perception model corresponding to the vehicle to be tested is constructed according to the perception component model after attribute calibration.

[0057] The perceptual component selection operation may be understood as an operation of selecting a perceptual component model. Optionally, in response to the perceptual component selection operation, a perceptual component model selected from a perceptual component library is determined, wherein the perceptual component library includes at least one candidate perceptual model.

[0058] In the embodiment of the present invention, the perception component selection operation can be preset according to the scene requirements and is not specifically limited here. Exemplarily, the perception component selection operation may include single-clicking the candidate perception model, double-clicking the candidate perception model, or dragging the candidate perception model to the target position.

[0059] The perception component model can be understood as a simulation model corresponding to the perception component of the vehicle to be tested. In an embodiment of the present invention, the perception component model can be preset according to the scene requirements, and is not specifically limited here. Optionally, the perception component model can include one or more sensor models such as a radar model or a camera model.

[0060] The perception component entity may be understood as an entity of the perception component of the vehicle to be tested. In an embodiment of the present invention, the perception component entity may correspond to the perception component model one to one. Optionally, the perception component entity may include one or more of a sensor entity, a radar entity, and a camera entity.

[0061] The second attribute data may be understood as the attribute data of the perception component entity. Optionally, the second attribute data may include structural parameters and perception performance parameters, etc. The structural parameters may include size and posture, etc., and the perception performance parameters may include perception range and perception speed, etc.

[0062] The perception component calibration operation can be understood as an operation of calibrating the perception component model based on the second attribute data corresponding to the perception component entity.

[0063] Based on the above-mentioned embodiment scheme, a perception component model having a structure consistent with the perception component entity of the vehicle to be tested and having a consistent perception performance can be obtained.

[0064] S120 . Determine a driving decision rule in response to the rule selection operation.

[0065] Optionally, in response to the rule selection operation, determining the driving decision rule comprises:

[0066] In response to a selection operation on a plurality of candidate decision rules, a driving decision rule is determined.

[0067] The rule selection operation may be a trigger operation for a decision rule candidate item in the display interface. The display interface may include multiple decision rule candidates. Each decision rule candidate item may correspond to one candidate decision rule.

[0068] The driving decision rule can be understood as a selected decision rule. In an embodiment of the present invention, the power-related data and scene-related data acquired by perception can be processed by the driving decision rule to determine the decision response data, so that the vehicle power model performs the corresponding response driving action based on the decision response data.

[0069] S130. In response to the model integration operation, the vehicle dynamics model, the vehicle perception model, and the driving decision rule are integrated to obtain an integrated simulation model.

[0070] The model integration operation can be understood as an operation of integrating a power model, a perception model and a decision rule.

[0071] The integrated simulation model can be understood as a simulation model corresponding to the vehicle to be tested. The integrated simulation model has the power, perception, and decision-making capabilities of the vehicle to be tested.

[0072] S140: In response to the scene building operation, determine a driving simulation scene.

[0073] Among them, the scene building operation can be understood as an operation of building a simulation test scene. In an embodiment of the present invention, the scene building operation can be preset according to the scene requirements, and is not specifically limited here. Exemplarily, the scene building operation may include a basic scene selection operation and an interference adding operation. The basic scene selection operation may be a selection operation for multiple candidate basic scenes. The basic scene selection operation may be an operation of selecting a target basic scene. The candidate basic scenes may include forest scenes, high-speed scenes, and mountain road scenes. The interference adding operation may be understood as an operation of adding an interference test node to the selected target basic scene. The interference adding operation may be an operation of adding an interference test node to the target basic scene. Optionally, the interference adding operation may be an operation of adding obstacles or adding emergency road conditions. Among them, the added emergency road conditions may be sudden braking of the vehicle in front or the appearance of a fast pedestrian in front of the vehicle.

[0074] The driving simulation scenario may be determined based on a selected target basic scenario and an interference test node added to the target basic scenario.

[0075] S150: In response to the driving test operation, determine a driving test result of the simulated vehicle model in the driving simulation scenario.

[0076] The driving test result includes a test pass and / or a test fail.

[0077] The driving test operation may be understood as an operation of starting a driving simulation test. Optionally, the driving test operation may be a triggering operation for a driving test start control.

[0078] The driving test result can be understood as the result of the driving simulation test. The driving test result can characterize the driving performance of the vehicle to be tested. In layman's terms, if the driving test result is a test pass, it indicates that the driving performance of the vehicle to be tested is sufficient to perform safe driving in the actual driving scenario corresponding to the driving simulation scenario, and the driving performance is high; otherwise, the driving performance is low.

[0079] The technical solution of the embodiment of the present invention is to construct a vehicle power model corresponding to the vehicle to be tested in response to a power construction operation, and to construct a vehicle perception model corresponding to the vehicle to be tested in response to a perception construction operation; to determine a driving decision rule in response to a rule selection operation; to integrate the vehicle power model, the vehicle perception model and the driving decision rule in response to a model integration operation to obtain an integrated simulation model; to determine a driving simulation scene in response to a scene construction operation; and to determine a driving test result of the simulated vehicle model in the driving simulation scene in response to a driving test operation, wherein the driving test result includes a test pass and / or a test fail. Based on the platform integrated by the present invention, a complete simulation model construction, scene construction and driving test are realized through a highly integrated platform, avoiding the problems of incompatibility and low efficiency existing in the traditional driving simulation test requiring multiple platforms, improving the convenience and efficiency of the driving simulation test, and enhancing the user experience.

[0080] Embodiment 2

[0081] Figure 2 This is a flowchart of a driving simulation test method provided in the second embodiment of the present invention. This embodiment refines the driving test results of determining the simulated vehicle model in the driving simulation scenario described in the above embodiment. Figure 2 As shown, the method includes:

[0082] S210: In response to a power building operation, building a vehicle power model corresponding to the vehicle to be tested; and, in response to a perception building operation, building a vehicle perception model corresponding to the vehicle to be tested.

[0083] S220: In response to the rule selection operation, determine a driving decision rule.

[0084] S230: In response to the model integration operation, the vehicle dynamics model, the vehicle perception model, and the driving decision rule are integrated to obtain an integrated simulation model.

[0085] S240: In response to the scene building operation, determine a driving simulation scene.

[0086] S250: In response to a driving test operation, determine driving test data of the integrated simulation model in the driving simulation scenario.

[0087] In an embodiment of the present invention, the driving simulation scenario includes multiple interference test nodes, and the driving test data includes response driving data corresponding to the response driving action of the simulated vehicle model at each interference test node.

[0088] The driving test data may be understood as the driving data of the integrated simulation model during the driving test, and the driving data may include the driving direction, driving speed, driving acceleration, and climbing grade.

[0089] The interference test node can be understood as a test node that interferes with the simulated driving of the integrated simulation model. Optionally, the interference test node may include an obstacle node or an emergency road condition node. Exemplarily, the obstacle node may be a stone node or a maintenance sign node. The emergency road condition node may be a fast pedestrian node or a front vehicle emergency brake node.

[0090] The responsive driving action can be understood as the responsive action of the integrated simulation model under the interference test node. The responsive driving action may include emergency braking, emergency braking, deceleration, and adjusting the driving direction.

[0091] The responsive driving data may be understood as data corresponding to the responsive driving action, and may include the driving direction, driving speed, driving acceleration, and climbing grade, etc.

[0092] Optionally, determining the driving test data of the integrated simulation model in the driving simulation scenario includes:

[0093] For each of the interference test nodes, determining the scene-related data corresponding to the interference test node and the power-related data of the vehicle power model under the interference test node through the vehicle perception model;

[0094] The scenario-related data and the power-related data are processed by the driving decision rule to obtain decision response data, so that the vehicle power model performs the response driving action based on the decision response data.

[0095] Among them, the scene-related data can be understood as data related to the driving scene. Optionally, the scene-related data may include obstacle-related data, weather-related data, and traffic light-related data. Exemplarily, the obstacle-related data may include obstacle distance, obstacle type (including stones, maintenance signs, or pedestrians, etc.), and obstacle size. The weather-related data includes weather categories (including sunny, rainy, or snowy days) and weather intensity (including low, medium, or high). The traffic light-related data may include indicator light categories (including red, yellow, or green) and indicator light end time.

[0096] The power-related data may be understood as driving data related to the power of the vehicle power model. Optionally, the power-related data may include driving direction, driving speed, driving acceleration, climbing grade, and the like.

[0097] Specifically, after obtaining the decision response data, the method further includes:

[0098] A decision response signal corresponding to the decision response data is generated, and the decision response signal is sent to the vehicle dynamics model.

[0099] The decision response data may be understood as data for controlling the vehicle dynamics model so that the vehicle dynamics model can cope with driving scenarios. Optionally, the decision response data may include driving direction, driving speed, driving acceleration, and climbing grade, etc., or the decision response data may also include direction adjustment data, speed adjustment data, acceleration adjustment data, and climbing grade adjustment data, etc.

[0100] S260: Determine comparative test data.

[0101] In an embodiment of the present invention, the comparative test data includes comparative driving data of the simulated vehicle model at each of the interference test nodes.

[0102] The comparative test data may be understood as pre-stored benchmark test data.

[0103] The comparative driving data may be understood as pre-stored reference driving data.

[0104] S270. Determine a driving test result corresponding to the driving test data according to the driving test data and the comparative test data.

[0105] Specifically, for each interference test node, if the response driving data in the driving test data is consistent with the comparison driving data in the comparison test data, the driving test result is determined as the test passed; otherwise, the test is determined as failed.

[0106] Optionally, after determining the driving test result of the simulated vehicle model in the driving simulation scenario, the method further includes:

[0107] When the driving test result is that the test fails, the vehicle perception model and / or the driving decision rule of the integrated simulation model are adjusted according to the driving test data to obtain the adjusted integrated simulation model.

[0108] In the embodiment of the present invention, the adjustment method for the vehicle perception model and / or the driving decision rule is not specifically limited herein. Exemplarily, the position or perception performance parameters of the vehicle perception model may be adjusted, or the sub-decision rules in the driving decision rule may be adjusted. The sub-decision rules may include direction decision rules, speed decision rules, acceleration decision rules, etc.

[0109] Based on the above-mentioned embodiment scheme, the integrated simulation model is optimized based on the driving test results to further achieve performance optimization for the vehicle to be tested.

[0110] The technical solution of the present invention can be implemented by the Modelica platform, which can realize complete simulation model construction, scene construction and driving test. Figure 3 3 is an overall flow chart of a driving simulation test method provided according to an embodiment of the present invention. In combination with 3, the overall steps of the driving simulation test method are described as follows:

[0111] 1. Construction of the execution system model (vehicle power model) of the vehicle (the vehicle to be tested). Use the Modelica basic model library to build the vehicle's suspension, tires, power system, braking system, steering system, etc.;

[0112] 2. Component calibration of the execution system model, benchmarking the attribute data of each component model in the execution system model with the real vehicle components to ensure the accuracy of the physical characteristics of the components;

[0113] 3. Build the execution system model according to the vehicle model selection, that is, the vehicle dynamics model;

[0114] 4. Construct the vehicle's perception system model (vehicle perception model), using the Modelica basic model library to build models of various sensors such as the vehicle's lidar, millimeter-wave radar, ultrasonic radar, and infrared radar;

[0115] 5. Perception system model: calibrate the sensor model according to the measured experimental data to ensure that the sensor model is consistent with the perception performance of the real sensor;

[0116] 6. Build a driving perception system and determine the number and installation locations of sensors;

[0117] 7. After completing the construction and calibration of the driving perception system and execution system models, integrate the two with the driving decision system (driving decision rules) to form a complete driving system simulation model (integrated simulation model);

[0118] 8. Build a driving system simulation scenario and build the simulation scenario to be verified according to the requirements;

[0119] 9. Use the platform model library to build test cases or test scenarios. Simulate complex scenarios such as pedestrians, external interfering vehicles, and random driver behaviors, and key indicators such as the anti-interference ability, response speed, and control accuracy of the driving decision-making system algorithm;

[0120] 10. Driving system simulation verification: deploy the driving system simulation model to the scene to verify the driving decision system, adjust the sensor model, quantity and installation location according to the simulation situation, and optimize the algorithm of the driving decision system.

[0121] The present invention realizes complete simulation model construction, scenario construction and driving testing through a highly integrated compatibility platform. The present invention has high flexibility, and various parameters and conditions can be easily set and modified to simulate different driving scenarios and conditions. At the same time, components can be easily added or deleted to verify their impact on the performance of the simulation model. The present invention has high reusability, and the component models that have been built and calibrated can be reused in subsequent simulation verification scenarios, which can reduce testing costs and cycles. The present invention has high safety. Through simulation testing, the performance and safety of the integrated simulation model can be verified in non-actual road conditions, greatly reducing the risks and costs of actual testing. The data reproducibility of the present invention, the results of the simulation test can be saved and reproduced, which is convenient for users to analyze and compare the test results, thereby analyzing the key points of vehicle performance improvement.

[0122] Embodiment 3

[0123] Figure 4 This is a schematic diagram of the structure of a driving simulation test device provided by Embodiment 3 of the present invention. Figure 4 As shown, the device includes: a power construction module 310, a rule selection module 320, a model integration module 330, a scenario construction module 340 and a driving test module 350.

[0124] Among them, the power construction module 310 is used to construct a vehicle power model corresponding to the vehicle to be tested in response to the power construction operation, and, in response to the perception construction operation, to construct a vehicle perception model corresponding to the vehicle to be tested; the rule selection module 320 is used to determine the driving decision rules; the model integration module 330 is used to integrate the vehicle power model, the vehicle perception model and the driving decision rules in response to the model integration operation to obtain an integrated simulation model; the scenario construction module 340 is used to determine the driving simulation scenario in response to the scenario construction operation; the driving test module 350 is used to determine the driving test result of the simulated vehicle model in the driving simulation scenario in response to the driving test operation, wherein the driving test result includes test pass and / or test fail.

[0125] The technical solution of the embodiment of the present invention is to construct a vehicle power model corresponding to the vehicle to be tested in response to a power construction operation, and to construct a vehicle perception model corresponding to the vehicle to be tested in response to a perception construction operation; to determine a driving decision rule in response to a rule selection operation; to integrate the vehicle power model, the vehicle perception model and the driving decision rule in response to a model integration operation to obtain an integrated simulation model; to determine a driving simulation scene in response to a scene construction operation; and to determine a driving test result of the simulated vehicle model in the driving simulation scene in response to a driving test operation, wherein the driving test result includes a test pass and / or a test fail. Based on the platform integrated by the present invention, a complete simulation model construction, scene construction and driving test are realized through a highly integrated platform, avoiding the problems of incompatibility and low efficiency existing in the traditional driving simulation test requiring multiple platforms, improving the convenience and efficiency of the driving simulation test, and enhancing the user experience.

[0126] Optionally, the driving simulation test device further includes: a power component selection module and a power component calibration module;

[0127] The power assembly selection module is used to determine the power assembly model corresponding to the vehicle to be tested in response to the power assembly selection operation before building the vehicle power model corresponding to the vehicle to be tested in response to the power building operation;

[0128] The power assembly calibration module is used to perform attribute calibration on the power assembly model according to first attribute data in response to a power assembly calibration operation to obtain the power assembly model after attribute calibration, wherein the first attribute data is attribute data of the power assembly entity on the vehicle to be tested obtained through a target database;

[0129] The power building module 310 is specifically used for:

[0130] The vehicle power model corresponding to the vehicle to be tested is constructed based on the power component model after attribute calibration.

[0131] Optionally, the driving simulation test device further comprises: perception component selection and perception component calibration;

[0132] The perception component selection is used to determine the perception component model corresponding to the vehicle to be tested in response to a perception component selection operation before building the vehicle perception model corresponding to the vehicle to be tested in response to the perception building operation;

[0133] The perception component calibration is used to perform attribute calibration on the perception component model according to second attribute data in response to a perception component calibration operation, so as to obtain the perception component model after attribute calibration, wherein the second attribute data is attribute data of the perception component entity on the vehicle to be tested obtained through a target database;

[0134] The power building module 310 is specifically used for:

[0135] The vehicle perception model corresponding to the vehicle to be tested is constructed according to the perception component model after attribute calibration.

[0136] Optionally, the rule selection module 320 is specifically configured to:

[0137] In response to a selection operation on a plurality of candidate decision rules, a driving decision rule is determined.

[0138] Optionally, the driving test module 350 includes: a test data determination unit, a comparison data determination unit, and a test result determination unit;

[0139] The test data determination unit is used to determine the driving test data of the integrated simulation model in the driving simulation scenario, wherein the driving simulation scenario includes a plurality of interference test nodes, and the driving test data includes response driving data corresponding to the response driving action of the simulated vehicle model in each interference test node;

[0140] The comparison data determination unit is used to determine comparison test data, wherein the comparison test data includes comparison driving data of the simulated vehicle model at each interference test node;

[0141] The test result determination unit is used to determine the driving test result corresponding to the driving test data according to the driving test data and the comparison test data.

[0142] Optionally, the test data determining unit is specifically configured to:

[0143] For each of the interference test nodes, determining the scene-related data corresponding to the interference test node and the power-related data of the vehicle power model under the interference test node through the vehicle perception model;

[0144] The scenario-related data and the power-related data are processed by the driving decision rule to obtain decision response data, so that the vehicle power model performs the response driving action based on the decision response data.

[0145] Optionally, the driving simulation test device further includes:

[0146] A model adjustment module is used to adjust the vehicle perception model and / or the driving decision rule of the integrated simulation model according to the driving test data after determining the driving test result of the simulated vehicle model in the driving simulation scenario, when the driving test result is that the test fails, to obtain the adjusted integrated simulation model.

[0147] The driving simulation test device provided in the embodiment of the present invention can execute the driving simulation test method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0148] Embodiment 4

[0149] Figure 5 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0150] like Figure 5As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0151] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0152] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a driving simulation test method.

[0153] In some embodiments, the driving simulation test method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the driving simulation test method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the driving simulation test method in any other appropriate manner (e.g., by means of firmware).

[0154] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0155] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0156] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0157] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0158] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0159] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0160] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0161] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A driving simulation test method, characterized in that: include: In response to the power building operation, a vehicle power model corresponding to the vehicle to be tested is built, and in response to the perception building operation, a vehicle perception model corresponding to the vehicle to be tested is built; In response to the rule selection operation, determining a driving decision rule; In response to a model integration operation, the vehicle dynamics model, the vehicle perception model, and the driving decision rule are integrated to obtain an integrated simulation model; In response to the scenario building operation, determining a driving simulation scenario; In response to the driving test operation, a driving test result of the simulated vehicle model in the driving simulation scenario is determined, wherein the driving test result includes a test pass and / or a test fail.

2. The method according to claim 1, characterized in that Before building a vehicle power model corresponding to the vehicle to be tested in response to the power building operation, the method further includes: In response to a power assembly selection operation, determining a power assembly model corresponding to the vehicle to be tested; In response to the power component calibration operation, the power component model is attribute-calibrated according to the first attribute data to obtain the power component model after attribute calibration, wherein the first attribute data is attribute data of the power component entity on the vehicle to be tested obtained through the target database; The step of constructing a vehicle dynamics model corresponding to the vehicle to be tested includes: The vehicle power model corresponding to the vehicle to be tested is constructed based on the power component model after attribute calibration.

3. The method according to claim 1, characterized in that Before building the vehicle perception model corresponding to the vehicle to be tested in response to the perception building operation, the method further includes: In response to the perception component selection operation, determining a perception component model corresponding to the vehicle to be tested; In response to the perception component calibration operation, the perception component model is attribute-calibrated according to the second attribute data to obtain the perception component model after attribute calibration, wherein the second attribute data is attribute data of the perception component entity on the vehicle to be tested obtained through the target database; The constructing of the vehicle perception model corresponding to the vehicle to be tested includes: The vehicle perception model corresponding to the vehicle to be tested is constructed according to the perception component model after attribute calibration.

4. The method according to claim 1, characterized in that: In response to the rule selection operation, determining the driving decision rule includes: In response to a selection operation on a plurality of candidate decision rules, a driving decision rule is determined.

5. The method according to claim 1, characterized in that Determining the driving test result of the simulated vehicle model in the driving simulation scenario includes: Determining driving test data of the integrated simulation model in the driving simulation scenario, wherein the driving simulation scenario includes a plurality of interference test nodes, and the driving test data includes response driving data corresponding to a response driving action of the simulated vehicle model in each of the interference test nodes; Determining comparative test data, wherein the comparative test data includes comparative driving data of the simulated vehicle model at each of the interference test nodes; A driving test result corresponding to the driving test data is determined according to the driving test data and the comparison test data.

6. The method according to claim 5, characterized in that The determining of the driving test data of the integrated simulation model in the driving simulation scenario includes: For each of the interference test nodes, determining the scene-related data corresponding to the interference test node and the power-related data of the vehicle power model under the interference test node through the vehicle perception model; The scenario-related data and the power-related data are processed by the driving decision rule to obtain decision response data, so that the vehicle power model performs the response driving action based on the decision response data.

7. The method according to claim 5, characterized in that After determining the driving test result of the simulated vehicle model in the driving simulation scenario, the method further includes: When the driving test result is that the test fails, the vehicle perception model and / or the driving decision rule of the integrated simulation model are adjusted according to the driving test data to obtain the adjusted integrated simulation model.

8. A driving simulation test device, characterized in that: include: A power building module, configured to build a vehicle power model corresponding to the vehicle to be tested in response to a power building operation, and to build a vehicle perception model corresponding to the vehicle to be tested in response to a perception building operation; A rule selection module for determining driving decision rules; A model integration module, configured to integrate the vehicle dynamics model, the vehicle perception model and the driving decision rule in response to a model integration operation to obtain an integrated simulation model; A scenario building module, for determining a driving simulation scenario in response to a scenario building operation; The driving test module is used to determine the driving test result of the simulated vehicle model in the driving simulation scenario in response to the driving test operation, wherein the driving test result includes a test pass and / or a test fail.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the driving simulation test method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the driving simulation test method according to any one of claims 1 to 7 when executed.

Images