CN115470616A - Vehicle simulation test method, apparatus, computer device, medium, and program product - Google Patents
Vehicle simulation test method, apparatus, computer device, medium, and program product Download PDFInfo
- Publication number
- CN115470616A CN115470616A CN202210973677.8A CN202210973677A CN115470616A CN 115470616 A CN115470616 A CN 115470616A CN 202210973677 A CN202210973677 A CN 202210973677A CN 115470616 A CN115470616 A CN 115470616A
- Authority
- CN
- China
- Prior art keywords
- simulation
- target
- vehicle
- target vehicle
- scene
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application relates to a vehicle simulation test method, a vehicle simulation test device, a vehicle storage medium and a vehicle simulation program product, wherein a simulation scene library is established by acquiring a first simulation model of a target vehicle, and an input signal and an output signal of an adaptive cruise algorithm are determined by combining a preset cruise speed, so that a second simulation model of the target vehicle is established, and 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 the efficient and convenient test of the adaptive cruise function of a tractor is realized.
Description
Technical Field
The present application relates to the field of automatic driving simulation testing of tractors, and in particular, to a vehicle simulation testing method, apparatus, computer device, storage medium, and computer program product.
Background
With the continuous maturity of the automatic driving technology, the adaptive cruise function has been applied to general passenger vehicles to a certain extent, and the actual way of the automatic driving vehicle needs a great amount of tests to verify the reliability of the technology.
Aiming at the self-adaptive cruise function of the existing tractor, the general method of the real vehicle test is to improve and update the algorithm according to the data processing result after one round of real vehicle test.
However, the testing method has long testing time of a single scene and long updating period of data processing and algorithm, so that the testing efficiency is low and the testing cost of a single vehicle is high.
Disclosure of Invention
In view of the above, it is necessary to provide a vehicle simulation test method, device, computer readable storage medium and computer program product capable of efficiently and conveniently testing the adaptive cruise function of the tractor.
In a first aspect, the present application provides a vehicle simulation test method, including:
acquiring a first simulation model of a target vehicle;
establishing a simulation scene library;
determining an input signal and an output signal of an adaptive cruise algorithm according to a first simulation model of a target vehicle, a simulation scene library and a preset cruise speed;
establishing a second simulation model of the target vehicle according to the input signal and the output signal of the adaptive cruise algorithm;
and carrying out simulation test on the target vehicle according to the second simulation model of the target vehicle and the simulation scene library.
In one embodiment, the obtaining the first simulation model of the target vehicle includes:
establishing a dynamic simulation model of the target vehicle;
adding a target sensor;
determining the preset state and the running process of the target vehicle according to the dynamic simulation model and the target sensor;
and acquiring a first simulation model of the target vehicle according to the dynamic simulation model, the target sensor and the preset state and the running process of the target vehicle.
In one embodiment, the creating a simulation scenario library includes:
acquiring road information of a target scene;
acquiring traffic vehicle information in a target scene;
determining a target vehicle and a pre-driving route corresponding to the traffic vehicle information according to the road information of the target scene;
acquiring a simulation model of the target scene according to the road information of the target scene, the target vehicle and the pre-driving route corresponding to the traffic vehicle information;
and establishing a simulation scene library according to the simulation models of the plurality of target scenes.
In one embodiment, the acquiring the road information of the target scene includes:
acquiring a road type and a road sign of a target scene;
determining preset road parameters of a target scene according to the road type;
acquiring a fixed object of a target scene according to a road sign;
and determining road information of the target scene according to the preset road parameters and the fixed object.
In one embodiment, the determining the input signal and the output signal of the adaptive cruise algorithm according to the first simulation model of the target vehicle, the simulation scene library and the preset cruise speed includes:
acquiring a state signal and a simulation scene signal of the target vehicle according to the first simulation model of the target vehicle and the simulation scene library;
taking a state signal, a simulation scene signal and a preset cruising speed of a target vehicle as input signals of an adaptive cruising algorithm;
an output signal of the adaptive cruise algorithm is obtained from an input signal of the adaptive cruise algorithm.
In one embodiment, the performing the simulation test of the target vehicle according to the second simulation model of the target vehicle and the simulation scenario library includes:
acquiring first data of a target vehicle and second data of a target sensor according to a second simulation model and a simulation scene library;
acquiring a first cruising speed of the target vehicle according to 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 continuously executing the step of acquiring the first data of the target vehicle and the second data of the target sensor;
and if the first cruising speed reaches the preset cruising speed, judging that the simulation test is finished.
In one embodiment, the method further includes:
calculating the speed adjustment time and the workshop time distance of the target vehicle according to the first data of the target vehicle and the second data of the target sensor; the vehicle speed adjusting time and the workshop time interval are used for evaluating whether the adaptive cruise algorithm achieves the target effect.
In a second aspect, the present application further provides a vehicle simulation testing apparatus, comprising:
the first model acquisition module is used for acquiring a first simulation model of the target vehicle;
the simulation scene establishing module is used for establishing a simulation scene library;
the target signal determination module is used for determining an input signal and an output signal of the adaptive cruise algorithm according to the first simulation model of the target vehicle, the simulation scene library and the preset cruise speed;
the second model building module is used for building a second simulation model of the target vehicle according to the input signal and the output signal of the adaptive cruise algorithm;
and the simulation test module is used for carrying out simulation test on the target vehicle according to the second simulation model of the target vehicle and the simulation scene library.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the method steps in any of the above-described first aspects when executing the computer program.
In a fourth aspect, the present application further provides a computer-readable storage medium. A computer-readable storage medium, having stored thereon a computer program which, when being executed by a processor, carries out the method steps of any of the embodiments of the first aspect described above.
In a fifth aspect, the present application further provides a computer program product. Computer program product comprising a computer program which, when executed by a processor, performs the method steps in any of the embodiments of the first aspect described above.
According to the vehicle simulation test method, the vehicle simulation test device, the computer equipment, the storage medium and the computer program product, the first simulation model of the target vehicle is obtained, the simulation scene library is established, the input signal and the output signal of the adaptive cruise algorithm are determined by combining the preset cruise speed, so that the second simulation model of the target vehicle is established, the simulation test of the target vehicle is carried out 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 the efficient and convenient test of the self-adaptive cruise function of the tractor is realized.
Drawings
FIG. 1 is a diagram of an exemplary vehicle simulation test system;
FIG. 2 is a schematic flow chart diagram of a vehicle simulation testing method in one embodiment;
FIG. 3 is a schematic flow chart of the step S201 in the embodiment shown in FIG. 2;
FIG. 4 is a flowchart illustrating the step S202 in the embodiment shown in FIG. 2;
FIG. 5 is a flowchart illustrating the step S401 in the embodiment shown in FIG. 4;
FIG. 6 is a schematic flowchart of step S203 in the embodiment shown in FIG. 2;
FIG. 7 is a flowchart illustrating the step S205 in the embodiment shown in FIG. 2;
FIG. 8 is a schematic flow chart diagram illustrating a vehicle simulation test method according to another embodiment;
FIG. 9 is a block diagram showing the construction of a vehicle simulation test apparatus according to an embodiment;
fig. 10 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
It will be understood that the terms "first," "second," and the like as used herein may be used herein to describe various data, but the data is not limited by these terms. These terms are only used to distinguish one datum from another. Unless defined otherwise, 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 belongs. The terminology used herein in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. It will be further understood that the terms "comprises/comprising," "includes" or "including," or "having," etc., specify the presence of stated features, integers, steps, operations, or combinations thereof, but do not preclude the presence or addition of one or more other features, integers, steps, operations, or combinations thereof. Also, as used in this specification, the term "and/or" includes any and all combinations of the associated listed items.
The vehicle simulation test method provided by the embodiment of the application can be applied to a computer device, the computer device can be any type of device, for example, a terminal device, or various personal computers, laptops, tablets, wearable devices, servers, and the like, and the embodiment of the application does not limit the type of the computer device. As shown in FIG. 1, a schematic diagram of an internal structure of a computer device is provided, and the processor of FIG. 1 is used for providing computing and control capabilities. The memory comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database is used for relevant data of the reliability evaluation process of the structure. The network interface is used for communicating with other external devices through network connection. The computer program is executed by a processor to implement a vehicle simulation testing method.
In one embodiment, as shown in fig. 2, there is provided a vehicle simulation testing method, comprising the steps of:
s201: a first simulation model of a target vehicle is obtained.
The first simulation model is a complete simulation model of the target vehicle and comprises a dynamic simulation model of the target vehicle, a sensor model of the vehicle and the like. The dynamic simulation model comprises a vehicle body model, a trailer model, a suspension model, a tire model, a steering model, a braking model and the like; the sensor model comprises sensors with the current lane of the target vehicle as a detection range and sensors with all lanes as detection ranges.
S202: and establishing a simulation scene library.
The simulation scene library comprises a plurality of simulation scenes for simulating test conditions in a real environment, and the forming factors of each simulation scene comprise static content and dynamic traffic flow content. The static content comprises basic roads, road related parameters, road signs, fixed objects and the like in a scene; the dynamic traffic flow includes the initial speed and initial position of the traffic vehicle and the action progress.
S203: and determining an input signal and an output signal of the adaptive cruise algorithm according to the first simulation model of the target vehicle, the simulation scene library and the preset cruise speed.
When the adaptive cruise function is started, the self-vehicle can run according to the set cruise speed under the front non-vehicle state, and can adjust the distance and the vehicle speed according to the set distance and the set cruise speed under the front vehicle state. The adaptive cruise algorithm is used for realizing model closed loop of simulation test, input signals of the adaptive cruise algorithm comprise real-time state signals of a simulated vehicle, simulation scene related signals, cruise speed set values and the like, and output signals of the adaptive cruise algorithm are expected acceleration of the simulated vehicle.
S204: a second simulation model of the target vehicle is established based on the input signals and the output signals of the adaptive cruise algorithm.
The second simulation model is a closed-loop model of the target vehicle and is used for controlling the behavior of the simulated vehicle, the control signal is converted into a signal which can be identified by simulation software through an interface, and when the expected acceleration output in the adaptive cruise algorithm is a positive value, the simulated vehicle has an acceleration behavior.
S205: and carrying out simulation test on the target vehicle according to the second simulation model of the target vehicle and the simulation scene library.
And testing the second simulation model of the target vehicle in each simulation scene in the built simulation scene library, and acquiring and recording real-time change data of the state of the target vehicle, real-time change data of the sensor and the like. The target vehicle state real-time data comprises a current vehicle speed, a current vehicle acceleration, vehicle speed adjusting time caused by scene change and the like; the real-time sensor change data is provided by establishing a sensor model and comprises the relative front vehicle distance of a target vehicle and the like. And judging whether the adaptive cruise algorithm achieves the expected function or not according to the acquired current vehicle speed and the set cruise speed in the input signal of the adaptive cruise algorithm.
According to the vehicle simulation test method, the first simulation model of the target vehicle is obtained, the simulation scene library is established, the input signal and the output signal of the adaptive cruise algorithm are determined by combining the preset cruise speed, the second simulation model of the target vehicle is established, the target vehicle is subjected to simulation test 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 the adaptive cruise function of the tractor can be tested efficiently and conveniently.
In one embodiment, as shown in fig. 3, the obtaining of the first simulation model of the target vehicle includes the following steps:
s301: and establishing a dynamic simulation model of the target vehicle.
The dynamic simulation model comprises a vehicle body model, a trailer model, a suspension model, a tire model, a steering model, a braking model and the like, and the models are parameterized simulation models.
S302: a target sensor is added.
Wherein the target sensor includes a first sensor and a second sensor. Wherein, the detection scope of first sensor is current lane, and output signal includes: whether other vehicles exist on the current lane, the acceleration of the nearest vehicle on the current lane, the relative speed and the relative distance between the other vehicles and the target vehicle and the like, and the output signal of the first sensor can be used as a part of input signals of the adaptive cruise algorithm in the test process; the detection range of the second sensor is all lanes, and the output signal can be used as a reference for assisting in setting the behavior of the traffic vehicle in a part of scenes.
S303: and determining the preset state and the running process of the target vehicle according to the dynamic simulation model and the target sensor.
The preset state of the target vehicle comprises a starting speed, a starting position, a starting gear and the like of the vehicle, wherein the starting speed is 40km/h, the starting position is 10m away from the starting point of the simulated road, and the starting gear is 4 gears. Setting cruise speed v in specific parameters of driving process t The cruise speed value is used as one of input signals of the adaptive cruise algorithm in the test process, the cruise speed needs to be referred to a speed range which can be reached in the algorithm, for example, the cruise speed in the algorithm can reach the range of 40 km/h-60 km/h, and then the cruise speed is set in the range of 40 km/h-60 km/h.
S304: and acquiring a first simulation model of the target vehicle according to the dynamic simulation model, the target sensor and the preset state and the running process of the target vehicle.
The method comprises the steps of setting a preset state and a driving process for a dynamic simulation model of a target vehicle, setting a corresponding detection distance and a corresponding detection angle for a target sensor, and establishing a complete simulation model of the target vehicle, namely a first simulation model.
In the embodiment, the preset state and the running process of the target vehicle are determined by establishing the dynamic simulation model of the target vehicle and adding the target sensor, so that the first simulation model of the target vehicle can be obtained, the running state of the tractor can be truly simulated, and the simulation test of the real vehicle is realized.
In one embodiment, as shown in fig. 4, the creating of the simulation scenario library includes the following steps:
s401: and acquiring road information of the target scene.
The road information of the target scene includes a road type, road-related parameters, road signs, fixed objects, and the like in the scene. The basic roads comprise different types of roads such as main roads, curves, crossroads and the like; the road related parameters comprise the parameters of lane length, the number of lanes, the road type, the transverse gradient of the road, the longitudinal gradient of the road, the road material and the like; the road signs comprise lane lines, road signs, traffic signs and the like; the fixed objects include building models, vegetation and the like.
S402: and acquiring the traffic vehicle information in the target scene.
The traffic vehicle information comprises the initial speed and the initial position of the traffic vehicle, wherein the initial speed is 60km/h, and the initial position is 100m away from the target vehicle; the traffic vehicle information also comprises an action progress, the transverse behavior and the longitudinal behavior of the traffic vehicle can be set in a progress, for example, the longitudinal acceleration of the traffic vehicle is 2m/s, the acceleration time is 5s, the transverse movement is 3.5m for lane change, in the progress, the ending condition of the progress is set, the time length of the progress or the triggering condition of the ending of the progress is set, for example, the current progress is ended in 10s, or the current progress is ended when the distance between a front vehicle and the current vehicle is 50 m.
S403: and determining the target vehicle and the pre-driving route corresponding to the traffic vehicle information according to the road information of the target scene.
And adding air routes for the target vehicle and the traffic vehicle according to the road information of the target scene, wherein the air routes are used as the pre-driving routes of the traffic participants in the simulation.
S404: and acquiring a simulation model of the target scene according to the road information of the target scene, the target vehicle and the pre-driving route corresponding to the traffic vehicle information.
The simulation model of the target scene comprises static content and dynamic traffic flow content of the simulation scene, wherein the static content is road information and target vehicles, and the dynamic traffic flow content is a pre-driving route corresponding to the traffic vehicle information.
S405: and establishing a simulation scene library according to the simulation models of the plurality of target scenes.
The simulation scene library comprises a plurality of target scenes and is used for simulating different test environments.
In the embodiment, the pre-driving route corresponding to the target vehicle and the traffic vehicle information can be determined by acquiring the road information of the target scene and the traffic vehicle information in the target scene, so that the simulation model of the target scene is acquired, the simulation scene library is established, a large number of virtual scenes can be provided for simulation test, and extreme working condition scenes which cannot be tested by real vehicles can be constructed due to the fact that the test process does not have danger coefficients, so that the scene coverage of the test is greatly improved.
In an embodiment, as shown in fig. 5, the acquiring the road information of the target scene includes the following steps:
s501: and acquiring the road type and the road sign of the target scene.
The road types comprise different types of roads such as a main road, a curve, a crossroad and the like; the road signs include lane lines, road signs, traffic signs, and the like.
S502: and determining preset road parameters of the target scene according to the road type.
The preset road parameters comprise lane length, lane number, road type, road transverse gradient, road longitudinal gradient, road material and the like.
S503: and acquiring a fixed object of the target scene according to the road sign.
Wherein, the fixed objects comprise building models, vegetation and the like.
S504: and determining road information of the target scene according to the preset road parameters and the fixed object.
In the embodiment, the preset road parameters of the target scene are determined by acquiring the road type and the road sign of the target scene, and the road information of the target scene can be determined by combining the fixed object of the target scene, so that the simulation model of the target scene is established, and a test environment is provided for the simulation test of the target vehicle.
In one embodiment, as shown in fig. 6, the determining the input signal and the output signal of the adaptive cruise algorithm according to the first simulation model of the target vehicle, the simulation scene library and the preset cruise speed comprises the following steps:
s601: and acquiring a state signal and a simulation scene signal of the target vehicle according to the first simulation model and the simulation scene library of the target vehicle.
The state signal of the target vehicle comprises the current vehicle speed, the longitudinal acceleration, the vehicle yaw angle, the engine rotation speed, the engine torque, the transmission output shaft rotation speed and the like; the simulation scene signal comprises whether the traffic vehicle of the current lane is effective, the acceleration of the vehicle nearest to the current lane, the speed of the vehicle nearest to the current lane and the distance between the vehicle nearest to the current lane and the target vehicle.
S602: and taking the state signal of the target vehicle, the simulation scene signal and the preset cruising speed as input signals of the self-adaptive cruising algorithm.
S603: an output signal of the adaptive cruise algorithm is obtained from an input signal of the adaptive cruise algorithm.
Wherein the output signal of the adaptive cruise algorithm is the desired acceleration of the target vehicle.
In this embodiment, the state signal and the simulation scene signal of the target vehicle are acquired through the first simulation model and the simulation scene library of the target vehicle, and the state signal, the simulation scene signal and the preset cruise speed of the target vehicle are used as the input signals of the adaptive cruise algorithm, so that the output signal of the adaptive cruise algorithm, that is, the expected acceleration of the target vehicle is obtained, the behavior of the target vehicle can be controlled, and the model closed loop of the simulation test is completed.
In an embodiment, as shown in fig. 7, the performing of the simulation test of the target vehicle according to the second simulation model of the target vehicle and the simulation scenario library includes the following steps:
s701: and acquiring first data of the target vehicle and second data of the target sensor according to the second simulation model and the simulation scene library.
The first data of the target vehicle are real-time change data of the state of the target vehicle, and comprise the current vehicle speed, the current vehicle acceleration, the vehicle speed adjustment time caused by scene change and the like; the second data of the target sensor is real-time change data of the sensor, including the relative front distance of the target vehicle and the like.
S702: and acquiring a first cruising speed of the target vehicle according to the first data of the target vehicle and the second data of the target sensor.
And taking the current vehicle speed in the real-time change data of the state of the target vehicle as the first cruising vehicle speed.
S703: and if the first cruising speed does not reach the preset cruising speed, returning to and continuously executing the step of acquiring the first data of the target vehicle and the second data of the target sensor.
And if the first cruise speed does not reach the preset cruise speed, the self-adaptive cruise algorithm does not reach the expected function, and returning to continue to execute the test.
S704: and if the first cruising speed reaches the preset cruising speed, judging that the simulation test is finished.
And if the first cruise speed does not reach the preset cruise speed, the adaptive cruise algorithm achieves the expected function, and the test is finished.
In the embodiment, the first data of the target vehicle and the second data of the target sensor are acquired through the second simulation model and the simulation scene library, the first cruising speed of the target vehicle is further acquired, the first cruising speed is compared with the preset cruising speed, whether the self-adaptive cruising algorithm achieves the expected function or not can be judged, and the self-adaptive cruising function of the tractor can be efficiently and conveniently tested.
In one embodiment, the vehicle simulation testing method further includes: and calculating the speed adjustment time and the inter-vehicle time distance of the target vehicle according to the first data of the target vehicle and the second data of the target sensor.
Wherein the time interval tau of the workshop passes through the current speed v 0 Distance d from target vehicle to front vehicle x And calculating to obtain the following formula: τ = d x /V 0 . And when the vehicle speed adjusting time and the workshop time interval reach set values, judging that the adaptive cruise algorithm reaches the target effect. The set value refers to a value that can be reached at the beginning of the design of the tested algorithm, for example: one algorithm is: when the speed of the vehicle is reduced by 20km/h in front, the vehicle speed adjusting time can be less than 10s, and the finally adjusted vehicle-to-vehicle time interval is 3s. When evaluating the algorithm, the obtained actual vehicle speed adjusting time needs to be compared with 10s, and the actual vehicle-to-vehicle time interval needs to be compared with 3s.
In the embodiment, whether the self-adaptive cruise algorithm achieves the target effect or not can be evaluated by calculating the speed adjusting time and the workshop time distance of the target vehicle, the testing efficiency of the self-adaptive cruise algorithm is improved, and the self-adaptive cruise function of the tractor can be efficiently and conveniently tested.
In another embodiment, as shown in fig. 8, a vehicle simulation testing method is provided, for example, when the method is applied to TruckMaker software and a Simulink simulation tool, the method includes the following steps:
(1) Establishing a vehicle dynamic simulation model of the tractor: and (3) establishing simulation models of all parts of the tractor through TruckMaker software and a Simulink tool, wherein the tractor vehicle dynamic model comprises a vehicle body model, a trailer model, a suspension model, a tire model, a steering model and a braking model.
(2) Configuring a sensor for the simulated vehicle, setting sensor parameters: designing a first sensor for a simulated vehicle in TruckMaker software, named as Radar _ Path, selecting a current lane as a detection range, and setting a detection distance and a detection angle of the sensor; designing a second sensor for the simulated vehicle in TruckMaker software, named as Radar _ All, selecting All lanes as detection ranges, and setting the detection distance and the detection angle of the sensor; assembling the sensors Radar _ Path and Radar _ All on the simulated vehicle, and setting the assembling positions of the sensors on the simulated vehicle.
(3) Setting a preset state and a running process of a simulation vehicle: setting the initial speed, the initial position and the initial gear of the simulated vehicle through TruckMaker software; adding a simulated vehicle running process, and setting a cruising speed v in specific running process parameters t As one of the inputs to the adaptive cruise algorithm during the test.
(4) A simulation scene library for testing is set up in TruckMaker software: establishing static content of a simulation scene for testing in TruckMaker software; and designing the behavior of the traffic vehicle, and constructing dynamic traffic flow content for the simulation scene.
(5) Embedding a self-adaptive cruise algorithm model, compiling an interface for the algorithm model according to test requirements, and realizing model closed loop of simulation test, wherein the model closed loop comprises the following steps: establishing communication between TruckMaker software and a Simulink tool, and loading an adaptive cruise algorithm model into the Simulink tool; providing an input signal for adaptive algorithm model testing: loading a 'writing' module interface in a model library provided by TruckMaker software into a Simulink tool, designing and writing a 'writing' module interface of the TruckMaker software in the Simulink tool, and providing partial input and output signals for an adaptive cruise algorithm; the input signals provided by the TruckMaker software for the algorithm comprise a simulated vehicle real-time state signal, a simulated scene related signal and a cruise speed set value; the cruise speed set value signal is determined by the cruise speed v set in the step (3) t Providing; according to the test requirement, a user-defined Signal built module is designed in a Simulink tool to provide an input Signal for an algorithm, namely a self-adaptive cruise algorithm interval gear set value Signal; receiving an output signal provided by an adaptive algorithm model: loading a 'read' module interface in a model library provided by TruckMaker software into a Simulink tool, and designing and writing a 'read' module interface of the TruckMaker software in the Simulink tool; the TruckMaker software receives the output signal provided by the algorithm as simulating the desired acceleration of the vehicle.
(6) And (3) controlling the behavior of the simulated vehicle through the calculation of the vehicle dynamics model in the step (1) to complete the model closed loop of the simulation test.
(7) And (3) testing and verifying the expected function of the adaptive cruise algorithm: and (4) operating the simulation closed-loop model in the step (6) in the simulation scene set up in the step (4), and acquiring and recording real-time change data of the state of the simulated vehicle and real-time change data of the sensor through TruckMaker software. Wherein the real-time data of the simulated vehicle state comprises the current vehicle speed v 0 Current vehicle acceleration a 0 Vehicle speed adjustment time t caused by scene change s (ii) a The real-time sensor change data is provided by Radar _ Path in the step (2), and comprises the distance d between the simulated vehicle and the front vehicle x (ii) a The workshop time distance tau is obtained by indirectly calculating the current speed and the relative front distance of the simulated vehicle, and the calculation formula is as follows: τ = dx/v 0 . Drawing images of simulation data under the same time coordinate system, and recording vehicle speed adjusting time t s Time lag τ between plants min (ii) a Comparing and analyzing the values of the two with the set values of the two in the expected function of the adaptive cruise algorithm; recording the adjusted cruising speed v 0 V. vehicle speed v 0 And the set cruising vehicle speed v in the step (3) t Carrying out comparative analysis to evaluate whether the algorithm achieves the expected function; and (5) after the adaptive cruise algorithm is updated, repeating the step (6) until the adaptive cruise algorithm reaches the expected functional standard, ending the test verification, and completing the full process of the in-loop simulation test of the model of the tractor adaptive cruise algorithm.
In the embodiment, the tractor adaptive cruise model in-loop test method based on TruckMaker software, the Simulink tool and a simulation scene can perform efficient simulation test, the time for finding the adaptive cruise algorithm problem is advanced, and the problems of high test cost, long test period and low test efficiency of the existing test method are solved. In addition, aiming at the problem of testing the coverage, the method can provide a large number of virtual scenes for simulation test, and because the test process has no danger coefficient, the method can also construct an extreme working condition scene which cannot be completed by the real vehicle test, thereby greatly improving the coverage of the test. Aiming at the problem that the same traffic scene cannot be reproduced, the method can accurately control variables in the scene, carry out real-time monitoring and playback on simulation data, effectively analyze test results and locate algorithm problems.
It should be understood that, although the steps in the flowcharts related to the embodiments are shown in sequence as indicated by the arrows, the steps are not necessarily executed in sequence as indicated by the arrows. The steps are not limited to being performed in the exact order illustrated and, unless explicitly stated herein, may be performed in other orders. Moreover, at least a part of the steps in the flowcharts related to the above embodiments may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a part of the steps or stages in other steps.
Based on the same inventive concept, the embodiment of the application also provides a vehicle simulation test device for realizing the vehicle simulation test method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the method, so that specific limitations in one or more embodiments of the vehicle simulation testing device provided below can be referred to the limitations of the vehicle simulation testing method in the above, and details are not repeated herein.
In one embodiment, as shown in fig. 9, there is provided a vehicle simulation test apparatus including: a first model obtaining module 10, a simulation scenario establishing module 20, a target signal determining module 30, a second model establishing module 40 and a simulation testing module 50, wherein:
a first model obtaining module 10, configured to obtain a first simulation model of a target vehicle;
a simulation scene establishing module 20, configured to establish a simulation scene library;
the target signal determining module 30 is configured to determine an input signal and an output signal of an adaptive cruise algorithm according to a first simulation model of a target vehicle, a simulation scene library, and a preset cruise speed;
a second model building module 40 for building a second simulation model of the target vehicle based on the input signals and the output signals of the adaptive cruise algorithm;
and the simulation testing module 50 is configured to perform a simulation test on the target vehicle according to the second simulation model of the target vehicle and the simulation scenario library.
In one embodiment, the first model obtaining module includes: the device comprises a simulation model establishing unit, a sensor adding unit, a driving state determining unit and a first model acquiring unit, wherein:
the simulation model establishing unit is used for establishing a dynamic simulation model of the target vehicle;
a sensor addition unit for adding a target sensor;
the driving state determining unit is used for determining the preset state and the driving process of the target vehicle according to the dynamic simulation model and the target sensor;
and the first model acquisition unit is used for acquiring a first simulation model of the target vehicle according to the dynamic simulation model, the target sensor and the preset state and the running process of the target vehicle.
In one embodiment, the simulation scenario setup module includes: the device comprises a road information acquisition unit, a vehicle information acquisition unit, a driving route determination unit, a simulation model acquisition unit and a simulation scene library establishment unit, wherein:
the road information acquisition unit is used for acquiring road information of a target scene;
the vehicle information acquisition unit is used for acquiring the traffic vehicle information in the target scene;
the driving route determining unit is used for determining a target vehicle and a pre-driving route corresponding to the traffic vehicle information according to the road information of the target scene;
the simulation model obtaining unit is used for obtaining a simulation model of the target scene according to road information of the target scene, the target vehicle and a pre-driving route corresponding to the traffic vehicle information;
and the simulation scene library establishing unit is used for establishing the simulation scene library according to the simulation models of the plurality of target scenes.
In one embodiment, the road information acquiring unit includes: a road sign acquisition subunit, a road parameter determination subunit, a fixed object determination subunit, and a road information determination subunit, wherein:
the road sign acquisition subunit is used for acquiring the road type and the road sign of the target scene;
the road parameter determining subunit is used for determining preset road parameters of the target scene according to the road type;
the fixed object determining subunit is used for acquiring a fixed object of the target scene according to the road sign;
and the road information determining subunit is used for determining the road information of the target scene according to the preset road parameters and the fixed object.
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:
the vehicle signal acquisition unit is used for acquiring a state signal and a simulation scene signal of the target vehicle according to the first simulation model of the target vehicle and the simulation scene library;
the system comprises an input signal determining unit, a cruise control unit and a cruise control unit, wherein the input signal determining unit is used for taking a state signal, a simulation scene signal and a preset cruise speed of a target vehicle as input signals of an adaptive cruise algorithm;
an output signal determination unit for obtaining an output signal of the adaptive cruise algorithm from an input signal of the adaptive cruise algorithm.
In one embodiment, the simulation testing module includes: data acquisition unit, speed of a motor vehicle acquisition unit and speed of a motor vehicle judgment module, wherein:
the data acquisition unit is used for acquiring first data of the target vehicle and second data of the target sensor according to the second simulation model and the simulation scene library;
the vehicle speed acquisition unit is used for acquiring a first cruising vehicle speed of the target vehicle according to the first data of the target vehicle and the second data of the target sensor;
the vehicle speed judging module is used for returning to continuously execute the steps of acquiring the first data of the target vehicle and the second data of the target sensor when the first cruising vehicle speed does not reach the preset cruising vehicle speed; and when the first cruising speed reaches the preset cruising speed, judging that the simulation test is finished.
In one embodiment, the simulation test module is further configured to calculate a vehicle speed adjustment time and a vehicle-to-vehicle time interval of the target vehicle according to the first data of the target vehicle and the second data of the target sensor; the vehicle speed adjusting time and the workshop time interval are used for evaluating whether the adaptive cruise algorithm achieves the target effect.
The various modules in the vehicle simulation testing device can be wholly or partially realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent of a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 10. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and the computer program to run on the non-volatile storage medium. The communication interface of the computer device is used for communicating with an external terminal in a wired or wireless manner, and the wireless manner can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a vehicle simulation testing method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on a shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 10 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program: acquiring a first simulation model of a target vehicle; establishing a simulation scene library; determining an input signal and an output signal of an adaptive cruise algorithm according to a first simulation model of a target vehicle, a simulation scene library and a preset cruise speed; establishing a second simulation model of the target vehicle according to the input signal and the output signal of the adaptive cruise algorithm; and carrying out simulation test on the target vehicle according to the second simulation model of the target vehicle and the simulation scene library.
In one embodiment, the obtaining of the first simulation model of the target vehicle, as referred to when the processor executes the computer program, comprises the steps of: establishing a dynamic simulation model of a target vehicle; adding a target sensor; determining the preset state and the running process of the target vehicle according to the dynamic simulation model and the target sensor; and acquiring a first simulation model of the target vehicle according to the dynamic simulation model, the target sensor and the preset state and the running process of the target vehicle.
In one embodiment, the creating of the simulation scenario library, involved in the execution of the computer program by the processor, comprises the steps of: acquiring road information of a target scene; acquiring traffic vehicle information in a target scene; determining a target vehicle and a pre-driving route corresponding to the traffic vehicle information according to the road information of the target scene; acquiring a simulation model of the target scene according to the road information of the target scene, the target vehicle and the pre-driving route corresponding to the traffic vehicle information; and establishing a simulation scene library according to the simulation models of the plurality of target scenes.
In one embodiment, the processor, when executing the computer program, is involved in obtaining road information for a target scene, comprising the steps of: acquiring a road type and a road sign of a target scene; determining preset road parameters of a target scene according to the road type; acquiring a fixed object of a target scene according to the road sign; and determining road information of the target scene according to the preset road parameters and the fixed object.
In one embodiment, the processor, in executing the computer program, is configured to determine input signals and output signals for an adaptive cruise algorithm based on a first simulation model of a target vehicle, a library of simulation scenarios, and a preset cruise speed, comprising the steps of: acquiring a state signal and a simulation scene signal of the target vehicle according to the first simulation model of the target vehicle and the simulation scene library; taking a state signal, a simulation scene signal and a preset cruising speed of a target vehicle as input signals of an adaptive cruising algorithm; an output signal of the adaptive cruise algorithm is obtained from an input signal of the adaptive cruise algorithm.
In one embodiment, the processor, when executing the computer program, is involved in performing a simulation test of the target vehicle based on the second simulation model of the target vehicle and the simulation scenario library, and comprises the following steps: acquiring first data of a target vehicle and second data of a target sensor according to a second simulation model and a simulation scene library; acquiring a first cruising speed of the target vehicle according to 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 continuously executing the step of acquiring the first data of the target vehicle and the second data of the target sensor; and if the first cruising speed reaches the preset cruising speed, judging that the simulation test is finished.
In one embodiment, the processor, when executing the computer program, further performs the steps of: calculating the speed adjustment time and the inter-vehicle time distance of the target vehicle according to the first data of the target vehicle and the second data of the target sensor; the vehicle speed adjusting time and the workshop time interval are used for evaluating whether the adaptive cruise algorithm achieves the target effect.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of: acquiring a first simulation model of a target vehicle; establishing a simulation scene library; determining an input signal and an output signal of an adaptive cruise algorithm according to a first simulation model of a target vehicle, a simulation scene library and a preset cruise speed; establishing a second simulation model of the target vehicle according to the input signal and the output signal of the adaptive cruise algorithm; and carrying out simulation test on the target vehicle according to the second simulation model of the target vehicle and the simulation scene library.
In one embodiment, the computer program, when executed by the processor, involves obtaining a first simulation model of the target vehicle, comprising the steps of: establishing a dynamic simulation model of a target vehicle; adding a target sensor; determining the preset state and the running process of the target vehicle according to the dynamic simulation model and the target sensor; and acquiring a first simulation model of the target vehicle according to the dynamic simulation model, the target sensor and the preset state and the running process of the target vehicle.
In one embodiment, the computer program, when executed by the processor, involves building a library of simulation scenarios, comprising the steps of: acquiring road information of a target scene; acquiring traffic vehicle information in a target scene; determining a target vehicle and a pre-driving route corresponding to the traffic vehicle information according to the road information of the target scene; acquiring a simulation model of the target scene according to the road information of the target scene, the target vehicle and the pre-driving route corresponding to the traffic vehicle information; and establishing a simulation scene library according to the simulation models of the plurality of target scenes.
In one embodiment, the computer program, when executed by a processor, is directed to obtaining road information for a target scene, comprising the steps of: acquiring a road type and a road sign of a target scene; determining preset road parameters of a target scene according to the road type; acquiring a fixed object of a target scene according to a road sign; and determining road information of the target scene according to the preset road parameters and the fixed object.
In one embodiment, the computer program, when executed by the processor, is directed to determining input signals and output signals for an adaptive cruise algorithm based on a first simulation model of a target vehicle, a library of simulation scenarios, and a preset cruise speed, comprising the steps of: acquiring a state signal and a simulation scene signal of the target vehicle according to the first simulation model of the target vehicle and the simulation scene library; taking a state signal, a simulation scene signal and a preset cruising speed of a target vehicle as input signals of an adaptive cruising algorithm; an output signal of the adaptive cruise algorithm is obtained from an input signal of the adaptive cruise algorithm.
In one embodiment, the computer program, when executed by the processor, involves performing a simulation test of the target vehicle based on the second simulation model of the target vehicle and the library of simulation scenarios, comprising the steps of: acquiring first data of a target vehicle and second data of a target sensor according to a second simulation model and a simulation scene library; acquiring a first cruising speed of the target vehicle according to 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 continuously executing the step of acquiring the first data of the target vehicle and the second data of the target sensor; and if the first cruising speed reaches the preset cruising speed, judging that the simulation test is finished.
In one embodiment, the computer program when executed by the processor further performs the steps of: calculating the speed adjustment time and the workshop time distance of the target vehicle according to 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 time interval are used for evaluating whether the self-adaptive cruise algorithm achieves the target effect.
In one embodiment, a computer program product is provided, comprising a computer program which when executed by a processor performs the steps of: acquiring a first simulation model of a target vehicle; establishing a simulation scene library; determining an input signal and an output signal of an adaptive cruise algorithm according to a first simulation model, a simulation scene library and a preset cruise speed of a target vehicle; establishing a second simulation model of the target vehicle according to the input signal and the output signal of the adaptive cruise algorithm; and carrying out simulation test on the target vehicle according to the second simulation model of the target vehicle and the simulation scene library.
In one embodiment, the computer program, when executed by the processor, involves obtaining a first simulation model of a target vehicle, comprising the steps of: establishing a dynamic simulation model of the target vehicle; adding a target sensor; determining the preset state and the running process of the target vehicle according to the dynamic simulation model and the target sensor; and acquiring a first simulation model of the target vehicle according to the dynamic simulation model, the target sensor and the preset state and the running process of the target vehicle.
In one embodiment, the computer program, when executed by a processor, involves building a library of simulation scenarios, comprising the steps of: acquiring road information of a target scene; acquiring traffic vehicle information in a target scene; determining a target vehicle and a pre-driving route corresponding to the traffic vehicle information according to the road information of the target scene; acquiring a simulation model of the target scene according to road information of the target scene, the target vehicle and a pre-driving route corresponding to the traffic vehicle information; and establishing a simulation scene library according to the simulation models of the plurality of target scenes.
In one embodiment, the computer program, when executed by a processor, is directed to obtaining road information for a target scene, comprising the steps of: acquiring a road type and a road sign of a target scene; determining preset road parameters of a target scene according to the road type; acquiring a fixed object of a target scene according to a road sign; and determining road information of the target scene according to the preset road parameters and the fixed object.
In one embodiment, the computer program, when executed by the processor, is directed to determining input signals and output signals for an adaptive cruise algorithm based on a first simulation model of a target vehicle, a library of simulation scenarios, and a preset cruise speed, comprising the steps of: acquiring a state signal and a simulation scene signal of the target vehicle according to the first simulation model of the target vehicle and the simulation scene library; taking a state signal, a simulation scene signal and a preset cruising speed of a target vehicle as input signals of an adaptive cruising algorithm; an output signal of the adaptive cruise algorithm is obtained from an input signal of the adaptive cruise algorithm.
In one embodiment, the computer program, when executed by the processor, is directed to performing a simulation test of a target vehicle based on a second simulation model of the target vehicle and a library of simulation scenarios, comprising the steps of: acquiring first data of a target vehicle and second data of a target sensor according to a second simulation model and a simulation scene library; acquiring a first cruising speed of the target vehicle according to 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 continuously executing the step of acquiring the first data of the target vehicle and the second data of the target sensor; and if the first cruising speed reaches the preset cruising speed, judging that the simulation test is finished.
In one embodiment, the computer program when executed by the processor further performs the steps of: calculating the speed adjustment time and the workshop time distance of the target vehicle according to the first data of the target vehicle and the second data of the target sensor; and the vehicle speed adjusting time and the vehicle-to-vehicle time interval are used for evaluating whether the self-adaptive cruise algorithm achieves the target effect.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, databases, or other media used in the embodiments provided herein can include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high-density embedded nonvolatile Memory, resistive Random Access Memory (ReRAM), magnetic Random Access Memory (MRAM), ferroelectric Random Access Memory (FRAM), phase Change Memory (PCM), graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. 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), for example. The databases referred to in various embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing based data processing logic devices, etc., without limitation.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, and these are all within the scope of protection of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.
Claims (11)
1. A vehicle simulation testing method, the method comprising:
acquiring a first simulation model of a target vehicle;
establishing a simulation scene library;
determining an input signal and an output signal of an adaptive cruise algorithm according to the first simulation model of the target vehicle, the simulation scene library and a preset cruise speed;
establishing a second simulation model of the target vehicle according to the input signal and the output signal of the adaptive cruise algorithm;
and carrying out simulation test on the target vehicle according to the second simulation model of the target vehicle and the simulation scene library.
2. The method of claim 1, wherein said obtaining a first simulation model of a target vehicle comprises:
establishing a dynamic simulation model of a target vehicle;
adding a target sensor;
determining a preset state and a running process of the target vehicle according to the dynamic simulation model and the target sensor;
and acquiring a first simulation model of the target vehicle according to the dynamic simulation model, the target sensor and the preset state and the running process of the target vehicle.
3. The method of claim 1, wherein the creating a library of simulation scenarios comprises:
acquiring road information of a target scene;
acquiring traffic vehicle information in the target scene;
determining the target vehicle and a pre-driving route corresponding to the traffic vehicle information according to the road information of the target scene;
acquiring a simulation model of the target scene according to the road information of the target scene, the target vehicle and a pre-driving route corresponding to the traffic vehicle information;
and establishing a simulation scene library according to the simulation models of the plurality of target scenes.
4. The method of claim 3, wherein the obtaining road information of the target scene comprises:
acquiring a road type and a road sign of a target scene;
determining preset road parameters of the target scene according to the road type;
acquiring a fixed object of the target scene according to the road sign;
and determining the road information of the target scene according to the preset road parameters and the fixed object.
5. The method of claim 1, wherein determining input signals and output signals for an adaptive cruise algorithm based on the first simulation model of the target vehicle, the library of simulation scenarios, and a preset cruise speed comprises:
acquiring a state signal and a simulation scene signal of the target vehicle according to the first simulation model of the target vehicle and the simulation scene library;
taking the state signal, the simulation scene signal and the preset cruising speed of the target vehicle as input signals of the self-adaptive cruising algorithm;
and acquiring an output signal of the adaptive cruise algorithm according to the input signal of the adaptive cruise algorithm.
6. The method of any one of claims 1 to 5, wherein said performing a simulation test of the target vehicle according to the second simulation model of the target vehicle and the simulation scenario library comprises:
acquiring first data of the target vehicle and second data of the target sensor according to the second simulation model and the simulation scene library;
acquiring a first cruising speed of the target vehicle according to 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 continuously executing the step of acquiring the first data of the target vehicle and the second data of the target sensor;
and if the first cruising speed reaches the preset cruising speed, judging that the simulation test is finished.
7. The method of claim 6, further comprising:
calculating the speed adjustment time and the workshop time distance of the target vehicle according to the first data of the target vehicle and the second data of the target sensor; and the vehicle speed adjusting time and the vehicle-to-vehicle time interval are used for evaluating whether the self-adaptive cruise algorithm achieves the target effect.
8. A vehicle simulation test apparatus, characterized in that the apparatus comprises:
the first model acquisition module is used for acquiring a first simulation model of the target vehicle;
the simulation scene establishing module is used for establishing a simulation scene library;
the target signal determining module is used for determining an input signal and an output signal of an adaptive cruise algorithm according to a first simulation model of the target vehicle, the simulation scene library and a preset cruise speed;
the second model building module is used for building a second simulation model of the target vehicle according to the input signal and the output signal of the adaptive cruise algorithm;
and the simulation testing module is used for carrying out simulation testing on the target vehicle according to the second simulation model of the target vehicle and the simulation scene library.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
11. A computer program product comprising a computer program, characterized in that the computer program realizes the steps of the method of any one of claims 1 to 7 when executed by a processor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210973677.8A CN115470616A (en) | 2022-08-15 | 2022-08-15 | Vehicle simulation test method, apparatus, computer device, medium, and program product |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210973677.8A CN115470616A (en) | 2022-08-15 | 2022-08-15 | Vehicle simulation test method, apparatus, computer device, medium, and program product |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115470616A true CN115470616A (en) | 2022-12-13 |
Family
ID=84366427
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210973677.8A Pending CN115470616A (en) | 2022-08-15 | 2022-08-15 | Vehicle simulation test method, apparatus, computer device, medium, and program product |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115470616A (en) |
-
2022
- 2022-08-15 CN CN202210973677.8A patent/CN115470616A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111797526B (en) | Simulation test scene construction method and device | |
| CN113515463B (en) | Automatic testing method and device, computer equipment and storage medium | |
| CN112286206B (en) | Automatic driving simulation method, system, equipment, readable storage medium and platform | |
| CN109060370B (en) | Method and device for vehicle testing of automatically driven vehicle | |
| US20200356849A1 (en) | Automated training data extraction method for dynamic models for autonomous driving vehicles | |
| CN113484851B (en) | Simulation test system and method for vehicle-mounted laser radar and complete vehicle in-loop test system | |
| CN113777952A (en) | Automatic driving simulation test method for interactive mapping of real vehicle and virtual vehicle | |
| CN115524675A (en) | Vehicle-mounted radar performance analysis method and device and computer equipment | |
| KR20230159308A (en) | Method, system and computer program product for calibrating and validating an advanced driver assistance system (adas) and/or an automated driving system (ads) | |
| CN115185205A (en) | Intelligent driving simulation method, system, terminal device and readable storage medium | |
| CN116167237A (en) | Driving scene simulation method and device, electronic equipment and storage medium | |
| CN114638103A (en) | Automatic driving joint simulation method and device, computer equipment and storage medium | |
| CN110647053A (en) | Automatic driving simulation method and system | |
| CN115981284A (en) | Vehicle simulation test method, apparatus, computer device, medium, and program product | |
| CN115470616A (en) | Vehicle simulation test method, apparatus, computer device, medium, and program product | |
| CN117131589A (en) | Simulation test method and device for intelligent network-connected vehicle cooperative algorithm | |
| CN114782926B (en) | Driving scene recognition method, device, equipment, storage medium and program product | |
| CN115782921A (en) | Environment sensing method and device for automatic driving and electronic equipment | |
| CN115391980A (en) | Road scene and dynamic traffic flow optimization method, system and storage medium | |
| CN115469635A (en) | Verification method, device and equipment for safety of automatic driving simulation test function | |
| US20220153283A1 (en) | Enhanced component dimensioning | |
| Duprey et al. | Simulation of the performance based standards (PBS) low-speed 90 turn test in TruckSim by jumping back in time | |
| CN116644585B (en) | Dangerous state scene data generation method and device based on target vehicle danger degree | |
| CN116300532A (en) | Method and device for vehicle in-loop simulation test, computer equipment and storage medium | |
| Cheng et al. | An Indoor Rapid Testing Platform for Autonomous Vehicles Using Vehicle-in-the-Loop Simulation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |