CN113865883A - Intelligent driving and ADAS test simulation method and system based on test vehicle state acquisition - Google Patents
Intelligent driving and ADAS test simulation method and system based on test vehicle state acquisition Download PDFInfo
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- CN113865883A CN113865883A CN202111043202.0A CN202111043202A CN113865883A CN 113865883 A CN113865883 A CN 113865883A CN 202111043202 A CN202111043202 A CN 202111043202A CN 113865883 A CN113865883 A CN 113865883A
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Abstract
The invention discloses an intelligent driving and ADAS test simulation method based on test vehicle state acquisition, which comprises the following steps: the vehicle environment state data are sent to the test vehicle intelligent driving and ADAS and the data center; the test vehicle motion state data is fed back to the test vehicle intelligent driving and ADAS and the data center; controlling the open circuit of each sensor corresponding to the recharging data of the test vehicle, and recharging the recharging data stored in the data center to the intelligent driving and ADAS of the test vehicle according to the one-to-one corresponding transmission mode and interface; the intelligent driving and ADAS of the test vehicle make decisions based on the recharge data. The invention also discloses an intelligent driving and ADAS test simulation system based on the test vehicle state acquisition. The invention can reproduce all and/or part of test scenes through data recharging and can restore the test process and working conditions when problems occur, thereby supporting the realization of more targeted reproduction and positioning problems in the test environment and being capable of developing and optimizing the algorithm more specifically and accurately.
Description
Technical Field
The invention relates to the field of automobiles, in particular to an intelligent driving and ADAS test simulation method based on test vehicle state acquisition and an intelligent driving and ADAS test simulation system based on test vehicle state acquisition.
Background
The data recharging technology based on data acquisition is widely applied to industries such as aerospace and the like which have high safety requirements or have high testing difficulty, automobiles have extremely high requirements on safety performance and are often accompanied with high-speed testing with high difficulty, and therefore the data recharging technology is necessary to be applied to the automobile industry.
With the continuous iterative development of intelligent driving and ADAS systems, the functions of each device are continuously increased and optimized, the cross-linking relationship among the systems is also increasingly complex, and the difficulty of system testing and troubleshooting is also continuously increased. At present, the test is carried out by placing a test vehicle on an actual road, recording vehicle driving data when the vehicle is driven on the road, analyzing the recorded data after the test is finished, and when a problem or a fault is found, the root cause of the problem is difficult to find out from the analysis of single group of recorded data. No mature system which can be used for state data acquisition in a finished automobile test environment and playback in a rack test process exists on the market, and only a similar scene can be established to perform comparative analysis on the problem data, so that the problem is solved.
Therefore, a data recharging method is needed to build a test simulation system, so that test data can be more completely reserved, and scene reproduction becomes possible.
Disclosure of Invention
In this summary, a series of simplified form concepts are introduced that are simplifications of the prior art in this field, which will be described in further detail in the detailed description. This summary of the invention is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.
The invention aims to solve the technical problem of providing an intelligent driving and ADAS test simulation method which is based on test vehicle state acquisition and can reproduce all and/or part of test scenes through data recharging.
And the intelligent driving and ADAS test simulation system can reproduce all and/or part of test scenes through data recharging based on test vehicle state acquisition.
In order to solve the technical problems, the invention provides an intelligent driving and ADAS test simulation method based on test vehicle state acquisition, which comprises the following steps:
s1, the test vehicle environment sensing system collects vehicle environment state data of a real test scene and sends the vehicle environment state data to the test vehicle intelligent driving and ADAS and the data center;
s2, the test vehicle decision system makes a decision according to the vehicle environment state data, sends a decision result to the test vehicle for execution, and feeds back the test vehicle motion state data to the test vehicle intelligent driving and ADAS and the data center;
s3, controlling the open circuit of each sensor corresponding to the recharge data of the test vehicle, and recharging the recharge data stored in the data center to the intelligent driving and ADAS of the test vehicle according to the one-to-one corresponding transmission mode and interface; it should be noted that the recharge data is selected according to actual test requirements;
and S4, testing intelligent driving of the vehicle and making a decision by the ADAS based on the recharge data.
Optionally, the intelligent driving and ADAS test simulation method based on test vehicle state acquisition is further improved, and the vehicle environment state data is digital environment data acquired by a vehicle-mounted sensor during the running process of the test vehicle;
the vehicle motion state data is the running state data of the test vehicle under the current scene working condition acquired by the vehicle-mounted sensor.
Optionally, the intelligent driving and ADAS test simulation method based on test vehicle state acquisition is further improved, and vehicle environment state data includes lane information, a front static object state, a front dynamic object state and a traffic sign in the vehicle driving process;
the vehicle motion state data comprises vehicle speed, acceleration, yaw rate, steering wheel angle, lateral acceleration and GPS information under the current scene working condition of the vehicle.
It should be noted that the vehicle environmental status data and the vehicle motion status data are exemplary, and the corresponding parameters may be selected according to the test requirements in the actual test.
Optionally, the method for simulating intelligent driving and ADAS test based on test vehicle state acquisition is further improved, and the method further includes:
and the vehicle environment state data and the vehicle motion state data are sent to a data center after high fidelity processing.
Optionally, the method for simulating intelligent driving and ADAS test based on test vehicle state acquisition is further improved, and the method further includes:
and the vehicle environment state data and the vehicle motion state data are subjected to manual time synchronization and then stored in groups.
For example, the above grouping may be according to data of different sensors. Due to the fact that the transmission mode and the data encryption storage mode of each sensor are different, the grouped storage is more beneficial to modularized storage, the data can be selected more conveniently for recharging, and different sensor data can be arranged and combined to generate new scene recharging data.
In order to solve the above technical problems, the present invention provides an intelligent driving and ADAS test simulation system based on test vehicle status acquisition, comprising:
the lower computer receives the vehicle motion state data of the test vehicle actuating mechanism and the vehicle environment state data of the real test scene collected by the test vehicle environment sensing system and sends the vehicle motion state data to the upper computer;
controlling the open circuit of each sensor corresponding to the recharging data of the test vehicle according to the instruction of the upper computer, and recharging the recharging data sent by the upper computer to the intelligent driving and ADAS of the test vehicle according to the one-to-one corresponding transmission mode and interface;
and the upper computer collects and manages the vehicle motion state data and the vehicle environment state data to form recharge data and sends the recharge data to the lower computer.
Optionally, the intelligent driving and ADAS test simulation system based on test vehicle state acquisition is further improved, and the vehicle environment state data is digital environment data acquired by a vehicle-mounted sensor during the running process of the test vehicle;
the vehicle motion state data is the running state data of the test vehicle under the current scene working condition acquired by the vehicle-mounted sensor.
Optionally, the intelligent driving and ADAS test simulation system based on test vehicle state acquisition is further improved, and vehicle environment state data includes lane information, a front static object state, a front dynamic object state and a traffic sign in the vehicle driving process;
the vehicle motion state data comprises vehicle speed, acceleration, yaw rate, steering wheel angle, lateral acceleration and GPS information under the current scene working condition of the vehicle.
Optionally, the intelligent driving and ADAS test simulation system based on test vehicle state acquisition is further improved, and the lower computer sends vehicle environment state data and vehicle motion state data to the upper computer after high-fidelity processing.
Optionally, the intelligent driving and ADAS test simulation system based on test vehicle state acquisition is further improved, and vehicle environment state data and vehicle motion state data of the lower computer are synchronized through manual time calibration and then are grouped and sent to the upper computer.
According to the invention, through complete acquisition of real test scene data, test vehicle self-vehicle parameters and motion state information, timestamp calibration and grouping are carried out on the data, and then the data are simultaneously back-filled to the test vehicle through different modes, so that the test vehicle can repeat the same test for multiple times, the test accuracy can be improved, and the decision stability of the test vehicle is ensured. The method can restore the test process and working condition when the problem occurs, thereby supporting the realization of more targeted reproduction and positioning in the test environment and being capable of developing and optimizing the algorithm more targeted and more accurate. Through the test of multiple groups of control variables, the encountered faults can be more clearly maintained, so that the data analysis after the test is more scientific and reasonable and has more basis.
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The accompanying drawings, which are included to provide a further understanding of the invention, are incorporated in and constitute a part of this specification. The drawings are not necessarily to scale, however, and may not be intended to accurately reflect the precise structural or performance characteristics of any given embodiment, and should not be construed as limiting or restricting the scope of values or properties encompassed by exemplary embodiments in accordance with the invention. The invention will be described in further detail with reference to the following detailed description and accompanying drawings:
FIG. 1 is a schematic diagram of the principle of the simulation method for intelligent driving and ADAS testing according to the present invention.
Fig. 2 is a schematic view of the working principle of the upper computer and the lower computer of the invention.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and technical effects of the present invention will be fully apparent to those skilled in the art from the disclosure in the specification. The invention is capable of other embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the general spirit of the invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict. The following exemplary embodiments of the present invention may be embodied in many different forms and should not be construed as limited to the specific embodiments set forth herein. It is to be understood that these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the technical solutions of these exemplary embodiments to those skilled in the art.
A first embodiment;
the invention provides an intelligent driving and ADAS test simulation method based on test vehicle state acquisition, which comprises the following steps:
s1, the test vehicle environment sensing system collects vehicle environment state data of a real test scene and sends the vehicle environment state data to the test vehicle intelligent driving and ADAS and the data center;
s2, the test vehicle decision system makes a decision according to the vehicle environment state data, sends a decision result to the test vehicle for execution, and feeds back the test vehicle motion state data to the test vehicle intelligent driving and ADAS and the data center;
s3, controlling the open circuit of each sensor corresponding to the recharge data of the test vehicle, and recharging the recharge data stored in the data center to the intelligent driving and ADAS of the test vehicle according to the one-to-one corresponding transmission mode and interface;
and S4, testing intelligent driving of the vehicle and making a decision by the ADAS based on the recharge data.
A second embodiment;
referring to fig. 1, the present invention provides an intelligent driving and ADAS test simulation method based on test vehicle state acquisition, including the following steps:
s1, the test vehicle environment sensing system collects vehicle environment state data of a real test scene, and the vehicle environment state data are sent to the test vehicle intelligent driving and ADAS and the data center after high fidelity processing;
the vehicle environment state data is digital environment data acquired by a vehicle-mounted sensor in the running process of a test vehicle, and comprises lane information, a front static object state, a front dynamic object state and a traffic sign in the running process of the vehicle;
s2, the test vehicle decision system makes a decision according to the vehicle environment state data, sends a decision result to the test vehicle for execution, and feeds back the motion state data of the test vehicle to the test vehicle intelligent driving and ADAS and the data center after high-fidelity processing;
the vehicle motion state data is the running state data of the test vehicle under the current scene working condition, which is acquired by a vehicle-mounted sensor, and comprises the vehicle speed, the acceleration, the yaw velocity, the steering wheel angle, the lateral acceleration and the GPS information under the current scene working condition of the vehicle;
s3, controlling the open circuit of each sensor corresponding to the recharge data of the test vehicle, and recharging the recharge data stored in the data center to the intelligent driving and ADAS of the test vehicle according to the one-to-one corresponding transmission mode and interface;
and S4, testing intelligent driving of the vehicle and making a decision by the ADAS based on the recharge data.
A third embodiment;
the invention provides an intelligent driving and ADAS test simulation system based on test vehicle state acquisition, which comprises:
the lower computer receives the vehicle motion state data of the test vehicle actuating mechanism and the vehicle environment state data of the real test scene collected by the test vehicle environment sensing system and sends the vehicle motion state data to the upper computer;
controlling the open circuit of each sensor corresponding to the recharging data of the test vehicle according to the instruction of the upper computer, and recharging the recharging data sent by the upper computer to the intelligent driving and ADAS of the test vehicle according to the one-to-one corresponding transmission mode and interface;
and the upper computer collects and manages the vehicle motion state data and the vehicle environment state data to form recharge data and sends the recharge data to the lower computer.
A fourth embodiment;
referring to fig. 2, the present invention provides an intelligent driving and ADAS test simulation system based on test vehicle status collection, including:
the lower computer receives the vehicle motion state data of the test vehicle actuating mechanism and the vehicle environment state data of the real test scene collected by the test vehicle environment sensing system, performs high-fidelity processing on the vehicle motion state data, performs manual time calibration synchronization on the vehicle motion state data and the vehicle environment state data, and then sends the vehicle motion state data and the vehicle environment state data to the upper computer after grouping;
controlling the open circuit of each sensor corresponding to the recharging data of the test vehicle according to the instruction of the upper computer, and recharging the recharging data sent by the upper computer to the intelligent driving and ADAS of the test vehicle according to the one-to-one corresponding transmission mode and interface;
the vehicle environment state data is digital environment data acquired by a vehicle-mounted sensor in the running process of a test vehicle, and comprises the following steps: lane information, a front static object state, a front dynamic object state and a traffic sign in the driving process of the vehicle;
the vehicle motion state data is the running state data of the test vehicle under the current scene working condition acquired by the vehicle-mounted sensor, and comprises the following steps: the method comprises the following steps of (1) vehicle speed, acceleration, yaw angular velocity, steering wheel angle, lateral acceleration and GPS information under the current scene working condition of a vehicle;
and the upper computer collects and manages the vehicle motion state data and the vehicle environment state data to form recharge data and sends the recharge data to the lower computer.
And the vehicle environment state data and the vehicle motion state data of the lower computer are grouped and sent to the upper computer after being synchronized through manual time calibration.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The present invention has been described in detail with reference to the specific embodiments and examples, but these are not intended to limit the present invention. Many variations and modifications may be made by one of ordinary skill in the art without departing from the principles of the present invention, which should also be considered as within the scope of the present invention.
Claims (10)
1. An intelligent driving and ADAS test simulation method based on test vehicle state acquisition is characterized by comprising the following steps:
s1, the test vehicle environment sensing system collects vehicle environment state data of a real test scene and sends the vehicle environment state data to the test vehicle intelligent driving and ADAS and the data center;
s2, the test vehicle decision system makes a decision according to the vehicle environment state data, sends a decision result to the test vehicle for execution, and feeds back the test vehicle motion state data to the test vehicle intelligent driving and ADAS and the data center;
s3, controlling the open circuit of each sensor corresponding to the recharge data of the test vehicle, and recharging the recharge data stored in the data center to the intelligent driving and ADAS of the test vehicle according to the one-to-one corresponding transmission mode and interface;
and S4, testing intelligent driving of the vehicle and making a decision by the ADAS based on the recharge data.
2. The intelligent driving and ADAS test simulation method based on test vehicle state acquisition of claim 1, wherein:
the vehicle environment state data is digital environment data acquired by a vehicle-mounted sensor in the running process of a test vehicle;
the vehicle motion state data is the driving state data of the test vehicle under the current scene working condition collected by the vehicle-mounted sensor.
3. The intelligent driving and ADAS test simulation method based on test vehicle state acquisition of claim 2, wherein:
the vehicle environment state data comprises lane information, a front static object state, a front dynamic object state and a traffic sign in the driving process of the vehicle;
the vehicle motion state data comprises vehicle speed, acceleration, yaw rate, steering wheel angle, lateral acceleration and GPS information under the current scene working condition of the vehicle.
4. The intelligent driving and ADAS test simulation method based on test vehicle state acquisition of claim 1, further comprising:
and the vehicle environment state data and the vehicle motion state data are sent to a data center after high fidelity processing.
5. The intelligent driving and ADAS test simulation method based on test vehicle state acquisition of claim 4, further comprising:
and the vehicle environment state data and the vehicle motion state data are subjected to manual time calibration synchronization and then stored in groups.
6. The utility model provides an intelligence is driven and ADAS test analog system based on test vehicle state gathers which characterized in that includes:
the lower computer receives the vehicle motion state data of the test vehicle actuating mechanism and the vehicle environment state data of the real test scene collected by the test vehicle environment sensing system and sends the vehicle motion state data to the upper computer;
controlling the open circuit of each sensor corresponding to the recharging data of the test vehicle according to the instruction of the upper computer, and recharging the recharging data sent by the upper computer to the intelligent driving and ADAS of the test vehicle according to the one-to-one corresponding transmission mode and interface;
and the upper computer collects and manages the vehicle motion state data and the vehicle environment state data to form recharge data and sends the recharge data to the lower computer.
7. The intelligent driving and ADAS test simulation system based on test vehicle state acquisition of claim 6, wherein:
the vehicle environment state data is digital environment data acquired by a vehicle-mounted sensor in the running process of a test vehicle;
the vehicle motion state data is the running state data of the test vehicle under the current scene working condition acquired by the vehicle-mounted sensor.
8. The intelligent driving and ADAS test simulation system based on test vehicle state acquisition of claim 7, wherein:
the vehicle environment state data comprises lane information, a front static object state, a front dynamic object state and a traffic sign in the driving process of the vehicle;
the vehicle motion state data comprises vehicle speed, acceleration, yaw rate, steering wheel angle, lateral acceleration and GPS information under the current scene working condition of the vehicle.
9. The intelligent driving and ADAS test simulation system based on test vehicle state acquisition of claim 6, wherein:
and the lower computer sends the vehicle environment state data and the vehicle motion state data to the upper computer after high-fidelity processing.
10. The intelligent driving and ADAS test simulation system based on test vehicle state acquisition of claim 6, wherein:
and the vehicle environment state data and the vehicle motion state data of the lower computer are grouped and sent to the upper computer after being synchronized through manual time calibration.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114047361A (en) * | 2022-01-11 | 2022-02-15 | 深圳佑驾创新科技有限公司 | Calibration system of ADAS visual equipment |
| CN114488854A (en) * | 2022-01-26 | 2022-05-13 | 上海和夏新能源科技有限公司 | Intelligent driving and ADAS analog simulation method and system based on test data |
| CN114488855A (en) * | 2022-01-26 | 2022-05-13 | 上海和夏新能源科技有限公司 | Intelligent driving and ADAS simulation test method and system based on satellite positioning |
| CN116827938A (en) * | 2023-08-29 | 2023-09-29 | 中汽智联技术有限公司 | Data recharging method, system and storage medium |
-
2021
- 2021-09-07 CN CN202111043202.0A patent/CN113865883A/en not_active Withdrawn
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114047361A (en) * | 2022-01-11 | 2022-02-15 | 深圳佑驾创新科技有限公司 | Calibration system of ADAS visual equipment |
| CN114047361B (en) * | 2022-01-11 | 2022-04-05 | 深圳佑驾创新科技有限公司 | Calibration system of ADAS visual equipment |
| CN114488854A (en) * | 2022-01-26 | 2022-05-13 | 上海和夏新能源科技有限公司 | Intelligent driving and ADAS analog simulation method and system based on test data |
| CN114488855A (en) * | 2022-01-26 | 2022-05-13 | 上海和夏新能源科技有限公司 | Intelligent driving and ADAS simulation test method and system based on satellite positioning |
| CN114488855B (en) * | 2022-01-26 | 2024-03-26 | 上海和夏骏智科技有限公司 | Intelligent driving and ADAS simulation test method and system based on satellite positioning |
| CN116827938A (en) * | 2023-08-29 | 2023-09-29 | 中汽智联技术有限公司 | Data recharging method, system and storage medium |
| CN116827938B (en) * | 2023-08-29 | 2023-11-28 | 中汽智联技术有限公司 | Data recharging method, system and storage medium |
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