1. An automatic emergency braking system hardware-in-the-loop simulation test method is characterized by comprising the following steps:

step one, executing a test process, acquiring test data in real time, and recording the test data;

the acquired test data includes: post-processing collected data, post-processing logical operation data and post-processing condition operation data;

the post-processing collected data is configured with the type, sampling time and data unit of the data;

post-processing the collected data includes: post-processing the frequently acquired data and post-processing the conditionally acquired data;

the post-processing frequently-acquired data are series of acquired parameters when the automatic emergency braking system is in different states;

the post-processing conditional acquisition data is a series of parameters which need to be acquired after the primary early warning moment and when a preset condition is met;

the post-processing logic operation data is configured with data type, sampling time, application formula, data unit and data calculation mode;

the post-processing condition operation data is configured with the application range of data indexes, data processing logic, data types, sampling time and data units;

analyzing the type of the test data, and judging an applicable test flow system of the test data;

step three, testing the test data according to the analyzed test data type and the test flow system;

and step four, outputting and storing the test result.

2. The test method according to claim 1,

the test flow system comprises: illegal working conditions are not a rule critical working condition process, a rule working condition or a rule critical working condition process.

3. The test method according to claim 2,

the flow of illegal and non-legal critical conditions comprises the following steps:

processing data of illegal conditions and non-legal critical conditions;

extracting the post-processing frequently-collected data, and printing the extracted data;

processing the conditionally acquired data after extraction, and printing the extracted data;

extracting post-processing condition operation data, and printing an operation result;

and testing through a full-working-condition general index evaluation system, and outputting a test result.

4. The test method according to claim 2,

the regulation condition or regulation critical condition flow comprises the following steps:

post-processing the data of the regulation working condition or the regulation critical working condition;

extracting the post-processing frequently-collected data, and printing the extracted data;

processing the conditionally acquired data after extraction, and printing the extracted data;

extracting post-processing condition operation data, and printing an operation result;

testing through a general index evaluation system under all working conditions to judge whether the working conditions are the rule working conditions;

if the rule working condition is adopted, testing is carried out through a special index evaluation system for the rule working condition and the rule critical working condition;

the method comprises the following steps of testing based on a special index evaluation system of the regulation working condition and the regulation critical working condition, wherein the special index evaluation system of the regulation working condition comprises a special evaluation index of the regulation working condition, a regulation-critical working condition evaluation index and a regulation plus-critical working condition evaluation index;

and outputting a test result.

Background

Currently, automobile technology has been advanced greatly, and many automobiles are provided with driving assistance systems, which include automatic emergency braking, adaptive cruise, lane keeping assistance, lane departure warning, forward collision warning, and the like, so that the safety of drivers and passengers is improved to a great extent.

In order to ensure stable operation of the driving assistance system of the vehicle, the driving assistance system is usually required to be tested, so that stable operation is ensured, and faults are reduced. In the technical field of vehicle driving assistance simulation test, an in-loop simulation test method of high-grade driving assistance hardware which is commonly used in the industry is lacked at present. At present, the national relevant laws and regulations for advanced vehicle auxiliary driving are all focused on the field of real vehicle testing, and virtual simulation testing cannot be directly guided. And the high-grade auxiliary driving hardware lacks an industry-recognized method system in the ring simulation test and also lacks regulation guidance in the aspect. Meanwhile, based on the existing intelligent driving hardware-in-the-loop simulation test system, high real-time reading, high real-time analysis and calculation and high real-time writing of data are difficult to achieve, and therefore control strategy verification type test cases with high real-time requirements are difficult to achieve sufficiently on the hardware-in-the-loop simulation test system, test verification is insufficient, and potential safety hazards are brought to later use of a driving auxiliary system.

Disclosure of Invention

In order to overcome the defects in the prior art, the invention provides a hardware-in-loop simulation test method for an automatic emergency braking system, which comprises the following steps:

step one, executing a test process, acquiring test data in real time, and recording the test data;

the acquired test data includes: post-processing collected data, post-processing logical operation data and post-processing condition operation data;

the post-processing collected data is configured with the type, sampling time and data unit of the data;

post-processing the collected data includes: post-processing the frequently acquired data and post-processing the conditionally acquired data;

the post-processing frequently-acquired data are series of acquired parameters when the automatic emergency braking system is in different states;

the post-processing conditional acquisition data is a series of parameters which need to be acquired after the primary early warning moment and when certain specific conditions are met;

the post-processing logic operation data is configured with data type, sampling time, application formula, data unit and data calculation mode;

the post-processing condition operation data is configured with the application range of data indexes, data processing logic, data types, sampling time and data units;

analyzing the type of the test data, and judging an applicable test flow system of the test data;

step three, testing the test data according to the analyzed test data type and the test flow system;

and step four, outputting and storing the test result.

As can be seen from the technical invention, the invention has the following advantages:

the invention solves the technical problem of lacking of an advanced driving assistance hardware in-loop simulation test method, provides a whole set of test method, comprises test data, test evaluation and test flow, and is a deep exploration on the in-loop simulation test method of the vehicle automatic emergency braking system hardware.

The invention solves the technical problem that the control strategy verification type test case with high real-time requirement in the existing intelligent driving hardware-in-loop simulation test system is difficult to realize, and the test verification of the control strategy verification type test case can be realized on the existing hardware-in-loop test equipment by establishing a whole set of test method based on a data post-processing system.

The invention has great significance for establishing an intelligent driving simulation test method and specification in the industry and developing and testing an intelligent driving system in the industry. The invention solves the blindness of the prior auxiliary driving hardware in-loop simulation test method and test purpose, also solves the problem that the guidance of the prior regulation of the vehicle automatic emergency braking system in the simulation test field is limited, and also solves the problem that the control strategy verification type test case with high real-time requirement is difficult to fully test and verify based on the prior hardware in-loop test equipment, so that the intelligent driving hardware in-loop simulation test is more systematic, more accurate and more practical, the software defect can be more timely and more comprehensively discovered, the development cycle is shortened, and the risk cost brought by a large amount of real vehicle tests can be saved. In addition, the theoretical systematicness and the feasibility of the method of the invention play an important role in promoting the industrial progress of the intelligent driving virtual simulation test, and the beneficial effect of the implementation is obvious.

The invention can make the intelligent driving hardware in-loop simulation test more systematic, more accurate and more practical, can more timely and more comprehensively discover the software defects, shortens the development period and can save the risk cost brought by a large amount of real vehicle tests.

Drawings

In order to more clearly illustrate the technical invention of the present invention, the drawings used in the description will be briefly introduced, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without inventive labor.

FIG. 1 is a flow chart of an automatic emergency braking system hardware-in-the-loop simulation test method;

FIG. 2 is a flow chart of an illegal condition and an illegal critical condition;

FIG. 3 is a flow chart of a regulatory operating condition or a regulatory critical operating condition.

Detailed Description

Technical inventions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is to be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The invention provides an automatic emergency braking system hardware-in-loop simulation test method in the field of vehicle advanced assistant driving simulation tests, which takes an automatic emergency braking system as an example and is shown in figures 1 to 3, aiming at the current situation that the existing vehicle advanced assistant driving simulation test technology field and an assistant driving hardware-in-loop simulation test method in the industry are insufficient.

In the loop simulation test of advanced driver assistance hardware, due to the fact that high real-time reading, high real-time analysis and calculation and high real-time writing of data are difficult to achieve, control strategy verification type test cases with high real-time requirements are difficult to achieve on a loop simulation test system of hardware sufficiently, and therefore test verification is insufficient. The invention takes the automatic emergency braking hardware in-loop simulation test as an example, and provides a whole set of data post-processing parameter evaluation system based on a dynamic model and an ideal radar model from the perspective of the simulation test.

According to the invention, through deep matching of the regulation requirements, relevant test scenes are exhausted, and a whole set of data automatic post-processing parameter evaluation system which can be realized by using scripts is extracted. And by refining scenes and setting parameters, critical parameters of the critical working conditions of the rules are matched, so that the quality of the algorithm to be tested can be deeply judged, and the algorithms of different companies can be transversely judged.

Specifically, in the automatic emergency braking system hardware-in-loop simulation test method, a set of all-condition general index evaluation system and a set of special index evaluation system for regulation working conditions and regulation critical working conditions are provided according to the existing dynamics model and the ideal radar model and by combining working experience from the regulation JTT 1242-2019, so as to accurately and systematically guide the automatic emergency braking system hardware-in-loop simulation test.

The automatic emergency braking system is called AEBS for short, and the automatic emergency braking function is called AEB for short. The AEB state is 1 when the AEB function is not activated, the AEB state is 3 when the AEB function is activated, the AEB state is 5 when the AEB sends out a first-level early warning, the AEB state is 6 when the AEB sends out a second-level early warning and points to brake, and the AEB state is 7 when the AEB brakes with full force. When AEB full force braking is over and there is no longer a collision risk, the AEB state returns to 1 again.

In the invention, TTC (time to collision) or ETTC (enhanced time to collision) values output from a controller bus are not adopted, but TTC and ETTC values are independently calculated in the background according to data collected by post-processing and more depending on data collected from an ideal model, so that the effectiveness and universality of TTC and ETTC indexes aiming at different algorithms are ensured.

Test data system

1. Post-processing frequently-collected data:

let us note T₅Recording the background calculation value of TTC at the system moment when the AEB state just enters 5 (the AEB just starts first-level early warning), and recording the calculation value as TTC₅(ii) a Recording the background calculation value of the ETTC at the moment, and recording the background calculation value as the ETTC₅；

Recording the longitudinal distance D from the front vehicle at the moment and recording the longitudinal distance D as D₅(from an ideal radar model);

recording the speed V of the vehicle at the moment_SVIs marked as V_SV5(from kinetic models);

recording the relative speed V of the front vehicle at the moment_{Relative to each other}(from an ideal radar model) and is denoted V_{Relative 5}；

Record the speed V of the front vehicle at this time_TV(from CAN bus, send out after fusion) and is noted as V_TV5；

② T₆Recording the TTC background calculation value at the system moment of just entering 6 (just starting secondary early warning and stopping) of the AEB state, and recording the TTC background calculation value as TTC₆(ii) a Recording the background calculation value of the ETTC at the moment, and recording the background calculation value as the ETTC₆；

Recording the longitudinal distance D from the front vehicle at the moment and recording the longitudinal distance D as D₆(from an ideal radar model);

recording the speed V of the vehicle at the moment_SVIs marked as V_SV6(from kinetic models);

recording the relative speed V of the front vehicle at the moment_{Relative to each other}(from an ideal radar model) and is denoted V_{Relative 6}；

Record the speed V of the front vehicle at this time_TV(from CAN bus, send out after fusion) and is noted as V_TV6；

C. recording T₇The system time for the AEB state just before 7 (AEB just starts full force braking); recording the background calculated value of the TTC at the moment, and recording the value as the TTC₇(ii) a Recording the background calculation value of the ETTC at the moment,

denoted ETTC₇；

Recording the longitudinal distance D from the front vehicle at the moment and recording the longitudinal distance D as D₇(from an ideal radar model);

recording the speed V of the vehicle at the moment_SVIs marked as V_SV7(from kinetic models);

recording the relative speed V of the front vehicle at the moment_{Relative to each other}(from an ideal radar model) and is denoted V_{Relative 7}；

Record the speed V of the front vehicle at this time_TV(from CAN bus, send out after fusion) and is noted as V_TV7；

Fourthly, recording T_a=-4The deceleration of the bicycle is just up to-4 m/s²(1242 beginning of emergency braking phase defined by regulation), recording the calculated value of TTC background at the moment, and recording the value as TTC _a=-4(ii) a Recording the background calculation value of the ETTC at the moment, and recording the background calculation value as the ETTC _a=-4；

Recording the longitudinal distance D from the front vehicle at the moment and recording the longitudinal distance D as D _a=-4(from an ideal radar model);

recording the speed V of the vehicle at the moment_SVIs marked as V_{SV a=-4}(from kinetic models);

recording the relative speed V of the front vehicle at the moment_{Relative to each other}(from an ideal radar model) and is denoted V_{Relative a = -4}；

Record the speed V of the front vehicle at this time_TV(from CAN bus, send out after fusion) and is noted as V_{TV a=-4}；

⑤T_{7 powder}The system time at the moment when the AEB state is just finished and the 7 returns to the 1; at this time, the speed of the vehicle is V_{End of SV7}(from kinetic models);

recording the longitudinal distance D from the front vehicle at the moment and recording the longitudinal distance D as D _a=-4(from an ideal radar model);

recording the speed V of the vehicle at the moment_SVIs marked as V _{SV a=-4}(from kinetic models);

recording the relative speed V of the front vehicle at the moment_{Relative to each other}(from an ideal radar model) and is denoted V_{Relative a = -4}；

Record the speed V of the front vehicle at this time_TV(from the CAN bus, issuing after fusion) Is marked as V _{TV a=-4}；

W the duration of the AEB state is 5 is T_（5），T_（5）=T₆-T₅；

Duration T of AEB State 6_（6），T_（6）=T₇-T₆；

Duration T of AEB State 7_（7）；

AEB Emergency braking phase duration T_(Emergency)；

Note t_（5）=TTC₅-TTC₆

t_（6）=TTC₆-TTC₇

t_（7）=TTC₇

2. Post-processing conditional acquisition data:

①T₅after time, V_SVThe first time satisfies: v is more than or equal to 0_SV<When the speed of the vehicle is 0.01km/h (namely when the vehicle just starts to brake), the speed V of the vehicle at the moment is recorded_SVAnd recording V_SV=0 km/h; and recording the distance D from the front vehicle at the moment.

②T₅After time, D satisfies for the first time: d is not less than 0<0.01m (i.e. when the vehicle and the preceding vehicle just collide with each other),

recording the speed V of the vehicle at the moment_SVIs marked as V_{SV bump}(ii) a The distance D from the vehicle ahead at this time is recorded, and D =0 m.

③T₅After time, V_SVAnd D satisfies for the first time: v_SV≤V_TVAnd D>When 0 hour (the vehicle does not collide with the front vehicle after braking and stably follows the vehicle after braking to a certain speed), the vehicle speed V of the vehicle at the moment is recorded_SV(ii) a Record the speed V of the front vehicle at this time_TV(ii) a And recording the distance D from the front vehicle at the moment.

Second, test evaluation system

1. All-condition general index evaluation system

(1) General formula:

(D is the distance from the vehicleThe longitudinal distance of the front vehicle, unit m, comes from an ideal radar model; v_{Relative to each other}Speed of the leading vehicle relative to the vehicle in m/s from an ideal radar model)

Unit m/sFrom an ideal radar model).

(2) General indexes are as follows:

processing acquired data (T) _a=-4、T₅、 T₆）

T _a=-4The deceleration of the bicycle is just up to-4 m/sThe system time of (1);

T₅the system time when the AEB state just enters 5 (the AEB just starts the first-level early warning);

T₆the system time is the system time when the AEB state just enters 6 (the AEB just starts the second-stage early warning and stops);

② post-processing logical operational data (TTC)₅、TTC _a=-4、ETTC₅、ETTC _a=-4）

The TTC background calculation value recorded at the system time of just entering 5 in the AEB state is recorded as TTC₅(ii) a Recording the background calculation value of the ETTC at the moment, and recording the background calculation value as the ETTC₅；

When the deceleration of the bicycle just reaches-4 m/sThe TTC background calculation value recorded at the system moment of time,

is marked as TTC _a=-4(ii) a Recording the background calculation value of the ETTC at the moment, and recording the background calculation value as the ETTC _a=-4；

③ post-processing conditional operation data (V)_{Pre-reduction}、V_{Total reduction}）：

I. Deceleration V at early warning stage_{Pre-reduction}=V_SV5 -V_{SV a=-4}

II total deceleration V_{Total reduction}：

i). T₅After time, V_SVThe first time satisfies: v is more than or equal to 0_SV<0.01km/h (namely when the vehicle just starts to brake),

V_{total reduction}=V_SV5；

ii). T₅After time, D satisfies for the first time: d is not less than 0<0.01m (i.e. when the vehicle and the preceding vehicle just collide with each other),

at this time, the vehicle speed V of the vehicle is read_SVIs marked as V_{SV bump}，

V_{Total reduction}=V_SV5-V_{SV bump}；

iii). T₅After time, V_SVAnd D satisfies for the first time: v_SV≤V_TVAnd D>0 hour (the vehicle does not collide with the front vehicle after braking, and stably follows the vehicle after braking to a certain speed), and the vehicle speed is read when the AEB state is 7

2. A special index evaluation system for regulation working conditions and regulation critical working conditions;

aiming at the working condition and the critical working condition thereof specified by 1242 regulations, deeper special evaluation is further performed on the premise of meeting the all-working-condition general index evaluation system. Through the working conditions, the advantages and the disadvantages of the algorithm to be detected can be deeply judged, and the advantages and the disadvantages of the same algorithm of different companies can be transversely compared.

(1) Evaluation indexes special for regulation working conditions are as follows:

firstly, 40 pairs of 0 working conditions (the vehicle speed is 40km/h, and the vehicle in front of the vehicle is static): the brake can be stopped to avoid collision;

the data source is as follows: distance D from the leading vehicle, from the ideal radar model (true value); speed V of the vehicle_SVFrom a kinetic model;

the method comprises the following steps: the first time satisfies: 0Speed V of the vehicle_SV<And when the speed is 0.01km/h, reading the distance D from the front vehicle. When D is at this time>At 0m, it can be judged to pass.

(80) for 0 working condition (the vehicle speed is 80km/h, the front vehicle of the vehicle is static): the speed reduction of the vehicle is not less than 30km/h when collision occurs;

the data source is as follows: distance D from the leading vehicle, from the ideal radar model (true value); speed V of the vehicle_SVFrom a kinetic model;

the method comprises the following steps: the first time satisfies: d is not less than 0<0.01m, reading the speed V of the vehicle_SV. When V is at this time_SV At 50km/h, the result is judged to be passed.

③ 80 pairs of 12 working conditions (the speed of the vehicle is 80km/h, and the speed of the vehicle in front of the vehicle is 12 km/h): the collision of two vehicles can be avoided;

the data source is as follows: distance D from the leading vehicle, from the ideal radar model (true value);

the method comprises the following steps: within a reasonable system time range, D > 0m is always true.

Fourthly, the pedestrian crosses the working condition (the speed of the vehicle is 60km/h, the pedestrian crosses the transverse speed 8 km/h),

the data source is as follows: distance D from pedestrian₁From the ideal radar model (true value); speed V of the vehicle_SVFrom a kinetic model;

the method comprises the following steps: the first time satisfies: d is not less than 0₁<0.01m, reading the speed V of the vehicle_SV. When V is at this time_SVWhen the speed is less than or equal to 40km/h, the judgment is passed.

(2) Evaluation index of 'rule-' critical working condition

If the rule 40 is aimed at 0 working condition (the vehicle speed is 40km/h, the vehicle in front of the vehicle is static): the brake can be stopped to avoid collision. The degradation of the critical working condition, such as 35 to 0 working conditions, must also avoid collision.

The test purpose is as follows: the method is characterized in that the universality of the rule working conditions of the algorithm is verified, but an algorithm development engineer aims at the strong standard parameters of the specific rule working conditions, so that the performance of individual rule working conditions is extremely excellent, and the performance difference of other rule critical working conditions is large.

(3) Evaluation index of 'rule +' critical working condition

If the rule 40 is aimed at 0 working condition (the vehicle speed is 40km/h, the vehicle in front of the vehicle is static): the brake can be stopped to avoid collision. For the critical working conditions, enumerated gradient parameters are configured in detail through a script language, for example, 42 for 0 working conditions, 44 for 0 working conditions, the gradient of the configuration parameters is upgraded, and a series of test cases are derived automatically, so that conditions such as the vehicle speed and the like which meet the logic of general indicators under all the working conditions and just collide with a front vehicle are tried out and marked. This critical index can be used to compare software algorithms across multiple companies.

Through the regulation working condition and the 'regulation plus' critical working condition, the quality of the same algorithm of different companies can be transversely judged. The general applicability of the algorithm of the same company can be judged through the 'rule-' critical working condition.

The invention solves the technical problem of the in-loop simulation test method of the auxiliary driving hardware, provides a whole set of test method, comprises test data, test evaluation and test flow, and is a deep exploration on the in-loop simulation test method of the vehicle automatic emergency braking system hardware. The invention has great significance for establishing an intelligent driving simulation test method and specification in the industry and developing and testing an intelligent driving system in the industry. The invention solves the blindness of the prior auxiliary driving hardware in-loop simulation test method and test purpose, also solves the problem that the guidance of the vehicle automatic emergency braking system rule in the simulation test field is limited, and also solves the problem that the control strategy verification type test case with high real-time requirement is difficult to fully test and verify based on the prior hardware in-loop test equipment, so that the intelligent driving hardware in-loop simulation test is more systematic, more accurate and more practical, the software defect can be more timely and more comprehensively discovered, the development cycle is shortened, and the risk cost brought by a large amount of real vehicle tests can be saved. In addition, the theoretical systematicness and the feasibility of the method of the invention play an important role in promoting the industrial progress of the intelligent driving virtual simulation test, and the beneficial effect of the implementation is obvious.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.