Automotive safety integrity level quantitative evaluation system, method, device and storage medium

Abstract

The application belongs to the technical field of functional safety, and particularly relates to a vehicle safety integrity level quantitative evaluation system, method, device and storage medium, which comprises the following steps: a simulation scene is built, a basic scene is used to obtain an exposure probability; key influence factors include at least one of the following: a front vehicle state, a rear vehicle state, a rear driver state and a vehicle distance; different simulation cases are obtained by permutation and combination based on modification of respective values of the key influence factors, and occurrence probabilities of different simulation cases are calculated, wherein the occurrence probability of the simulation case is obtained according to the key influence factors; the different simulation cases are executed to obtain results of different simulation cases; and a vehicle safety integrity level evaluation result is obtained based on calculation of the occurrence probability of the simulation case and the result of the simulation case.

Description

Technical Field

[0001] This invention belongs to the field of functional safety technology, specifically relating to a quantitative assessment system, method, device, and storage medium for automotive safety integrity levels. Background Technology

[0002] Safety is one of the key issues in the development of road vehicles. The development and integration of automotive functions have strengthened the need for functional safety, as well as the need to provide evidence that functional safety objectives are met. With increasing technological complexity and the growing application of software and mechatronics, the risks from systemic failures and random hardware failures are gradually increasing, all of which fall within the scope of functional safety considerations. To achieve functional safety, ISO 26262, "Road vehicle – functional safety," mitigates risks by providing appropriate requirements and procedures. This standard provides a vehicle-specific risk-based analysis method to determine the Vehicle Safety Integrity Level (ASIL) for hazardous events. The Vehicle Safety Integrity Level (ASIL) is composed of the parameters "severity," "probability of exposure," and "controllability." Overestimating the severity, probability of exposure, and controllability parameters, and the derived ASIL level, may lead to a reduction or even elimination of functions or features that are beneficial to improving overall vehicle safety. Underestimating the severity, probability of exposure, and controllability parameters, and the derived ASIL level, may result in insufficient safety requirements.

[0003] In existing technologies, the ASIL assessment of the deceleration of the preceding vehicle is not quantified, leading to inaccurate assessment results. Furthermore, existing technologies lack a simulation model and a method for assessing the ASIL level of the preceding vehicle's deceleration after the driver of the following vehicle recognizes the risk and applies emergency braking when the preceding vehicle decelerates due to a malfunction. Summary of the Invention

[0004] To address the above shortcomings, the purpose of this invention is to provide a quantitative assessment system, method, device, and storage medium for automotive safety integrity levels.

[0005] This invention provides the following technical solution: A quantitative assessment system for vehicle safety integrity level includes a simulation data processing module and a data acquisition module and a data processing module that are communicatively connected to the simulation data processing module. The data acquisition module is used to acquire the exposure probability, simulation test cases, and the probability of occurrence of different simulation test cases; The simulation data processing module is used to run simulation test cases in a simulation environment and output simulation results; The data processing module is used to calculate the vehicle safety integrity level assessment result based on the occurrence probability of the simulation test cases and the simulation results.

[0006] It also includes a simulation observer, which is used to debug the simulation model and observe the running status of the simulation model.

[0007] A quantitative assessment method for vehicle safety integrity level, applied to the aforementioned vehicle safety integrity level quantitative system, includes the following steps: S101. Build a simulation scenario, which includes a basic scenario and key influencing factors. The basic scenario is used to obtain the exposure probability. The key influencing factors include at least one of the following: the status of the vehicle in front, the status of the vehicle behind, the status of the driver of the vehicle behind, and the distance between vehicles.

[0008] In S101, the exposure probability of the simulation scene is obtained based on the road conditions of the basic scene and the key influencing factors.

[0009] The preceding vehicle's status includes its initial speed and deceleration; the following vehicle's driver status includes their reaction time; and the following vehicle's status includes its initial speed and braking deceleration. The preceding and following vehicles are assumed to have the same initial speed, meaning they start at the same speed. The basic scenario is a straight, dry road surface where both vehicles are traveling in the same direction at the same speed. If the preceding vehicle brakes unexpectedly, the driver of the following vehicle will recognize the risk and brake suddenly.

[0010] S102. Based on the modification of the values ​​of the key influencing factors, different simulation cases are obtained by permutation and combination, and the occurrence probability of different simulation cases is calculated, wherein the occurrence probability of the simulation cases is calculated based on the key influencing factors.

[0011] In S102, the values ​​of each key influencing factor are incrementally modified in fixed steps to obtain different simulation test cases through permutations and combinations; the probability P of different simulation test cases occurring... i It is the product of the probability distributions of each key influencing factor in the corresponding combination.

[0012] Specifically, several values ​​are set for the initial speed, the deceleration of the preceding vehicle, the vehicle spacing, the driver's reaction time, and the braking deceleration of the following vehicle. These values ​​are then arranged and combined in a fixed-step increment to obtain the probability distribution of each value. Simulation cases are generated based on the basic scenario. Each initial speed corresponds to one deceleration of the preceding vehicle, one vehicle spacing, one driver's reaction time, and one braking deceleration of the following vehicle. n simulation cases are created for each initial speed, for a total of N simulation cases. The probability P of each simulation case is... i = Probability of deceleration distribution of the vehicle in front * Probability of distance distribution between vehicles * Probability of driver reaction time distribution * Probability of braking deceleration distribution of the vehicle behind.

[0013] Specifically, X kinds of starting speeds satisfy a uniform distribution, and the distribution probability of each starting speed is 1; C kinds of decelerations of the leading vehicle satisfy a uniform distribution, and the distribution probability of each deceleration of the leading vehicle is 1; B kinds of vehicle spacings satisfy a Gaussian distribution, G kinds of driver reaction times satisfy a Gaussian distribution, and H kinds of decelerations of the following vehicle during braking satisfy a Gaussian distribution. Therefore, n = C * B * G * H, and N = n * X. P i = 1 * distribution probability of vehicle spacing * distribution probability of driver reaction time * distribution probability of deceleration of the following vehicle during braking.

[0014] S103. Execute the different simulation cases to obtain the results of different simulation cases.

[0015] In S103, execute the different simulation cases, and confirm the severity level according to the vehicle states of the leading vehicle and the following vehicle after executing the simulation cases; calculate the occurrence probability of the severity level based on the severity level to obtain the controllability.

[0016] Specifically, evaluate the severity based on the relative collision speed between the leading and following vehicles.

[0017] When the relative collision speed V between the leading and following vehicles satisfies 3 < V ≤ V1, the severity is S0; When V1 < V ≤ V2, the severity is S1; When V2 < V ≤ V3, the severity is S2; When V > V3, the severity is S3; Among them, V1 = 10 KPH, V2 = 20 KPH, and V3 = 40 KPH.

[0018] The calculation formula for the occurrence probability P of the severity level is: When the relative collision speed between the leading and following vehicles is evaluated as the corresponding severity, J is 1, otherwise J is 0; N is the total number of simulation cases; P i is the occurrence probability of different simulation cases; When 1 - P ≥ P1, the controllability is C0; when P1 > 1 - P ≥ P2, the controllability is C1; when P2 > 1 - P ≥ P3, the controllability is C2; when 1 - P > P3, the controllability is C3; P1 = 99.9%, P2 = 99%, and P3 = 90%.

[0019] When evaluating the occurrence probability when the severity is S0, if 3 < V ≤ V1, then J = 1, otherwise J = 0; when evaluating the occurrence probability when the severity is S1, if V1 < V ≤ V2, then J = 1, otherwise J = 0; when evaluating the occurrence probability when the severity is S2, if V2 < V ≤ V3, then J = 1, otherwise J = 0; when evaluating the occurrence probability when the severity is S3, if V > V3, then J = 1, otherwise J = 0.

[0020] S104. Calculate based on the occurrence probability of the simulation case and the result of the simulation case to obtain the evaluation result of the automotive safety integrity level.

[0021] In S104, the evaluation result of the automotive safety integrity level is calculated based on the exposure probability, controllability, and severity of the test case.

[0022] The exposure probability is E4. According to the obtained severity and controllability, the evaluation result of the automotive safety integrity level for each deceleration of the preceding vehicle can be obtained.

[0023] An automotive safety integrity level quantitative evaluation device includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the above-mentioned automotive safety integrity level quantitative evaluation method is implemented.

[0024] A computer-readable storage medium stores a computer program, and when the program is executed by a processor, the above-mentioned automotive safety integrity level quantitative evaluation method is implemented.

[0025] The beneficial effects of the present invention are as follows: This application can obtain quantified exposure probability, severity, and controllability, and evaluate the ASIL level according to the exposure probability, severity, and controllability, and further obtain the ASIL level for each deceleration of the preceding vehicle, thereby improving the evaluation accuracy, and realizing a simulation model capable of evaluating the ASIL level of the deceleration of the preceding vehicle and a method for evaluating the ASIL level of the deceleration of the preceding vehicle based on the simulation model. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is a flowchart of the present invention; Figure 2 is a schematic diagram of the automated simulation model of the present invention.

[0027] The marks in the figure are: data acquisition module 101, simulation data processing module 102, simulation environment 103, data processing module 104, simulation observer 105. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0028] Embodiment 1 As Figure 2As shown, a quantitative assessment system for vehicle safety integrity levels includes a simulation data processing module and a data acquisition module and a data processing module that are communicatively connected to the simulation data processing module. The data acquisition module is used to acquire the exposure probability, simulation cases, and the probability of occurrence of different simulation cases; The simulation data processing module is used to run simulation test cases in a simulation environment and output simulation results; The data processing module is used to calculate the vehicle safety integrity level assessment result based on the occurrence probability of the simulation test cases and the simulation results.

[0029] It also includes a simulation observer, which is used to debug the simulation model and observe the running status of the simulation model.

[0030] Specifically, a simulation scenario is first built, which includes a basic scenario and key influencing factors. The basic scenario is a straight and dry road surface where two vehicles are traveling in the same direction at the same speed. The vehicle in front brakes unexpectedly, and the driver of the vehicle behind brakes urgently after recognizing the risk. Key influencing factors include the starting speed, the deceleration of the vehicle in front, the distance between vehicles, the driver's reaction time, and the braking deceleration of the vehicle behind.

[0031] Then, several values ​​are set for the initial speed, the deceleration of the vehicle in front, the distance between vehicles, the driver's reaction time, and the braking deceleration of the vehicle behind. Each value is then arranged and combined in an increasing manner with a fixed step size to obtain the probability distribution of each value of the initial speed, the deceleration of the vehicle in front, the distance between vehicles, the driver's reaction time, and the braking deceleration of the vehicle behind. X initial speed values ​​can be set, and these values ​​follow a uniform distribution, meaning the probability of each initial speed value is 1. C preceding vehicle deceleration values ​​can be set, and these values ​​follow a uniform distribution, meaning the probability of each preceding vehicle deceleration value is 1. B vehicle spacing values ​​can be set, and these values ​​follow a Gaussian distribution. G driver reaction times can be set, and these values ​​follow a Gaussian distribution. H following vehicle braking deceleration values ​​can be set, and these values ​​follow a Gaussian distribution. The probability distribution of each key influencing factor is shown in the table below: Key Influencing Factors scope Distribution probability Remark Starting speed V1- VX 1 Average distribution deceleration of the vehicle in front 1-C 1 Average distribution vehicle spacing S1-SB [Ps1…PsB] Satisfies Gaussian distribution Driver reaction time T1-TG [PT1…PTG] Satisfies Gaussian distribution Rear vehicle braking deceleration a1-aH [Pa1…PaH] Satisfies Gaussian distribution Simulation test cases are generated by combining basic scenarios. The basic scenarios serve as the simulation premise environment for the simulation test cases. Each starting speed corresponds to a deceleration of the vehicle in front, a distance between vehicles, a driver's reaction time, and a braking deceleration of the vehicle behind. Each starting speed creates n simulation test cases, for a total of N simulation test cases, i.e., n=C*B*G*H, N=n*X. Considering that the probabilities of occurrence of key influencing factors are different in real life, calculate the probability P of each simulation case according to the distribution probabilities of the values of starting speed, deceleration of the vehicle in front, vehicle spacing, driver reaction time, and deceleration of the vehicle behind in the key influencing factors i , P i = Distribution probability of deceleration of the vehicle in front * Distribution probability of vehicle spacing * Distribution probability of driver reaction time * Distribution probability of deceleration of the vehicle behind; Since the distribution probability of deceleration of the vehicle in front is 1, so P i = 1 * Distribution probability of vehicle spacing * Distribution probability of driver reaction time * Distribution probability of deceleration of the vehicle behind; That is, the corresponding P of each simulation case is obtained i .

[0032] Import the above data into Excel; The data acquisition module reads the Excel data through MATLAB and transmits it to the simulation data processing module, and the simulation data processing module converts the data into simulation model control instructions; The simulation model control instructions include the simulation start time, simulation end time, speed of the simulation vehicle, etc. Under the simulation environment, the simulation cases are automatically run and the simulation results are output; The simulation results include whether the vehicles in front and behind collide and the relative collision speed of the vehicles in front and behind; The data processing module groups the relative collision speed of the vehicles in front and behind in the simulation results and exports it to an Excel table; The simulation observer is used to debug the simulation model and observe the running state of the simulation model

[0033] The data processing module evaluates the severity according to the relative collision speed of the vehicles in front and behind; Specifically, when the relative collision speed V of the vehicles in front and behind satisfies 3 < V ≤ V1, the severity is S0; when V1 < V ≤ V2, the severity is S1; when V2 < V ≤ V3, the severity is S2; when V > V3, the severity is S3; V1 = 10 KPH, V2 = 20 KPH, V3 = 40 KPH

[0034] The data processing module calculates the occurrence probability P of each severity according to the above simulation results and the probability P i of the simulation test cases respectively, and evaluates the controllability according to P The calculation formula for the occurrence probability P of each severity is When the relative collision speed of the vehicles in front and behind is evaluated as the corresponding severity, J is 1, otherwise J is 0; That is, when calculating the occurrence probability of the severity S0, if 3 < V ≤ V1, then J = 1, otherwise J is 0; when calculating the occurrence probability of the severity S1, if V1 < V ≤ V2, then J = 1, otherwise J is 0; when calculating the occurrence probability of the severity S2, if V2 < V ≤ V3, then J = 1, otherwise J is 0; when calculating the occurrence probability of the severity S3, if V > V3, then J = 1, otherwise J is 0

[0035] When 1-P≥P1, the controllability is C0; when P1>1-P≥P2, the controllability is C1; when P2>1-P≥P3, the controllability is C2; when 1-P>P3, the controllability is C3; P1=99.9%, P2=99%, P3=90%.

[0036] With an exposure probability of E4, the ASIL level for each preceding vehicle deceleration is determined based on the severity and controllability already obtained.

[0037] The following table shows the deceleration of the vehicle in front as -2 m / s². 2 and -8m / s 2 ASIL level assessment results at that time: Example 2 like Figure 1 As shown, this embodiment provides a method for quantitatively assessing the safety integrity level of a vehicle, applied to the vehicle safety integrity level quantitative system of the above embodiment, including the following steps: S101. Build a simulation scenario, which includes a basic scenario and key influencing factors. The basic scenario is used to obtain the exposure probability. The key influencing factors include at least one of the following: the status of the vehicle in front, the status of the vehicle behind, the status of the driver of the vehicle behind, and the distance between vehicles.

[0038] In S101, the exposure probability of the simulation scene is obtained based on the road conditions of the basic scene and the key influencing factors.

[0039] The preceding vehicle's status includes its initial speed and deceleration; the following vehicle's driver status includes their reaction time; and the following vehicle's status includes its initial speed and braking deceleration. The preceding and following vehicles are assumed to have the same initial speed, meaning they start at the same speed. The basic scenario is a straight, dry road surface where both vehicles are traveling in the same direction at the same speed. If the preceding vehicle brakes unexpectedly, the driver of the following vehicle will recognize the risk and brake suddenly.

[0040] S102. Based on the modification of the values ​​of the key influencing factors, different simulation cases are obtained by permutation and combination, and the occurrence probability of different simulation cases is calculated, wherein the occurrence probability of the simulation cases is calculated based on the key influencing factors.

[0041] In S102, the values ​​of each key influencing factor are incrementally modified in fixed steps to obtain different simulation test cases through permutations and combinations; the probability P of different simulation test cases occurring... i It is the product of the probability distributions of each key influencing factor in the corresponding combination.

[0042] Specifically, several values ​​are set for the initial speed, the deceleration of the preceding vehicle, the vehicle spacing, the driver's reaction time, and the braking deceleration of the following vehicle. These values ​​are then arranged and combined in a fixed-step increment to obtain the probability distribution of each value. Simulation cases are generated based on the basic scenario. Each initial speed corresponds to one deceleration of the preceding vehicle, one vehicle spacing, one driver's reaction time, and one braking deceleration of the following vehicle. n simulation cases are created for each initial speed, for a total of N simulation cases. The probability P of each simulation case is... i = Probability of deceleration distribution of the vehicle in front * Probability of distance distribution between vehicles * Probability of driver reaction time distribution * Probability of braking deceleration distribution of the vehicle behind.

[0043] Specifically, X types of initial speeds follow a uniform distribution, with each initial speed distribution having a probability of 1; C types of preceding vehicle decelerations follow a uniform distribution, with each preceding vehicle deceleration distribution having a probability of 1; B types of vehicle spacing follow a Gaussian distribution; G types of driver reaction time follow a Gaussian distribution; and H types of following vehicle braking deceleration follow a Gaussian distribution.

[0044] Simulation test cases are generated by combining the basic scenario. The basic scenario serves as the simulation premise environment for the simulation test cases. Each starting speed corresponds to a deceleration of the vehicle in front, a distance between vehicles, a driver's reaction time, and a braking deceleration of the vehicle behind. Each starting speed creates n simulation test cases, for a total of N simulation test cases, i.e., n=C*B*G*H, N=n*X.

[0045] Considering that the probabilities of key influencing factors occurring in real life vary, the probability P of each simulation case is calculated based on the probability distribution of the values ​​of initial speed, deceleration of the preceding vehicle, vehicle spacing, driver reaction time, and braking deceleration of the following vehicle among the key influencing factors. i P i = Probability of the deceleration distribution of the vehicle in front * Probability of the distance between vehicles * Probability of the driver's reaction time * Probability of the braking deceleration distribution of the vehicle behind; Since the probability of the deceleration distribution of the vehicle in front is 1, therefore P i = 1 * vehicle spacing probability distribution * driver reaction time probability distribution * rear vehicle braking deceleration probability distribution; thus, P is obtained for each simulation case. i .

[0046] S103. Execute the different simulation test cases to obtain the results of the different simulation test cases.

[0047] In S103, the different simulation test cases are executed, and the severity level is determined based on the status of the preceding and following vehicles after the simulation test cases are executed; the probability of the severity level occurring is calculated based on the severity level to obtain the controllability.

[0048] Specifically, the severity is evaluated based on the relative collision speed between the front and rear vehicles.

[0049] When the relative collision speed V between the front and rear vehicles satisfies 3 < V ≤ V1, the severity is S0; When V1 < V ≤ V2, the severity is S1; When V2 < V ≤ V3, the severity is S2; When V > V3, the severity is S3; Among them, V1 = 10 KPH, V2 = 20 KPH, V3 = 40 KPH.

[0050] The calculation formula for the occurrence probability P of the severity level is: When the relative collision speed between the front and rear vehicles is evaluated as the corresponding severity, J is 1, otherwise J is 0; N is the total number of simulation cases; P i Is the occurrence probability of different simulation cases; When 1 - P ≥ P1, the controllability is C0; when P1 > 1 - P ≥ P2, the controllability is C1; when P2 > 1 - P ≥ P3, the controllability is C2; when 1 - P > P3, the controllability is C3; P1 = 99.9%, P2 = 99%, P3 = 90%.

[0051] When evaluating the occurrence probability of the severity S0, if 3 < V ≤ V1, then J = 1, otherwise J is 0; when evaluating the occurrence probability of the severity S1, if V1 < V ≤ V2, then J = 1, otherwise J is 0; when evaluating the occurrence probability of the severity S2, if V2 < V ≤ V3, then J = 1, otherwise J is 0; when evaluating the occurrence probability of the severity S3, if V > V3, then J = 1, otherwise J is 0.

[0052] S104. Calculate based on the occurrence probability of the simulation cases and the results of the simulation cases to obtain the evaluation result of the automotive safety integrity level.

[0053] In S104, the evaluation result of the automotive safety integrity level is calculated based on the exposure probability, controllability, and severity of the test cases.

[0054] The exposure probability is E4. According to the obtained severity and controllability, the evaluation result of the automotive safety integrity level for each deceleration of the front vehicle can be obtained.

[0055] Example Three This embodiment provides a vehicle safety integrity level quantitative assessment device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the above-described vehicle safety integrity level quantitative assessment method.

[0056] Example 4 This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for quantitatively assessing the vehicle safety integrity level.

[0057] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for quantitatively assessing the safety integrity level of a vehicle, characterized in that, It includes the following steps: S101. Build a simulation scenario, which includes a basic scenario and key influencing factors. Among them, the basic scenario is that when two vehicles are driving in the same direction at the same speed on a flat and dry road surface, if the leading vehicle brakes unexpectedly and the driver of the following vehicle recognizes the risk and brakes emergently; the basic scenario is used to obtain the exposure probability; the key influencing factors include at least one piece of data of the leading vehicle state, the following vehicle state, the state of the driver of the following vehicle, and the vehicle distance; according to the road conditions of the basic scenario and the key influencing factors, the exposure probability of the simulation scenario is obtained; S102. Set several values for each key influencing factor, and generate different simulation cases by permuting and combining different values of each key influencing factor; calculate the occurrence probability of each simulation case according to the distribution probability of the key influencing factors; S103. Execute the different simulation cases to obtain the results of the different simulation cases; Confirm the severity level according to the leading vehicle state and the following vehicle state after executing the simulation case, and calculate the occurrence probability of the severity level based on the severity level to obtain the controllability; S104. Based on the exposure probability, severity level and controllability, obtain the evaluation result of the automotive safety integrity level corresponding to the deceleration of the leading vehicle; In S102, the value of each key influencing factor is incrementally modified in a fixed step size to obtain different simulation cases by permutation and combination; The probability P of different simulation test cases i It is the product of the probability distributions of each key influencing factor in the corresponding combination; In S103, the severity is evaluated based on the relative collision speed of the front and rear vehicles; When the relative collision speed V of the front and rear vehicles satisfies 3 < V ≤ V1, the severity is S0; When V1 < V ≤ V2, the severity is S1; When V2 < V ≤ V3, the severity is S2; When V > V3, the severity is S3; Among them, V1 = 10 KPH, V2 = 20 KPH, V3 = 40 KPH; The calculation formula for the occurrence probability P of the severity level is: When the relative collision speed of the front and rear vehicles is evaluated as the corresponding severity, J is 1, otherwise J is 0; N is the total number of simulation cases; P i The probability of occurrence for different simulation test cases; When 1 - P ≥ P1, the controllability is C0; when P1 > 1 - P ≥ P2, the controllability is C1; when P2 > 1 - P ≥ P3, the controllability is C2; when 1 - P > P3, the controllability is C3; P1 = 99.9%, P2 = 99%, P3 = 90%.

2. A quantitative assessment system for vehicle safety integrity levels, characterized in that, It is used to implement the quantitative evaluation method for the automotive safety integrity level as described in claim 1, including a simulation data processing module and a data acquisition module and a data processing module that are communicatively connected to the simulation data processing module; The data acquisition module is used to acquire the exposure probability, simulation cases and the occurrence probabilities of different simulation cases; The simulation data processing module is used to run the simulation cases in the simulation environment and output the simulation results; The data processing module is used to calculate according to the occurrence probabilities of the simulation cases and the simulation results to obtain the evaluation result of the automotive safety integrity level.

3. A quantitative assessment device for vehicle safety integrity level, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, it implements the quantitative evaluation method for the automotive safety integrity level as described in claim 1.

4. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by the processor, it implements the quantitative evaluation method for the automotive safety integrity level as described in claim 1.

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