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GB/Z 42285-2022 (GB/Z42285-2022, GBZ 42285-2022, GBZ42285-2022)
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GB/Z 42285-2022: PDF in English (GBZ 42285-2022)

GB/Z 42285-2022
ICS 43.040
CCS T 35
Road vehicles - ASIL determination guidelines for electrical
and electronic system
Issued by: State Administration for Market Regulation;
Standardization Administration of PRC.
Table of Contents
Foreword ... 4
1 Scope ... 5
2 Normative references ... 5
3 Terms and definitions ... 5
4 Hazard analysis and risk assessment ... 6
4.1 Identification of hazards ... 6
4.2 Risk assessment ... 8
4.3 Relationship between safety goals and safety status ... 17
Appendix A (Informative) Movement at whole vehicle level ... 19
Appendix B (Informative) Guidelines for severity rating ... 21
B.1 General introduction ... 21
B.2 Description... 24
Appendix C (Informative) Example of hazard analysis and risk assessment of
steering function ... 27
C.1 General ... 27
C.2 Definition of dependent items: Overview of functional concepts ... 27
C.3 HAZOP analysis ... 27
C.4 Hazard analysis and risk assessment ... 28
Appendix D (Informative) Example of hazard analysis and risk assessment for drive
and transmission functions ... 31
D.1 General ... 31
D.2 Definition of dependent items: Overview of functional concepts ... 31
D.3 Hazard and operability analysis ... 32
D.4 Hazard analysis and risk assessment ... 33
D.5 Example details ... 42
Appendix E (Informative) Example of hazard analysis and risk assessment for
suspension control function ... 48
E.1 Introduction ... 48
E.2 Definition of dependent items: Overview of functional concepts ... 48
E.3 Hazard analysis ... 48
E.4 Hazard analysis and risk assessment ... 49
E.5 Other considerations ... 51
Appendix F (Informative) Example of hazard analysis and risk assessment for
braking and parking brake functions ... 52
F.1 General ... 52
F.2 Definition of dependent items: Overview of functional concepts ... 52
F.3 HAZOP analysis ... 53
F.4 Hazard analysis and risk assessment ... 55
F.5 Explanation and detail description of example ... 58
References ... 60
Road vehicles - ASIL determination guidelines for electrical
and electronic system
1 Scope
This document presents methods for determining the ASIL (Automotive Safety
Integrity Level) of electrical and electronic systems in road vehicles. Determining
ASIL (Automotive Safety Integrity Level) of electrical and electronic systems is
required by GB/T 34590.3-2022.
This document applies to safety-related systems, which incorporate one or more
electrical/electronic systems, as installed on mass-produced road vehicles other than
2 Normative references
The contents of the following documents constitute the essential provisions of this
document through normative references in the text. Among them, for dated
references, only the version corresponding to the date applies to this document; for
undated references, the latest version (including all amendments) applies to this
GB/T 34590 (all parts) Road vehicles - Functional safety
GB/T 34590.1-2022 Road vehicles - Functional safety - Part 1: Vocabulary (ISO
26262-1:2018, MOD)
GB/T 34590.3-2022 Road vehicles - Functional safety - Part 3: Concept phase
(ISO 26262-3:2018, MOD)
3 Terms and definitions
The terms and definitions as defined in GB/T 34590.1-2022, as well as the following
terms and definitions, apply to this document.
4 Hazard analysis and risk assessment
4.1 Identification of hazards
Hazard analysis and risk assessment (HARA) is an analysis process, that identifies
potential hazards and combines them with operating scenarios, to form a set of
specific hazard events, assessing the risk of each hazard event, to determine its ASIL
level and safety goals.
The definition of dependent item is a prerequisite for HARA. Hazard identification
can be achieved, through different hazard analysis techniques. This document gives
examples of hazard identification, using Hazard and Operability Analysis (HAZOP)
techniques. HAZOP is an exploratory analysis method, which can be used to identify
and evaluate the abnormal performance of dependent items; helps to check the
operation of dependent items at the vehicle level, in a structured and systematic way.
This analysis method adds appropriate introductory words to each function of
dependent item, to assume its different abnormal performance, which can lead to
hazards, meanwhile the hazards may be harmful to the occupants of the target
vehicle, other vehicles and their occupants, or other persons at risk, for example, the
potential hazards to the pedestrians, cyclists, or maintenance personnel in the vicinity
of the target vehicle.
Other effective methods can also be used, to identify relevant hazards. This
document does not recommend or support a specific hazard identification method.
Hazard identification is part of hazard analysis and risk assessment. Appendix A
describes the motion behavior of the vehicle, along different axes.
The following is an example of the application of a simple HAZOP method, to
identify hazards, which are caused by potential abnormal performance of dependent
items. For example, based on the function described in the definition of dependent
item, consider the role and capability of the dependent item actuator, then assume the
following abnormal function of the dependent item.
a) Loss of function - When required, no function is provided.
b) Provide wrong function, when required:
1) Wrong functions - More than expected;
2) Wrong functions - Less than expected;
3) Wrong function - Opposite direction.
c) Unexpected functions - Provide functions when not required.
e) When evaluating certain vehicle operating scenarios, a combination of factors
may be required, to cause a hazard to cause a specific injury. A vehicle
operation scenario may be composed of several factors; some of these factors
may be closely related. For the combination of factors that form the
prerequisites of a hazardous event, the correct value of the exposure
probability can only be calculated, after identifying the relationship between
each factor.
Example: For a scene with snow and ice, there is a high correlation with the
reduction of pavement friction. If the exposure probability of the scene with snow or
ice for the reduction of road friction is considered to be E2 levels independently of
each other, THEN without these two exposure probability factors rated as E2, an
exposure probability lower than E2 is equivalent (for scenes with snow and ice).
Treating these linked scenarios as independent might lead to inappropriate
downgrading of the exposure probability.
f) In the hazard analysis and risk assessment, do not consider the hazards that
have been covered by the safety regulations of the workplace for maintenance
personnel, as well as all hazards caused by dependent items that are being
repaired (see Note 1 in 4.1).
g) The defined hazardous events shall be specific enough, to ensure accurate
definition of the degree of harm and determination of controllability.
● A scene can be divided into several newly added specific scenes (may lead to
different S and C parameters);
● If the analysis results of multiple scenarios related to the same hazard are
similar or identical, these scenarios shall be combined for analysis;
● The above guidelines shall not be used, to artificially increase or decrease
exposure probability factors;
● This does not require an exhaustive examination of every possible
combination, it is sufficient to consider typical vehicle operating scenarios
and include those that lead to the highest ASIL level.
4.2.3 Step 2: Determine severity General information
According to GB/T 34590 (all parts), the "severity" level of potential harm, which is
caused by a specific hazardous event, can be defined as one of the four levels shown
in Table 5. These "severity" levels are a general classification, to provide guidance
on assigning an ASIL for a given hazardous event.
Often, "severity" levels are difficult to define exactly. Because, the "severity" result
hazard event. The development of this hypothetical scenario involves multiple
sources of information, including but not limited to expert analysis and judgment,
analysis of technical reports, particularly relevant accidents or analysis of test,
simulation and historical accident data. Appendix B provides some general
information, that can be used to assign the appropriate "severity" level to motion
control hazards, at a given vehicle level. Guidance on assignment of "severity" to crash-related hazards
During the hazard analysis and risk assessment process, assigning a "severity" level
requires expert assessment and consideration of a representative sample of various
traffic conditions, vehicle speeds, road conditions. Due to continued advances in
vehicle road and crash-related active and passive safety technologies, as well as
increased education and law enforcement on road user safety behaviors, analysis of
historical accident data tends to overestimate future measures targeting injury risk
AND may also do not contain suitable data for a new and different scenario. In these
cases, models can be used, to incorporate new scenarios in the context of historical
data, in order to better predict outcomes.
In general, the risk of injury to road users increases as the collision speed increases.
For planar collisions, the estimation of the velocity difference (ΔV), before and after
the collision, which is available in some historical accident databases, can assist the
evaluation of the "severity" of the accident. Consideration may be given to replacing
ΔV with other pre- and post-crash estimators (e.g., energy-equivalent velocity,
relative vehicle/object velocity), and to account for other crash characteristics such
as vehicle overlap and crush/intrusion. Appendix B provides some general guidance,
that may assist in the "severity" rating. For non-planar crashes, such as rollovers,
other available criteria depending on the hazard scenario can be used for the
"severity" assessment. The examples given in GB/T 34590.3-2022 can also be used,
as a reference for the assignment of "severity".
When determining the likely "severity" level of a crash from historical data, the
available data relevant to the system under development shall be analyzed. For
example, the balance between driver and vehicle control is changing, due to the
introduction of new active safety features, that automatically intervene in vehicle
dynamics, in certain specific crash-imminent environments. Therefore, as new
features are applied, current data may not reflect suitable results. When determining
the "severity" and ASIL level, the vehicle or system manufacturer shall analyze all
technologies, that are applied to a specific vehicle.
The "severity" levels of the hazardous events, that are representative of the various
scenarios considered, are to be documented in the hazard analysis and risk
assessment document.
Note 1: The "probability of exposure" needs to be considered to set the "severity" level
related to it. For a certain driving condition, if a value higher than the "severity" level
accidents, due to abnormal performance of the new system, if applicable, can be
compared with existing relevant accident data. The test subject's response behavior
to the hazard can then be assessed, to derive a preliminary level of controllability.
Overestimation of severity, probability of exposure, controllability parameters and
derived ASIL levels needs to be avoided, which may result in the reduction, or even
elimination, of functions or features that are beneficial to overall safety. Also avoid
underestimating severity, probability of exposure, controllability parameters, derived
ASIL level; otherwise, it may lead to insufficient safety requirements.
Appendix C provides examples of hazard analysis and risk assessment for electric
power steering (EPS) assistance functions.
Appendix D provides examples of hazard analysis and risk assessment for drive and
transmission functions.
Appendix E provides an example of a hazard analysis and risk assessment for a
suspension control function.
Appendix F provides examples of hazard analysis and risk assessment for brake and
parking brake functions.
4.3 Relationship between safety goals and safety status
When performing a Hazard Analysis and Risk Assessment, the output is a set of
safety objectives to ensure safe operation. The definition of these safety goals
considers avoiding or mitigating the potential harm, that may be caused by the
abnormal function of dependent items; the controllability measurement can be used
for the definition of safety goals. In a functional safety concept or a technical safety
concept, a safe state and associated safety measures are appropriately defined, to
achieve safety goals in the event of a failure of the dependent item. A "hazard
analysis and risk assessment" for a safe state is not always required, although the
hazards of a safe state can be derived from a "hazard analysis and risk assessment",
when the safe state coincides with a specific failure at the dependent item level.
Therefore, inconsistencies may arise, as both the safety goal and the safety state are
derived from consideration of failure behavior, at different points in the safety life
cycle. For the consistency of the safety profile, it is recommended to avoid the safety
state from violating the safety goal. This recommendation can be achieved, by
different formulations of safety goals and individual safety states. For example, a
safety goal could be "avoiding loss of the emergency braking function without
warning", whilst a safety state could be "disabling the function and notifying the
driver that the function is not available". In this safe state, an alarm mitigates the
consequences of loss of function, because the driver becomes aware that the function
is no longer available. The safety concept and HARA shall be consistent; otherwise,
it will have a negative impact on the safety file. If the safety status of this safety goal
Appendix B
Guidelines for severity rating
B.1 General introduction
This Appendix contains general information on assigning severity levels to vehicle
movement control hazards, that form part of the hazard analysis and risk assessment.
However, the content in this Appendix is not exhaustive and complete, which shall
be noted in the application.
The assignment of severity levels may involve a variety of sources of information,
including (but not mandatory or limited to): expert analysis and judgment, analysis
of specific relevant crash or crash test technical reports, simulation tests, or historical
crash data. Crash accidents, lab tests, road tests and other test data provide objective,
reliable, repeatable results. Simulation testing can provide direction, for pre-crash
scenarios and the relative contributions of many factors and interactions that
typically occur in crash events. Analysis of historical traffic accident data can
provide overall guidance on accident frequency and injury likelihood, for various
crash accident scenarios. However, inherent limitations make it impossible to make
precise predictions about future conditions.
For scenarios based on vehicle collision accidents, GB/T 34590.3-2022 defines the
concept of severity levels, based on the injuries suffered by personnel in collision
accidents (see Table B.1). GB/T 34590.3-2022 refers to the Abbreviated Injury Scale
(AIS) (which assigns a severity score of 0 ~ 6 to a single injury); takes the
"probability of injury" of a specific AIS level as an example, for assigning S0 ~ S3
severity levels. AIS that determines injuries to some or all road users, which are
involved in traffic accidents within a geographic location, is provided in some
historical accident databases. The collection of these accident data is usually a small
sample size; the case selection criteria vary by location.
In order to properly use damage ratings, which are derived from available accident
databases, the inherent limitations of the data sources shall be analyzed. The use of
accident data to support severity ratings requires a solid understanding of the data
collected and the limitations of the data available, to ensure that appropriate methods
are used and results are properly interpreted.
In general, literature publications and real-world analysis of different global crash
accident databases reveal the principle, that crash severity increases with relative
speed. For this reason, a higher driving speed may increase the possibility of a
collision accident, at a higher relative speed, which consequently lead to an increase
in the possibility of injury. However, there may be wide variation, when considering
the definition of speed intervals for the allocation of S0 ~ S3, based on different
sources of accident history data and specific crash screening criteria. These
variations may be due to regional differences in the traffic environment, changes in
sampling criteria for accident history data, or consideration of other factors such as
available crash attributes, crash types, occupant restraints equipped or used.
Technical and practical considerations, for the use of historical accident data
available in the literature or in specially developed analyzes to support severity
ratings, include:
- For deep accident databases, case sampling criteria and collected data vary
globally. The discrepancy in the analysis results of different databases may be
partly due to the variation of sampling criteria.
- The size of the sample size shall be considered, to better understand the
uncertainty in the accident sampling process, because the sampling process
varies with each available database. In particular, the low frequency of crashes
to the highest injury severity, in existing deep accident databases, may limit any
injury classification and thus the assignment of supporting severity.
- Selection of sample population (level of analysis). For a given set of crashes, the
damage ratings for the crash, for the vehicle involved, for the road user, for the
vehicle user may vary, based on the highest injury severity recorded. That is to
say, for any set of specific crash accidents, the specific severity injury rating,
which is calculated at the crash level, vehicle level or occupant level, is different.
- According to Note 1 of in GB/T 34590.3-2022, the severity classification
should take into account the possible injuries, which are suffered by all
participants involved in the accident.
- Many data, which is collected after the crash that may be related to the risk of
injury, are unknown before the crash, so these data cannot be used in the pre-
crash scenario. Examples include occupant characteristics (e.g., older occupants
are generally at higher risk of injury than younger occupants, in similar crashes)
and crash object characteristics (e.g., lightly loaded versus fully loaded large
commercial vehicles, the collision energy potential is different).
- Estimation of collision energy after a collision accident (for example: relative
vehicle speed, equivalent vehicle speed for obstacle avoidance):
● Calculations are not necessarily performed for each vehicle (for example: in
the current case of trailer collision accidents, if the collision object is a
medium/heavy truck, no relative speed estimation is available);
● Not necessarily consistent with the occupant impact pulse, which may be
- Although accidents are sampled, according to a well-defined method, there are
some deviations compared with official statistics, which can be compensated by
standardized and published weighting methods.
- For the use of the existing database to determine the accident severity of
vehicles still under development, it needs to consider the active and passive
safety and road infrastructure improvements, that occurred during this period.
One possible way to influence this progress is to consider only recent models or
vehicles with certain systems (e.g., ABS, ESC, air curtains, pedestrian
- A given hazardous condition may lead to a range of possible accident scenarios.
Analysts should avoid detailed analysis, that can only be predicted a posteriori
and cannot be predicted in hazard analysis and risk assessment.
Based on each individual analysis of the above data sources, a discrete set of velocity
ranges is generated for severity levels S0 ~ S3. Table B.1 shows the summary results
of the independent analysis, defining the minimum and maximum speed ranges for
each of the severity levels S0 ~ S3. Those ranges shown in Table B.1 reflect the
overlap of discrete velocity ranges, which are produced by different analyses, which
may be due to differences in available data sources and analysis methods. These
differences may include:
- Regional driving mode and environment;
- Crash selection criteria for the deep accident database;
- Extrapolation from deep accident databases to wider populations;
- Composition of regional vehicle teams;
- Vehicle selection criteria (for example: vehicle age, equipment for specific
vehicle technologies, such as airbags);
- Definition of collision type (frontal collision, side collision, rear collision) (for
example: damaged plane, direction of impact force);
- Classification of collision types (for example: amount of overlap);
- Included collision objects and classifications;
- Passenger wrapping (e.g., seat position, restraint use);
- Occupant characteristics (for example: age);
- Included non-occupant injury results (for example: pedestrians, occupants on
other vehicles).
Appendix C
Example of hazard analysis and risk assessment of steering function
C.1 General
This Appendix provides examples of hazard analysis and risk assessment for electric
power steering (EPS) assistance functions. C.3 provides a HAZOP analysis, to
identify abnormalities in EPS function, that correspond to hazards at the vehicle
level. C.4 provides some examples of EPS malfunctions, resulting hazards at the
vehicle level, associated ASIL levels. This Appendix does not represent a transition
to functionally complete hazard analysis and risk assessment, but rather a subset of
functional safety hazards for EPS functions, to provide guidance.
Note: This Appendix contains examples of ASIL levels for selected hazardous events. The
determination of ASIL level shall be determined, through negotiation between relevant
parties. Appendix B of GB 17675-2021 gives the minimum requirements for the steering
C.2 Definition of dependent items: Overview of functional concepts
The EPS function assists the driver in providing directional control of the vehicle to
the steering wheels, while reducing the amount of steering effort required by the
driver to steer the vehicle. EPS measures driver intent at the steering wheel;
processes it simultaneously with other inputs from the vehicle, to provide steering
torque assistance. The scope of this analysis is assuming that, the EPS system has a
mechanical steering connection; when the power assist function of the EPS is lost, it
can still support the driver to steer the vehicle manually.
C.3 HAZOP analysis
Table C.1 lists the HAZOP analysis, to identify dysfunctional manifestations of the
EPS assist function. Table C.2 lists the mapping from EPS functional abnormalities
to vehicle hazards.
Source: Above contents are excerpted from the PDF -- translated/reviewed by: www.chinesestandard.net / Wayne Zheng et al.