IEEE Consumer Electronics Magazine - April 2017 - 75

HARDWARE ARCHITECTURAL METRICS CALCULATION
Hardware architectural metrics can be used to determine if a
designed system meets given ASIL requirements. For example, PMHF can be used in a four-step procedure to determine
a design's conformance to given ASIL requirements:
1) overall failure rate estimation of hardware components
composing an automotive system
2) substituting the determined failure rates in the automotive
system's model (e.g., Markov model)
3) determining the system reliability from the model
4) comparison of the calculated system's reliability with target values for a given ASIL [reliability values corresponding to a given ASIL can be determined assuming a failure
rate distribution (e.g., exponential distribution)].
Alternatively, the calculation of other hardware architectural metrics (i.e., SPF metric and LF metric) provides objective evidence that a given hardware design has achieved a
safety goal, as summarized in the following four steps [12]:
1) failure rate estimation of SPF and latent MPF
2) diagnostic coverage estimation of the safety mechanism
3) calculation of SPF and LF metrics
4) comparison of calculated hardware architectural metrics
with target values for a given ASIL.
These steps are described in the following sections.

FAILURE RATE ESTIMATION OF SPF AND LATENT MPF
ISO 26262 suggests that the failure rate m of a hardware element can be determined in any of the following ways:
▼▼ using a recognized industry source (e.g., IEC 61709, IEC
TR 62380, MIL-HDBK-217F, NPRD95, EN 50129
Annex  C, EN 62061 Annex D, MIL-HDBK-338, RAC
FMD97, etc.)
▼▼ utilizing statistics based on tests or field returns
▼▼ employing expert judgement founded on an engineering
method.
The hardware architectural metrics calculation also requires
determining failure rates for different failure modes of a hardware
element. Practically, hardware architectural metrics can be determined by estimating failure rates for only a few failure modes of
the hardware element, which are m SPF, m RF, and m MPFL . The following equations are used to determine these failure rates:
m SPF + m RF = m· (1 - c),

(6)

where c denotes the diagnostic coverage of a safety mechanism for SPFs, and
m MPFL = m· (1 - c l),

(7)

where c l denotes the diagnostic coverage of a safety mechanism for latent MPFs.

26262 specifies minimum diagnostic coverage requirements for
a safety function. For example, ASIL-B, ASIL-C, and ASIL-D
safety functions require low ^260%h, medium ^290%h, and
high ^299%h diagnostic coverage [5]. Diagnostic coverage for
different fault detection techniques varies. For example, selftests by software provide low diagnostic coverage, watchdogs
provide medium diagnostic coverage, whereas comparators and
majority voters provide high diagnostic coverage. Similarly, onebit redundancy in random access memory (RAM) can attain a
low diagnostic coverage, whereas error detection codes and
block replication can provide comparatively higher diagnostic
coverage for RAM errors.

CALCULATION OF SPF AND LF METRICS
After determining failure rates of a hardware element and
diagnostic coverage of the safety mechanism, we can obtain
SPF and LF metrics using (1) and (4), respectively.

COMPARISON OF CALCULATED HARDWARE
ARCHITECTURAL METRICS WITH TARGET ASIL VALUES
To objectively claim the compliance of a product (i.e., incorporating a safety mechanism using a given hardware element)
with ISO 26262, the determined hardware architectural values are compared with target ASIL values of the implemented safety function.

RESEARCH CHALLENGES AND FUTURE DIRECTIONS
Although efforts have been made toward development of safety mechanisms and safety standards for automobiles, various
challenges and issues related to safety and dependability of
cybercars remain. In this section, we discuss several research
challenges and future research directions for realizing safe and
dependable cybercars.

SOFT ERROR RATES
There has been an increase in soft error rates (SERs) due to
modern transistor and device scaling trends. Device scaling permits lower operating voltages that can offer energy savings but
also decrease the energy needed to generate a voltage pulse at a
logic gate's output or to flip the value stored within a sequential
element. Hence, low-energy particle strikes that did not present
an issue in previous technology generations could engender soft
errors in current and subsequent technology generations. Furthermore, the rate of particle strikes escalates exponentially
with the decrease in the particles' energy levels. Consequently,
the rate of particle strikes that can possibly impact the microprocessors' logical operations increases significantly with each
new process technology. To minimize the impact of SERs on
availability of safety-critical automotive systems, various FT
techniques can be leveraged, such as acceptance tests, FT by
redundant multithreading (FT-RMT), N-version programming,
and checkpointing.

DIAGNOSTIC COVERAGE ESTIMATION
OF SAFETY MECHANISM

ECU ARCHITECTURES

Diagnostic coverage c of a safety mechanism depends on hardware/software techniques employed by the mechanism. ISO

To meet the dependability and performance requirements stipulated by automotive standards, automotive OEM suppliers have
APRIL 2017

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IEEE Consumer Electronics Magazine

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