Although the era of automated cars seamlessly whisking us from home to work remains years away, much of the foundational effort to enable driverless vehicles and assisted driving is well underway. Importantly, the automotive industry needs to build trust to ensure users are ready to accept various levels of assistance and automation. Underpinning this are a series of regulations that impose criteria and enable risk classification for road vehicles.
One key system of classification is the Automotive Safety Integrity Level (ASIL). ASIL is defined by the ISO 26262 standard and is adapted from Safety Integrity Level (SIL) guidance published in IEC 61508. The ASIL rating is calculated by putting each vehicle system or component through a full hazard analysis and risk assessment (HARA) process which identifies potential malfunctions and dangers that could result in failures. At a system level, for example for airbags, HARA is used to assess the risks that could result from failures.
The level of risk that is determined in the HARA procedures aligns with what the consequences of component or system failure could be. Severe consequences include the risk of injury or heavy damage and whether there is a role for the driver in averting failure. The ASIL rating, which runs from level A to level D where A represents the lowest risk, enables developers and designers to keep their projects on track.
The increasing importance of ASIL ratings for automotive GNSS
A further classification for quality management (QM) addresses non-hazardous aspects of a vehicle that only require standard quality management compliance. As innovation continues, ASIL rating is increasingly seen as best practice in the automotive industry and a way to assure users that vehicles are ready to utilize self-driving features. There is also flexibility in the rating with components rates ASIL B, for example, able to have their level raised or lowered with additional hazard analyses if integrated with other systems.
Many of these issues were discussed in a recent Quectel Masterclass which took an in-depth look at how to navigate the requirements of ASIL for GNSS automotive devices. Presented by Christian Schmidt the Project Lead for Functional Safety at Trimble, and Brandon Oakes, the Director of Sales for Short Range and GNSS, North America, at Quectel, the Masterclass is titled ‘How to navigate ASIL requirements for GNSS automotive solutions’.
The Masterclass provides an introduction to ASIL requirements and ASIL hardware and software solutions. In addition, the session includes a detailed explanation of how to achieve an ASIL B rating for automotive solutions by combining Quectel’s LG69T (AB) raw data GNSS module with Trimble’s ProPoint positioning engine and RTX correction service.
Autonomous and assisted driving offer huge potential for enhanced safety and greater productivity for people as they travel. The importance of a rigorous system to assure users of the capabilities of the latest vehicles and to help OEMs mitigate risks is essential. Adoption of the ASIL risk classification achieves these goals so check out this Masterclass to increase your knowledge and understand the benefits of engaging with ASIL ratings.
Source: Quectel blog
