
The Importance of Sensor Technology in Autonomous Vehicles
To avoid chip or software failures, manufacturers must adhere to automotive functional safety criteria at the earlier stages of sensor manufacturing.
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CIO Applications Europe | Friday, October 01, 2021

Sensor degradation, agreement on industry standards, and maintenance/servicing of the software's cybersecurity defenses during the vehicle's lifetime are all difficulties that tech suppliers and automakers are factoring in to enable developments in autonomous vehicles.
Fremont, CA: To avoid chip or software failures, manufacturers must adhere to automotive functional safety criteria at the earlier stages of sensor manufacturing. The automotive standard ISO 26262 specifies the development process that automotive OEMs and suppliers must follow and record for their products to be certified functionally safe. As a result, automotive OEMs and suppliers may ensure that their devices will perform as expected, when expected, by adhering to ISO 26262.
Sensor deterioration is another facet of the ever-changing sensor world. Sensor degradation is an unavoidable element of the autonomous vehicle equation, especially given that today's vehicles have a 10- to 15-year lifespan. General wear and tear of sensors, their severe operating environments, and degradation of other electronic system elements are the leading causes of degradation.
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For the whole intended lifespan of the vehicle, automakers and technology providers will need to factor in the ability of installed sensors for tasks such as LiDAR, cameras, ultrasound, and other sensors to work at the same, if not higher, level than when the car was new. They'll also have to figure out what happens if the sensor fails. OEMs must model and design semiconductors and other components within the vehicle to create predictive failure rates and alternatives in various situations to combat degradation.
When it comes to ensuring the safety of autonomous car sensors, there are several variables to consider. Hacking into an autonomous car is always a danger that should be handled, but a less evident security element is attackers manipulating the vehicle's machine-learning system to behave in a harmful manner.
System designers must protect system operations while finding the correct balance in terms of driver notifications. As the complexity and capability of these devices develop, the number of ways in which cybersecurity attacks might occur will increase in proportion. To protect against these atypical assaults, designers and manufacturers will need to upgrade their defenses and handle these types of unforeseen consequences.
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