What is ADAS? A Primer From Automotive Expert Robert Bielby
Advanced Driver Assistance Systems (ADAS) are all the rage. Increasingly, consumer car purchasing decisions are based on ADAS features as compared to vehicle style, engine size, or branding, which historically has been the case.
A quick internet search will provide one with an obligatory understanding of the capabilities associated with each ADAS level. A high-level summary of the different ADAS levels is as follows:
Level 0: No Driving Automation
Level 1 - Driver Assistance
Level 2 - Partial Driving Automation
Level 3 - Conditional Driving Automation
Level 4 - High Driving Automation
Level 5 - Full Driving Automation
What is profound, at least in my mind, is that there is no consistency regarding what specific ADAS capabilities are associated with a given ADAS level. Furthermore, the industry has introduced yet a new level called L3+. Not quite High Driving Automation but approaching autonomy. Apparently, good enough isn’t good enough.
The general goal of ADAS is to improve the overall safety of the driving experience. To keep this tone upbeat, I won’t focus on the mortality rate associated with driving, however, one key point to note is that it is estimated that 97% of all auto accidents are due to driver negligence. The key takeaway is that most accidents can be easily avoided through the use of technology, which is what ADAS brings to the table.
At the lower ADAS levels, the goal is to provide the driver with safety assistance features so the driver is more aware of their surroundings and can respond to the environment appropriately. Features like blind spot detection or backup cameras, typically considered Level 1/ Level 2 don’t have any physical impact on the operation of the vehicle itself but provide valuable insights to the driver to avoid what may have otherwise been a significant incident.
The progression from Level 2 to Level 3 and beyond is significant in terms of the level of electronic content that is employed to actively prevent accidents leading to the point where, at levels 4 and 5, the vehicle is driving autonomously without some level or any level of human intervention.
The impact in the reduction of accidents associated with each progressive ADAS level along with the benefits of freedom that comes from emancipating the need for a driver are profound. These benefits range from enabling a “greener” relationship between our cars and the environment to providing mobility to those who otherwise might be immobile.
The technology that is required to pull off these increasing levels of ADAS is pushing the state-of-the-art in every category. The overused phrase “data center on wheels” is an understatement regarding the level of complexity and technology that is under the hood of the modern car. Achieving level 3 ADAS typically requires 18 or more high-resolution cameras in addition to a dozen radar sensors and typically a LIDAR (light detection and range) sensor. The underlying computing engine that processes these massive amounts of sensor data typically employs AI computing that delivers 100s of Trillion - Tera Operations Per Second (TOPs).
To date, few passenger vehicles have been certified to be Level 3 compliant. And yet, Level 3 still requires a driver to be present and ready to take over control of the vehicle in the case where the capabilities of the electronics are exceeded in their ability to control the vehicle – a far cry from the vision of the self-driving car. Achieving Level 3 ADAS and beyond is pushing semiconductor process technology limits – TSMC has announced an automotive-qualified 3 nm process technology expressly to address the demands of this market as the number of transistors and their associated thermal footprint have become meaningful. One of the hottest technologies – chiplets – is also being readily embraced by the automotive market to most effectively address the mismatch in technologies required to achieve the vision of the self-driving car.
The emerging industry standard UCIe™ (Universal Chiplet Interconnect Express™) announced a 1.1 version of the specification expressly to address the automotive application space focusing on areas such as data integrity and reliability. More about chiplets and the UCIe specification will be discussed in future blogs. In short, outside of quantum computing, it seems like the automotive market is taking a leading role in defining the future of many of the emerging technologies and is a good reason to follow the exciting innovations that the automotive market is now “driving.”
Advanced Driver Assistance Systems (ADAS) are all the rage. Increasingly, consumer car purchasing decisions are based on ADAS features as compared to vehicle style, engine size, or branding, which historically has been the case.
A quick internet search will provide one with an obligatory understanding of the capabilities associated with each ADAS level. A high-level summary of the different ADAS levels is as follows:
Level 0: No Driving Automation
Level 1 - Driver Assistance
Level 2 - Partial Driving Automation
Level 3 - Conditional Driving Automation
Level 4 - High Driving Automation
Level 5 - Full Driving Automation
What is profound, at least in my mind, is that there is no consistency regarding what specific ADAS capabilities are associated with a given ADAS level. Furthermore, the industry has introduced yet a new level called L3+. Not quite High Driving Automation but approaching autonomy. Apparently, good enough isn’t good enough.
The general goal of ADAS is to improve the overall safety of the driving experience. To keep this tone upbeat, I won’t focus on the mortality rate associated with driving, however, one key point to note is that it is estimated that 97% of all auto accidents are due to driver negligence. The key takeaway is that most accidents can be easily avoided through the use of technology, which is what ADAS brings to the table.
At the lower ADAS levels, the goal is to provide the driver with safety assistance features so the driver is more aware of their surroundings and can respond to the environment appropriately. Features like blind spot detection or backup cameras, typically considered Level 1/ Level 2 don’t have any physical impact on the operation of the vehicle itself but provide valuable insights to the driver to avoid what may have otherwise been a significant incident.
The progression from Level 2 to Level 3 and beyond is significant in terms of the level of electronic content that is employed to actively prevent accidents leading to the point where, at levels 4 and 5, the vehicle is driving autonomously without some level or any level of human intervention.
The impact in the reduction of accidents associated with each progressive ADAS level along with the benefits of freedom that comes from emancipating the need for a driver are profound. These benefits range from enabling a “greener” relationship between our cars and the environment to providing mobility to those who otherwise might be immobile.
The technology that is required to pull off these increasing levels of ADAS is pushing the state-of-the-art in every category. The overused phrase “data center on wheels” is an understatement regarding the level of complexity and technology that is under the hood of the modern car. Achieving level 3 ADAS typically requires 18 or more high-resolution cameras in addition to a dozen radar sensors and typically a LIDAR (light detection and range) sensor. The underlying computing engine that processes these massive amounts of sensor data typically employs AI computing that delivers 100s of Trillion - Tera Operations Per Second (TOPs).
To date, few passenger vehicles have been certified to be Level 3 compliant. And yet, Level 3 still requires a driver to be present and ready to take over control of the vehicle in the case where the capabilities of the electronics are exceeded in their ability to control the vehicle – a far cry from the vision of the self-driving car. Achieving Level 3 ADAS and beyond is pushing semiconductor process technology limits – TSMC has announced an automotive-qualified 3 nm process technology expressly to address the demands of this market as the number of transistors and their associated thermal footprint have become meaningful. One of the hottest technologies – chiplets – is also being readily embraced by the automotive market to most effectively address the mismatch in technologies required to achieve the vision of the self-driving car.
The emerging industry standard UCIe™ (Universal Chiplet Interconnect Express™) announced a 1.1 version of the specification expressly to address the automotive application space focusing on areas such as data integrity and reliability. More about chiplets and the UCIe specification will be discussed in future blogs. In short, outside of quantum computing, it seems like the automotive market is taking a leading role in defining the future of many of the emerging technologies and is a good reason to follow the exciting innovations that the automotive market is now “driving.”
