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Micron technology glossary

ADAS

Advanced driver-assistance systems (ADAS) are becoming an integral part of both the tech and automotive sectors. As ADAS evolves, it presents unique challenges and opportunities for innovation, particularly through the integration of artificial intelligence (AI). 

Learn more about ADAS and discover how Micron is leading the enduring and transformative technologies that shape ADAS. 

What is ADAS?

ADAS definition: Advanced driver-assistant systems, or ADAS, are technologies that provide assistance to vehicle drivers to make the journey safer. 

ADAS technology aids manual driving to reduce the likelihood and occurrence of traffic accidents. For this reason, ADAS is crucial in modern vehicles. 

According to the World Health Organization and its​ ​report on road safety in 2023, the number of traffic fatalities dropped from the previous year. The recent increase in ADAS technology and its implementation has likely contributed to lowering global traffic fatalities. 

The majority of new cars sold now include some form of ADAS. The variety of ADAS technologies that are part of modern cars ranges from rearview cameras to parking assistants and antilock brakes. 

The advancement of ADAS technologies also means that new and improved versions of existing ADAS tools can further improve automotive safety. This technology has a clear use case and is developing rapidly to improve the safety of drivers and pedestrians alike. 

How does ADAS work?

With most motor vehicle accidents occurring due to human error, the main purpose of ADAS technology is to negate human error in the best way possible. Cameras and sensors provide this added safety by, for example, identifying objects on the road before the driver does. 

If objects on the road are identified, the ADAS employs automatic emergency braking (AEB) as a safety measure. Because cars with ADAS have more precise sensing capabilities than humans, they can help keep both drivers and pedestrians safer. 

ADAS vehicles use a variety of applications that are partitioned into systems on a chip or SoCs. Electric controller units (ECUs) then connect these sensors to actuators to ensure that the ADAS technologies are working properly.

ADAS is also the driving force behind the ever-growing popularity and use of self-driving or autonomous vehicles. By incorporating technologies such as ultrasound and LIDAR (light detection and ranging) with camera systems, ADAS enables self-driving cars to rapidly interpret their surroundings, enhancing safety and reducing motor vehicle accidents. 

Efforts to make ADAS as effective as possible within vehicles are also driving the evolution of a centralized architecture that integrates and processes data from multiple sensors and subsystems efficiently. 

Centralized vehicle architectures, which require robust memory and storage solutions to function effectively, also simplify system design by consolidating multiple functions into a single, integrated system. 

This simplified approach not only enhances performance and reliability, but it also maximizes the potential of ADAS in cars, ensuring that drivers, passengers and pedestrians are safer than ever on the roads. 

Micron is leading and shaping centralized vehicle architectures with its 4150AT SSD, which features the world’s first automotive-class SSD with quad-port support. 

This capability allows any centralized storage system to directly connect up to four SoCs to a single SSD without the need for special switching circuitry, an approach that simplifies design and reduces storage requirements. The 4150AT SSD’s flexibility supports evolving system architectures, ensuring high performance, reliability and functional safety compliance. 

Micron’s automotive LPDDR5X complements these benefits by enhancing the potential of ADAS in vehicles and ensuring the safety of others on the road. 

What is the history of ADAS?

ADAS technologies have existed for many years, but their complexity and influence on road safety for both vehicle users and pedestrians has gradually been increasing in recent years. 

  • 1971, antilock brakes: The introduction of antilock brakes was the breakthrough of ADAS technology and paved the way for further safety development in vehicles. 
  • 1985, traction control: Traction control was introduced commercially just over a decade after antilock brakes, further improving vehicle safety. 
  • 1999, adaptive cruise control: While road safety was improved, autonomous cars still seemed far into the future. However, Mercedes introduced adaptive cruise control, a technology that provides a glimpse into what autonomous vehicle technology could be. 
  • 2000, lane departure warning systems: Advancements in sensor technology led to the development of lane departure warning systems. These systems alert drivers if they drift from their lanes. 
  • 2010s, automatic emergency braking: The integration of computer vision and radar technologies enabled automatic emergency braking systems, which can detect obstacles and apply brakes to prevent collisions. 
  • 2014, autonomous cars in the mainstream: The push for the normalization of autonomous vehicles gained momentum with the introduction of systems that reduce the overall workload of drivers by automatically accelerating, braking and steering when activated. 
  • 2020s, enhanced object detection and classification: Higher-resolution sensors and AI integration have significantly improved object detection and classification, enhancing the capabilities of ADAS and autonomous systems. 

What are key types of ADAS?

ADAS is divided into different types based on the level of assistance provided to vehicle drivers. Every increasing level of ADAS offers more assistance to the driver. 

  • Level 0 ADAS equates to the lowest level of assistance for drivers. ADAS technologies that are considered to be level 0 include parking sensors and blind spot information. 
  • Level 1 and level 2 ADAS technologies still require drivers to do most of the work, but they offer more assistance than level 0 does. These technologies can range from emergency braking assistance to autonomous parking. 
  •  Level 3 is the start of drivers being able to carry out other tasks rather than purely focusing on driving. Automated lane-keeping systems (ALKS) allow vehicles to maintain a steady course within a lane under certain conditions without the need for constant driver intervention. ALKS is just one of the technologies that highlights how drivers can focus on other tasks. However, drivers still have to be attentive to intervene when necessary. 
  • Level 4 is a step toward full autonomy. Cars with these specific ADAS technologies can navigate streets and highways with ease. 
  • Level 5 refers to total autonomy within the vehicle, meaning that the vehicle can operate without any human intervention. 

How is ADAS used?

There are many uses for ADAS and autonomous vehicles, and they are being used in many fields today. 

One significant application of autonomous vehicles is in the transportation industry. Self-driving cars are now available to chauffeur passengers from points A to B, making it increasingly common to see self-driving taxis in the U.S. These autonomous taxis are designed to reduce traffic congestion and enhance passenger safety. 

There is also a push for self-driving trucks to become more prevalent on roads worldwide. Because of the demanding nature of their work, long-haul drivers often face challenges that can lead to human error. Automated trucks can either assist drivers or take over driving entirely, ensuring more efficient and safer transportation of goods. 

Frequently asked questions

ADAS FAQs

One major limitation is that ADAS technology can be somewhat limited in inclement weather, which can reduce its benefits to driver and passenger safety.

If ADAS is not properly calibrated, it can compromise technology functions and, in some instances, cause vehicles to lose control.

ADAS improves vehicle safety by providing features such as adaptive cruise control, lane-keeping assistance and automatic emergency braking. All of these feature help prevent accidents and reduce the severity of collisions.

While some ADAS features can be retrofitted to older vehicles, retrofitting often requires significant modifications and the systems may not be as effective as those integrated into newer models.

ADAS uses advanced algorithms and machine learning to handle complex driving scenarios, such as navigating through heavy traffic, detecting pedestrians or responding to sudden changes in road conditions.