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Advanced Driver Assistance System [ADAS] Everything You Needs to Know


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Introduction to ADAS:

Advanced Driver-Assistance Systems (ADAS) are intricate systems that perform various computer vision tasks, such as semantic segmentation, object detection, and image categorization.

Technology-based elements called advanced driver assistance systems are meant to increase vehicle security. Through enhanced indicators and automated systems, these systems improve safety and response times to possible hazards.

While some of these systems can be added later to customize the automobile to the driver, aftermarket features and even whole systems can be integrated into some vehicles as standard equipment.

When embedded electronics in an automobile communicate with one another using the CAN bus, the system may be open to security risks.

Regarding ADAS security, FPGAs can be used to execute system authentication using a hardware root-of-trust or to use encryption for intra-vehicle communication.

Due to its excellent performance and energy economy, FPGA is a viable option for deep learning-based computer vision accelerators.

However, creating a high-performance FPGA accelerator takes a lot of time to compile and necessitates a solid understanding of fundamental hardware principles.

Overlays can solve the issues by utilizing a hardware design and a compiler to accelerate software programs. Nearly all of the common compute layers for learning-based ADAS are present in the overlay architecture.

Additionally, we develop a compiler that can automatically translate high-level neural network descriptions from deep learning frameworks like Caffe and Tensorflow into FPGA programmable instructions, which our overlay architecture can run without reprogramming.

Studies demonstrate that our overlay can process learning tasks in ADAS with less memory utilization and minimal latency.

What is ADAS?

The phrase “advanced driver assistance systems,” or ADAS, refers to the expanding set of safety features intended to increase the safety of drivers, passengers, and pedestrians by lowering the severity and overall frequency of motor vehicle accidents.

To prevent accidents, ADAS can alert drivers to prospective hazards, step in to help the driver maintain control, and, if necessary, lessen the severity of an accident if it is unavoidable.

To a certain extent, ADAS makes up for our errors, including inattention, incorrect control inputs, and outright idiocy.

Humans find it difficult to recognize that we are fallible, but ADAS is available to assist. That is, at least, the concept.

The ADAS umbrella has grown increasingly broad as related ADAS technologies are created and improved. Automakers try to attract customers with a wider variety of features emphasizing convenience and safety.

The word “ADAS” today refers to various passive and active systems provided as options or standards for an increasing number of new cars and commercial vehicles.

These systems are becoming more widespread and comprehensive. Some ADAS features have been so successfully tested and confirmed to work that they are now required in some parts of the world.

Today’s ADAS goes beyond everyday comfort and convenience for drivers and passengers to accident and injury mitigation and prevention.

The boundaries are a little hazy now, and it can often be difficult to tell where the scope of ADAS begins and stops.

What’s the Purpose of ADAS?

Advanced Driver Assistance Technologies (ADAS) are passive and active safety systems created to eliminate human mistakes from driving various automobiles.

ADAS systems use cutting-edge technology to aid drivers while driving and enhance their performance.

ADAS uses various sensor technologies to understand the environment surrounding the car and, if necessary, either inform the driver or take action.

ADAS system Self driving car
ADAS system Self driving car while reading a book – Logic Fruit Technologies

Image Credit:

ADAS systems are currently used in military, agricultural, construction, and commercial vehicles, as well as cars, trucks, and buses.

The National Highway Traffic Safety Administration reports that more than 36,000 Americans lost their lives in car accidents in 2019 alone. According to the NHTSA’s Traffic Safety Facts Research Note from August 2016, 94% of the collisions resulted from human error or mistakes made by the driver.

Given this fact, it is simple to picture how many lives could be spared if ADAS systems effectively prevented many of these mistakes.

In fact, according to estimates from the IIHS (the Insurance Institute for Highway Safety), even the ADAS technology currently in use might stop or mitigate the impact of 1.8 million accidents annually, potentially sparing up to 10,000 lives.

There are many levels of ADAS, from primary backup cameras and blind-spot warning sensors to lane departure warning systems, adaptive cruise control, self-parking, and more.

Genuinely autonomous vehicles, sometimes known as “self-driving,” which do not require a human driver, will someday be the ultimate extension of ADAS. Although completely driverless vehicles are still years away, ADAS safety measures are already making driving much safer.

Businesses from all around the world are investing billions of dollars in the creation of ADAS technologies. General Motors, Volvo, Toyota, Ford, Volkswagen, Tesla, BMW, and Audi exist. Almost every vehicle manufacturer worldwide is on the lengthy list.

Since ADAS technology is developing quickly, nobody wants to fall behind.

Why is ADAS Important?

The majority of traffic collisions are the result of human mistakes. These cutting-edge safety systems automate and improve several parts of the driving experience to improve safety and safe driving practices.

ADAS has been demonstrated to lower the number of traffic deaths by lowering the possibility of human mistakes.

Those that automate driving, such as automatic emergency braking systems, and those that aid increase drivers’ awareness, like lane departure warning systems, can be divided into two primary types.

These safety systems’ main goal is to make roads safer by generally lowering the number of traffic accidents and minimizing vehicle injuries.

Additionally, they restrict the number of insurance claims resulting from minor mishaps that only cause property damage and no injuries.

How Does ADAS Work?

ADAS functions by alerting the driver of risk or even intervening to avert a collision.

Autonomous driving assistance systems (ADAS) enable vehicles to perceive their surroundings, interpret this data fast and correctly in a computer system and then give the driver the appropriate output.

ADAS-equipped vehicles include a variety of cutting-edge sensors that support the human driver’s eyes, ears, and decision-making.

Do you have night vision? Although not very well, RADAR can. Before putting your car in reverse, can you echolocate like a bat or a dolphin to check whether there is a child behind it? But SONAR sensors can, so no.

Can you see everything at once? No, but LiDAR sensors and cameras can. Do you always know your precise latitude and longitude? No, but several satellite constellations that provide global positioning services can send that data and more to your car.

Different types of ADAS sensors used in today's autonomous vehicle
Different types of ADAS sensors used in today’s autonomous vehicle

Several sensors, interfaces, and a potent computer processor make up the ADAS system architecture, which integrates all the data and makes real-time choices.

The onboard ADAS computers use this data to prioritize and take appropriate action after scanning the area around the vehicle.

They are saving lives by averting accidents. These innovations will enable fully autonomous vehicles.

What are some ADAS Applications?

Shatter-resistant glass, three-point seatbelts, and airbags, among other significant vehicle safety advancements from the past, were passive safety features created to reduce injuries during an accident.

With the aid of embedded vision, ADAS systems today actively increase safety by lowering the frequency of accidents and occupant injuries.

A novel AI function that uses sensor fusion to recognize and process things is integrated into the vehicle’s cameras. With image recognition software, ultrasonic sensors, lidar, and radar, sensor fusion combine massive volumes of data, like how the human brain processes information.

Physically, this technology can react more quickly than a driver ever could. It can instantly evaluate streaming video, identify what it reveals, and decide how to respond.

Some of the most typical ADAS applications are as follows:

Adaptive Cruise Control:

On the highway, where drivers may find it challenging to check their speed and other vehicles continuously, adaptive cruise control is beneficial. Depending on the behavior of nearby objects, advanced cruise control can automatically accelerate, slow down, and occasionally halt the car.

Glare-Free High Beam and Pixel Light:

High beams and pixels that don’t cause glare employ sensors to adjust to the surrounding environment and darkness without disturbing oncoming vehicles. To prevent briefly blinding other road users, this innovative headlight program detects the lights of other vehicles and guides the vehicle’s lights away.

Adaptive Light Control:

The vehicle’s headlights are adjusted to the ambient lighting with adaptive light control. Depending on the surroundings and darkness around the car, it modifies the headlights’ brightness, rotation, and direction.

Automatic Parking:

Automatic parking warns drivers of hidden spaces so they know when to turn the wheel and stop. Compared to conventional side mirrors, vehicles with rearview cameras have a more incredible view of their surroundings. Some systems may even accomplish parking tasks automatically and without the driver’s assistance by merging the input from several sensors.

Autonomous Valet Parking:

Automated valet parking is a novel technology that controls vehicles in parking lots using car sensor meshing, 5G network connection, and cloud services. The vehicle’s location, where it has to travel, and how to get there safely are all provided via sensors. Until the car is securely parked, all this data is meticulously assessed and used to conduct drive acceleration, braking, and steering.

Navigation System:

Drivers can follow a route while focusing on the road with the assistance of voice prompts and on-screen instructions provided by car navigation systems. Some navigational tools can show precise traffic information and, if necessary, suggest an alternative route to avoid gridlock. Even heads-up displays may be available in advanced systems to lessen driver attention.

ADAS: Navigation System of Self driving car

Image Credits

Night Vision:

Drivers can see objects at night that would otherwise be challenging or impossible to view, thanks to night vision devices. Both active and passive night vision systems use thermal energy from moving vehicles, animals, and other objects. Active night vision systems project infrared light.

Unseen Area Monitoring:

Unseen area detection systems use sensors to give drivers access to crucial information that would otherwise be difficult or impossible to gain. Some systems will alert the driver if they attempt to enter an occupied lane or when they identify an object in the driver’s blind spot.

Automatic Emergency Braking:

Sensors are used in automatic emergency braking to determine whether the driver is about to collide with another car or another object on the road. This program can gauge the proximity of oncoming cars and warn the driver of any hazard. Some emergency braking systems can reduce speed, tighten seat belts, and activate adaptive steering to avert a crash.

Crosswind Stabilization:

This ADAS function, which is still relatively new, helps the car combat powerful crosswinds. When a strong wind is blowing across the vehicle while it is moving, the sensors in this system may detect it and apply brakes to the wheels that are being impacted.

Driver Drowsiness Detection:

Drivers are alerted to fatigue or distraction on the road through driver drowsiness detection. There are a few techniques to tell if a motorist is losing concentration. Sensors can examine the driver’s head movement and heart rate to see if they signify tiredness. Other systems send motorist alerts that resemble lane-detecting warning signals.

Driver Monitoring System:

Another tool for assessing the driver’s attentiveness is the driver monitoring system. The video sensors can detect if the driver is drifting or keeping their eyes on the road. Driver warning systems might sound an alarm, vibrate the steering wheel, or use flashlights to warn the driver. Sometimes the car would go to the extreme of entirely stopping the car.

5G and V2X:

With this cutting-edge 5G ADAS capability, commonly referred to as V2X, communication between the vehicle and other vehicles or pedestrians is made more dependable and responsive.

For real-time navigation, millions of automobiles today are linked to cellular networks. By enhancing current techniques and the cellular network, this application will boost situational awareness, control or advise speed reductions to account for traffic congestion, and deliver real-time GPS map updates.

V2X must provide over-the-air software updates for the wide variety of software-driven systems in cars that are currently available, including map updates, bug patches, security upgrades, and other updates.

Advantages of ADAS include:

  • Automated safety system modification and improvement to encourage safer driving among the general public ADAS employ technology to warn drivers of prospective hazards or take over control of the vehicle to avoid such danger to prevent collisions.
  • Adaptive features. Automated lighting, adaptive cruise control, and pedestrian crash avoidance mitigation (PCAM) incorporate navigational warnings to alert drivers to potential dangers, such as vehicles in blind spots, lane departures, and more.
  • Future sensors may be able to adjust themselves to focus on the inherent dependability and safety of these systems.

Why the Industry is Demanding FPGAs for Advanced Driver-Assistance Systems

Designing ADAS requires flexibility and customization. Here’s why FPGAs, as opposed to ASICs, are increasingly preferred.

Integrating advanced driver assistance systems (ADAS) into nearly all new cars is happening swiftly.

These systems frequently present Tier 1 suppliers and automakers with special computational requirements for which the CPU or GPU may not be well suited.

It is well known that there are disadvantages to using an FPGA. They aren’t the most affordable devices because silicon provides all programmability.

Because all the connection switches slow down signals more than plain wires, they are slower than other devices made on the same manufacturing node. They reportedly used more energy on the same node than other gadgets.

Studies on how to teach a vehicle to learn on its own and subsequently drive on its own have not yet been completed, even though there has been a lot of research on this subject since the 1950s.

There is now a lot of research on self-driving cars under human supervision in controlled environments with ideal road and climatic conditions, but creating a completely autonomous vehicle presents several difficulties.

Before autonomous vehicles may be used on our roads, there are still several major obstacles that must be removed.

ADAS applications

Constraints Unique to Automotive Design

Due to its complex settings and complicated limitations, designing using FPGAs in a mission-critical automotive design differs from designing in other environments.

FPGAs in ADAS are primarily concerned with reliability. In the past, high temperatures have caused problems with packing, assembly, environmental overstress, and ESD, all of which are causes of FPGA failure.

Due to the high operating temperatures in automobiles, this is a crucial design factor for employing FPGAs in ADAS.

As a result, numerous providers have developed FPGA topologies that can function in challenging circumstances.

Layers of automotive security - ADAS
Layers of automotive security – ADAS

The Future of ADAS

To solve the convergence of conflicting aims, the growing amount of vehicle electronic hardware and software necessitates considerable modifications in the current automobile design process:

  • Improved dependability
  • Lower expenses
  • Reduced development cycle length

Distributed ADAS electronic controller units (ECUs) are becoming less common in favor of a more integrated ADAS domain controller with centralized ECUs.

This indicates that we currently operate at Level 2, or “Partial Driving Automation,” as SAE International defines.

A vehicle can control steering, accelerating, and decelerating at this level. Still, it is not fully autonomous because a human driver is always present and able to take over at any time.


Logic Fruit Technologies creates FPGA technology for a variety of applications, including communications, computing, avionics, security, automotive, and consumer electronics, among others. We specialize in real-time FPGA-software heterogeneous systems with great performance.

Advanced driver assistance systems have gone from being scarcely available to being included in the majority of newly released vehicles in just a few short years. Automotive industry analysts predict that ADAS will be the next major way for businesses to stand out in such a crowded market. Perhaps ADAS will improve to the point where self-driving cars become the norm in the future.

The most effective form of development taking place right now is ADAS. Of course, electric and hybrid vehicle innovations are ongoing, and both are crucial for lowering greenhouse gas emissions and the usage of fossil fuels.

The most crucial part of travel is human safety, which ADAS directly address. Every development in ADAS has an evident and definitive impact on preventing injuries and deaths because more than 90% of traffic accidents, injuries, and fatalities result from human mistakes.

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