With the rapid development of science and technology, our lives have entered a new era of intelligence. In this era, cars are not only a means of transportation, but also an indispensable part of our lives. With the continuous advancement of automotive technology, our driving style is also undergoing profound changes.

Among them, ADAS (Advanced Driver Assistance Systems), as an important part of automotive intelligence, is gradually changing our driving style. It not only improves driving safety, but also provides drivers with a more convenient, safe and comfortable driving experience.

01. What is ADAS?

Advanced driver assistance systems (ADAS) are systems that integrate multiple sensors, cameras, radars and other equipment to achieve real-time perception and decision-making of the vehicle’s surroundings. It can provide a variety of auxiliary functions during vehicle driving, such as adaptive cruise control and automatic parking, so that drivers can control the vehicle more easily and reduce driving fatigue and stress. At the same time, it can also sense changes in the surrounding environment in real time and remind drivers of potential dangers, thereby avoiding traffic accidents and improving driving safety.

02. How are ADAS classified?

The related functions covered by the ADAS system include lane departure warning, adaptive cruise control, etc., which are complicated and dazzling. Proper classification can help us better understand and apply them.

The “Terms and Definitions of Road Vehicle Advanced Driver Assistance Systems (ADAS)” released in 2020 divides the functions covered by ADAS into information assistance and control assistance.

1 Information assistance category
Information assistance ADAS mainly assists driving by providing the information needed by the driver, which can help the driver understand the surrounding situation and traffic environment, and improve driving safety and efficiency.
According to the information type and functional characteristics provided by ADAS, the information assistance category can be further divided into driving monitoring category, danger warning category, and driving convenience category.

(1) Driving monitoring category
This type of ADAS mainly monitors the driving status and surrounding environment of the vehicle in real time through various sensors and cameras, and provides the driver with real-time vehicle information and traffic conditions. For example, BSD (blind spot detection), ISLI (intelligent speed limit information), etc. belong to this category.
(2) Danger warning category
This type of ADAS senses and identifies dangerous factors around the vehicle and issues warnings to the driver in a timely manner, reminding the driver to pay attention to potential dangers. For example, DFM (driver fatigue monitoring), FCW (forward collision warning), etc. belong to this category.
(3) Driving convenience category
This type of ADAS improves driving convenience and comfort by providing the information and functions required by the driver. For example, RCA (reversing condition assist), NV (night vision), etc. belong to this category.

2 Control Assistance Category
ADAS of the control assistance category assists driving by controlling the vehicle’s driving state, which can help the driver reduce the burden of driving. According to the specific functional characteristics and usage scenarios, the control assistance category can be further divided into emergency response category, driving convenience category, lane keeping category and intelligent lighting category.
(1) Emergency Response Category
ADAS of the emergency response category mainly provides rapid response and auxiliary decision-making for sudden or emergency situations, and takes effect quickly in dangerous situations to help drivers avoid or reduce accidents. For example, AEB (advanced/automatic emergency braking) belongs to this category.
(2) Driving Convenience Category
ADAS of the driving convenience category assists driving by providing the functions and operational convenience required by the driver. For example, ACC (adaptive cruise control), IPA (intelligent parking assist), TJA (traffic jam assist), etc., belong to this category.
(3) Lane Keeping Category
ADAS of the lane keeping category assists the driver to keep the vehicle in the correct lane by identifying and tracking lane lines. Help the driver avoid lane deviation or keep the vehicle in the correct lane, improving driving safety and stability. For example, LKA (lane keeping assist), LCC (lane centering control), etc.
(4) Intelligent lighting category
Intelligent lighting ADAS assists the driver in driving under various lighting conditions by automatically adjusting the brightness and illumination range of the lights. For example, AFL (adaptive front light), ADB (adaptive driving beam), etc., belong to the intelligent lighting category.

03. What do several common ADAS functions do?

1 LKA (lane keeping assist)
LKA can help drivers keep their vehicles in lanes and reduce the risk of lane departure accidents caused by driver negligence or fatigue.
The LKA system achieves its functions by using cameras, sensors and control systems. The camera is usually installed at the front of the vehicle to capture the lane line in front of the vehicle. The sensor is responsible for monitoring the driving status and direction of the vehicle, including steering angle, vehicle speed, etc.
When the vehicle approaches the lane line during driving, the LKA system detects the position and shape of the lane line and makes a judgment based on the driving status and direction of the vehicle. If the system believes that the vehicle is about to deviate from the lane, it will help the driver guide the vehicle back to the normal lane by controlling the steering system.
2 ACC (adaptive cruise control)
The ACC system uses on-board sensors, including radar, laser radar, etc., to detect the vehicles and obstacles in front of the vehicle during driving, as well as the position and speed of the vehicle. The system can monitor the distance and speed of the vehicles and obstacles in front in real time, and automatically adjust the speed and driving trajectory according to the speed and driving status of the vehicle to maintain a safe distance from the vehicle in front.
Compared with traditional cruise control systems, adaptive cruise systems are more intelligent and flexible. Traditional cruise control systems can only drive at a preset speed and trajectory, while adaptive cruise systems can automatically adjust the speed and trajectory according to the actual situation of the vehicle and obstacles in front to maintain a safe distance.
In addition, the adaptive cruise system can also automatically adjust the vehicle’s speed and trajectory according to the speed and driving status of the vehicle and obstacles in front to maintain the relative position with the vehicle in front. This automatic adjustment function can help drivers drive the vehicle more easily while improving driving comfort and safety.
3 FCW (forward collision warning)
The FCW system uses on-board sensors, including radar, cameras, etc., to detect the distance and relative speed between the obstacle in front of the vehicle and the vehicle. The system monitors the situation in front of the vehicle in real time. When a collision risk is detected, it will issue a warning to remind the driver to take timely measures.
The warning methods of the FCW system usually include sound warnings, vibration seats or steering wheels, etc. The level and method of the warning will vary depending on the size and specific circumstances of the collision risk. If the driver does not take timely measures, the FCW system may also automatically intervene in the vehicle’s braking system to avoid or mitigate the collision.
Collision prevention systems are usually combined with other driver assistance technologies such as lane departure warning systems and adaptive cruise control systems to provide drivers with more comprehensive and reliable driving safety protection.
4 AEB (advanced/automatic emergency braking)
The implementation of the AEB system function requires the cooperation of multiple sensors and controllers. The sensor in front of the vehicle (such as radar, camera or laser) detects obstacles in front. If there is a risk of collision based on speed and distance analysis, the system will warn the driver through warning lights, alarm sounds, etc. If the driver does not brake after the warning, or the system determines that the driver cannot brake in time after sensing the signal, the AEB system will actively intervene and brake when the threshold is exceeded.
5 IPA (intelligent parking assist)
IPA integrates sensors, cameras and computer algorithms to realize functions such as automatic parking space identification and automatic parking.
In actual use, the driver only needs to press the start button of IPA intelligent parking assist, and the system will automatically detect the surrounding environment and find a suitable parking space. Once a suitable parking space is found, the system automatically calculates the best parking trajectory and controls the vehicle to complete automatic parking. The whole process does not require manual operation by the driver.
6 BSD (blind spot detection)
BSD mainly detects the blind spot range of the rearview mirror through two millimeter-wave radars equipped on the rear of the vehicle. When other road users are detected in the blind spot, the driver is warned to assist driving or changing lanes.
7 DFM (driver fatigue monitoring)
DFM aims to monitor the driver’s physiological state and driving behavior, reminding the driver to rest in time when fatigued, so as to ensure driving safety.
The DFM system monitors the driver’s physiological state in real time through various sensors, such as eye closure, head position, heart rate, etc. These data can provide clues about whether the driver is fatigued. For example, when the driver’s eyes are closed more or the head position is not correct, this may indicate that the driver is in a state of fatigue. In addition, the DFM system also monitors the driver’s behavior patterns, such as driving speed, braking frequency, etc. These behavior patterns can also reflect the driver’s fatigue level. For example, when the driver slows down or brakes more frequently, this may indicate that the driver is tired.
The DFM system uses specific algorithms and models to comprehensively analyze the driver’s physiological and behavioral characteristics to assess the driver’s fatigue level. These algorithms and models are usually based on machine learning and artificial intelligence technologies, and can determine whether the driver is in a state of fatigue based on the driver’s characteristic data.
8 NV (night vision)
NV can detect obstacles and pedestrians at a farther distance than ordinary visible light, which is particularly useful in night and low-light environments. By identifying these obstacles and pedestrians, the NV night vision function can provide drivers with additional warnings, allowing them to react in advance and avoid potential dangers.
NV night vision can also be combined with other ADAS technologies, such as automatic emergency braking and adaptive cruise control. When the NV night vision system detects potential dangers, it can trigger these higher-level safety systems to automatically take evasive or braking measures, thereby further enhancing driving safety.
However, NV performance is affected by many factors such as light conditions, ambient temperature, and equipment quality. Therefore, when using NVD, it is necessary to make appropriate adjustments and use it according to actual conditions.

04. Q&A

Q1: Is ADAS autonomous driving?
A1: Many people mistakenly believe that ADAS is already autonomous driving. In fact, ADAS and autonomous driving have different focuses and cannot be confused.
ADAS is an advanced driver assistance system. Its main function is to use various sensors, algorithms and data processing technologies to provide drivers with a more intelligent, safe and convenient driving experience. Autonomous driving is the ultimate goal of ADAS. Autonomous driving technology uses various sensors, high-precision maps, computer vision, artificial intelligence and other technologies to achieve autonomous driving of vehicles. In autonomous driving mode, the vehicle can autonomously perceive the environment, make decisions, and execute control to complete the entire driving process.
According to the SAE J3016 standard, L3 is the watershed of autonomous driving. ADAS mainly covers areas below L3, and only when it reaches L3 can it be truly autonomous driving. ADAS technology can be regarded as a ladder to achieve autonomous driving. It provides the necessary technical support and preparation for the realization of autonomous driving. Through the development of ADAS technology, we can gradually improve various aspects of autonomous driving technology, such as sensor technology, data processing capabilities, decision-making and control, etc.
ADAS technology still requires the participation and monitoring of the driver, while autonomous driving is completely independent of the driver’s control. Therefore, achieving full autonomous driving still requires solving many technical and social problems, such as safety, regulations, and ethics.
Q2: What is the relationship between ADAS and automotive functional safety, expected functional safety, and information security?
A2: Functional safety solves the problem of failure of electronic and electrical systems, such as a camera suddenly breaking down or a domain controller system failure. Traditional ADAS systems will fully consider functional safety during the system design stage. At present, this field is the most mature compared to other safety areas, and is also supported by international standards ISO26262 and some regulations.
Expected functional safety solves the problems of insufficient related functions, performance limitations, and human misuse after the complexity of system functions increases. For example, if the driver does not operate the intelligent driving function correctly, the perception algorithm function is limited and cannot accurately identify the faded lane line, or the perception identifies the truck in front as blue daytime, this will bring fatal problems.
At present, the ADAS system has not yet achieved a good implementation combination with expected functional safety, but according to my observation, some companies are also paying attention to this aspect and starting to make some expected functional safety supervision mechanisms. Expected functional safety is more targeted at high-level ADAS systems (L3 and above), because the system is more complex and needs to pay more attention to expected functional safety.
Information security, this direction involves more and wider areas than the first two, involving data communication security between vehicles and within the vehicle. At present, I personally have not been exposed to information security in ADAS, and I hope that other experts in information security can talk about it together.
Q3: How to do functional safety-related design and verification for important algorithm parts in ADAS?
A3: On the one hand, ADAS-related codes need to follow the software development requirements of the functional safety standard ISO 26262, use strict coding specifications to write coding, and perform complete functional safety processes during the development process, such as requirements management and code unit testing. In advanced ADAS, safety needs to be achieved through redundancy and monitoring mechanisms in algorithms and system architectures, such as two independent neural network modules that monitor each other, and a safety monitor that continuously detects the status. This can avoid systematic errors or random failures in the algorithm design process.
On the other hand, for algorithm defects that cannot be fully foreseen in the ADAS system, such as insufficient performance, a large number of test cases are needed to cover various usage scenarios to simulate and test the entire system. At the same time, the system robustness is continuously improved by iteratively optimizing the algorithm model and performance.
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