Advances in The Automotive Industry and Technology
The automotive industry has been continuously improving the safety features of its vehicles through technological advancements. One of the technologies at the forefront of these advancements is 4D imaging radar technology. This futuristic technology has high potential to significantly improve the level of automotive reliability by revolutionizing the way vehicles sense and react to their surroundings.
A New Approach to Automotive Radar, 4D Imaging Radar
In fact, automotive radar is not just an issue for drivers on the road - it's a critical issue that affects almost everyone, from drivers to pedestrians and their families and friends, so it's only natural that there is a growing industrial and societal need to develop new technologies that can help ensure the safety of vehicles.
4D imaging radar (or imaging radar) is the latest technology to come under intense scrutiny in the automotive industry in terms of ensuring vehicle safety as autonomous driving technology advances at a rapid pace in recent years, as it provides drivers with advanced information about the vehicle's driving environment in real time.
What is 4D Imaging Radar Technology? Definitions and descriptions
Radar technology has been evolving since the 19th century, when German physicist Heinrich Hertz conducted classic experiments on electromagnetic field radiation. The 20th century saw a number of significant developments beginning in the 1930s and a quantum leap forward during World War II. 4D imaging radar has its roots in radar technology that has been evolving for over a century.
4D imaging radar works by emitting radio frequency signals and then detecting the electromagnetic waves that bounce back after hitting an object, similar to how traditional radar works. A transmitter sends out modulated signals using 77 GHz or 79 GHz radar waves, and a receiver distinguishes each signal as it bounces back from the surrounding area. By interpreting the Doppler shift of the reflected waves by measuring the time it takes for the signal to bounce back, the system determines velocity information in addition to spatial information about the object.
Unlike traditional radar systems, 4D imaging radar technology uses more powerful chip systems and antennas to generate four-dimensional information by adding velocity information to the intact three-dimensional spatial information of the driving environment. Imaging radar uses radio waves to detect and localize objects and can provide real-time information about the distance (Range), horizontal angle (Azimuth), vertical angle (Elevation), and velocity of objects within the detection range. Furthermore, 4D imaging radar can recognize more detailed object information in the form of a point cloud through multiple transmitting and receiving antennas and an improved digital signal recognition system compared to conventional radar. By distinguishing objects on the road and using SLAM (Simultaneous Localization and Mapping) algorithms that utilize static objects to build 3D information of the surrounding environment into a virtual reality, 4D imaging radar systems are more suitable for advancing autonomous driving, which is the future of automobiles.
The Advent of The Motorized Car, and The Societal Need for It, Automotive Reliability.
Automotive reliability has always been a top priority for manufacturers and consumers alike since the first steam-powered, three-wheeled automobile hit the road in 1770, when military engineer Nicolas-Joseph Cugnot, a French captain of engineers, developed it to tow cannon-carrying wagons. The number of vehicles traveling on the road has increased in most countries on the planet since World War II, along with industrial advances in heavy industry, and the societal need for automotive reliability has continued to grow. In response to this need, automotive driver assistance systems, often referred to as advanced driver assistance systems (ADAS), began to emerge in the mid-to-late 1990s.
ADAS, Modern Technology's Answer to Automotive Reliability
A prime example of ADAS is Adaptive Cruise Control (ACC, or adaptive cruise control). Since the Mercedes-Benz S Class was equipped with the first radar-based cruise control in 1999, this revolutionary technology ended the Stone Age of automotive technology, when drivers relied solely on their feet to control their vehicles, and ushered in a new era of ADAS. Along with this technology, radar has been a revolutionary major in reducing automobile accidents on the road. According to a report by the U.S. National Highway Traffic Safety Administration (NHTSA), forward collision warning (FCW) and automatic emergency braking (AEB) systems that use radar technology can reduce rear-end crashes by up to 50% (Source: National Highway Traffic Safety Administration, "Forward Collision Warning and Automatic Emergency Braking Systems: Summary of Technology Research," 2018).
Obvious limitations of ADAS: inability to recognize existing stationary objects, inability to recognize height information
Despite the incredible contributions radar has made to traffic safety, traditional radar has a clear limitation: its reliance on a single chip limits its ability to process information. By default, traditional radar recognizes objects moving on the road in 2D. While this makes the system somewhat effective at detecting dynamic objects, it is not able to measure vertical angles, which makes it less discriminating against tall structures. Furthermore, it cannot process speed information, which means it cannot recognize stationary or stopped targets. When these limitations are combined with (Semi) autonomous driving, it is inevitable that the driving safety of such vehicles will be compromised.
A prime example of this is the rear-end collision of a Tesla car on a highway in Taiwan in 2020, where the car was driving head-on at high speed without recognizing a truck that had overturned several hundred meters in front of it. Due to the limitations of the existing radar on the car at the time, it may not have recognized the truck, or it may not have recognized the boundary between the truck and the sky as a space that it could pass through.
The Importance and Social Impact of Road Safety
No matter how advanced a technology is, it's useless if it's not stable and meaningful if it can't contribute to society. 4D imaging radar has clear technology stability and contribution to society.
4D imaging radar has its roots in traditional radar technology. During World War II, radar was mainly used for military purposes such as detecting aircraft and ships, and was thoroughly tested in the immediate war situation. After the end of World War II, it began to make a significant impact in civilian environments based on many tests, applications, and practical applications. Radar-based systems for various purposes such as weather forecasting, air traffic control, and surveillance are typical examples of civilian industrial applications.
In this post, we looked at the features, capabilities, and reliability of 4D imaging radar, an autonomous driving technology that's gaining traction. Will Elon Musk put HD RADAR on his Tesla? What do you think? The story of 4D imaging radar and automotive reliability continues in the next post.
















