These 11 new technologies are booming due to autonomous driving

Today's self-driving car innovation reminds me of the classic comic book "Kevin's Gem Tiger World." In the comic, Kevin calls himself "the climax of creation," but now autopilot cars have surpassed Kevin and become a new climax.

This judgment is not exaggerated. Be aware that networking and autonomous vehicles not only incorporate a number of new technologies, but are also driving the development, investment and innovation of these technologies to continuously expand their boundaries. After summarizing these technologies, I actually listed a big list of TOP 11 directly. Automatic driving is indeed a comprehensive major project.

Next, we came to know together these 11 new technologies that are booming due to autonomous driving:

Internet of Things technology

Autonomous cars carry hundreds of sensors that convert the physical world around the vehicle into digital signals. Taking the "eyes" of autonomous vehicles - radar, cameras and lidars - can not get a 720-degree field of view (both horizontal and vertical) without their vehicles.

The complexity of autonomous vehicle sensors has also made it the most powerful IoT product in history. The future of autonomous driving cars will continue to increase, so certainly will be more from other areas of the Internet of Things solutions and platforms.

2. Mass data management

Data generated by devices such as autopilot systems and sensors can easily break the TB level and these data must be quickly processed and transformed.

Now that cars are becoming the largest source of data in human history, innovation in data management, databases, data flow analysis, security, data alignment, distributed computing and loan management is imminent.

3. Edge Analysis

Imagine the future of autonomous vehicles may produce several GB of data per second and make thousands of judgments, all this is a smooth process behind the powerful computing power.

If the vehicle can not handle some of the data on its own, but instead sends all the data back to the cloud and waits for the "total brain" in the back office to feed back, its latency is simply unacceptable.

Cloud computing

While edge computing is crucial for real-time analytics and decision-making, large amounts of data still need to be returned to the cloud for processing.

Therefore, a powerful cloud computing capability will become an important guarantee for such functions as data management, application analysis and operation, software upgrade, HD map, path planning, payment, visualization, city management and diagnosis. With it, it can ensure that autonomous vehicles have The best life-cycle experience.

Computer vision

Computer vision is the fundamental technology that automatically drives a car to perceive its surroundings. It analyzes video streams in real time to understand traffic lights, pedestrians, roadblocks, and road signs. At the same time, the target detection, modeling, path prediction and other work is also one of the challenges of computer vision technology. Due to the large amount of video stream data, speed and limited analysis time, so want to do a good job of computer vision is not easy.

In addition to being responsible for sensing the exterior environment, computer vision technology has to analyze the video stream in the car to detect in time whether the driver is distracted or not. In addition, it also records and correlates incident events. Only "inside and outside take", computer vision technology to ensure that passengers have a safe and comfortable journey.

Autonomous driving has led to the development of several technologies

6. Safety

If you drive through the Volkswagen Beetle of the 1950s, you know that the software in that classic car is sparse and the connection is simply gone. In contrast, today's vehicles are often powered by hundreds of processors and microcontrollers, while complex networks in vehicles are responsible for swapping large amounts of data and control signals between the vehicle and the cloud. Such a complex system is not vertically integrated, it has a large number of subsystems from different vendors, so a great deal of innovation must be applied to ensure security.

In addition, the entire system also ensures the safety of passengers and responds to the challenges posed by vehicle ownership, speed of movement and different external conditions. This means that the industry as a whole innovates in areas such as blockchain, OTA upgrades, hardware reliability, malware, security / behavior analysis, identity / credential management, network and system isolation, honor / security mechanisms and more.

7. Connect

The car has become a highly interconnected system, and a large number of connectivity technologies such as internal high-speed data and control networks, 5G networks, dedicated short-range communications technologies / V2X and WiFi, BT and many others remain stable. In fact, the system not only uses a lot of connection technology, but also integrates many complicated transformation, routing and security infrastructures. To manage this system, we must rethink the internal and external networks.

8. Software

Complicated software on autonomous vehicles is also a staple that contributes to planning, strategy, safety and algorithms for vehicles, ensuring that subsystems and microcontrollers provide precise control of the vehicle.

Hyundai is no longer just a transporter, it's a software-controlled supercomputer on wheels. Autopilot vehicles probably have 100 million lines of code to use, and we know much less about the code for Facebook, Microsoft Office and Android apps. At the same time, breakthrough innovation is needed for language, safety, performance, real-time processing, and software upgrade capabilities to support the software scale of autonomous vehicles.

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