autonomous driving

Understanding The Software And Hardware Architecture Of Smart Cars

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Understanding The Software And Hardware Architecture Of Smart Cars

Software Architecture Industry Chain With the trend of automotive intelligence, “Software Defined Vehicles” has become an industry consensus. Software Defined Vehicles (SDVs) refer to the deep involvement of software in the definition, development, verification, sales, and service processes of vehicles, continuously changing and optimizing each process to achieve ongoing optimization of experience, processes, and value … Read more

Introduction to Automotive Intelligent Technology

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Introduction to Automotive Intelligent Technology

Automotive Intelligent Technology The intelligence and connectivity of automobiles have become the focus of development in the global automotive industry. As an upgrade of automotive products and technologies, intelligent connected vehicles will bring profound changes to the automotive and related industries. China has also clearly identified the intelligent connected vehicle industry as a national strategy … Read more

Understanding V2X Technology for Autonomous Driving

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Understanding V2X Technology for Autonomous Driving

Image Source: stock.adobe.com Vehicle to Everything (V2X) technology, simply put, enables vehicles to communicate with various objects that they can interact with, including other vehicles, pedestrians, roadside infrastructure, and networks. V2X connects pedestrians, vehicles, roads, clouds, and other traffic elements, allowing vehicles to gather more information and facilitating innovation and application of autonomous driving technologies. … Read more

Mainstream Autonomous Driving Chips: GPU, FPGA, ASIC

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Mainstream Autonomous Driving Chips: GPU, FPGA, ASIC

The current mainstream AI chips can be divided into three categories: GPU, FPGA, ASIC. Both GPU and FPGA are relatively mature chip architectures and belong to general-purpose chips. ASICs are chips customized for specific AI scenarios. The industry has confirmed that CPU is not suitable for AI computing, but it is still indispensable in the … Read more

Top 10 Cutting-Edge Technologies in Robotics

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Top 10 Cutting-Edge Technologies in Robotics

1. Flexible Robot Technology Flexible robot technology refers to the design using flexible materials and structures, allowing robots to possess characteristics such as flexibility, agility, lightness, and durability, enabling them to work in irregular, complex, and hazardous environments. These robots can achieve high levels of autonomy, have good adaptability and intelligence, and can perform a … Read more

Communication and Storage Technologies for Advanced Autonomous Driving Systems

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Communication and Storage Technologies for Advanced Autonomous Driving Systems

Advanced autonomous vehicles require high-bandwidth and low-latency networks to connect all sensors, cameras, diagnostic tools, communication systems, and central artificial intelligence. These technologies generate, send, receive, store, and process vast amounts of data. For the next generation of autonomous driving domain controllers, commonly used in-vehicle networks include CAN, LIN, FlexRay, MOST, and LVDS. Except for … Read more

Understanding In-Vehicle Cameras: The Eyes of Autonomous Driving

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Understanding In-Vehicle Cameras: The Eyes of Autonomous Driving

In-Vehicle Cameras: The Eyes of Autonomous Driving In-vehicle cameras are known as the “eyes of autonomous driving” and are the core sensing devices in ADAS systems and the field of automotive autonomous driving. They mainly collect image information through lenses and image sensors, achieving 360° visual perception and compensating for radar’s shortcomings in object recognition, … Read more

Mainstream Autonomous Driving Chips and Platform Architecture (Part 3) Low-Computing Power Platforms

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Mainstream Autonomous Driving Chips and Platform Architecture (Part 3) Low-Computing Power Platforms

Author / A Bao Editor / A Bao Produced by / A Bao 1990 As mentioned earlier, with each increase in the level of autonomous driving, the required computing power of the chips will increase by dozens of times. The computing power requirement for L2 level autonomous driving is only 2-2.5 TOPS, but for L3 … Read more

Key Indicators for Autonomous Driving AI Chip Selection

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Key Indicators for Autonomous Driving AI Chip Selection

The central controller, as the core component of autonomous driving, acts as the “brain” of the system, typically requiring external connections to multiple cameras, millimeter-wave radars, laser radars, and IMUs, among other devices, to perform functions including image recognition and data processing. The domain controller, as an intelligent hardware, needs to handle complex AI computations … Read more

Overview of Mainstream ADAS/AD Domain Control Chip Platforms

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Overview of Mainstream ADAS/AD Domain Control Chip Platforms

1. ADAS/AD System Solutions (1) L0-L2 Level ADAS Solutions As mentioned earlier, most early L0-L2 level ADAS systems are based on a distributed controller architecture. The entire ADAS system consists of 4-5 ADAS subsystems, each of which is usually an all-in-one solution (which can be viewed as a smart sensor). Each subsystem exclusively occupies the … Read more