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The global automotive industry is accelerating innovation with a focus on EVs and autonomous driving technology, alongside software-defined vehicles. This vision of safety, efficiency, and sustainability is creating a new blue ocean for automotive sensors
1. Different Types of Automotive Main Control Chips
2. MCU
3. Cockpit SoC
4. Autonomous Driving SoC
5. TRI’s View
1. Development of Global AI Industry Chain
2. Analysis of Cross-Modal Business Opportunities in AI
3. A Breakdown of Hardware Supply Chain
4. TRI’s View
1. Global Overview of the AI Market Development
2. The Necessity of Openness in AI Development
3. Current Applications and Development of AI
4. TRI’s View
1. Development of Electrical / Electronic Architecture (EEA)
2. Status Quo of ADAS Domain Controllers for NEVs
3. TRI’s View
1. Overview of the Market for Autonomous Driving SoCs
2. Statuses of Main Competitors
3. Analysis of the Competitive Landscape
4. TRI’s View
At CES 2023, the Metaverse and Web 3.0 became the focal points across various industries, particularly drawing interest from automotive-related companies, who have been utilizing the concept of the Metaverse to provide virtual reality experiences from remote car maintenance, digital sales centers, to showcasing new car performance. This gradually unveils the vertical integration of the Metaverse into the automotive industry. This report primarily analyzes the current state and applications of the Metaverse market, with a detailed exploration of the application and trends of Metaverse technology in "industrial operations" and "retail experiences".
Autonomous or self-driving vehicles are endowed with perception capabilities through sensors and cameras. In general, LiDAR and cameras are the two main categories of technological solutions for enabling perception capabilities. The Society of Automotive Engineers (SAE) in the United States has proposed a classification system for automated driving, comprising a total of six levels from L0 to L5. In particular, L3 marks a significant threshold. Under specific conditions, drivers of vehicles equipped with L3~L5 solutions can temporarily keep their hands away from the steering wheel due to the support from the automated driving system (ADS).
L3 functionality allows for emergency control to be quickly handed back to the driver when needed, so there still must be a person ready to take over the driving task in the driver’s seat. Nevertheless, L3 remains an important milestone in the progress towards fully automated driving. The adoption of automated driving technologies extends beyond improving traffic efficiency and reducing carbon emissions; the core purpose of adopting these technologies is to reduce traffic accidents caused by human errors, thereby improving safety. Automated driving technologies can contribute to the optimization of traffic flows in smart cities. Furthermore, as automated driving advances from L3 to L4, the landscape of the transportation sector, along with the business models of transport operators, will gradually change.
GaN components, already excelling in rapid charging for end devices, are now becoming more prominent in the automotive and network communication sectors. This report delves into the growth potential of GaN components within the automotive industry, pinpoints their primary applications, and centers on the emerging market for automotive GaN components in China, spotlighting prospects for the country's local supply chain.
Due to the close relation between vehicle safety and both traffic and personal safety, various features such as internet connectivity, communication requirements, and software-defined vehicles all contribute to an increase in potential attack vectors. Moreover, as the number of electric vehicles (EVs) rises and the charging infrastructure expands, the scope of cyberattack targets also widens accordingly. Consequently, there is a pressing need to enhance cybersecurity measures and effectively manage vulnerabilities to safeguard vehicles from multiple security threats.