"The development of automotive technology has reached a stage where few doubt that driverless driving will become a major transformation in the automotive industry. However, as various technologies mature, different stakeholders—such as major automakers, internet companies, research institutions, and tech giants—have diverse opinions on the timeline and approach. This article references a study by Monita Caixin Think Tank, which systematically outlines the key technological milestones for autonomous driving and their expected timelines."
**Key Points**
1) Automotive electronics follow a two-horizontal and three-vertical technical framework, gradually achieving mature intelligence and networking: 2016–2018 focused on sensor fusion; 2017–2019 on high-precision maps; 2019–2022 on in-vehicle communication modules; and 2022–2025 on decision chips and algorithms.
2) 2016–2018: Three-sensor fusion. Domestic millimeter-wave radar began shipping, vehicle vision systems reached consumer level, and laser radar costs dropped, accelerating ADAS and driverless adoption.
3) 2017–2019: High-precision maps matured. Traditional maps couldn’t meet autonomous driving needs, making high-precision maps essential for L3 and L4 levels. Key players included mapping companies, AI firms, and traditional car manufacturers.
4) 2019–2022: In-vehicle communication modules matured. LTE-V offered advantages in delay, bandwidth, reliability, and cost. Companies like Datang Telecom launched LTE-V equipment, expecting rapid growth in in-vehicle communication modules.
5) 2022–2025: Decision chips and algorithms matured. Major manufacturers used specialized chips to support AI algorithms, with Google’s TPU, Horizon’s BPU, and Intel’s acquisition of Mobileye showing the trend toward chip-algorithm integration.
**Automotive Electronics Development Timeline**
**1.1 Automotive Electronics Develop Along Two Horizontal and Three Vertical Technical Frameworks**
Intelligent connected vehicles are equipped with advanced sensors, controllers, and actuators, integrating modern communication and network technologies to enable information exchange between vehicles and people, roads, and environments. This leads to complex environmental awareness, intelligent decision-making, and coordinated control, aiming for safe, efficient, and comfortable driving. The technical architecture is formed based on application scenarios and use cases.
**1.2 Automotive Electronics Development Timeline – Intelligent and Networked Synergy**
The development of automotive electronics involves two dimensions: intelligence and networking. From 2016–2018, sensor fusion enabled partial automation. From 2017–2019, high-precision maps supported lane-keeping and parking. From 2019–2022, 5G and V2X accelerated connectivity. By 2022–2025, decision chips and AI algorithms enabled full autonomy.
**1.3 Global Policies Promote ADAS Adoption**
Europe introduced mandatory safety features like automatic emergency braking and lane departure warnings. China required 100% installation of ADAS systems by 2017, pushing automotive electronics development forward.
**1.4 Google and Tesla Lead Autonomous Driving Development**
Google focused on high-precision maps and deep learning, while Tesla used sensor fusion. Google's Waymo became independent, reducing lidar costs by 90%, and targeting freight and shared mobility. Tesla’s Autopilot 2.0 featured 8 cameras, 12 ultrasonic sensors, and a powerful NVIDIA chip.
**1.5 Domestic Tech Companies Collaborate with Traditional Automakers**
Chinese universities and companies made progress in developing ADAS systems, including adaptive cruise control and lane departure warning. Tsinghua University and others have developed prototypes entering industrialization.
**2. 2016–2018: Sensor Fusion**
**2.1 Millimeter-Wave Radar Starts Shipping in China**
Mainstream frequencies are 24 GHz and 77 GHz. 77 GHz is preferred for long-range radar. Chinese companies like Huayu Automobile produce 24 GHz radars, while foreign firms dominate 77 GHz components.
**2.2 Car Vision Systems Mature Hardware, Software Upgrades**
Car cameras include CMOS lenses, image processing chips, and software upgrades. Mobileye improved processing speeds and resolution, enhancing pedestrian and collision detection.
**2.3 Laser Radar Costs Drop**
Lidar combines lasers, GPS, and inertial navigation for 3D imaging. While domestic companies lag behind, the "Made in China 2025" roadmap aims for low-cost, miniaturized solutions by 2025.
**3. 2017–2020: High-Precision Maps Maturity**
High-precision maps are critical for L3 and L4 autonomous driving. They reduce reliance on sensors, improve reliability, and integrate with V2X. They consist of active, dynamic, and analysis layers, providing real-time updates and aiding autonomous decision-making.
**3.1 Traditional Maps Can't Meet Needs**
High-precision maps offer centimeter-level accuracy and richer data. They help in path planning and real-time updates, supporting higher-level autonomy.
**3.2 Industry Chain and Key Players**
Participants include mapping companies, AI firms, ADAS providers, and traditional automakers. Each has unique strengths in data collection and processing.
**3.3 Foreign Trends: Hardware and Software Integration**
Companies like HERE focus on location services, collaborating with automakers and tech firms. Google and Apple emphasize real-time updates and large-scale data collection for map optimization.
**3.4 High-Precision Map Maturity Timeline**
By 2020, sub-meter accuracy maps will be available for PA-class vehicles. By 2025, CA-level coverage will extend to main highways. By 2030, full national coverage and standardization will support fully autonomous driving.
With advancements in AI and 5G, high-precision maps will play an even more critical role in the future of autonomous driving.
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