**First, What Is Unmanned Driving?**
In simple terms, driverless driving is a technology that enables vehicles to perceive their surroundings, plan routes, and control themselves automatically—essentially allowing the car to drive on its own, mimicking human-like behavior or even surpassing it.
The sensors act as the "eyes" of the vehicle, capturing 360-degree information about objects around the car. Meanwhile, the vehicle's control system functions as the "brain," processing real-time data and making intelligent decisions based on high-precision maps. This combination allows autonomous cars to navigate complex environments safely and efficiently.
Experts describe the sensors installed on the vehicle as its "eyes," capable of detecting distances and obstacles in all directions. Common types of sensors include laser radar, millimeter-wave radar, cameras, ultrasonic sensors, and GPS modules. The "brain" of the car, which includes advanced control systems, can analyze environmental data and predict the actions of other vehicles and pedestrians, enabling optimal route planning and safe navigation.
Lin Yuanqing, Director of Baidu's Deep Learning Lab, explained that Baidu’s self-driving car uses artificial intelligence to detect the surrounding environment through cameras, laser radar, and GPS. This helps the car determine the best route and operate without any human intervention.
"The core technology behind Baidu’s self-driving car is Baidu Brain, which offers a comprehensive solution for autonomous driving," Lin said. These technologies include computer vision, high-precision mapping, multi-sensor fusion, and intelligent decision-making. They are used throughout the entire process of starting, driving, and parking the vehicle. For example, if a vehicle ahead suddenly slows down, the intelligent system can decide whether to slow down or change lanes based on the environment. Additionally, the system continuously learns from human driving experiences to improve its performance and ensure a safe and comfortable ride.
Unmanned driving relies heavily on breakthroughs in artificial intelligence. Like AI itself, it benefits from massive data, powerful computing, and advanced algorithms. One key factor in AI development is the accumulation of large amounts of data, which is essential for training deep learning models. Autonomous vehicles generate vast amounts of data—about 100 GB per hour from sensors. With 10,000 such vehicles, this could amount to dozens of petabytes of data daily, used to train and refine the self-driving system. High-precision maps also contain 100,000 times more data per kilometer than traditional maps, further enhancing the capabilities of autonomous vehicles.
With improvements in cloud computing and onboard computing power, vehicles can now handle complex tasks in real time, enabling real-time road sensing, intelligent decision-making, and control. Since 2013, advancements in machine learning and deep learning have accelerated AI development. By 2015, the error rate for vehicle recognition using deep learning was 69% lower than traditional methods.
**Second, the Principle of Driverless Technology – Application of Driverless Technology**
The technical principle of autonomous vehicles involves sensing the road environment through an onboard sensor system, planning a driving route, and controlling the vehicle to reach its destination.
Using onboard sensors, the car detects its surroundings and controls steering and speed based on road conditions, vehicle position, and obstacle information. This ensures safe and reliable travel on the roads.
Driverless technology integrates various fields, including automatic control, architecture, artificial intelligence, and visual computing. It represents the culmination of advancements in computer science, pattern recognition, and intelligent control. It is also a key indicator of a country’s technological and industrial strength, with broad applications in the national economy.
**Application of Driverless Technology**
Let’s explore some real-world examples of driverless technology:
**1. Adaptive Cruise Control (ACC)**
Adaptive Cruise Control is an intelligent system built upon traditional cruise control. It is available in many mid-range and luxury vehicles. Using radar and camera sensors, the system detects the distance to other vehicles and automatically adjusts speed to maintain a safe following distance.
**2. Tesla Autopilot**
In October 2014, Tesla introduced Autopilot, allowing drivers to hand over control on highways. The system supports adaptive cruising, lane changes, emergency braking, and automatic steering. However, in June 2021, a fatal accident involving a Tesla Model S in Autopilot mode raised concerns. In response, Tesla updated the system to improve safety, including alerts for drivers who don’t hold the wheel for too long.
**3. Apple Car**
Although still shrouded in mystery, Apple has been rumored to be developing its own electric vehicle. Reports suggest that the company has been working on the project since 2014, with plans to launch it as early as 2020. Apple has also applied for patents related to car keys, allowing users to control their vehicles via devices like iPhones. However, progress has been slow, with internal challenges reported.
**4. Ford Self-Driving Vehicle**
Ford has been testing self-driving cars based on the Fusion model, equipped with LiDAR sensors and other advanced systems. The company plans to introduce fully driverless taxis by 2021. To achieve this, Ford has invested in startups that help enhance the perception and understanding of the environment for autonomous driving.
**Third, the Status Quo and Development of Driverless Technology**
**Current Status of Driverless Technology**
China started researching autonomous vehicles later than other countries. In the 1980s, the National University of Defense Technology began exploring this field. In 1989, China’s first smart car was developed at the university. It was small, lightweight, and featured basic autonomous driving functions.
By 1992, the university had created China’s first true unmanned car, capable of autonomous control. In 2000, the fourth generation of driverless cars reached a top speed of 76 km/h, setting a national record. In 2007, the Red Flag unmanned sedan achieved world-class performance. By 2013, China planned to conduct long-distance tests from Beijing to Tianjin and later to Shenzhen.
**Development of Driverless Technology**
**1. Driverless Cars Enter Mainstream Consciousness**
Media coverage of driverless cars has grown significantly, rivaling reports on drones and virtual reality. As the technology matures, public interest continues to rise. While Waymo remains the most advanced project, many startups are gaining attention.
**2. Financing Data Shows Increased Maturity**
Investment in driverless technology has surged, with venture capital funding increasing dramatically. Companies like GM and Mobileye have played a key role in driving growth. Since 2017, the industry has shown signs of maturity, with more focus on later-stage investments.
**3. Electric Driverless Taxi Service Model**
Many companies aim to shift from private ownership to shared mobility, creating a future where cars are used on demand. This model often combines electric vehicles with autonomous technology, leading to new concepts like ACES (Autonomous, Connected, Electric, Shared).
**4. Future Development: A New Look and Reimagining Car Design**
As driverless technology advances, it may reshape car design and culture. In urban areas, larger vehicles like autonomous shuttles may become common. The widespread use of networked self-driving cars could lead to a rethinking of traditional car designs, promoting more efficient and flexible transportation solutions.
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