- Originating in August 1925, a car named American Wonder appeared on the streets of New York. It operated without a driver, instead being controlled by a wireless radio system to achieve functions such as acceleration, deceleration, and turning. This can be considered the first self-driving vehicle in human history.
- During this period of expansion, American tech giants such as Tesla and Nvidia played a role in the transition from 0 to 1.
- Meanwhile, China’s new forces in car manufacturing and solution providers represented by companies like Huawei and Horizon have also embarked on a broader path towards autonomous driving, leveraging the advantages of algorithm exploration from academic papers and large-scale engineering implementation.
A self-driving car, also known as an autonomous vehicle, is a vehicle that is capable of navigating and operating without human input. These cars use a variety of sensors, cameras, radar, and artificial intelligence (AI) to perceive their surroundings, interpret the data, and make decisions about acceleration, braking, and steering. Self-driving cars have the potential to revolutionise transportation by improving safety, reducing traffic congestion, and providing mobility options for those who cannot drive.
Origination
Originating in August 1925, a car named American Wonder appeared on the streets of New York. It operated without a driver, instead being controlled by a wireless radio system to achieve functions such as acceleration, deceleration, and turning. This can be considered the first self-driving vehicle in human history.
Since that time, the concept of self-driving has taken root in the hearts and minds of people, awaiting an opportunity for realisation.
Over the past decade, self-driving technology has progressed hand in hand with AI. It is no longer a distant and unattainable concept but has gradually begun to materialise and move towards the general public.
Also read: Nvidia accelerates China’s EV future with innovative driving solutions
Expansion
With advancements in various scientific technologies such as ultrasonic sensors, computer technology, LiDAR, cameras, and others, the autonomous driving systems have gradually matured. Self-driving vehicles can now acquire more accurate information about their surroundings. Additionally, the development of machine learning and artificial intelligence algorithms enables vehicles to better understand and respond to complex traffic environments.
As we entered the 2020s, autonomous driving technology has reached a stage of high automation. Some automakers have introduced vehicles equipped with Advanced Driver Assistance Systems (ADAS), achieving automated driving under specific conditions. Currently, autonomous driving technology is advancing towards commercialisation and practical applications.
More and more automotive manufacturers and technology companies are investing in the field of autonomous driving, launching commercialised solutions for autonomous driving.
Also read: Kia EV3 debuts with AI assistant and 300+ mile range
The currently popular companies
During this period of expansion, American tech giants such as Tesla and Nvidia played a role in the transition from 0 to 1. Without a doubt, Tesla’s AutoPilot is currently the undisputed leader in the new field of autonomous driving.
When discussing autonomous driving, Tesla is always mentioned, and when talking about Tesla, autonomous driving is inevitably brought up – the two are almost synonymous.
At the recent CES 2023 technology exhibition, NVIDIA’s series of projects, especially in the automotive sector, attracted attention: first, the Thor chip, set to be mass-produced by 2025, supporting a complete cockpit integration, deeply penetrating the smart cockpit race; later, there were updates on the application of the metaverse in the automotive sector, continuously partnering with Mercedes-Benz, Foxconn.
Meanwhile, China’s new forces in car manufacturing and solution providers represented by companies like Huawei and Horizon have also embarked on a broader path towards autonomous driving, leveraging the advantages of algorithm exploration from academic papers and large-scale engineering implementation.
