Domestic car companies have made frequent moves in the field of smart cars, especially in the choice of autonomous driving technology. Lidar technology, which used to rely on high costs, is now moving to more economical visual recognition technology.
The influence of Tesla and its founder, Elon Musk, cannot be ignored. They started reducing their reliance on lidar a few years ago, and this strategy seems to be being adopted by a growing number of Chinese automakers. What's going on here?
A few years ago, Tesla made a bold decision in the field of autonomous driving: abandon lidar altogether in favor of lower-cost visual recognition technology. This decision caused quite a bit of controversy in the industry at the time.
Many traditional automakers and autonomous driving technology companies are skeptical, arguing that lidar is critical to improving the safety of autonomous driving due to its accurate ranging capabilities.
Behind Tesla's strategy is a deep consideration of cost and technology trends. Although LiDAR is accurate, the cost per unit is as high as thousands of yuan, much higher than that of a camera system of several hundred yuan. Tesla firmly believes that through a large amount of data and advanced algorithms, visual recognition technology can match or even exceed the performance of LiDAR.
In 2022, Tesla announced that it would completely abandon lidar and rely on its self-developed vision system to realize the vehicle's self-driving function.
Tesla's decision initially caused an uproar in the Chinese market. Many domestic auto companies and technology critics have criticized this, arguing that lidar-free autonomous driving systems may pose safety risks. Some domestic companies have even begun to increase the use of lidar in an attempt to attract consumers with "safer" technology.
2023 has begun to turn around. With the advancement of technology and cost pressures, several major domestic automakers have begun to re-evaluate their autonomous driving strategies
。 Some of the newly released models on the market are starting to significantly reduce the use of lidar, some even equipped with only one lidar, and more often make use of multiple cameras and sensors. This shift is not only a change in technology choices, but also a need for cost control.
With the entry of 2023, the competition for electric vehicles in the domestic market is becoming more and more fierce. The start of the price war of electric vehicles has made major manufacturers have to control the cost more strictly. In this environment, expensive lidar systems are clearly a disadvantage.
Due to the influence of Tesla and changes in market demand, domestic lidar manufacturers have also begun to seek technological breakthroughs to reduce costs. They claim to have achieved a significant reduction in the cost of lidar in an attempt to maintain their position in a highly competitive market through technological innovation.
For many automakers, cost considerations remain a top priority. More and more voices in the market are recognizing the potential of visual identity technology, especially in dealing with complex traffic environments.
By collecting large amounts of driving data and using deep learning algorithms to continuously optimize the performance of vision systems, developers have made great progress in vehicle localization, obstacle detection, and path planning.
This technological shift is not just a choice for a single business, but an industry-wide response to cost and technology trends. From relying on a single, high-cost technology to adopting a diverse portfolio of sensors, the smart automotive industry is looking for a balance between cost-effectiveness and safety.
At the end of 2023, several major domestic car brands officially announced that their new smart models will mainly use visual recognition technology, marking their official alignment with Tesla and reducing their reliance on lidar. While this shift has generated a lot of discussion in the market, it has also demonstrated the adaptability and flexibility of Chinese automakers in the global automotive technological revolution.
Consumers have reacted differently to such market trends. Some consumers are concerned about the safety of visual recognition technology, and whether cameras and algorithms can accurately process real-time data in complex driving environments. Some technology enthusiasts have praised this cost-effective technological change as an important step towards more democratization of smart cars.
This is also putting pressure on lidar manufacturers to push for lower costs and higher performance. Some companies have even begun to explore hybrid solutions that combine lidar with visual recognition systems, hoping to provide a safer and more reliable autonomous driving experience through technology convergence.