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25/02/2019

The field of electric vehicles has attracted new attention

Daimler and Geely are discussing cooperation in the field of electric vehicles. Daimler's future electric smart is likely to be manufactured and developed in China, while Geely intends to cooperate with Daimler in the production of electric smart cars, which are currently under negotiation. Previously, Daimler's other partner in China, Beiqi, was also interested in working with Daimler on smart cars.
In fact, since February 2018, Geely Chairman Li Shufu purchased 9.69% of Daimler's voting shares with about $9 billion, and became Daimler's largest shareholder, rumors about the cooperation between the two sides have continued and are being implemented step by step.
In August last year, Li Donghui, director, executive vice president and CFO of Zhejiang Geely Holding Group Co., Ltd., disclosed that Geely has been discussing with Daimler the three major areas of electrification, automatic driving technology and future automobiles, and has set up several projects to communicate.
Later, in October 2018, Geely and Daimler announced that they would form a joint venture in China to provide high-end private car travel services. In February, there was news that Geely and Daimler were negotiating to expand their cooperation. Yang Xueliang, vice president of Geely Automobile Group, confirmed the authenticity of the news on his personal social media account.
Behind Geely's and Daimler's announcement of discussions on expanding the scope of cooperation, there is a growing desire for transformation between the two sides. A few days ago, Daimler Financial Services Co. CEO Entenman said that Daimler Group is ready to continue to promote the transformation; Zhejiang Geely Holdings Co., Ltd. President Anconghui also mentioned that Geely will be transformed from an automobile manufacturer to a global automotive technology group.
And in the field of electric vehicles, or the best choice for cooperation. Geely has been working on developing a new architecture for electric vehicles and hopes to make it available to other car manufacturers. At the end of last year, Daimler Group said it would buy more than $23 billion worth of batteries by 2030 for mass production of hybrid and electric vehicles. If bilateral cooperation is achieved, it can further promote the realization of planning objectives.

20/02/2019

With the development of autopilot technology in the direction of wider application, it has made a lot of progress in imaging. However, a technical challenge associated with improving safety is the ability of a self driving vehicle to not have a strong ability to observe the surrounding corners.
Imaging and sensing are the key technologies of automatic driving, and also the key areas of 3D laser scanning system, such as lidar (optical detection and ranging). Such a system allows automatic driving vehicles to detect and avoid obstacles by using rotating laser beams to drive safely. However, the current imaging technology needs to be improved in order to improve the performance of the self driving vehicle. According to foreign media reports, researchers at Boston University have conducted a study to develop a new method that allows artificial intelligence components in autonomous driving vehicles to see the corners of vehicles around the University.
Researchers at Boston University have succeeded in making autonomous vehicles perceive the surrounding corners without using advanced optical devices. The technology is based on a standard digital camera and a special algorithm called "computational periscope".
It works like a toy periscope, a device consisting of two mirrors or prisms that allow people to see objects blocked by obstacles. Although the technology does not rely on mirroring, the principle is similar. The algorithm developed by Boston University uses the fact that light can be reflected from structures similar to walls in different modes to assess the degree of disorder created by different objects. The main task of the AI component is to interpret the scattered reflection image.

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