Roadstar.ai to build self-driving vehicle fleet

Artificial intelligence startup Roadstar.ai has announced plans to produce more than 1,000 self-driving electric vehicles by 2020 and to expand its presence in overseas markets, such as Japan, Europe and North America.

The company has already obtained a license to test its self-driving cars on open roads in California, the United States, and will be granted licenses to test its driverless cars in two Chinese cities next month, said Tong Xianqiao, founder and CEO of Roadstar.ai.

"We will modify 50 self-driving passenger vehicles in China, collaborate with original equipment manufacturers to produce 200 self-driving vehicles equipped with our autonomous driving solutions in 2019, and launch 1,500 pre-assembled self-driving electric vehicles by 2020," Tong said.

"We are collaborating with foreign car manufacturers. Moreover, we will propel the commercialization of autonomous driving technology through providing chauffeur services to improve city public transportation," said Tong.

He said he is bullish on the prospects of self-driving vehicles and the company's accelerated steps to expand into overseas markets.

"We don't rule out the possibility of cooperating with ride-hailing giant Didi Chuxing in the future. We have teamed up with group-buying and dining information platform Meituan-Dianping to develop driverless delivery vehicles," Tong said.

Founded by three engineers who had previously led autonomous driving technologies at Google Inc, Tesla Inc, Apple Inc, Nvidia Corp and Baidu USA, Roadstar.ai has established twin research and development centers in Silicon Valley and Shenzhen in Guangdong province.

Roadstar.ai is now focusing on Level 4 autonomous driving solutions, which means the self-driving car can drive by itself without human intervention in certain circumstances. The company's autonomous driving R&D covers sensors, perception, maps, localization, planning, control, hardware, systems engineering, cloud services and more.

"Companies should invest and establish more testing sites that imitate different traffic scenarios rather than testing their vehicles on urban roads prematurely," said Lin Jian, a senior engineer in the automobile engineering department at Tsinghua University.