News Unveils HD RealityMaps at Automotive World
来源 Press Release


TOKYO – January 16, 2019 – Chinese Level 4 self-driving startup pioneer is unveiling a mapping technology specifically tailored for autonomous driving at 11th Automotive World in Tokyo. 

HD RealityMaps accurately captures real-world environments and generates high definition 3D maps with intensive detail and vivid colors, greatly improving the safety and reliability of autonomous vehicles (AVs). Compared with traditional HD maps, HD RealityMaps provides a 360-degree VR-like vision, showing objects and road conditions in ultra-detail and full color. 


HD RealityMaps bring full-color detail and 360 degrees of vision to traditional mapping

Following a preview at the World Internet Conference in Wuzhen, China last year, will officially showcase the HD RealityMaps of the city of Shenzhen, where’s autonomous fleets has performed extensive road tests.  

Thanks to HD RealityMaps’ automatic labeling capability,’s autonomous vehicles can generate high-definition maps of any new territories within a 10km range on one single ride and within a few hours, compared to traditional HD maps that took up to two weeks to generate.


Providing high definition and accuracy, HD RealityMaps can greatly reduce the complexity of autonomous driving computing, expand sensor boundaries and serve as accurate reference for actual and virtual data training of AVs. This technology further drives the development of overall autonomous technology through detailed breakdowns of roadways, highways and even tunnels.

To see demonstrations of HD RealityMaps, along with’s latest self-driving platform, please visit booth E62-20 in East Hall 7-8 in Tokyo Big Sight. 

About is a Chinese self-driving pioneer focused on Level 4 autonomous vehicle technology development, backed by $138 million in Series A and angel funding. Developing a multi-sensor framework for its fleet of 20 self-driving vehicles, Roadstar has put in more than 100,00 km/62,137 miles of public road testing in China and the United States, along with over 1 million km/621,371 miles of virtual training. With unique data fusion and multi-sensor synchronization technologies powering an accurate and efficient autonomous framework, is dedicated to completing the link between autonomous vehicle sensors and its control system. By coordinating data with the computers that analyze it, is equipping self-driving cars to handle the roadways in complex urban environments.