Beijing (Gasgoo)- According to information disclosed on the website of the Department of Natural Resources of Anhui Province, Anhui NIO Intelligent Mobility ("Zhixing" in Chinese) Technology Co., Ltd., a subsidiary specializing in intelligent mobility under NIO, recently applied for the Class-A qualification for Internet-based mapping service.
Photo cedit: NIO
Internet-based map services include map search, location-based services, geographical information tagging, map downloading and copying services, and map sharing and referencing services. Entities obtaining the qualification can engage in the aforementioned services, but high-precision map creation is not covered.
As per relevant national policies, the surveying and mapping of high-precision maps can only be legally undertaken by enterprises holding a Class A Navigation Electronic Map Production Qualification issued by the state. The scope of the qualification applied for by Anhui NIO Intelligent Mobility Technology Co., Ltd., as disclosed by the Department, does not involve the requirements related to the production of navigation electronic maps.
Last year, the China’s Ministry of Natural Resources released three batches of the latest Class A Navigation Electronic Map Production Qualification review results, with 19 units successfully passing the review, including major players like Amap, NavInfo, and ECARX, as well as industry giants like Huawei, Tencent, Baidu, and Alibaba. However, the number of qualified units reduced by nearly one-third compared to the previous review, indicating stricter controls on high-precision map production qualifications.
With the tightening of high-precision map production qualifications, the industry has started to explore new approaches for autonomous driving perception and route planning. The concept of "going map-less" has become a new consensus among automakers and autonomous driving technology providers, including companies like Huawei, XPeng, Li Auto, and Great Wall Motor’s Haomo.ai, all of whom have expressed their intentions to gradually reduce reliance on high-precision maps.
