In this interview, we were asking Li Qingjian of China Dayou Positioning Intelligence Co., Ltd. a few questions on mapping and digital twins in China. His answers provide good insight in the business on the far side of the Great Wall. This interview is also a first – it’s provided in both languages, English and Chinese.
Li Qingjian, thank you very much for taking the time to answer a few questions for the blog of our GEONATIVES think-tank. In your role as Vice President and CTO of China Dayou Positioning Intelligence Co., Ltd, you are definitely one of THE experts on maps and mobility in Greater China. Would you mind introducing yourself and your company to our readers? （介绍我和我的公司）
I am the Vice President of China Dayou Positioning Intelligence Co., Ltd, Deputy leader of automatic driving map and positioning working group of China Industry Innovation Alliance for the Intelligent and Connected Vehicles; expert of high precision map and positioning of China Society of Automotive Engineering; former head of high precision map and positioning of National Intelligent Networked Vehicle Innovation Center; Graduated from Wuhan University, I have been engaged in the R&D of navigation map and high precision map for many years, I have also strong experience in software development and product design, written a number of patents, and participated in the development of multiple provincial and ministerial high precision map projects.
How do you see the business landscape for digital twins (i.e., maps and environment models) in China? To what extent is technology sourced and applied within China?
China’s digital twin technology has huge business prospects. First of all, a number of map data companies have emerged in China with map qualifications in the map industry after more than 20 years of development. They also have national dedicated map data and have formed an industry chain of data collection applications. Secondly, due to China’s huge market space, the scale and the R&D capabilities in the field of geographical information application have increased, which further formed a huge 2B and 2C commercial application market. Thirdly, China’s data management service enterprises based on the government and public institutions are provided with professional mapping data, application planning and natural resource management, which need to be further released.
At the current stage, China’s digital twin map technology has become increasingly perfect, gradually narrowing the gap with international map technology capabilities. Map data acquisition and production capabilities have been formed. It has begun to take shape in the traditional industrial applications and achieved application capabilities, but the new industry includes digital twins with new applications, yet to be tapped, or to be verified. Geographic information and digital twin applications have not formed large-scale, deep and professional applications. The current technology is still stuck in the data acquisition and visualization and basic computing tools. It can be seen that the scale of the new digital twin application field has not yet been formed.
In a huge country, planning, building, surveying, and updating traffic networks is a major task. In Europe and in the US, we see technologies emerging where regular vehicles with an ADAS or autonomous driving sensor set may be used as sources for creating the “data lake” and keeping it up to date. Also more and more companies utilize crowd-sourced data from citizen such as OpenStreetMap. What strategies and technologies do you see in your country?
China has also recognized the importance of digital services for transport infrastructure based on map data and has formed their own data service providers in map, transport, and automobile fields. Crowdsourcing of data based on ADAS or autonomous vehicles is also a trend for future development, but based on the management of national policy qualification, few qualified enterprises are allowed to product data. So based on crowdsourcing data technology is the focus of everyone ‘ s research, but can’t be widely used in the market.
On the other hand, qualified enterprises are fully equipped with crowdsourcing data and technology, and market application abilities. With the improvement of policy qualification, the promotion of commercialization will be further developed. China’s data manufacturers are often data service providers and data application users; therefore, future data use areas including Intelligent and Connected Vehicle, intelligent transportation is the key to data integration; at the same time, it is also the focus of current enterprise technology strategy, such as the development of Intelligent and Connected Vehicle field.
Which user groups of geodata do you see in your business and how compatible or diverse are their requirements when it comes to the idea of aggregating geodata in generic “lakes” and extracting relevant sub-sets for certain user groups?
In our related fields, the application of data lake has different stages of development in different industries. Vehicle navigation map data is maturely developed. With the automotive and cell phone field and other users of geographic information data applications increasingly planning, has formed a perfect technology and data standards. However, in the traditional planning and related fields, there are still geographical characteristics, and each application uses each local data. Although there are also certain standards and planning, there are still geographical characteristics. Therefore, the demand for data depends on the application field market, or the degree of concentration of application fields of the leading companies, which often also have map qualifications and huge data resources or become data lakes.
Today, we see that many companies measure the same areas again and again (just think of all the digital twins of San Francisco’s traffic network). With a more centralized planning, we would assume that redundancies can be minimized, and the use of resources can be optimized. Is it correct to assume that in China data collection and processing are managed more efficiently?
The management of map data collection and production qualifications adopted in China does not limit the scope of collection, so several companies with national data collection and production capabilities have been formed. Centralized planning and unified collection are not conducive to market competition, but also to the development of technological competition. Although the future development of intelligent transportation and application technology will require the unification of data standards and planning, and even the unification of crowdsourcing data. But it will be the need of market competition, so as to complete the unification of data.
Reality is more-or-less available to everyone. But who owns or should own the digital twin of reality? What is your experience in terms of data ownership?
Data acquisition and production will be the cooperation between static data manufacturers and crowdsourcing-based service providers to form future digital twin data capabilities. Mastering crowdsourcing technology application market capabilities requires more capabilities with digital twin data. The technical ability of digital twinning does not depend on the ability of data acquisition and production, but depends on the application manufacturers that generate data, the ability to have the Internet of Things terminal service, and the Internet of Things world dynamic data acquisition ability.
We are aware that geodata sourced in China is not supposed to leave the country and that any data available publicly may have offsets applied to geo-locations. This seems to make sharing of data, e.g. between surveying companies and users, somewhat of a burden. But, maybe, we are missing the big picture. When working with geodata, what policies and/or restrictions do you have to consider if you are trying to share data among various stakeholders?
First of all, to provide data sharing, it needs surveying and mapping qualifications and corresponding data security capabilities. From national policy side, it needs the system of qualification and data management security. The car side needs to ensure data security for shared data and data application processes between stakeholders.
Centrally held data lakes may be made available for a large range of use cases (traffic planning, routing, infrastructure planning and maintenance, municipal administration etc.). According to our credo, the incorporation of standards into the data pipeline will facilitate data re-use. Which standards (e.g., for data formats) do you see as relevant in your business domain?
At present, traffic and infrastructure planning and maintenance, municipal management and other applications are still mastered in local institutions. The common enterprise can not obtain the market application since there are stricter standards and unity and data security management. Our application field is in intelligent transportation and intelligent application data service; Our business areas are related to Intelligent and Connected Vehicle, vehicle navigation, intelligent transportation, data simulation and others.
Complex road data (images by Dayou PI)
Looking at mobility solutions: how would you summarize the state of the “mobility sector” in China. How, for example, do you see the maturity of “multi-modal transport solutions” (i.e. using public transport of various kinds – plane/train/metro/bus/minibus/scooter – up to the last mile)?
The logistics field is one of the developed application areas in China. Some of the large companies are building their own airports or logistics fleets and other professional logistics parks thus forming a fast logistics on a national scale. This enterprise also has mapping qualification, with data collection and production capability. But there are still many aviation and logistics parks, ports, railroads, and other multimodal transport still in the application of undeveloped digital twin geographic information wedge. These enterprises have a lot of room for development. However, due to the imperfect digital application capability of each link, it is a very difficult job to form the digital service application of geographic information.
What role will highly automated driving play in the future of China’s mobility sector? Will it be limited to road applications or will other transport means, for example trains or river traffic, also be fully automated?
Automated driving has become a consensus development in China’s transportation, but it can’t be widely used in the market and is still at the stage of developing test demonstration. The future of automated driving is not limited to road applications, but more scene applications including parks. It will become the trend of application development in various industries. The establishment of commercial applications with autonomous driving mobile carriers is the future development trend. In the field of train and high-speed rail, China has completed automation. There is no large-scale investment in automation technology in river transport due to market size or application constraints.
To what extent will the infrastructure and regulations need to be modified in order to enable autonomous mobility solutions? Will these adaptations make it easier to develop devices (e.g., vehicles) that may operate in the new environments? Or, asked in a different way: will infrastructure adapt to mobility solutions or vice versa?
In order to achieve autonomous mobility solutions, relevant policies and laws are being improved, involving multiple ministries and laws; according to the development and promotion of autonomous driving industry, the relevant laws are also put on the agenda. The improvement of laws and regulations will facilitate the large-scale application of existing autonomous mobility solutions. Meanwhile, infrastructure planning and service applications facilitate mobility solutions. The new planning and application of current infrastructure will adapt to mobility solutions, which will bring more rapid development of autonomous mobility solutions.
Final question: What topics would you like to see covered in a blog like ours?
I hope to see more industry applications, data standards, infrastructure and other application cases covering in the blog.