As an emerging technology that integrates multidisciplinary and multi-technology, Automated Driving is triggering a new round of scientific and technological revolution and industrial transformation, thus attracting the attention of all countries in the world. Based on the Derwent patent database, this paper collects relevant patent information related to Automated Driving from 1998 to 2016 by using software tools such as patent measurement and CiteSpace, and empirically analyzes the temporal distribution, structural distribution, hotspot and frontier technologies, and geographical distribution of automated driving. The study found that automated vehicles have rapidly developing in the past 5 years, which indicates that the technical innovation of automated driving is in an emerging stage. There are geographical differences in innovative activities and capabilities in the field of automated driving. The United States has the absolute competitive advantages, while each country has different technological innovation capabilities in different technical fields. Finally, this paper puts forward some suggestions of our country to develop the technology and industry of automated driving in the future.
With the rapid development of information technologies such as Big Data, Artificial Intelligence and Internet of Things, the emerging multi-disciplinary and interdisciplinary emerging technologies are setting off a new wave of technology. Automated Driving is a technology that enables vehicles to travel safely and reliably on the road with on-board sensors, artificial intelligence, visual computing, and global positioning systems that can plan routes and precisely control the steering and speed of the vehicle. The core technologies of automated driving include positioning and navigation, environmental perception, planning control, etc., which have the advantages of predictable behavior, rapid response and accurate perception. As a cutting-edge technology with high comprehensiveness and high R & D cost, automated driving can be effectively applied in the fields of intelligent transportation, intelligent logistics, agricultural automation, mining and military and bring huge economic and environmental benefits. In 2015, the State Council issued “Made in China 2025”, clearly pointing out that it is necessary to master the overall Automated Driving technology and various key technologies by 2025 [
At present, however, most of the research on automated driving focuses on the theory and application research of the technology itself. Few scholars analyze the innovation characteristics and trend of Automated Driving technology from the perspective of patent measurement. As an open technical information resource, patent data, covering almost 90% of the world’s technical information, is scientific, authoritative and time-efficient, and is the first choice for many scholars to analyze current and future technological trends (CHENC, 2006). Based on co-citation analysis theory and routing algorithm, patentometrics measures information in specific fields, analyzes evolution paths and important nodes in specific fields, and explores the dynamic mechanism of knowledge evolution and the forefront trend with visual methods. Besides, FABRY B puts forward the “Relative Patent Position (RPP)―Revealed Patent Advantage (RPA)” as the combination of indicators to evaluate and identify the core competition in the various competitors force, and then to analysis of innovation in specific areas. Therefore, based on the Derwent patent database as the analysis data source, this paper analyzes the patent distribution features of the technology by using patented measurement and CiteSpace software tools and other methods to reveal the development trend of global automated driving technology and the advantages and disadvantages of technological innovation in various countries, but also provide scientific decision-making basis for the development of automated driving in our country.
The research data of this paper come from Derwent Innovation Index (DII). The reason why choosing this database is that the Derwent Patent Database is a Web-based patent information database jointly launched by Thomson Derwent and Thomson ISI that incorporates over 40 patent publications agency about more than 30 million pieces of patent information, covering a wide range from 1963 till now [
Based on patented analysis, this study draws a patent map of Automated Driving using CiteSpace, an information visualization tool, to identify and analyze the hot technologies, key technical fields and development trends of Automated Driving. Patent measurement methods can intuitively demonstrate the regular pattern and characteristics of technological innovation [
Then, this study draws on the concept of patent portfolio analysis through the establishment of “Relative Patent Position―Revealed Patent Advantage” of the combination of indicators to monitor and evaluate the automated driving technology in the world countries, identify the core competition in the various competitors force, and then to analysis of innovation in specific areas [
Data Sources | Derwent Innovation Index |
---|---|
Patent Search Terms | TS = (“Self-Driving car*” OR “Automated car*” OR “Automated vehicle*” OR “Self-piloting automobile*” OR “automated car*” OR “automated vehicle*” OR “automated car*” OR “self-driving vehicle*” OR “self-driving automobile*” OR “automated vehicle*” OR “self-piloting vehicle*”) |
Time Range | 1998-2016 |
Bibliographic Data | “Full record” |
Patents Count | 2137 |
number of the most prolific competitors in the technology area of patent ownership, used to assess the technical gap with the strongest competitors. The Revealed patent advantage (RPA) is used to reveal the technological comparative advantage of the patentee in different technical fields, and is measured by the patentee’s distribution of patent activity in each technical field [
R P A = 100 × tanh [ ln ( P i j / ∑ i P i j ∑ j P i j / ∑ i j P i j ) ] .
Pij denotes the patent application amount of the patentee i in the technical field j. When RPA > 0, patentee i has a technological comparative advantage in technical area j, and the larger the value, the stronger the patentee’s innovative activities and capabilities in the field [
Since the concept of automated was introduced in 1939, its development has experienced a long period of dormancy. It was not until nearly that the technology had entered a rapid growth period (
various global enterprises and research institutions have engaged in related technology research and development. All of these have accelerated the industrialization of automated driving technology.
According to the results of a patent search and the combination of automated driving related papers, reports and other documents, we classify the automated technology in five technical areas, including: environmental perception, precise positioning, path planning, motion control, network communication, such as the specific interpretation of the
Specifically, the proportion of patents in each subdivision technology field of automated vehicles is shown in
In order to explore the time distribution and evolution process of technological innovation in the various fields of automated, we analyzed the related patent changes in various fields, such as
Technical field | Meaning |
---|---|
Environmental perception | Collection and processing of environmental information, including road boundary monitoring, vehicle detection, pedestrian recognition, etc. |
Precise positioning | Precise measurement of position through sensor information, GPS, and high-precision maps, etc. |
Path planning | Based on the perception and location of environmental information, the route can be planned according to the search algorithm to achieve automated navigation, which is the central decision system of the automated driving vehicle. |
Motion control | Control the vehicle’s driving track on the basis of path planning, including longitudinal control and lateral control. |
Network communication | Based on the car network, inter-car network and car-mounted mobile Internet, the wireless communication and information exchange and interconnection are carried out between cars and cars, roads and clouds. |
is a turning point for automated driving technology activities. Before this, patent filings and patent growth rates in various segments were at a low level. After that, the technological invention activities in various fields showed a surge trend. Among them, the patents in the field of precision positioning started relatively early, mainly due to the fact that GPS and map technologies, as their basic technologies, developed earlier and maintained a leading growth. However, the trend of sharp increase in recent five years may be due to the phased breakthrough achieved by high-precision map technology in recent years, which has promoted the innovation of precision positioning technology. The trend of patent growth in the field of path planning is basically the same as that of precise positioning. On the one hand, the precision positioning has been maturing in recent years as the underlying technology of path planning; on the other hand, the maturity of path search algorithms such as neural networks, fuzzy logic and convolution, has further promoted the development of decision-making and planning technology.
To further analyze the growth of the five major areas of automated driving, we use two-dimensional matrices to analyze the numbers of patent applications and relative growth rates in all areas of automated driving during 2008-2016. We plot the number of patents in each area of automated driving on the horizontal axis and the relative growth rate on the vertical axis respectively, just as
Different technical codes can characterize different technical innovation capabilities [
as the original data source, and CiteSpace was used for statistical analysis and processing. The key nodes in the network can be judged by the frequency and centrality of the nodes. The higher the node frequency is, the more important it is to represent the corresponding technology. The higher the centrality is, the more important it is to represent the position of the node in the network. When using CiteSpace software for data analysis, it is necessary to convert the patent data of 2137 automated driving technologies in the time domain into a system-recognized data format and set related parameters: “Year Per Slice” is set to “1” the type selection “category”, keyword source selection “title, abstract, author keyword, keyword”, threshold (2, 2, 23), (4, 3, 23) and (4, 3, 23), respectively, corresponding category frequency, co-occurrence frequency, the minimum similarity coefficient between words and the highest frequency of occurrence of 20 nodes node data each year. The automated driving knowledge map shows in
1) Key Technical Analysis
In a co-word network, the shortest path that passes through a node and connects the two points accounts for the ratio of the total number of the shortest path lines between these two points, which is called Betweenness Centrality [
Environmental perception | Precision positioning | Path planning | ||||||
---|---|---|---|---|---|---|---|---|
Code | Centrality | Frequency | Code | Centrality | Frequency | Code | Centrality | Frequency |
T01-J10B2 | 0.06 | 131 | T01-J04B2 | 0.11 | 12 | S02-B08 | 0.09 | 61 |
T01-J10B2A | 0.04 | 37 | S02-A03B4 | 0.05 | 5 | W06-B01B1 | 0.05 | 74 |
T01-S03 | 0.03 | 54 | T06-B01 | 0.04 | 211 | W06-B01A5 | 0.05 | 67 |
T01-J10G | 0.03 | 5 | T01-J07D3A | 0.03 | 502 | T01-S03 | 0.03 | 175 |
X22-X06F | 0.02 | 95 | T01-S03 | 0.03 | 405 | T01-J05B4P | 0.03 | 68 |
X22-X06 | 0.02 | 77 | W06-A03A5C | 0.02 | 42 | T01-J07D3 | 0.02 | 154 |
X22-X06X | 0.02 | 48 | W06-A06D1 | 0.02 | 32 | X22-E06 | 0.02 | 136 |
X22-E09A | 0.01 | 70 | T06-B01A | 0.01 | 409 | T01-J07D1 | 0.01 | 429 |
T04-D04 | 0.01 | 19 | W06-A03 | 0.01 | 13 | W06-A06H1K | 0.01 | 35 |
Data source: Derwent Innovation Index.
Data source: Derwent Innovation Index.
From
2) Cutting-Edge Technology Identification
By using the word frequency detection technology provided by CiteSpace software, the frequency change rate is extracted by analyzing the temporal distribution of word frequency. The frequency change rate is expressed as Burst, and the stronger the degree of burst is, the higher the rate of word frequency change is [
Environmental perception | Precision positioning | ||||||
---|---|---|---|---|---|---|---|
Code | Burst | Start year | End year | Code | Burst | Start year | End year |
T01-J10B2A | 3.68 | 2014 | 2016 | W06-A03A5C | 4.14 | 2015 | 2016 |
W06-A04H1K | 3.27 | 2015 | 2016 | T01-J07D3A | 3.57 | 2008 | 2011 |
T01-J10B1 | 4.45 | 2012 | 2013 | T06-B01A | 4.49 | 2013 | 2014 |
X22-X06 | 11.66 | 2007 | 2014 | W06-A06 | 3.20 | 2008 | 2011 |
X22-J05C | 4.97 | 2012 | 2013 | W06-A03 | 4.00 | 2008 | 2010 |
X22-X06G | 5.49 | 2012 | 2014 | T01-J04B2 | 4.26 | 2009 | 2012 |
T01-J10A | 5.18 | 2008 | 2010 | W06-A06D1 | 3.38 | 2011 | 2016 |
X22-X06X | 6.34 | 2014 | 2016 | ||||
X22-E09A | 6.49 | 2014 | 2016 |
Data source: Derwent Innovation Index.
Data source: Derwent Innovation Index.
It can be seen from
The number of patent applications is one of the indicators to measure the characteristics and innovation ability of a country’s technological innovation activities. From
position; Japan ranked second, with 392 patents. China followed closely with 326 patents and ranked the third largest patent application in the world. t is not difficult to find that the output of patents in the field of automated driving is significantly different from country to country. The United States has obviously taken the first array of technological innovation in the field of automated driving. The reason is that the United States started the research on automated technology earlier. As early as 2009, Silicon Valley companies began to study automated technology. At the same time, thanks to the government and research institutions emphasis on this technology, the United States masters the core technology. In September 2016 and September 2017, the US Department of Transportation issued the “Guide for US Automated Driving Car Policies” and the “Automated Driving Systems (ADS): A Vision for Safety 2.0”, which provide guidance with the performance of automated driving vehicles, the unification of state policies, the National Highway Traffic Safety Administration current management methods, innovations in regulatory measures in the future [
Besides, from the annual distribution of the number of patent applications in various countries
Patent portfolio analysis can be used to identify the core technology competencies of the relevant patent subjects, so as to analyze the technological innovation
activities and innovations in specific fields. This study uses a combination analysis of “Relative Patent Position” and “Revealed Patent Advantage”, and then examines the technological innovation characteristics and advantages and disadvantages of several countries in several core technologies. The measurement results of the RPP and the RPA are shown in
It can be seen from
Environment perception | Precision positioning | Path planning | Movement control | Network communication | |
---|---|---|---|---|---|
USA | 1 | 1 | 1 | 1 | 1 |
Japan | 0.14 | 0.56 | 0.33 | 0.50 | 0.22 |
China | 0.41 | 0.21 | 0.31 | 0.54 | 0.26 |
Korea | 0.17 | 0.21 | 0.25 | 0.27 | 0.19 |
Europe | 0.10 | 0.12 | 0.18 | 0.20 | 0.09 |
Data source: Derwent Innovation Index.
Environment perception | Precision positioning | Path planning | Movement control | Network communication | |
---|---|---|---|---|---|
USA | 0.01 | 0.01 | 0.14 | 0.17 | −0.17 |
Japan | −0.03 | 0.46 | −0.30 | 0.18 | −0.29 |
China | −0.11 | −0.45 | 0.59 | 0.25 | −0.12 |
Korea | 0.17 | −0.04 | 0.30 | 0.04 | 0.06 |
Europe | 0.28 | −0.12 | 0.27 | 0.17 | −0.21 |
Data source: Derwent Innovation Index.
Japan has a comparative advantage in the field of precision positioning and motion control. On the one hand, Japan owns major auto companies such as Toyota, Honda and Mitsubishi. The research of these car companies mainly concentrates on the fields of vehicle control or regulation system, vehicle joint control, vehicle radar and navigation accessories, and has accumulated certain technical advantages. On the other hand, the Japanese government also actively promotes research cooperation, builds technology alliances, and encourages car manufacturers joint local university and Matsushita, Hitachi and other suppliers, to set up the Dynamic Map Planning project, force the high precision positioning map and technology.
According to the relative patent location (RPP), China has a layout in all technical areas of automated driving. However, from the perspective of RPA, China only has comparative advantages in the field of path planning and motion control. This shows that our country has formed a pattern of coordinated development of the IT enterprises represented by Baidu and the traditional car enterprises represented by Chang an, BYD and Chery in the field of automated driving. The former mainly focuses on intelligent decision-making and planning. The latter mainly focuses on practical assisted driving control technology. However, the advantages in precision positioning, environment awareness and network communications are slightly inadequate. In view of the growth and development prospects of the various technical fields analyzed in the foregoing, China should step up R & D in the field of precision positioning and environmental perception in order to enhance the capability of technological innovation and maintain the competitive edge in the future.
Automated driving technology was born in the 1930s. Starting from the 90s, automated technology showed substantial growth in the recent five years. Automated driving is still in its early stage of development as an emerging technology for interdisciplinary integration. However, the development of automated is growing rapidly. In order to seize a new round of scientific and technological revolution opportunities and enhance scientific and technological competitive advantages, this paper made some suggestions on China’s future development of automated driving:
Firstly, grasping the development trend of automated driving technology, consolidating the existing technical advantages and strengthening the layout of various technical fields. On the one hand, encouraging auto enterprises represented by SAIC, BAIC and GAC to continuously improve and develop the functions and technologies of driving assistance system, and gradually improve the degree of automation and intelligence of automobiles to continuously develop towards fully automated driving. On the other hand, conducting Tencent, Huawei and other IT enterprises continue to improve the machine learning ability and independent decision-making ability through advanced Internet technology, sophisticated algorithms and cloud service platform, to further achieve precision positioning, environmental awareness and other technology breakthroughs.
Secondly, to promote integration and innovation. Accelerate the integration and innovation of the automotive industry, mobile communications network, big data, cloud computing, and artificial intelligence industries. Support the research and development of vehicles such as Internet cars and automated vehicles to promote the key common technology of automated driving technology breakthroughs and commercial development through building technology alliances, industry-university-research institutes, building innovation bases and science parks.
Thirdly, accelerate the introduction of automated driving instructional policies and technical routes to provide policy support for R & D, testing and commercial application of automated vehicles. And realize the large-scale application of mid- and low-level driver assistance functions based on short-term path planning and motion control technology advantages; realize middle-high-level automated driving supplemented by Internet-based information services in the medium term, And complete long-term complete automated driving functions and industrialization with a certain scale in the long-term.
Based on the Derwent patent data from 1998 to 2016, this paper analyzes the technical innovation of global automated through the combination of visualization and patent portfolio. The main conclusions are as follows:
There is uneven development of innovative activities in all technical fields of automated driving. Among them, the areas of precision positioning and path planning have high patented output and high relative growth rate, indicating that they have the highest level of technical activity and have entered a stage of rapid development. They are the leading technical fields of automated driving. Environmental perception and motion control have low patents output and high growth characteristics, indicating that the technology activity is in growth, and it may become the key technology for automated driving in the future. And network communications with low-patent output and low growth, reflecting that the fields of the technological innovation activities are relatively stable, are still in the exploratory stage.
There are also differences between the key technologies in automated driving and the frontier hotspot technologies. Environmental perception, precision positioning, path planning and motion control are more obvious burst technologies, software-based algorithm technology, image recognition and analysis, sensor information fusion, high-precision maps and vehicle control technology on behalf of the research hotspots and the future direction of development.
Innovation activities and capabilities of automated driving technology show an uneven geographical distribution. The United States, Japan and China are powers in the field of technology innovation in automated driving. There are also country-specific differences in the capability of technological innovation in all automated driving subdivisions. The United States is in the pre-layout of the field of automated driving, and has the absolute patent status and relative technical advantages of environmental perception, precise positioning, path planning and motion control. Japan is the second with the ability to innovate in automated driving technology and has comparative advantages in precision positioning and motion control. China followed the United States and Japan in the layout of all technical fields of automated driving and possessed the comparative advantages of technology in the field of path planning and motion control.
1) Guangdong Provincial Science and technology plan project “Science and Technology Revolution and Technology Foresight Think Tank Construction” (No.2016B07072001).
2) Funded by: Guangzhou City Humanities and Social Science Key Research Base; Guangzhou City Large Enterprise Innovation System Construction Research Center.
Zhang, Z.G., Chen, X.Y. and Huang, J.M. (2018) Research on Innovation Posture of Automated Driving Technology Based on Patentometrics. Technology and Investment, 9, 137-153. https://doi.org/10.4236/ti.2018.93010