Intelligent Connected Vehicles (ICV) refer to vehicles equipped with advanced onboard sensors, controllers, actuators, and other devices, integrating modern communication and network technologies to achieve intelligent information exchange and sharing between vehicles and X (vehicles, roads, people, clouds, etc.). They possess functions such as complex environmental perception, intelligent decision-making, and collaborative control, enabling safe, efficient, comfortable, and energy-saving driving, ultimately leading to a new generation of vehicles that can replace human operation.[1]
Originally, intelligent connectivity referred to two technological routes in automotive technology development: intelligent vehicles and vehicle networking. Intelligent vehicles[2] are new types of cars that, through advanced electronic control systems and the use of AI, information communication, big data, and cloud computing, possess semi-automatic or fully automatic driving capabilities, transforming from simple transportation tools to intelligent mobile carriers. Vehicle networking[3] leverages new information and communication technologies to create a network system connecting vehicles, roads, people, clouds, etc., enhancing vehicle intelligence and automation, creating new traffic service models, improving traffic efficiency, and providing users with safer and more convenient comprehensive services. The characteristics of vehicle networking include networking, vehicle intelligence, and new service formats. It is evident that the two are complementary and inseparable, thus the combination of vehicle networking and intelligent vehicles is referred to as intelligent connected vehicles.
Next, Cao Sir will unveil the mystery of intelligent connected vehicles from three dimensions: the development history of intelligent connected vehicles, the key technologies used in intelligent connected vehicles, and the development situation of intelligent connected vehicles, aiming to achieve a glimpse into the whole picture.
1. Development History of Intelligent Connected Vehicles
As early as the 1920s, a radio company installed a radio receiver on a Chandler vehicle, controlling the motor via radio signals, which in turn controlled the steering wheel, brakes, accelerator, etc. This vehicle was briefly demonstrated in New York City, traveling from Broadway to Fifth Avenue.
At the 1939 New York World’s Fair, engineers proposed scenarios for future vehicles to drive automatically on highways and in cities[4].
In 1977, Japan developed the first autonomous vehicle based on camera-detected navigation information. This vehicle was equipped with two cameras and used analog computer technology for signal processing, but required assistance from elevated tracks. This is known as the earliest attempt to use visual equipment for autonomous driving.
In 1989, Carnegie Mellon University was the first to use neural networks to guide the control of autonomous vehicles, forming the basis for modern control strategies. In the same year, Japanese scientists proposed the Road/Automobile Communication Systems (RACS)[5], mainly providing V2I communication between vehicles and roadside fixed-position devices, but with a short communication distance, its function was to provide reliable navigation assistance, information distribution services, and bidirectional communication services to moving vehicles.
By the 1990s, an increasing number of portable computing devices, cameras, and GPS devices were used to enhance the autonomous driving capabilities of vehicles.
In 2009, Google started its own autonomous vehicle project.
On July 14, 2011, the Hongqi HQ3 completed its first full highway autonomous driving test from Changsha to Wuhan, with an average speed of 87 km/h throughout the journey.
In 2013, traditional automakers such as Audi, BMW, Ford, Nissan, and Volvo entered the fray, developing autonomous vehicles and intelligent vehicles.
In 2014, Google publicly released its “completely autonomous design” for autonomous vehicles, and the following year, Google’s first prototype vehicle officially debuted and could be tested on the road.
In 2015, Mercedes-Benz released the surreal F015 concept autonomous vehicle. In December of the same year, Baidu announced that its autonomous vehicle had achieved full autonomous driving for the first time in mixed urban, ring road, and highway conditions in China, reaching a maximum speed of 100 km/h during testing.
On April 17, 2016, Changan Automobile announced the completion of a 2000 km super autonomous driving test project. Since then, autonomous driving has entered a fast track of development. More and more companies have eagerly participated, relevant laws and regulations have begun to be introduced, practical testing bases have been established, and the public has begun to discuss autonomous driving and intelligent vehicles, along with related ethical and legal issues, marking the issues related to application implementation being put on the agenda, and indicating that the ecosystem surrounding intelligent connected vehicles has become relatively complete.[6]
2. Key Technologies Used in Intelligent Connected Vehicles
Intelligent connected vehicles mainly consist of perception systems, decision systems, execution systems, and communication systems[7], with key technologies closely related to automotive sensors, high-precision maps, high-performance chips, V2X communication, network cloud platforms, MEC, and information security.
1. Sensor Technology. This includes visual sensors, ultrasonic radars, millimeter-wave, and laser radars. Visual sensors simulate human eyes, using surround-view cameras to synthesize images of the environment around the vehicle at close distances, while monocular cameras generate long-distance images by adjusting focal lengths. Among visual sensors, cameras have the advantage of recognizing flat objects, especially colors and text labels, such as traffic lights or speed limit signs, and can serve as backups for other sensors (in case of sensor failure), increasing accuracy and safety. Ultrasonic sensors can determine the distance from the vehicle to an object by emitting and reflecting ultrasonic waves. Millimeter-wave and laser radar sensors also operate on the principle of reflecting electromagnetic or light waves after encountering obstacles, calculating in real-time the distance and relative speed between the intelligent vehicle and obstacles. The 77 GHz radar installed at the front and rear of the vehicle can detect the speed of other vehicles in real-time, and increasing the redundancy of cameras and other sensors enhances safety.
2. High-Precision Maps. The higher the accuracy of location information, the higher the success rate, safety, and reliability of vehicle networking-related services. For instance, the precision required for connected vehicle precise parking services often needs to reach centimeter-level accuracy. In outdoor unobstructed scenarios, commonly used high-precision positioning methods include China’s Beidou, US GPS, European Galileo, and Russia’s GLONASS satellite navigation systems, as well as AOA and TOA positioning methods based on wireless microcell networks. Positioning technology becomes more complex in situations of satellite obstruction or interference. To meet positioning performance requirements in tunnels or indoor obstructed scenarios, related enterprises and research institutions have explored and researched continuously in recent years, leading to diversified market navigation methods, such as using Bluetooth and WLAN wireless networks to achieve positioning technology for mobile terminals in obstructed scenarios, with positioning accuracy reaching meter-level, and even down to 0.1-meter accuracy using ultra-wideband technology, although requiring the deployment of a large number of basic RF devices. Some commercial markets utilize integrated positioning methods such as GPS + inertial navigation, GPS + high-precision maps + camera recognition algorithms (feature matching), balancing accuracy, complexity, and economic viability, which is also a challenge in developing indoor positioning systems.
3. High-Performance Chips. The processing power of high-performance chips for real-time processing of multiple high-bitrate images and various auxiliary information determines the performance of intelligent connected vehicles. Compared to ordinary consumer electronic chips, automotive chips have higher reliability requirements, not only regarding defect rates and operating temperature ranges but also longer design cycles and supply assurance periods. Currently, major international automotive chip manufacturers include NXP, HiSilicon, and others.
4. V2X Communication Technology[8]. Vehicle-to-Everything refers to a communication method for information exchange between vehicles (V2V), between vehicles and pedestrians (V2P), between vehicles and road infrastructure (V2I), and between vehicles and the cloud through mobile networks (V2N). There are mainly two routes: DSRC communication technology evolved from Wi-Fi and C-V2X communication technology based on edge cellular networks.
5. Cloud Platform Technology. A cloud platform is a service system based on hardware and software resources that provides users with computing, networking, and storage capabilities[9]. Cloud computing platforms can be divided into three categories: data storage cloud platforms, data processing cloud platforms, and comprehensive cloud computing platforms that balance computing and data storage processing. Cloud platforms generally possess the following characteristics: hardware management is highly abstracted for users; when users need certain applications or resources, they issue commands to the “cloud,” and results are quickly presented, but users do not know which servers and hosts provide the services, hiding the relevant implementation details and ultimately providing results to customers as a whole. Intelligent connected vehicles are essentially large mobile terminals, utilizing cloud platforms to support the stable and secure operation of the decision systems in intelligent connected vehicles.
6. Multi-access Edge Computing. Multi-access Edge Computing (MEC) consists of three parts: edge, core, and cloud data centers[10]. MEC brings cloud platforms from within mobile core networks to the edge of mobile access networks, facilitating the expansion and extension of computing and storage resources. MEC provides third parties with cloud computing capabilities with very low latency, high bandwidth, and strong real-time accessibility conditions at the network edge. The realization of these functions is closely related to high-performance chips and virtual storage technologies. MEC achieves “zero distance” between mobile networks and mobile applications, supporting various OTT (Over The Top) application scenarios.
7. Information Security Technology. The foundation of intelligent vehicle networking applications is a low-latency, high-reliability communication network, and its promotion will be one of the largest application directions for the Internet of Things, as vehicle networking involves human life, property safety, and public safety, making data communication security particularly important. Intelligent connected information security encompasses the application system security and key security of the vehicle itself, roadside unit security, cloud platform security, network transmission security, and linked device security. To comprehensively ensure the information security of intelligent connected vehicles, on one hand, it is essential to strengthen top-level design, standardizing industry behavior through guidelines and policy formulation, and building an information security protection system for intelligent connected vehicles, giving sufficient attention and support to the research and application of this information security technology, while also identifying research topics and enhancing cooperation among departments to jointly tackle key technologies. On the other hand, from the perspective of the lifecycle, it is necessary to strengthen the protective research work, treating the innovation of key chips, software, communication protocols, and system applications as key tasks, comprehensively improving the security protection technology levels of automotive cloud platforms and application software. In national and enterprise-level remote monitoring platforms, it is crucial to quickly introduce information security monitoring modules to monitor and provide early warnings for security risks associated with vehicles and external linked devices in real-time, suppressing the spread of malicious attacks within the internal network of the system, and once any malicious attacks or vulnerabilities are discovered in any link, immediate security protection measures should be taken while ensuring the improvement and upgrading of systems and technologies to prevent secondary risks.[11].
3. Development Situation of Intelligent Connected Vehicles
1. Development Situation Abroad:
a. Policy and Regulation Level: In September 2016, the U.S. Department of Transportation released the federal automated vehicle policy guideline “Federal Automated Vehicles Policy,” continuously promoting safety regulation and testing of autonomous vehicles. In October 2018, it published “Preparing for the Future of Transportation: Automated Vehicles 3.0,” enhancing the safety integration of autonomous vehicles with the entire transportation system. The European Union’s “European Strategy for Future Mobility” released in May 2018 clearly outlined the strategic planning for the development of autonomous driving and smart transportation, while Japan revised the “Road Transport Vehicle Act” in 2019, clarifying the authority to regulate information on autonomous vehicles and establishing a vehicle electrification inspection delegation system.
b. Testing Demonstrations and Application Level: Currently, California in the U.S. is the most representative region for the testing and application development of autonomous vehicles, with local open policies allowing most global autonomous vehicle companies to conduct open road tests here. As of December 2018, 62 companies had been authorized to test autonomous vehicles in California. Countries such as Germany and Japan have also introduced regulations allowing enterprises to conduct large-scale testing on open roads, including highways. As autonomous driving tests continue to break through, the application scenarios are increasingly expanding, and application services are becoming diversified. Waymo, an American company, launched the first commercial autonomous ride-hailing service, Waymo One, in Phoenix, Arizona; Japan’s taxi giant “Hinomaru Kotsu” and startup ZMP are conducting the world’s first passenger-carrying operation of autonomous taxis in the central area of Tokyo.
c. Industry Ecosystem Level: Foreign automotive companies are relatively advanced in development speed, with major traditional automakers such as Mercedes-Benz, BMW, Volvo, and Toyota generally achieving mass production of L2-level intelligent connected vehicles. Most automakers plan to start launching L3-level mass-produced vehicles around 2019 and achieve L4-level autonomous driving around 2021. The global autonomous vehicle industry chain has initially taken shape, with increasing occurrences of cross-holdings and mergers among companies across the industry chain, making deep integration across industries a trend.
2. Development Situation in China:
a. Policy Level: The development of intelligent connected vehicles in China has risen to the national strategic level, with the development positioning shifting from being an important component of vehicle networking concepts to intelligent manufacturing and intelligent connectivity in integrated intelligent industries. In terms of top-level design, guiding planning documents such as the “Automotive Industry Medium and Long-term Development Plan,” “Intelligent Vehicle Innovation Development Strategy,” and “Vehicle Networking (Intelligent Connected Vehicles) Industry Development Action Plan” have been intensively issued. The National Development and Reform Commission, the Ministry of Industry and Information Technology, the Ministry of Transport, and other ministries have actively taken action in their respective fields of industrial planning, product access, safety regulation, and scenario application, in addition to implementing the State Council’s strategic deployment in the field of intelligent connected vehicles.
b. Industry Standard System Construction: The construction of China’s intelligent connected vehicle standard system is a key effort to meet new opportunities and challenges. With the rapid development of the intelligent connected vehicle industry, the original industrial standard system has begun to hinder the development process, and a new standard system needs to be established. In June 2018, the Ministry of Industry and Information Technology and the National Standardization Administration Committee issued the “National Vehicle Networking Industry Standard System Construction Guide (Overall Requirements),” aiming to build a complete vehicle networking industry standard system from five aspects: intelligent connected vehicle standard system, information communication standard system, intelligent transportation-related standard system, vehicle intelligent management standard system, and electronic product and service standard system. In August of the same year, the National Automotive Standardization Technical Committee and other industry organizations jointly compiled the “Automated Driving Function Testing Regulations (Trial),” providing quantifiable standards for the road testing regulations of autonomous vehicles.
c. Open Road Testing: Currently, open road testing for autonomous driving in China is in a developmental trial stage. In April 2018, the Ministry of Industry and Information Technology, the Ministry of Public Security, and the Ministry of Transport issued the “Intelligent Connected Vehicle Road Testing Management Specification (Trial),” establishing the basic framework for the management of intelligent connected vehicle testing, allowing localities to conduct autonomous driving road tests at the national level. Subsequently, local governments began to vigorously promote this, with cities like Beijing, Shanghai, Baoding, Chongqing, Shenzhen, Changsha, Changchun, Pingtan, and Tianjin successively issuing local road testing management regulations, specifying requirements and regulations regarding testing entities, testing vehicles, testers, licensing methods, and testing areas. As of August 2019, 13 cities had issued 179 licenses for autonomous driving road testing. Among them, Beijing’s Economic and Technological Development Zone, Shunyi District, Haidian District, and Fangshan District have opened a total of 44 open testing roads, while Shanghai has designated the world’s first intelligent road fully supporting various communication modes for V2X testing. The western section of Qilin Avenue on Pingtan Island in Fujian has become the first testing site, and the Lijia Ring Road has become Chongqing’s first open road for autonomous driving, with Wuxi becoming the world’s first region to establish a city-level vehicle-road collaborative system.
d. Demonstration Application Promotion: With the promotion of the “Intelligent Vehicles and Smart Transportation Application Demonstration Based on Broadband Mobile Internet” project established by the Ministry of Industry and Information Technology, China is actively advancing the construction of intelligent connected vehicle testing demonstration zones, which have formed demonstration zones authorized by the Ministry of Industry and Information Technology in various locations, including Beijing-Hebei, Shanghai-Zhejiang, Jilin (Changchun), Hubei (Wuhan), Jiangsu (Wuxi), Chongqing, Guangdong, and Hunan (Changsha). Research and development of new technologies and products such as vehicle-road collaboration, advanced driver assistance, autonomous driving, and traffic big data are underway. At the same time, functional operational projects such as experimental verification, testing evaluation, closed testing, and application demonstration are being carried out to create demonstrative conditions for the rapid development of autonomous vehicles. Currently, intelligent connected vehicle testing demonstration zones and closed testing sites in cities such as Shanghai, Chongqing, and Beijing have been completed and put into use. Meanwhile, cities like Changsha, Tianjin, Changzhou, and Xiamen are actively exploring the testing and demonstration of autonomous vehicles based on regional development conditions and unique resources.
It can be seen that intelligent connected vehicles are not a new concept; the grand vision of intelligent driving was proposed a century ago, and efforts towards this goal have never ceased. It has now taken shape, and while the future of large-scale mature applications seems distant, it could be just around the corner. Let us wait and see!
