Its core technologies are the following five:
1. Car networking
V2X wireless communication technology can organically combine the traffic participation elements such as \"human-vehicle-road-network-cloud\" together, which can not only support vehicles to obtain more information than the perception of a bicycle, promote the research and development, transformation, and application of technologies such as autonomous driving, but also support the construction of a smart transportation system, and promote the development of cars and traffic services towards a new mode of business.
2. Lidar
As the \"eyes\" of autonomous vehicles, Lidar is one of the important sensors, which is of great significance to ensure the driving safety of autonomous vehicles. The application of LiDAR is mainly divided into two parts: one is to land on the unmanned vehicle for autonomous driving testing, and the other is to land on the mass production vehicle with assisted driving function launched by the automobile manufacturer.
Lidar is one of the core sensors of L4 ~ L5 level automatic driving in the future, which will gradually develop from the current mechanical rotation to the direction of chip and all-solid state with lower cost and higher reliability.
3. Precise positioning
Self-driving cars require very precise positioning. In addition to ordinary sensors based on radar, lidar, GNSS and cameras, trajectory estimation is essential for lane-level positioning required for automated navigation in urban environments. At present, there are three main high-precision positioning technologies for autonomous driving:
First, absolute positioning technology based on reference system signals: a representative one is the global navigation satellite system, as well as UWB, WiF, Bluetooth and so on.
Second, environmental feature matching, that is, based on the relative position of liDAR and vision sensor, the characteristics observed by the sensor and the characteristics stored in the database are matched to locate the vehicle;
Third, the INS system provides track estimation, an integrated navigation technology based on inertial navigation IMU.
4. Human-computer interaction
Human-computer interaction technology, especially touch screen, voice control, gesture recognition technology, is likely to be widely adopted in the global future automotive market. The human-machine interface of the autonomous vehicle should integrate function setting, vehicle control, infotainment, navigation system, car phone and other functions, so as to facilitate the driver to quickly set, query, and switch various information of the vehicle system, so that the vehicle can achieve the ideal operation and control state from the surface.
Of course, the design of the human-machine interface must be balanced between good user experience and security. With the rapid maturity of technology, the vehicle information display system and smart phone will achieve seamless connection, and the input method provided by the human-machine interface will have more room for choice, and users can take different operations and freely switch between different functions.
5. Planning decisions
Decision-making is the core technology of intelligent driverless driving, which is equivalent to the brain of self-driving cars, involving many aspects such as safe driving of cars, comprehensive management of cars and roads. Through comprehensive analysis of the information provided by the environmental awareness system and the results of routing the address from the high-precision map, the planning decision-maker can plan the speed and orientation of the current vehicle, and produce the corresponding parking, car following, lane change and other decisions.
At the same time, the planning technology also needs to consider the mechanical characteristics of the vehicle, dynamic characteristics, kinematic characteristics and so on. At present, the commonly used decision-making techniques include expert control, fuzzy logic, Bayesian network, hidden Markov model and so on. As the technology of 5G network, vehicle, road surface, cloud, platform and other aspects continues to mature, vehicles are shifting from assisted driving to automatic driving, and collaborative intelligent transportation based on automatic driving is also getting closer.
The ability of environmental perception is to know and sense the surrounding environment. Like human eyes, this wheeled robot also has its own eyes to identify the surrounding vehicles, obstacles, pedestrians and other conditions on the road.
The main component of our eye is the eyeball, which changes the lens focus by adjusting the curvature of the lens
There are a variety of core technologies for automatic driving, but in general, it needs to be further improved and perfected.
2 The core of autonomous driving technology includes sensing technology, data fusion, positioning, scene understanding and decision planning.
At present, some of these problems still need to be solved.
For example, the quality of sensors still needs to be improved, and data fusion and processing algorithms need to be optimized.
3 In the future, with the continuous progress and development of technology, the core technology of automatic driving technology will continue to change and update.