Smart cars are the future of automotive transportation. They are packed with innovative technologies that make them safe, efficient, and connected. In this article, we will explore the key technologies of smart car software.
The connector is one of the key technologies of smart car software. It is a platform that enables different software applications to share data and work together. The connector is used to connect the car to the Internet, to other cars, and to external devices such as smartphones.
The basic process of autonomous driving is divided into three parts: perception, decision-making, and control. Its key technology is the software algorithm and model of automatic driving.
By fusing the data of various sensors, different algorithms, and supporting software are used to calculate the required automatic driving scheme. Environmental perception in autonomous driving refers to the ability to understand the scene of the environment, such as the type of obstacles, road signs and markings, detection of driving vehicles, traffic information, and other data classification.
Positioning is the post-processing of the perception results, and the positioning function helps the vehicle understand its position relative to its environment. Environmental perception needs to obtain a large amount of surrounding environment information through multiple sensors to ensure a correct understanding of the vehicle’s surrounding environment and make corresponding plans and decisions based on this.
At present, there are two mainstream technology routes, one is a camera-led multi-sensor fusion solution represented by Tesla; the other is a lidar-led and other sensor-assisted technology represented by Google and Baidu plan. Decision-making is based on the cognitive situation map of the driving scene, and the task decision is made according to the driving needs.
Then, on the premise of avoiding the existing obstacles, through some specific constraints, multiple selectable safe paths between two points can be planned. , and choose an optimal path among these paths to determine the vehicle trajectory.
The execution system is to execute driving instructions and control the state of the vehicle, such as the longitudinal control of the vehicle and the driving and braking control of the vehicle.
The lateral control is the adjustment of the steering wheel angle and the control of the tire force. Given the goals and constraints, the car is automatically controlled to run.
The analysis of smart cockpit mainly covers the innovation and linkage of cockpit interior and cockpit electronics, and the human-computer interaction (HMI) system constructed from the perspective of consumer application scenarios.
The smart cockpit collects data and uploads it to the cloud for processing and calculation, so as to make the most effective adaptation of resources and increase the safety, entertainment, and practicality in the cockpit.
The current smart cockpit mainly meets the functional requirements of the cockpit. On the basis of the original, it integrates existing functions or scattered information to improve the performance of the cockpit, improve the way of human-computer interaction, and provide digital services.
The future form of the smart cockpit is “smart mobile space”. Under the premise of the high popularity of 5G and the Internet of Vehicles, the integration of smart cockpit and high-level automatic driving gradually evolves into a smart space integrating “home, entertainment, work, and social interaction”.
The Internet of Vehicles is a large-scale system network that performs wireless communication and information exchange between “people-vehicle-road-cloud” based on the intra-vehicle network, the inter-vehicle network, and the vehicle-mounted mobile Internet.
In accordance with agreed communication protocols and data interaction standards, is an integrated network that can realize intelligent traffic management, intelligent dynamic information services, and intelligent vehicle control, and is a typical application of Internet of Things technology in the field of transportation systems.
The level of networking, according to the content of the communication of the network, is divided into three levels:
♦ The auxiliary information interaction of the network,
♦ The collaborative perception of the network,
♦ The collaborative decision-making and control of the network.
At present, the industry is in the stage of network auxiliary information interaction, that is, based on vehicle-road, vehicle-background communication, the acquisition of auxiliary information such as navigation, and the upload of data such as vehicle driving and driver operations are realized.
Therefore, at the present stage, the Internet of Vehicles mainly refers to information services derived from Internet-connected auxiliary information interaction technologies, such as navigation, entertainment, and rescue V2X-related technologies and services.
The global Internet of Vehicles market is made up of a number of leading players, including communication terminals (T-Box) on vehicles and related controllers, vehicle machines, background TSPs (Internet of Vehicles Service Integrators), mobile applications, web pages, content providers and service providers such as OBU (On-Board Unit), RSU (Road Side Unit) and roadside communications base stations.
These components operate together to create smart services for vehicle users.
Among them, T-Box is the only bridge on the car to communicate with the outside world. It not only realizes in-vehicle networking, but also realizes out-of-vehicle communication, and is also connected with various terminals to realize business integration and information transmission.
Mobile apps, webpages, and vehicles are all direct contact points for users, undertaking the task of interacting with users, and are the embodiment of various service points;
Content and service providers are the sources of most of the data, and they are specialized providers in Internet segments.
The T-BOX architecture of the vehicle communication module usually includes a dual-channel high-speed CAN transceiver, a 4G/5G/V2X module, and a high-performance microprocessor chip capable of real-time processing. It is mainly responsible for communication services inside and outside the vehicle.
Application deployment scenarios The types of applications and collaborative service businesses are gradually enriched, and the evolution route of technologies and applications is also developing from node processing to higher-level complex applications.
High-precision map refers to a high-precision, high-freshness, and high-rich navigation map with absolute and relative accuracy at the decimeter level, referred to as HD Map (High Definition Map) or HAD Map (Highly Automated Driving Map).
High-precision maps contain rich information, including road information such as road type, curvature, and lane line position, as well as environmental object information such as roadside infrastructure, obstacles, and traffic signs, as well as real-time dynamic information such as traffic flow and traffic lights.
The application scenarios and real-time requirements of different map information are different. By classifying the information, the management, collection efficiency, and wide application of maps can be effectively improved.
Compared with traditional onboard electronic maps, high-precision maps are more precise and have more dynamic elements. And the volume of the vehicle map is limited by the storage capacity of the embedded system.
At present, the storage density of high-precision maps (centimeter level) for autonomous driving is very high, and the overall capacity has far exceeded the storage capacity of current mainstream controller solutions. Therefore, cloud storage and cloud distribution are needed to realize it.
In addition, the update frequency of traditional navigation electronic maps is static data (usually the update frequency is a quarterly or monthly update), and quasi-static data (the frequency is a daily update).
High-precision maps have higher requirements for real-time data, and the update frequency is usually quasi-dynamic data (updated in minutes) and real-time dynamic data (updated in seconds or milliseconds). If you need any help finding the right product for your application, please contact us at email@example.com and we will be happy to assist you.
--- END ---
Jan 11, 2024
Dec 29, 2023