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Transportation
Sensor Data Storage
Driverless vehicles are equipped with a variety of sensors, such as LIDAR, camera, radar, etc. These sensors generate a large amount of sensory data. Solid state drives (SSDs) and magnetic hard disks (HDDs) are commonly used to store these massive amounts of sensory data for real-time processing and subsequent analysis within the vehicle.
Map Data Storage
Driverless vehicles need to use highly accurate map data to plan paths and make decisions. These map data need to be stored inside the vehicle for use by the navigation and path planning system, SSD and HDD are usually used for map data storage.
Control Algorithm Storage
Driverless vehicles need to install complex control algorithms and software to realize autonomous driving functions. These algorithms and software need to be stored inside the vehicle, and SSDs are usually used to ensure high performance and fast algorithm loading.
High Speed Storage Cache
To enable real-time decision-making and control, driverless vehicles typically use high-speed storage caching technologies, such as flash memory (NAND Flash), to temporarily store the most commonly used data and intermediate results to improve algorithm execution efficiency and real-time performance.
Data Logger
Driverless vehicles are typically equipped with data loggers that are used to continuously record the vehicle's sensor data, vehicle status, and control information. These data loggers typically use high-capacity storage media, such as SSDs or HDDs, to ensure long periods of data recording and analysis.
Cloud Storage
To further analyze and improve driverless systems, it is sometimes necessary to upload sensory data, control data, and logging information to cloud servers for processing and storage. Cloud storage provides large-scale data storage and computational resources that enable complex data analysis and model training to improve the performance and safety of driverless vehicles.
