Transportation

In order to make vehicles safer and easier to operate, the automotive industry is seeing a dramatic proliferation of cameras and other types of sensors, such as LiDAR, RADAR and motion sensors around the vehicle and within the cockpit. Altera FPGAs and SoCs have specialized, AI-enabled Digital Signal Processors (DSPs), embedded throughout their logic fabric, which can be used to perform the demanding matrix multiplication tasks required by AI. These AI-enabled DSPs allow for very fast and efficient processing and fusion of sensor data so that it can consumed efficiently by the central brain of the car, making the vehicle smarter and safer.

AI-enabled FPGAs can be used by camera systems and sensors within the cabin of the vehicle to identify drivers and occupants and to monitor driver behavior as well as occupant safety and comfort. AI-driven analysis of driving behavior can be used to alert the driver of potentially hazardous driving behavior, predict and prevent potential mishaps, and even allow the vehicle to take preventative actions to avoid a collision. In addition, AI can be used to implement very fast and highly accurate AI-based voice recognition algorithms to allow drivers and passengers to safely and easily interact with the vehicle.

FPGAs facilitate localized AI processing, allowing continuous monitoring of sensors, electrical and mechanical systems within the vehicle to predict potential failures before they occur and alert the vehicle owner of the need for preventative maintenance or repairs. They can also do localized monitoring of battery state-of-health and state-of-charge to perform advanced management and load balancing of battery cells to extend battery life and reduce the need for battery maintenance or replacement. AI capability within the FPGA is essential for time-sensitive sensing and diagnoses where fast, accurate insights can lead to increased reliability and extended life of the vehicle and its battery.