The processing powerhouse that drives modern day ADAS in passenger cars
Cars are equipped with various features listed above to make driving safer. Having variety if sensors across the length of the car performing different application requires dedicated processing hardware setup or a powerful GPU performing the desired task of all the sensors. Various semiconductor manufacturers like Texas Instruments, Renesas, NXP, Qualcomm have specific boards meant only for ADAS applications which are developed to handle complex sensor data and machine learning on the edge for certain application. These special purpose hardware or hardware accelerators need to manage flow of data from the sensors to them, process and further to the mechanical actuators that control various aspects of the car like steering, throttle and brakes.
Challenges in developing an SAE Level 2 features
With numerous features arises challenges of integrating multiple of those in a vehicle. Some of the common difficulties or challenges are discussed below;
- Developing processing capabilities for data handling. Semiconductor manufacturers have also made significant advances in developing systems to incorporate vast amount of data that needs to be processed in fraction of a second.
- Fusion of multiple sensors, this can mean using multiple sensors of same nature or fusing image sensor with other type like radar.
- Developing a dependant mapping software when GPS fails (like in tunnels).
- High cost of sensors like LiDAR which are priced steeply compared to radar or camera
One might argue for or against a single type of sensor for all the ADAS features. But researchers are still a long way from developing a single sensor system for all the features with necessary processing support either on edge or a powerful ECU.
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