Modern vehicles are transitioning from multiple Electronic Control Units (ECUs) to powerful System-on-Chip (SoC) architectures that integrate processing, memory, and safety functions into a single chip. This shift addresses the growing need for compact, energy-efficient, high-performance computing to support diverse automotive applications.
By combining multiple functions, SoCs help reduce system complexity and latency. This allows for seamless integration of tasks such as infotainment, telematics, electrification, and Advanced Driver Assistance Systems (ADAS). With real-time processing and AI capabilities, SoCs enable vehicles to make intelligent decisions across critical operations.
As the backbone of embedded intelligence, SoCs are transforming how automotive systems function, communicate, and adapt to the changing needs of next-generation mobility.
Sensor Fusion at the Edge
The ADAS system relies on sensors such as cameras, radar, LiDAR, ultrasonic sensors, and GPS. Each of these collects different types of data from the vehicle’s environment. SoC plays a key role in bringing this data points together and processing it on the edge without the need to send it to the cloud.
This edge-level processing is important for time-critical decisions. For example, when a pedestrian suddenly appears, the vehicle should immediately detect and react. SoCs use dedicated hardware accelerators that combine data from various sensors and enable ADAS functions such as Automatic Emergency Braking (AEB) or Adaptive Cruise Control (ACC) to make quick and accurate decisions.
AI/ML-Driven Perception
AI/ML integration strengthens ADAS at all autonomy levels from basic driver alert in Level 0 to complete self-driving in Level 5. Edge AI models enable real -time perception, decision making and monitoring of the driver. Running these models on SoCs with AI accelerators (NPUs or DSPs) ensures low-delay reactions, increased safety, and adaptability without relying on cloud connectivity.
These enable the system to:
- Detect other vehicles, pedestrians, and road signs
- Understand road lanes and drivable paths
- Monitor driver behaviour (like drowsiness or distraction)
Running these inferences in the vehicle ensures rapid and safe decisions independent of limited connectivity. It also improves data privacy and system reliability, especially in areas with poor network coverage.
Functional Safety and Redundancy
Safety is at the core of each ADAS feature. SoCs used in vehicles are specially designed to meet automotive safety standards such as ISO 26262 (from ASIL-B to ASIL-D). These safety-ready chips include features:
- Lockstep CPU cores are typically two identical CPU cores (Arm Cortex-R5, Cortex-R52, etc.) in lockstep mode. They execute the same instructions simultaneously, and the system compares their outputs. If a mismatch occurs, it flags a fault to ensure system safety.
- Error-Correcting Code (ECC) memory: This memory is typically a SoC part (SRAM or external DRAM) that can automatically detect and correct small data errors, helping the system run smoothly without crashing due to minor faults.
- Redundant paths: These are backup hardware or communication paths. If the main system fails, the backup takes over to keep the vehicle operating safely.
This ensures the vehicle performs safely and reliably, even during unexpected hardware defects. This makes these SoCs suitable for Level 2 and Level 3 autonomy and preparing the foundation for Level 4 systems in the future.
OTA Updates and Scalability
ADAS features are continuously evolving, and modern SoCs are designed to support this evolution through software updates and scalable hardware. With over-the-air (OTA) updates, manufacturers can remotely deploy new features, upgrade ADAS features (lane detection, driver monitoring, etc.), and improve system performance without recalling the vehicle.
Additionally, a single SoC platform can scale across multiple car variants, enabling automakers to reduce hardware complexity, lower costs, and simplify the rollout of advanced functionalities across their vehicle fleet.
MosChip brings deep expertise in edge AI, SoC integration, and functional safety, enabling the rapid development of intelligent, secure, and reliable ADAS solutions for next-generation autonomous and software-defined vehicles.
