accelerators for tasks such as high-speed signal processing, data conversion or complex mathematical computation. By integrating AFE circuits, ADCs, DACs and tightly coupled memory on a single chip, ASICs minimise signal path lengths, reduce parasitic capacitance and ensure efficient, high-bandwidth communication between functional blocks. The result is predictable, low-latency performance, with multiple high- bandwidth inputs processed simultaneously and minimal computational overhead. For ADAS, this means raw sensor data can be digitised, filtered and fed into dedicated processing pipelines without travelling across multiple chips or buses, avoiding queuing and bandwidth bottlenecks. Fixed-function accelerators, performing operations such as convolution, correlation, FFTs or Doppler extraction, transform raw waveforms and images into geometric and motion information with guaranteed timing. This helps to ensure that object detection, lane tracking and trajectory prediction remain stable even as sensor resolutions increase and frame rates rise. For user inputs, on-chip integration supports
Delivering seamless experiences depends on the electrical systems that stabilise, convert and process every signal the components generate
units pass their reflected waveforms through high-speed analogue-to-digital converters (ADCs) and precision filters, translating raw echoes into digital point clouds and Doppler data ready for interpretation. Similarly, signals from infotainment interfaces such as touchscreens, haptic sensors and microphones, are cleaned and normalised, ensuring responsive control and accurate feedback. These conditioning stages ensure that user inputs and sensor readings remain electrically stable and accurately represented, even under vibration, temperature fluctuations or strong electromagnetic fields. Once conditioned, these signals enter the
processing layer, where they are fused, analysed and converted into actions. In ADAS systems, multiple sensor streams are combined to detect obstacles, assess distances and trigger safety interventions such as automatic emergency braking. Infotainment processors synchronise touch inputs, graphics rendering, haptic feedback and audio streams, delivering smooth, intuitive interaction without perceptible lag. By orchestrating these processes in real-time, the processing layer ensures that both sensors and user inputs translate into predictable, safe and seamless experiences. But as the complexity of input data continues to grow, ensuring fast, deterministic processing
within constrained power and thermal budgets becomes increasingly challenging.
Within the processing layer, semiconductor processors, such as Central Processing Units (CPUs) and Graphics Processing Units (GPUs), perform general computation, coordinating data from sensors and user inputs. CPUs handle sequential processing
tasks, running operating systems and coordinating control flows, while GPUs accelerate parallel workloads such as image or point-cloud processing. However, their general-purpose architecture
contains extra logic and memory resources that automotive workloads do not require. This can lead to increased power draw, higher heat generation, unpredictable latency and larger chip area: factors that can compromise real-time, deterministic performance when processing multiple high-bandwidth sensors and user inputs concurrently. ASICs overcome these constraints. Unlike
general-purpose CPUs and GPUs, ASICs are specifically designed to execute a narrowly defined set of operations and can be optimised for deterministic, low-latency performance. Their pipelines are precisely configured for targeted operations, with dedicated
low-jitter acquisition of touch, haptic and audio signals, while dedicated signal processing engines handle filtering, gesture recognition, echo cancellation and event classification with minimal overhead. As memory hierarchies and data paths are purpose-built, the system avoids contention between infotainment workloads and safety-critical ADAS tasks, a common limitation in general-purpose chips. The result is a processing architecture
where both sensor fusion and human-machine interactions can run concurrently, predictably and with guaranteed worst-case execution times, supporting the fluid driver experiences and real-time safety functions demanded by modern vehicles. Just as Ford’s Model T once offered
uniformity, today’s consumers expect vehicles that deliver responsive, safe and immersive human-centric experiences. ASICs make this possible, enabling deterministic control over sensor fusion, infotainment and user interfaces. By combining high-performance computing with tightly integrated hardware accelerators, manufacturers can meet these evolving expectations, turning vehicles into intelligent, connected platforms that define the modern automotive experience. Every 1.5 seconds a new car leaves the
production line with a Swindon Silicon Systems technology onboard. If you have an automotive project that would benefit from an ASIC, get in touch with the company on the details below.
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