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Automotive Driver Assistance Systems: Using the Processing Power of FPGAs

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By Paul Zoratti
Driver Assistance Senior System Architect
Automotive Division
Xilinx Corporation

This is a reprint of a Xilinx-published white paper which is also available here (344 KB PDF).

In the last five years, the automotive industry has made remarkable advances in driver assistance (DA) systems that truly enrich the driving experience and provide drivers with invaluable information about the road around them. This white paper looks at how FPGAs can be leveraged to quickly bring new driver assistance innovations to market.

Driver Assistance Introduction

Since the early 1990s, developers of advanced DA systems have striven to provide a safer, more convenient driving experience. Over the past two decades, DA features such as ultrasonic park assist, adaptive cruise control, and lane departure warning systems in high-end vehicles have been deployed. Recently, automotive manufacturers have added rear-view cameras, blind-spot detection, and surround-vision systems as options. Except for ultrasonic park assist, deployment volumes for DA systems have been limited. However, the research firm Strategy Analytics forecasts that DA system deployment will rise dramatically over the next decade.

In addition to government legislation and strong consumer interest in safety features, innovations in remote sensors and associated processing algorithms that extract and interpret critical information are fueling an increase in DA system deployment. Over time, these DA systems will become more sophisticated and move from high-end to mainstream vehicles, with FPGA-based processing playing a major role.

Driver Assistance Sensing Technology Trends

Sensor research-and-development activities have leveraged adjacent markets, such as cell-phone cameras, to produce devices that not only perform in the automotive environment, but also meet strict cost limits. Similarly, developers have refined complex processing algorithms using PC-based tools and are transitioning them to embedded platforms.