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Renesas Electronics Enables Embedded Automotive ADAS Developments

Auto News - Published on Wed, 05 Jun 2019

Image Source: enesas.com
Renesas Electronics Corporation continues to accelerate the development of advanced driver assistance systems systems with a new Perception Quick Start Software based on its R-Car V3H system-on-chip. The solution delivers reference software for camera obstacle detection, LiDAR obstacle detection and road feature detection three key recognition areas for sensor-based Level 2+ autonomous vehicle systems. The R-Car V3H SoCs deliver a combination of high computer vision performance and artificial intelligence processing at low power levels, providing an optimized embedded solution for automotive front cameras in Level 2+ autonomous vehicles (Note 1). To achieve state-of-the-art recognition technology, Renesas designed the SoCs with dedicated hardware accelerators for key algorithms including convolutional neural networks, dense optical flow, stereo disparity, and object classification.

The new perception software provides an end-to-end pipeline reference for developers working with these complex yet cost-effective and power-efficient accelerators, which allows customers to kickstart their application design whether they are experts at using the accelerators or have limited experience. The reference software covers input from sensor or recorded data, all stages of processing and display output on a screen.

Mr Tim Grai, Director of Automotive Advanced Systems Innovation Department, Renesas said that “Specialized hardware accelerators play an essential role in achieving the computer vision performance and accuracy required in embedded ADAS and autonomy applications while still meeting stringent in-vehicle power consumption limits; however, the complexity of these accelerators can present a steep learning curve. With the new Perception Quick Start Software, we are able to offer a set of application software along with the underlying primitives to simplify the use of these complex accelerators needed to achieve embedded ADAS.”

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Posted By : Rabi Wangkhem on Wed, 05 Jun 2019
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