AUTOMOTIVE Embedded Systems

Tuesday 6/18

While the marketplace is beginning to recognize that electric vehicles (EV) are a growing and permanent part of society going forward, there is a lot of development still to be done. EVs are far from mature, and the nature of electromobility is still being determined. Although Tesla has a head start in both perception and product, there are a lot of players out there jumping into the EV game with both feet.
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MIPI? Alliance has selected Valens? technology as the foundation for their A-PHY physical layer standard aimed toward automotive applications, providing high-speed links for cameras, displays and sensors, through native CSI-2 and DSI/DSI-2 interfaces, for autonomous driving and other use cases.
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Renesas? new Cockpit Reference Solution offers an out-of-the-box development experience for efficient digital cockpit application design that?s based on Renesas R-Car M3 system-on-chip (SoC), offering production focused, module-level hardware and software supplemented by Renesas? automotive partner network to accelerate system-level design.
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Infineon?s XENSIV? TLE4999I3 satisfies the safety standard ISO26262 for automotive applications, as it helps meet the highest level of functional safety (ASIL D) in fault-tolerant systems such as electric steering systems, electric throttle control systems and pedal applications.
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As automobile electronics become more prevalent and sophisticated, ensuring the reliability of the embedded software code within those systems becomes critical to the safety of passengers and pedestrians.
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OmniVision Technologies, Inc. released its OAX4010 automotive image signal processor (ISP) including the new HDR and LFM Engine (HALE) combination algorithm, which can process images from one camera at 60fps or two cameras at 30fps, minimizing the quantity of ISPs necessary for surround-view system (SVS) cameras by 50 percent.
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MulticoreWare, Inc. has expanded its system and software services to all phases of product development for advanced driver assistance systems (ADAS) and autonomous driving (AD) vehicles.
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Toshiba Electronic Devices & Storage Corporation?s Visconti? 4 image recognition processor was essential in Toyota Motor Corporation vehicles achieving top scores in the 2018 Japan New Car Assessment Program (JNCAP).
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TriEye made a $17M Series A funding round, led by Intel Capital, to continue development of the company's HD SWIR camera that enables ADAS systems to perceive their surroundings in low light and adverse weather conditions.
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Machine learning isn?t yet mainstream, but it?s getting there. One example of that is how it?s affecting the automotive space. To understand how that works, I invited Ricardo Margalho, the Co-founder and CEO of Stratio Automotive, to join me in this week?s Five Minutes With?discussion. How they handle that technology is quite interesting and it?s easy to see how it can evolve and expand. Tune in for more.

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