There are similar requirements in the field of IVI, as this also demands intensive processing power to stitch together image data from multiple sources (for instance, to deliver full surround view), for example, and/or to ‘understand’ it (for instance, driver monitoring). As 100 TOPS is considered to be a requirement for fully autonomous vehicles, Tesla plans to use two FSD chips in its FSD computer. ![]() The 260mm 2 chip supplies a total of 50 TOPS (trillion operations per second) – in other words, 50 x 1012 processing operations per second at a power consumption of 100W. Besides an LP-DDR4 memory interface, Tesla installed a 1 Gpixel/s ISP (image signal processor), two NNPs clocked at 2 GHz, a GPU cycled at 1 GHz and a 12-core ARM CortexA72 CPU (2.2 GHz). In 2019, American electric vehicle pioneer Tesla developed its own ADAS chip called FSD (Full Self-Driving), and disclosed its architecture. Modern, high-speed memory interfaces like LP-DDR5 or HBM, as well as good system design to prevent bottlenecks, are therefore important for ADAS. One major challenge in this type of system is the enormous amount of data transferred between the memory and processing units. In vehicles, ‘CNN inference systems’ are used to replicate CNNs that have already ‘learned’ to detect certain structures.ĬNNs are replicated in hardware with a mix of DSPs (digital signal processors), GPUs (graphical processing units) and NNPs (neural network processors). They have been proven to work well in fields such as image detection. These systems are capable of learning, replicating biological brain cells in electronic form. CNNs (convolutional neural networks) are often used to detect the vehicle’s surroundings, together with other road users, in video data. In terms of hardware, both IVI and ADAS require complex multi-processor systems with high computing power, which can only be implemented in the form of highly integrated circuits.ĪDAS video data processing is a good example. To implement these features, complex hardware and software is required. Typical applications include 360° surround view, parking assist and driver monitoring. Deep learning and object recognition are then used to gather additional information to help support the driver and enhance comfort levels. This involves processing relevant information from a fusion of many different sensors, including radar, LiDAR, ultrasound and cameras, along with real-time decision making. To further improve the driving experience and offer greater comfort and safety, modern IVI systems also integrate a large number of ADAS features. This will open up a whole new range of possibilities for in-vehicle passenger entertainment, in conjunction with in-car payment options.ĭrivers of the future will see this in a purely digital cockpit, presenting all relevant information on a seamless wide-screen display consisting of multiple high-resolution screens. This trend is only set to intensify when the introduction of level 3 and 4 autonomous vehicles evolve the actual process of driving a car into a secondary task. This makes people, with their individual demands and requirements, the increasing focus when specifing new IVI systems. ![]() Using artificial intelligence and biometric recognition, these settings can also be automated and transferred from vehicle to vehicle. Furthermore, simple and convenient operation through touch interfaces, plus voice and gesture control, together with a variety of customisation options, such as light, audio and seat settings, are mandatory. For instance, connectivity, including seamless integration of mobile devices, now plays an important role. When people buy cars these days, they consider more factors than simply the look and driving characteristics of the vehicle in making their purchasing decision. As Markus Moosmüller & Stephan Ahles, Senior Marketing Engineers at system-on-chip company, Socionext tell us, ASICs (or custom SoCs) offer the ideal solution for a customer- and application-optimised platform. In order to implement these new features, complex and integrated hardware and software solutions are required. Sign up to receive your own copy each month. This article was originally featured in the October 2020 issue of EPDT magazine. This process involves merging IVI (in-vehicle infotainment) & ADAS (advanced driver assistance systems) with the aim of improving the driving experience, while ensuring increased safety. ![]() Socionext_ASICs meet the need for speed in ADAS & IVI systems_580x280 Changes to vehicle interiors are continuing apace, as the industry moves inexorably towards autonomous driving.
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