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Future cars as mobile supercomputers

12 Oct 2015  | Klaus Neuenhuskes

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The SfM accelerator enables accurate identification of unknown obstacles that are not included in the image library, such as guardrails, kerbs or small objects on the road surface (figure 3). Conventional pattern recognition has only limited ability to identify unknown objects, whereas the SfM accelerator allows the use of 3D reconstruction techniques by analysing the image feed from a monocular camera at high speed.


Figure 3: The SfM accelerator enables the system to deal more effectively with unusual situations.


The extensive integration of hardware-based accelerators seen in this family of processors is effective in lowering overall processor power consumption.

Project development is supported via a Software Development Kit (SDK) with drivers and sample application programs, as well as a dedicated Integrated Development Environment (IDE), media processor debugger and simulator. A set of APIs for the software drivers, as well as hardware accelerators and an image-processing library are also included. Toshiba also has a number of ready-to-use algorithms such as pedestrian detection, vehicle detection and line detection, and others are at beta stage and preparing for release. Engineers can also implement their own algorithms if preferred.


Special automotive requirements
If automotive systems designers are to use the latest image-recognition technology in future vision-based systems, other important issues besides performance and power must be considered. Unlike the situation in consumer markets, automotive product lifecycles are relatively long and devices such as processors must be supported for periods of many years.

Moreover, systems such as collision avoidance and pedestrian detection are considered safety-critical and therefore must meet the appropriate Automotive Safety Integrity Level (ASIL). Toshiba has developed its image-recognition processor families including the TMPV7608XBG using its own ISO26262-certified process flow, and has designed the devices to satisfy the requirements for ASIL-C/D (Automotive Safety Integrity Level) systems.


Conclusion
The automotive sector is not the first to make use of extensive hardware acceleration to perform complex signal-processing algorithms at high speed and low power. The case for hardware acceleration is already proved in applications such as the software-defined radios of 3G and 4G cellular base stations, as well as equipment such as high-speed internet infrastructure, data-centre computing, and military signalling and radar systems.

Advanced vision-based driver assistance can take advantage of image-recognition algorithms and power-efficient hardware developed specifically for automotive application. This approach enables today's driver aids to deliver real-time performance within tight power, thermal and cost constraints, and allows scalability to support increasingly complex ADAS functions.


About the author
Klaus Neuenhüskes is Manager Automotive Solution Marketing at Toshiba Electronics Europe.


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