Cover art for podcast The Drive to Level 5

The Drive to Level 5

6 EpisodesProduced by Jack HeslinWebsite

Cars are getting smarter. But the shift to Level 5 autonomy will take time, testing, and the technical chops to perfect the connected car at the component level. That means sensors, 5G, systems on chip, and other foundational elements that are the heart of the autonomous vehicle.Drive World Conferen… read more


Drive to Level 5: Car 2.0: Transportation-as-a-Service

Wrapping up our summer series on autonomous vehicles, our final Drive to Level 5  interview is with Willard Tu, Senior Director of Automotive Technologies at Xilinx. 

Willard will be giving his presentation on "Transportation as a Service" at The Drive World Conference in Santa Clara CA on Thursday August 29th.  The continuing evolution of autonomous vehicles has enormous implications for all of us. Whether it comes to fruition in five years or ten, this technology will change they way we work, they way we play and essentially how we live. 

But how this evolution takes place requires a number of different technologies to continue to develop and come together. Those include :

  • Artificial Intelligence: Computer Vision vs. Neural Nets
    Computer Vision – demands more performance, which drives cost up and thermal dissipation, better suited for FuSa
    Neural Nets – are a true black box, but will likely be lower performance than Computer Vision and lower thermal
  • Compute: Distributed vs. Centralized
    Most of the traditional passenger owned vehicles are driven by costs. These vehicles today are distributed intelligence so that OEMs can source an ECU = 1 function to a supplier. Centralization is much more complex as either the OEM or a Tier 1 has to take on greater responsibility for multiple functions that might be put into a centralized computing center.
    Centralization has trade-offs — you now have to stream a lot of data to a central node this is not easy. Cost is moved from processing at the edge to data transportation across the vehicle
    Robotaxi — vendors are doing it completely differently. They are all for centralization, cost as strong a consideration.
  • Sensing: Camera, Radar, LiDAR
    We will discuss the trade-offs and likely cost projections of each technology.
  • Processing Engines: CPU, DSP, FPGA, GPU
    Will contrast and compare each of these engines.
    Latency: Batch vs. Batch-less will be covered in this comparison.

In this interview Willard takes us through these technologies and discusses the implications autonomous vehicles have for all of us. 

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