The complexity and sophistication of manufacturing machines is obviously much more complex than the autonomous car, so it’s not a big surprise to automation engineers that the basics of developing these vehicles isn’t a huge technological leap.
In a recent white paper entitled the Secret Sauce of Autonomous Cars, Real-Time Innovations’ CEO Stan Schneider commented that intelligent vehicles are really complex distributed systems combining sensors for vision, radar, Lidar, proximity sensors, GPS, mapping, navigation, planning, and control. His conclusion: “An autonomous car is more a robot on wheels than it is a car.”
What’s interesting is how new data and networking technology is evolving with the need for distributed systems that must share information to be effective. I think this is precisely the primary hurdle that the IoT must overcome to deliver on its immense promise and separate it from the networking technology deployed in the recent past. What is the secret sauce of autonomous cars? Schneider writes that it is simply, “system components that can interact through data flow.”
The illustration above shows the basics of data-centric communications and its impact on the connected car. A databus can link any language, device or transport, automatically discovering information sources, understanding data type, and communicating them to participants. It potentially scales across millions of data paths, enforces millisecond timing, ensures reliability, supports redundancy, and selectively filters information. Each path can be unicast, multicast, open data, or fully secure. In the diagram, a perception system tracking many objects will send only those close to, and approaching, the vehicle. Although the perception system can update at 100Hz, the receiver only needs it at 10Hz. (Source: Real-Time Innovations Inc.)
In the white paper, he writes: “Data-centric connectivity was originally developed for autonomous systems. Unlike messaging technologies, it directly controls data interactions. It removes all of the complexity of managing data communications from components. It excels at highly reliable, complex system integration. It is fully standardized, proven in hundreds of industrial systems, and already controlling many autonomous planes, robots, submarines, and cars.”
Automakers Invest in Digital Modernization
Most of us agree that the car of the future will be connected. Manufacturers will monitor data in real time for safety and reliability purposes, and vehicles will communicate to create an increasingly smart roadway infrastructure. The convergence of the IoT, sophisticated new sensor and telematics systems, cloud computing, and Big Data analytics will give automakers access to new streams of real-time data from vehicles, and valuable insight into both products and consumers.
|Design Things That Move. Doug Seven will deliver a not-to-be-missed keynote on the massive transformations going on in the auto industry, including Microsoft's view of the connected car space moving toward full autonomy, at DesignCon 2017, Jan. 31 to Feb. 2 in Santa Clara, Calif. Register here for the event, hosted by Design News’ parent company, UBM.|
According to Nitin Rakesh, CEO and president of Syntel, manufacturers are still scratching the surface of the potential for this technology, and the ability to efficiently handle, store, and interpret massive amounts of vehicle data is the key to success.
By leveraging tools including the company’s SyntBots automation platform, Syntel enables manufacturers to quickly move to more efficient, scalable Big Data systems, which has the potential to improve performance while reducing maintenance and support costs by as much as 30%. The results, according to Rakesh, are higher quality products, greater customer satisfaction, and the ability to create real value from this data.
“Cars are increasingly becoming mobile technology hubs, and digital features are no longer just a fancy option, but an integral part of the vehicle itself,” he said. “Connected cars can send manufacturers valuable performance data that enables them to recognize patterns and apply predictive analytics to detect faults or breakdowns before they occur.”
If connectivity is the key to success for both autonomous cars and complex robotic systems, it’s obvious that mastering “data-centric connectivity” in applications is the final step. In the world of automation and control, 2017 will see many new IoT networking strategies move from the idea stage to implementation. But for data to feed new distributed IoT systems, a new generation of software solution will need to continue to emerge that effectively tie components together.
Al Presher is a veteran contributing writer for Design News, covering automation and control, motion control, power transmission, robotics, and fluid power.