Intel® GO™ Automated Driving Solutions

Automated driving, accelerated.

Fast Development

  1. 1

    Incredibly scalable in-vehicle computing gives developers more flexibility.

  2. 2

    A software development kit maximizes hardware capabilities.

  3. 3

    A 5G-ready platform speeds innovation for new use cases.

  4. 4

    A robust data center powers artificial intelligence (AI) and handles unprecedented amounts of data.

Solutions for Automated Driving, from Car to Cloud
Automated driving will change lives and societies for the better, resulting in fewer accidents, greater mobility, and more efficient traffic flow. With Intel® GO™ automated driving solutions, Intel brings its deep expertise in compute, connectivity, and the cloud to the automotive industry.

Automated driving on a global scale takes more than high-performance sensing and compute in the vehicle. It requires an extensive infrastructure of data services and connectivity. Each automated vehicle will generate a massive amount of data—about 4,000 GB every day.1 This data will be shared among vehicles to continuously improve their ability to accurately sense and safely respond to surroundings.

To communicate with the data center, infrastructure on the road, and other cars, automated vehicles will need high-bandwidth, reliable two-way communication, along with extensive data center services to receive, label, process, store, and transmit huge quantities of data every second.                 

Intel® GO™ Development Platforms for Automated Driving
As driving becomes more automated, the vehicle must be able to visualize the road ahead, evaluate countless possible scenarios, and choose the best sequence of actions. It must process millions of data points every second and quickly respond to a constantly changing environment. This requires a tremendous amount of both parallel and sequential computing.

Intel GO development platforms for automated driving offer a flexible architecture that includes central processing units (CPUs), field-programmable gate arrays (FPGAs), and hardware acceleration technology for deep learning. This provides a unique and optimized blend of parallel and sequential processing—ideal for partitioning automated workloads into the most efficient compute type. With a combination of next-generation Intel® Atom™ and Intel® Xeon® processors for automotive and Arria® 10 FPGAs, Intel delivers a solution that can lead to more power-efficient and effective designs.

Ideal Balance of Sequential and Parallel Computing
The compute required for automated driving can be divided into three intertwined stages: perception, fusion, and decision-making. Each stage requires different levels and types of compute performance.

Sequential computing is the primary type of compute used for decision-making. It is also critical to the process of sensor fusion.

Intel offers a spectrum of powerful and efficient solutions for sequential computing that range from Intel Atom processors at less than 10 watts up to high-core-count Intel Xeon processors. This delivers the compute performance needed to fuel actionable insights from the most demanding decision-making and data processing workloads.

To deliver flexible hardware acceleration for highly parallel workloads, Intel will offer solutions that combine the compute performance of Intel Atom and Intel Xeon processors with the flexibility of FPGAs and the efficiency of both programmable and fixed-function accelerators—all in a single platform.

Incredibly Scalable Development Platforms
Intel GO development platforms for automated driving, including both Intel Atom and Intel Xeon processor versions, make it easier for developers to build, evaluate, benchmark, and optimize automated driving solutions, from Advanced Driver Assistance Systems (ADAS) to fully autonomous vehicles. These platforms jump-start development, enable flexibility in design, and speed time to market. Both platforms include Arria 10 FPGAs to speed production and come with a set of sample applications, run times and libraries, and middleware. In addition, they provide building blocks to enable developers to deliver functional safety and security to platforms.

Intel® GO™ Automotive Software Development Kit (SDK)
The software stack within automated driving systems must be able to efficiently handle demanding real-time processing requirements while minimizing power consumption. The Intel GO automotive SDK helps developers and system designers maximize hardware capabilities while speeding the pace of development with a variety of tools:

  • Computer vision, deep learning, and OpenCL™ tool kits to rapidly develop the necessary middleware and algorithms for perception, fusion, and decision-making.
  • Sensor data labeling tool for the creation of “ground truth” for deep learning training and environment modeling.
  • Automated driving-targeted performance libraries, leading compilers, performance and power analyzers, and debuggers to enable full stack optimization and rapid development in a functional safety compliance workflow.
  • Sample reference applications, such as lane change detection and object avoidance, to shorten the learning curve for developers.
     

Intel® GO™ Automotive 5G Platform
To confidently support vehicle-to-everything (V2X) communications, over-the-air updates, and new in-vehicle experiences, providers will need increasingly higher data transfer speeds, as well as faster response times—not just in seconds, but in milliseconds. The Intel GO automotive 5G platform, available February 2017, offers the industry’s first 5G-ready platform for the automotive segment. This platform allows automakers to develop and test a wide range of use cases and applications for 5G:

  • High-definition (HD) map downloads in real time
  • HD content for in-vehicle infotainment (IVI)
  • Over-the-air firmware and software updates
  • Sensor data uploads from the vehicle for machine learning
  • Use cases leading to safety, smart intersections, and cooperative driving
     

Intel® Technologies for the Data Center
High-performance computing in the car is essential to making immediate driving decisions. However, the data center is responsible for all artificial intelligence (AI) simulation and ongoing training. The data generated by automated vehicles will serve as a new kind of currency, opening the door for the automotive ecosystem to act on emerging business opportunities. The greatest opportunity lies in AI, as machine learning and deep learning will enable automated driving models. In addition, data about traffic, roads, and users can be used to create new applications and better experiences.

Intel provides extensive data center capabilities and expertise to support these demanding workloads. Intel® technologies for the data center support Intel GO automated driving solutions with full scalability to continuously store and manage unprecedented volumes of data and enable cloud services.

  • Sophisticated hardware, based on Intel Xeon and Intel® Xeon Phi™ processors, delivers the high-performance computing needed to support AI and other intensive workloads.
  • Platform services, including database services, distributed compute engines, and frameworks for machine learning and deep learning, offer specialized support for automated driving.
  • Functional applications and capabilities for automated driving are optimized to run most efficiently on data center infrastructure.
     

Future Intel Automotive Solutions
As part of Intel’s vision to accelerate the adoption of automated driving, Intel is planning to introduce an extensive roadmap of new solutions, from processors optimized for automotive and automated driving, to acceleration capabilities for computer vision and deep learning. In addition, Intel will continue to provide new automotive reference platforms to enable carmakers and automotive suppliers to accelerate innovation and speed time to market.

Automated Driving, Accelerated.


Read more about advanced solutions for the future of driving.

Informazioni su prodotti e prestazioni

1“Data Is the New Oil in the Future of Automated Driving.” Intel, Nov. 2016, https://newsroom.intel.com/editorials/krzanich-the-future-of-automated-driving